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1. WO2020117795 - ASSESSMENT AND MONITORING OF MUCOSAL HEALING IN CHILDREN AND ADULTS WITH CROHN'S DISEASE

Note: Text based on automatic Optical Character Recognition processes. Please use the PDF version for legal matters

[ EN ]

ASSESSMENT AND MONITORING OF MUCOSAL HEALING IN CHILDREN AND ADULTS WITH CROHN’S DISEASE

CROSS-REFERENCE

[0001] This application claims the benefit of U.S. Provisional Application No.62/775,039 filed December 4, 2018, which application is incorporated herein by reference in its entirety.

BACKGROUND

[0002] Management of Crohn’s disease (CD) is challenging. Despite growing evidence regarding the importance of mucosal healing, pediatric patients and parents, and adult patients, can be reluctant about repeat endoscopic evaluation. There is an unmet need for noninvasive tests to assess or monitor mucosal healing in adults and children.

SUMMARY

[0003] Disclosed herein, in certain embodiments, are methods for assessing or monitoring mucosal healing in a patient (for example, an adult or pediatric patient) with Crohn’s Disease (CD). In some embodiments, the method comprises detecting in a level of at least one angiogenesis biomarker, inflammation biomarker, immune signaling biomarker, matrix remodeling biomarker, growth factor, and/or cell adhesion biomarker in a sample from the pediatric or adult patient with CD. In some embodiments, the method comprises: detecting in a sample from the pediatric or adult patient with CD a level of each of one or more biomarkers selected from the group comprising Ang1, Ang2, VEGFa, FGF2, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, AREG, ANXA13, EREG, HB-EGF, HGF, TGFb, IL-7, GM-CSF, IL-1b, IL-2, IL-5, IL-6, IL-10, IL-12/23p40, IL-13, IL-15, IL-17a, IL-17f, IL-22, IL-23, IL-31, IL-33, CRP, SAA1, ADA, TWEAK, IFN-g, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, and Fibronectin; and applying a mathematical algorithm to the detected levels of the one or more biomarkers, thereby producing a Endoscopic Healing Index (EHI) score for the adult or pediatric patient. In some embodiments, the method comprises: receiving a level for each of one or more biomarkers selected from the group comprising Ang1, Ang2, CEACAM1, VCAM1, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7; and applying a mathematical algorithm to the received levels

of the one or more biomarkers, thereby producing a Endoscopic Healing Index (EHI) score for the adult or pediatric patient.

[0004] Some embodiments include providing the sample from an adult or pediatric patient with CD. In some embodiments, the sample is a serum sample. In some embodiments, the pediatric patient is a human under 18 years of age, for example a human 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17 years of age, or a range defined by any two of the aforementioned ages.

[0005] In some embodiments, the detecting comprises detecting in the sample a level of each of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13 (for example, 13) of the biomarkers selected from the group comprising Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7. In some embodiments, the detecting comprises contacting the sample with a binding partner for each of the one or more biomarkers and detecting binding between each biomarker and its respective binding partner. In some embodiments, each binding partner is an antibody.

[0006] Some embodiments include determining that the adult or pediatric patient is likely to be in remission or have mild endoscopic disease when the EHI score is less than or equal to 40 on a scale from 0 to 100. In some embodiments, the likelihood of the adult or pediatric patient being in remission or having mild endoscopic disease is greater than or equal to 86% or 92%, or is 100%. In some embodiments, the remission corresponds to a Crohn's Disease Endoscopic Index of Severity (CDEIS) score of less than 3. Some embodiments include determining that the adult or pediatric patient is likely to have an endoscopically active disease when the EHI score is greater than or equal to 50 on a scale from 0 to 100. In some embodiments, the high likelihood of the adult or pediatric patient having endoscopically active disease is greater than or equal to 87%, or is 100%. In some embodiments, the endoscopically active disease corresponds to a CDEIS score of greater than or equal to 3. Some embodiments include determining that the adult or pediatric patient has a moderate probability of having endoscopically active disease when the EHI score is between 40 and 50 on a scale from 0 to 100.

[0007] In some embodiments, the mathematical algorithm comprises two or more models relating the levels of the biomarkers to an endoscopic score. In some embodiments, the two or more models comprises two models. In some embodiments, the two or more models comprises three models. In some embodiments, the two or more models comprises four models. In some

embodiments, the two or more models comprises five models. In some embodiments, one or more of the two or more models are derived by using classification and regression trees, and/or one or more of the two or more models are derived by using ordinary least squares regression to model diagnostic specificity. In some embodiments, each of the two or more models comprises regression. In some embodiments, one or more of the two or more models are derived by using random forest learning classification. In some embodiments, each of the two or more models comprises random forest learning classification. In some embodiments, one or more of the two or more models are derived by using quantile classification. In some embodiments, each of the two or more models comprises quantile classification. In some embodiments, one of the two or more models is derived by regression, and another is derived using random forest learning classification. In some embodiments, one or more of the two or more models are derived by using logistic regression to model diagnostic sensitivity, and/or one or more of the two or more models are derived by using logistic regression to model diagnostic specificity. In some embodiments, a first model such as a first logistic regression model uses the biomarkers to predict the probability of the adult or pediatric patient having endoscopically active Crohn’s disease. In some embodiments, a second model such as a second logistic regression model uses the biomarkers to predict the probability of the adult or pediatric patient having moderate to severe endoscopic Crohn’s disease. In some embodiments, endoscopically active Crohn’s disease corresponds to a CDEIS score of greater than or equal to 3 (CDEIS score > 3). In some embodiments, the use of two or more models provides an unexpected benefit of increasing sensitivity in relating the biomarkers to the a CDEIS score.

[0008] Some embodiments include assessing mucosal healing based on the EHI score. Some embodiments include providing or discontinuing a CD therapy to the adult or pediatric patient based on the EHI score. In some embodiments, the adult or pediatric patient is receiving biologic or non-biologic therapy. In some embodiments, the method assesses mucosal healing by determining the efficacy of the therapy. In some embodiments, the method assesses mucosal healing at a colonic, ileocolonic, and/or ileal disease location in the adult or pediatric patient. In some embodiments, the method assesses mucosal healing in the adult or pediatric patient after surgery. In some embodiments, the method assesses mucosal healing by identifying post-operative, endoscopic recurrence in the adult or pediatric patient. In some embodiments, the method assesses mucosal healing by predicting or monitoring the mucosal status in the adult or pediatric patient. Some embodiments include monitoring mucosal healing. Some

embodiments include detecting, in a second sample taken from the adult or pediatric patient with CD at a second time, a level of each of the one or more biomarkers, and applying the mathematical algorithm to the detected levels of the second sample, thereby producing a second EHI score for the adult or pediatric patient. In some embodiments, the one or more biomarkers comprise or consist of Ang1, Ang2, VEGFa, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, IL-7, CRP, SAA1, ADA, TWEAK, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, and/or Fibronectin. In some embodiments, the one or more biomarkers comprise or consist of Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, or IL-7. In some embodiments, the one or more biomarkers comprise or consist of Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7.

[0009] Disclosed herein, in certain embodiments, are methods of detecting in a pediatric or adult patient with Crohn's disease an expression level of one or more biomarkers selected from the group comprising Ang1, Ang2, VEGFa, FGF2, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, AREG, ANXA13, EREG, HB-EGF, HGF, TGFb, IL-7, GM-CSF, IL-1b, IL-2, IL-5, IL-6, IL-10, IL-12/23p40, IL-13, IL-15, IL-17a, IL-17f, IL-22, IL-23, IL-31, IL-33, CRP, SAA1, ADA, TWEAK, IFN-g, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, and Fibronectin. In some embodiments, the method comprises: obtaining a serum sample from the adult or pediatric patient; and detecting the expression level of each of the one or more biomarkers in the serum sample by contacting the serum sample with a binding partner for each of the one or more biomarkers and detecting binding between each biomarker and its respective binding partner. In some embodiments, each binding partner is an antibody. In some embodiments, the adult or pediatric patient is a human under 18 years of age, for example, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17 years of age, or a range defined by any two of the aforementioned ages. In some embodiments, the one or more biomarkers comprise 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13 (for example, all 13) of the biomarkers selected from the group comprising Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7. In some embodiments, the one or more biomarkers comprise or consist of Ang1, Ang2, VEGFa, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, IL-7, CRP, SAA1, ADA, TWEAK, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, and/or Fibronectin. In some embodiments, the one or more biomarkers comprise or consist of Angl, Ang2, CEACAMl, VCAMl, TGFa,

CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, or IL-7. In some embodiments, the one or more biomarkers comprise or consist of Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7.

[0010] Disclosed herein, in certain embodiments, are methods of evaluating the efficacy of a therapy administered to a pediatric or adult patient with CD. In some embodiments, method comprises: providing a serum sample from the adult or pediatric patient; detecting in the serum sample an expression level of each of one or more biomarkers selected from the group comprising Ang1, Ang2, VEGFa, FGF2, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, AREG, ANXA13, EREG, HB-EGF, HGF, TGFb, IL-7, GM-CSF, IL-1b, IL-2, IL-5, IL-6, IL-10, IL-12/23p40, IL-13, IL-15, IL-17a, IL-17f, IL-22, IL-23, IL-31, IL-33, CRP, SAA1, ADA, TWEAK, IFN-g, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, and Fibronectin; applying a mathematical algorithm to the expression levels of the one or more biomarkers, thereby producing an EHI score for the adult or pediatric patient; and adjusting the therapy in response to the EHI score. In some embodiments, the adult or pediatric patient is a human under 18 years of age, for example, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17 years of age, or a range defined by any two of the aforementioned ages. In some embodiments, the one or more biomarkers comprise 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13 (for example, all 13) of the biomarkers selected from the group comprising Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7. In some embodiments, the one or more biomarkers comprise or consist of Ang1, Ang2, VEGFa, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, IL-7, CRP, SAA1, ADA, TWEAK, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, and/or Fibronectin. In some embodiments, the one or more biomarkers comprise or consist of Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, or IL-7. In some embodiments, the one or more biomarkers comprise or consist of Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7. In some embodiments, the adjusting comprises decreasing subsequent doses of the therapy when the EHI score is less than or equal to 40 on a scale from 0 to 100. In some embodiments, the adjusting comprises increasing subsequent doses of the therapy when the EHI score is greater than or equal to 50 on a scale from 0 to 100. In some embodiments, the therapy comprises one or more biologic agents, conventional drugs, nutritional supplements, or combinations thereof.

[0011] Disclosed herein, in certain embodiments, are methods of treating Crohn's disease in an adult or pediatric patient. In some embodiments, the method comprises: obtaining a serum sample from an adult or pediatric patient; detecting in the serum sample an expression level of each of one or more biomarkers selected from the group comprising Ang1, Ang2, VEGFa, FGF2, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, AREG, ANXA13, EREG, HB-EGF, HGF, TGFb, IL-7, GM-CSF, IL-1b, IL-2, IL-5, IL-6, IL-10, IL-12/23p40, IL-13, IL-15, IL-17a, IL-17f, IL-22, IL-23, IL-31, IL-33, CRP, SAA1, ADA, TWEAK, IFN-g, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, and Fibronectin; applying a mathematical algorithm to the expression levels of the one or more biomarkers, thereby producing an EHI score for the adult or pediatric patient; diagnosing the adult or pediatric patient with a high probability of having endoscopically active disease when the EHI score is greater than or equal to 50 on a scale from 0 to 100; and administering an effective amount of a therapeutic agent to the diagnosed adult or pediatric patient. In some embodiments, the adult or pediatric patient is a human under 18 years of age, for example, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17 years of age, or a range defined by any two of the aforementioned ages. In some embodiments, the one or more biomarkers comprise 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13 (for example, all 13) of the biomarkers selected from the group comprising Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7. In some embodiments, the therapeutic agent comprises one or more biologic agents, conventional drugs, nutritional supplements, or combinations thereof. In some embodiments, the one or more biomarkers comprise or consist of Ang1, Ang2, VEGFa, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, IL-7, CRP, SAA1, ADA, TWEAK, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, and/or Fibronectin. In some embodiments, the one or more biomarkers comprise or consist of Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, or IL-7. In some embodiments, the one or more biomarkers comprise or consist of Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7.

INCORPORATION BY REFERENCE

[0012] All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference.

BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The novel features of the invention are set forth with particularity in the appended claims. A better understanding of the features and advantages of the present invention will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the invention are utilized, and the accompanying drawings of which:

[0014] FIG. 1A is a chart showing Endoscopic Healing Index (EHI) (also referred to as Mucosal Healing Index or MHI) scores for some pediatric patients in which serum samples were taken within 90 days of an endoscopy. Patients with moderate to severe Crohn’s disease (CD) are shown on the left. Patients in remission are shown on the right. The Y axis shows EHI scores with values ranging between 0 and 100 in increments of 20. Patients with moderate to severe CD had EHI scores ranging from 49 to 97, with a median of 74. Patients in remission had EHI scores ranging from 4 to 49, with a median of 19. The p-value for EHI scores for patients with moderate to severe CD compared to EHI scores for patients with endoscopic remission was less than 0.0001.

[0015] FIG.1B is a chart showing EHI scores for some pediatric patients. in which serum samples were taken within 30 days of an endoscopy. Patients with moderate to severe CD are shown on the left. Patients in remission are shown on the right. The Y axis shows EHI scores with values ranging between 0 and 100 in increments of 20. Patients with moderate to severe CD had EHI scores ranging from 73 to 97, with a median of 82. Patients in remission had EHI scores ranging from 4 to 19, with a median of 13. The p-value for EHI scores for patients with moderate to severe CD compared to EHI scores for patients with endoscopic remission was less than 0.0001.

[0016] FIG.2 is a chart showing EHI scores over time for a pediatric patient. The X axis shows weeks of treatment with time points at 0 weeks, 6 weeks, 14 weeks, and 22 weeks. The Y axis shows EHI scores with values ranging between 0 and 100 in increments of 20. The patient was a sixteen-year-old male human who had moderate to severe CD at week 0 (by

endoscopy). His EHI scores were 82 at week 0, 81 at week 6, 87 at week 14, and 57 at week 22.

[0017] FIG.3A is a chart showing receiver operating characteristic (ROC) curves of CRP and EHI, in accordance with some embodiments. ROC curves of EHI and CRP for distinguishing active disease vs endoscopic remission in Validation Cohort 1 are shown. In Validation Cohort 1, mixed logistic regression models with random intercepts for individual subjects were used to combine multiple samples of same subjects.

[0018] FIG. 3B is a chart showing Receiver operating characteristic curves of CRP and EHI, in accordance with some embodiments. ROC curves of EHI and CRP for distinguishing active disease vs endoscopic remission in Validation Cohort 2 are shown.

[0019] FIG.4A is a chart showing receiver operating characteristic curves of EHI and FC in accordance with some embodiments. ROC curves of EHI and FC for distinguishing active disease vs endoscopic remission in Validation Cohort 1 are shown. In Validation Cohort 1, mixed logistic regression models with random intercepts for individual subjects were used to combine multiple samples of same subjects.

[0020] FIG.4B is a chart showing receiver operating characteristic curves of EHI and FC in accordance with some embodiments. ROC curves of EHI and FC for distinguishing active disease vs endoscopic remission in Validation Cohort 2 are shown.

[0021] FIG.5A and FIG.5B are graphical depictions showing use of EHI for monitoring. Boxplots of effect size (ES) of SES-CD, CDEIS score, Endoscopic Healing Index (EHI), fecal calprotectin and C-reactive protein (CRP) in monitoring disease changes in Validation Cohort 1. FIG.5A: between baseline and Week 12 (n=70). The median ES of EHI (1.10, IQR 0.52 -1.83) was on par with those of SES-CD (1.53, IQR 0.67 - 2.23, P=0.077) and CDEIS score (1.29, IQR 0.80 - 2.25, P=0.182), slightly better than that of fecal calprotectin (0.96, IQR 0.43 - 1.96, P=0.423) and significantly better than that of CRP (0.26, IQR 0.11 - 0.51, P<0.001). FIG. 5B: between baseline and Week 54 (n=59). The median ES of EHI (1.64, IQR 0.65– 2.29) was at par with that of SES-CD (1.87, IQR 0.93 - 2.67, P=0.069), slightly better than those of CDEIS (1.50, IQR 0.81 - 2.17, P=0.997) and fecal calprotectin (1.16, IQR 0.51– 2.32, P=0.574) and significantly better than that of CRP (0.21, IQR 0.09 - 0.56, P<0.001).

[0022] FIG.6 is a chart of CDEIS and SES-CD scores in Validation Cohort 1. The linear fit (CDEIS score = 0.1569 + 0.6744*SES-CD) was used to convert SES-CD scores to CDEIS scores for samples that had only SES-CD scores in the training cohort.

[0023] FIG.7A is a patient and sample flowchart for Validation Cohort 1.

[0024] FIG.7B is a patient and sample flowchart for Validation Cohort 2.

[0025] FIG. 8 is a chart showing reproducibility of EHI, in accordance with some embodiments. The figure includes reproducibility of EHI when same samples were analyzed using two different lots of reagents. Serum samples from clinically diagnosed CD patients (n = 77) were used to study reproducibility of EHI. The Deming regression had a slope of 1.005 (95% CI: 0.926 to 1.087) and an intercept of -0.298 (95% CI: -2.790 to 2.144).

[0026] FIG. 9 is a chart showing diagnostic accuracy of EHI in patients with surgery, in accordance with some embodiments. The receiver operating characteristic (ROC) curves of Endoscopic Healing Index (EHI) in distinguishing AD vs ER in patient sub-cohorts with (red) or without (blue) a history of IBD-related surgery in Validation Cohort 2. The area under the ROC curve (AUROC) of EHI in the two sub-cohorts was not significantly different (p=0.801).

[0027] FIG. 10 is a chart showing diagnostic accuracy of EHI in endohistopathologic healing in accordance with some embodiments. The chart includes a ROC curve of EHI in distinguishing EHPH versus non-EHPH in Validation Cohort 2.

[0028] FIG. 11A and FIG. 11B are charts showing comparative accuracy of EHI across disease locations. The charts include receiver operating characteristic (ROC) curves of Endoscopic Healing Index (EHI) in distinguishing AD vs ER by disease location in Validation Cohort 1 (FIG.11A) and Validation Cohort 2 (FIG.11B). A mixed logistic regression model with random intercepts for individual subjects was used to combine multiple samples of same subjects in Validation Cohort 1. The minimum pairwise P values comparing the area under the ROC curve (AUROC) of EHI on patients with different disease locations were (A) 0.171 and (B) 0.292, respectively, indicating that EHI performance was consistent across disease locations.

[0029] FIG. 12A and FIG. 12B are charts showing comparative accuracy of EHI across disease behaviors in accordance with some embodiments. The charts include ROC curves of EHI in distinguishing active disease vs endoscopic remission by disease behavior in Validation Cohort 1 (FIG.12A) and Validation Cohort 2 (FIG.12B). A mixed logistic regression model with random intercepts for individual subjects was used to combine multiple samples of same subjects in Validation Cohort 1. The pairwise P values comparing the area under the ROC curve (AUROC) of EHI on different groups of patients were (A) P³0.290, and (B) P³0.300, respectively.

DETAILED DESCRIPTION

[0030] There is an unmet need for noninvasive tests that assess a status of gut mucosa to, for example, monitor mucosal healing in adult and pediatric populations. The methods described herein fill that need. For example, described herein are noninvasive blood or serum-based tests. The noninvasive nature of such methods enables assessment of mucosal healing in adult or pediatric patients without endoscopy or stool-based methods. This is especially beneficial in some situations, such as when the patient suffers from an inflammatory event and an endoscopy would put the patient at risk of experiencing a rupture in the patient’s gut.

[0031] For example, Crohn's disease endoscopic index of severity (CDEIS) score and simple endoscopic score for Crohn's disease (SES-CD) are endoscopic indices for assessing the state of mucosal healing or inflammation/disease in Crohn’s Disease (CD) patients and to determine the outcome of clinical trials that utilize mucosal healing as an endpoint. Although CDEIS score is informative of a patient’s mucosal healing status, CDEIS score is generated invasively through an endoscopy. The methods described herein provide a Endoscopic Healing Index (EHI) score that replaces the need for, or can be used in conjunction with endoscopy methods such as CDEIS score or SES-CD.

[0032] Disclosed herein, in some embodiments, are methods for assessing or monitoring mucosal healing in an adult or pediatric patient. In some embodiments, the adult or pediatric patient has CD. Some embodiments include providing a sample, such as a serum sample, from the adult or pediatric patient. In some embodiments, the method includes detecting biomarker levels in a sample from the adult or pediatric patient with CD. Some embodiments include receiving information about biomarker levels. Various combinations and levels of biomarkers are contemplated. In some embodiments, the biomarkers comprise angiopoietin 1 (ANG1; e.g. UniProt accession no. Q15389) and 2 (ANG2; e.g. UniProt accession no. O15123), carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1; e.g. UniProt accession no. P13688), C-reactive protein (CRP; e.g. UniProt accession no. P02741), serum amyloid A1 (SAA1; e.g. UniProt accession no. P0DJI8), Interleukin-7 (IL7; e.g. UniProt accession no. P13232), transforming growth factor alpha (TGFa; e.g. UniProt accession no. P01135), vascular cell adhesion molecule 1 (VCAM1; e.g. UniProt accession no. P19320), extracellular matrix metalloproteinase inducer (EMMPRIN; e.g. UniProt accession no. P35613), and matrix metalloproteinase-1 (MMP1; e.g. UniProt accession no. P03956), -2

(MMP2; e.g. UniProt accession no. P08253), -3 (MMP3; e.g. UniProt accession no. P08254), and -9 (MMP9; e.g. UniProt accession no. P14780).

[0033] An EHI score has been validated for assessing and monitoring mucosal healing based on a serologic panel of biomarkers. The EHI score may be used to provide a report on the mucosal inflammatory activity of CD patients. The panel may include biomarkers from multiple biological categories, such as angiogenesis (including, for example, ANG1, ANG2), inflammation (including, for example, CRP, SAA1), immune signaling (including, for example, IL7), matrix remodeling (including, for example, EMMPRIN, MMP1, MMP2, MMP3, MMP9), growth factor (including, for example, TGFa) and/or cell adhesion (including, for example, CEACAM1, VCAM1). Thus, in some embodiments, the method comprises detecting a level of at least one angiogenesis biomarker, inflammation biomarker, immune signaling biomarker, matrix remodeling biomarker, growth factor, and/or cell adhesion biomarker. An EHI score described herein corresponds with endoscopic measurements, and thus the panel of biomarkers and EHI score are useful for monitoring and assessing inflammatory activity or mucosal healing in pediatric adult or patients.

[0034] Some embodiments include producing an EHI score for a patient such as an adult or pediatric patient based on the biomarker levels. Some embodiments include producing an EHI score for an adult patient based on the biomarker levels. Some embodiments include producing an EHI score for the patient based on the biomarker levels. Some embodiments include applying a mathematical algorithm to the biomarker levels. Some embodiments include applying a mathematical algorithm to the biomarker levels, thereby producing an EHI score for the patient. In some embodiments, the EHI score has a scale from 0 to 100. In some embodiments, the pediatric patient is at a pediatric age. In some embodiments, the pediatric age is under 18 years. In some embodiments, the pediatric age is between 0 and 18 years (for example, birth to 17 years of age). In some embodiments, the adult patient is 18 years or older. Some embodiments include treating the patient with a CD therapy as described herein. In some embodiments, the treatment is based on the mucosal healing as monitored or assessed. Some embodiments include modifying a CD treatment or CD therapy for the patient, based on the mucosal healing as monitored or assessed.

[0035] Some embodiments include: detecting biomarker levels in a sample from a patient such as an adult or pediatric patient, wherein the biomarkers comprise Ang1, Ang2, CEACAM1, VCAM1, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN,

and/or IL-7; and applying a mathematical algorithm to the biomarker levels, thereby producing an EHI score for the pediatric patient.

[0036] Some embodiments include providing or obtaining a sample from a patient, such as an adult or pediatric patient, with CD; detecting in the sample a level of one or more biomarkers selected from the group comprising Ang1, Ang2, CEACAM1, VCAM1, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7; and/or applying a mathematical algorithm to the detected levels of the one or more biomarkers, thereby producing a Endoscopic Healing Index (EHI) score for the patient.

[0037] Disclosed herein, in certain embodiments, are methods of detecting in a patient, such as an adult or pediatric patient, with Crohn's disease an expression level of one or more biomarkers selected from the group comprising Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7. Some embodiments include obtaining a serum sample from the patient. Some embodiments include detecting the expression level of the one or more biomarkers in the serum sample by contacting the serum sample with a binding partner for the one or more biomarkers and detecting binding between each biomarker and its respective binding partner.

[0038] In some embodiments, each biomarker level has an amount of influence on the EHI score. In some embodiments, the amount of influence varies between biomarker levels. Some embodiments include receiving, via a graphical user interface of a computer system, the biomarker levels; determining the amount of influence each biomarker has on the EHI score; and/or producing the EHI score based on the amount of influence of each biomarker level on the EHI score. Some embodiments include displaying an EHI score after receiving the biomarker levels, for example from a user using a graphical user interface.

[0039] Some embodiments include repeating the method (or repeating specific steps) at a later date. The method can further include comparing a first EHI score to a second EHI score to monitor mucosal healing, monitor disease status, monitor efficacy of a treatment, evaluate whether a patient should receive a treatment, or evaluate whether a patient should change treatments. In some embodiments, the method includes changing a treatment regimen if the patient is/is not responding, initiating a treatment regimen, ceasing a treatment regime, changing a treatment dose, increasing the frequency of treatment doses, or decreasing the frequency of treatment doses. Some embodiments provide an improved method of endoscopic patient monitoring or endoscopic assessment. Some embodiments include producing or

receiving an EHI score for a patient (e.g. adult or pediatric patient), thereby monitoring or assessing mucosal healing in the patient without the need to perform an endoscopy on the patient. Some embodiments include receiving or measuring biomarker levels, and producing an EHI score, for example using a method as provided herein. Some embodiments include performing an endoscopy or receiving endoscopy data. Some embodiments include performing an endoscopy on a patient, and then, for example, at a later date producing or receiving an EHI score for the patient, thereby monitoring mucosal healing in the patient without the need to perform a second endoscopy.

[0040] Some embodiments include a treatment method comprising administering a CD therapy as provided herein to a patient (e.g. an adult or pediatric patient) identified as having an EHI score above 50, or identified as having an EHI score of 50 or above. Some embodiments include a treatment method comprising administering a CD therapy as provided herein to a patient identified as having an EHI score of 40-50. Some embodiments include a treatment method comprising administering a CD therapy as provided herein to a patient identified as having an EHI score below 40.

I. BIOMARKERS

[0041] Some embodiments of the methods and systems provided herein include obtaining biomarker levels. In some embodiments, obtaining biomarker levels comprises detecting biomarker levels. In some embodiments, obtaining biomarker levels comprises measuring biomarker levels. In some embodiments, a biomarker level comprises a biomarker measurement. In some embodiments, obtaining biomarker levels comprises receiving biomarker levels. In some embodiments, obtaining biomarker levels comprises detecting or receiving biomarker levels.

[0042] Some embodiments of the methods and systems provided herein include detecting biomarker levels. In some embodiments, the biomarkers comprise at least one angiogenesis biomarker. Exemplary angiogenesis biomarkers include Ang1, Ang2, VEGFa, and FGF2. In some embodiments, the biomarkers comprise Ang1. In some embodiments, the biomarkers comprise Ang2. In some embodiments, the biomarkers comprise VEGFa. In some embodiments, the biomarkers comprise FGF2.

[0043] In some embodiments, the biomarkers comprise at least one cell adhesion biomarker. In some embodiments the biomarkers comprise 0, 1, 2, 3, 4, 5, or 6 cell adhesion biomarkers. Exemplary cell adhesion biomarkers include CEACAM1, VCAM1, Alcam, a4b7,

ICAM-1, and MAdCAM. Thus, in some embodiments, the biomarkers comprise 0, 1, 2, 3, 4, 5, or 6 cell adhesion biomarkers selected from CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, and MAdCAM. In some embodiments, the biomarkers comprise CEACAM1. In some embodiments, the biomarkers comprise VCAM1. In some embodiments, the biomarkers comprise Alcam. In some embodiments, the biomarkers comprise a4b7. In some embodiments, the biomarkers comprise ICAM-1. In some embodiments, the biomarkers comprise MAdCAM.

[0044] In some embodiments, the biomarkers comprise at least one growth factor biomarker. In some embodiments, the biomarkers comprise 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 growth factor biomarkers. Exemplary growth factor biomarkers include TGFa, BTC, EGF, SCF, AREG, ANXA13, EREG, HB-EGF, HGF, and TGFb. Thus, in some embodiments, the biomarkers comprise 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 growth factor biomarkers selected from TGFa, BTC, EGF, SCF, AREG, ANXA13, EREG, HB-EGF, HGF, and TGFb. In some embodiments, the biomarkers comprise TGFa. In some embodiments, the biomarkers comprise BTC. In some embodiments, the biomarkers comprise EGF. In some embodiments, the biomarkers comprise SCF. In some embodiments, the biomarkers comprise AREG. In some embodiments, the biomarkers comprise ANXA13. In some embodiments, the biomarkers comprise EREG. In some embodiments, the biomarkers comprise HB-EGF. In some embodiments, the biomarkers comprise HGF. In some embodiments, the biomarkers comprise TGFb.

[0045] In some embodiments, the biomarkers comprise at least one immune signaling biomarker. In some embodiments, the biomarkers comprise 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 immune signaling biomarkers. Exemplary immune signaling biomarkers include IL-7, GM-CSF, IL-1b, IL-2, IL-5, IL-6, IL-10, IL-12/23p40, IL-13, IL-15, IL-17a, IL-17f, IL-22, IL-23, IL-31, and IL-33. Thus, in some embodiments, the biomarkers comprise 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 immune signaling biomarkers selected from IL-7, GM-CSF, IL-1b, IL-2, IL-5, IL-6, IL-10, IL-12/23p40, IL-13, IL-15, IL-17a, IL-17f, IL-22, IL-23, IL-31, and IL-33. An“immune signaling biomarker” may also be referred to as an “immune modulation biomarker.” In some embodiments, the biomarkers comprise IL-7. In some embodiments, the biomarkers comprise GM-CSF. In some embodiments, the biomarkers comprise IL-1b. In some embodiments, the biomarkers comprise IL-2. In some embodiments, the biomarkers comprise IL-5. In some embodiments, the biomarkers comprise IL-6. In some embodiments, the biomarkers comprise IL-10. In some embodiments, the biomarkers comprise

IL-12/23p40. In some embodiments, the biomarkers comprise IL-13. In some embodiments, the biomarkers comprise IL-15. In some embodiments, the biomarkers comprise IL17a. In some embodiments, the biomarkers comprise IL-17f. In some embodiments, the biomarkers comprise IL-22. In some embodiments, the biomarkers comprise IL-23. In some embodiments, the biomarkers comprise IL31. In some embodiments, the biomarkers comprise IL-33.

[0046] In some embodiments, the biomarkers comprise at least one inflammation biomarker. In some embodiments, the biomarkers comprise 0, 1, 2, 3, 4, or 5 inflammation biomarkers. Exemplary inflammation biomarkers include CRP, SAA1, ADA, TWEAK, and IFN-g. Thus, in some embodiments, the biomarkers comprise 0, 1, 2, 3, 4, or 5 inflammation biomarkers selected from CRP, SAA1, ADA, TWEAK, and IFN-g. In some embodiments, the biomarkers comprise CRP. In some embodiments, CRP is or comprises hsCRP. In some embodiments, the biomarkers comprise SAA1. In some embodiments, the biomarkers comprise ADA. In some embodiments, the biomarkers comprise TWEAK. In some embodiments, the biomarkers comprise IFN-g.

[0047] In some embodiments, the biomarkers comprise at least one matrix remodeling biomarker. In some embodiments, the biomarkers comprise 0, 1, 2, 3, 4, 5, or 6 matrix remodeling biomarkers. Exemplary matrix remodeling biomarkers include EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, and Fibronectin. Thus, in some embodiments, the biomarkers comprise 0, 1, 2, 3, 4, 5, or 6 matrix remodeling biomarkers selected from EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, and Fibronectin. In some embodiments, the biomarkers comprise EMMPRIN. In some embodiments, the biomarkers comprise MMP-1. In some embodiments, the biomarkers comprise MMP-2. In some embodiments, the biomarkers comprise MMP-3. In some embodiments, the biomarkers comprise MMP-9. In some embodiments, the biomarkers comprise Fibronectin.

[0048] In some embodiments, the detecting comprises detecting in the sample a level of each of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, or 47 (for example, 13) of the biomarkers described herein. In some embodiments, the detecting comprises detecting in the sample a level of each of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, or 47 of the following biomarkers: Ang1, Ang2, VEGFa, FGF2, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, AREG, ANXA13,

EREG, HB-EGF, HGF, TGFb, IL-7, GM-CSF, IL-1b, IL-2, IL-5, IL-6, IL-10, IL-12/23p40, IL-13, IL-15, IL-17a, IL-17f, IL-22, IL-23, IL-31, IL-33, CRP, SAA1, ADA, TWEAK, IFN-g, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, or Fibronectin. In some embodiments, the detecting comprises detecting in the sample a level of each of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 (for example, 13) of the biomarkers described herein. In some embodiments, the detecting comprises detecting in the sample a level of each of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 of the following biomarkers: Ang1, Ang2, VEGFa, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, IL-7, CRP, SAA1, ADA, TWEAK, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, or Fibronectin. In some embodiments, the detecting comprises detecting in the sample a level of each of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13 biomarkers selected from Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7. Some embodiments include detecting a level of two or more of the biomarkers. Some embodiments include detecting a level of three or more of the biomarkers. Some embodiments include detecting a level of four or more of the biomarkers. Some embodiments include detecting a level of five or more of the biomarkers. Some embodiments include detecting a level of six or more of the biomarkers. Some embodiments include detecting a level of seven or more of the biomarkers. Some embodiments include detecting a level of eight or more of the biomarkers. Some embodiments include detecting a level of nine or more of the biomarkers. Some embodiments include detecting a level of ten or more of the biomarkers. Some embodiments include detecting a level of eleven or more of the biomarkers. Some embodiments include detecting a level of twelve or more of the biomarkers. Some embodiments include detecting a level of all thirteen of the biomarkers.

[0049] Some embodiments include detecting the level of each of the following biomarkers: Ang1, Ang2, CEACAM1, VCAM1, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7. Some embodiments include detecting a level of any number of any combination of the following biomarkers Ang1, Ang2, CEACAM1, VCAM1, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7. For example, some embodiments, include measuring all but 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 of the aforementioned biomarkers, or all but a range of biomarkers defined by any two of the aforementioned integers. Some embodiments include detecting a level of a number biomarkers in the following list of biomarkers, or in a list that omits 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 of the following biomarkers: Ang1, Ang2, CEACAM1, VCAM1, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and/or IL-7.

[0050] Various combinations of markers can also be used. For example, in some embodiments, a biomarker can be replaced with one or more biomarkers from the same category, as described above. In some embodiments, one or more of the biomarkers can be substituted for one or more of VEGFa, Alcam, a4b7, ICAM-1, MAdCAM, BTC, EGF, SCF, ADA, TWEAK, and Fibronectin.

[0051] In some embodiments, the one or more biomarkers comprise SAA1 and CRP. In some embodiments, the one or more biomarkers comprise Ang1, Ang2, CEACAM1, VCAM1, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7. In some embodiments, the one or more biomarkers comprise Ang2, CEACAM1, VCAM1, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7. In some embodiments, the one or more biomarkers comprise Ang1, CEACAM1, VCAM1, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and/or IL-7. In some embodiments, the one or more biomarkers comprise Ang1, Ang2, CEACAM1, VCAM1, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-3, EMMPRIN, and IL-7. In some embodiments, the one or more biomarkers comprise Ang1, Ang2, CEACAM1, VCAM1, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7. In some embodiments, the one or more biomarkers comprise Ang1, Ang2, CEACAM1, VCAM1, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-9, EMMPRIN, and IL-7.

[0052] In some embodiments, the one or more biomarkers comprise Ang2, CEACAM1, VCAM1, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7. In some embodiments, the one or more biomarkers comprise Ang2, CEACAM1, VCAM1, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-9, EMMPRIN, and IL-7. In some embodiments, the one or more biomarkers comprise Ang1, Ang2, CEACAM1, VCAM1, CRP, SAA1, MMP-1, MMP-2, MMP-9, EMMPRIN, and IL-7. In some embodiments, the one or more biomarkers comprise Ang2, CEACAM1, VCAM1, CRP, SAA1, MMP-1, MMP-2, MMP-9, EMMPRIN, and IL-7.

[0053] In some embodiments, the one or more biomarkers comprise Ang1, CEACAM1, VCAM1, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7. In some embodiments, the one or more biomarkers comprise Ang1, Ang2, CEACAM1, VCAM1, CRP, SAA1, MMP-1, MMP-2, MMP-3, EMMPRIN, and IL-7. In some embodiments, the one or more biomarkers comprise Ang1, CEACAM1, VCAM1, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-3, EMMPRIN, and IL-7. In some embodiments, the one or more biomarkers comprise Ang1, CEACAM1, VCAM1, CRP, SAA1, MMP-1, MMP-2, MMP-3, EMMPRIN, and IL-7. In some embodiments, the one or more biomarkers comprise CEACAM1, VCAM1, CRP, MMP-1, MMP-2, EMMPRIN, and IL-7.

[0054] In some embodiments, the one or more biomarkers further comprises ADA. In some embodiments, the one or more biomarkers comprise ADA and do not include EMMPRIN. In some embodiments, the one or more biomarkers further comprise ALCAM. In some embodiments, the one or more biomarkers comprise ALCAM and do not include CEACAM1. In some embodiments, the one or more biomarkers further comprise EGF. In some embodiments, the one or more biomarkers comprise EGF and do not include ANG1. In some embodiments, the one or more biomarkers comprise EGF and do not include MMP9. In some embodiments, the one or more biomarkers further comprise HGF. In some embodiments, the one or more biomarkers comprise HGF and do not include ANG1. In some embodiments, the one or more biomarkers comprise HGF and do not include CRP. In some embodiments, the one or more biomarkers comprise HGF and do not include MMP9. In some embodiments, the one or more biomarkers comprise HGF and do not include TGFa. In some embodiments, the one or more biomarkers further comprise IL6. In some embodiments, the one or more biomarkers comprise IL6 and do not include CRP. In some embodiments, the one or more biomarkers comprise IL6 and do not include SAA1. In some embodiments, the one or more biomarkers further comprise MADCAM1. In some embodiments, the one or more biomarkers comprise MADCAM1 and do not include CEACAM1. In some embodiments, the one or more biomarkers further comprise TWEAK. In some embodiments, the one or more biomarkers comprise TWEAK and do not include ANG1. In some embodiments, the one or more biomarkers further comprise VEGF. In some embodiments, the one or more biomarkers comprise VEGF and do not include MMP9. In some embodiments, the one or more biomarkers further comprise VCAM1. In some embodiments, the one or more biomarkers comprise CRP and do not include SAA1. In some embodiments, the one or more biomarkers comprise SAA1 and do not include CRP.

[0055] In some embodiments, the one or more biomarkers comprise SAA1, CRP, IL6, HGF, MMP3, MMP9, VEGF, ANG1, IL7, ADA, MMP1, EMMPRIN, and TGFa. In some embodiments, the one or more biomarkers comprise SAA1, CRP, IL6, HGF, MMP1, MMP3, MMP9, VEGF, ANG1, ANG2, IL7, ADA, and TGFa.

II. EHI SCORES

[0056] Provided herein are methods of assessing and monitoring endoscopic inflammation, remission, and healing in a subject. Some embodiments of the methods and systems described herein include producing an EHI score for a patient based on the levels of the one or more biomarkers. In some embodiments, determining an EHI score comprises determining a probability that a subject has an active disease or condition based on the levels of the one or more biomarkers. In some embodiments, determining an EHI score comprises determining a probability that a subject has a moderate and/or severe form of the disease or condition based on the levels of the one or more biomarkers.

[0057] Some embodiments include applying a mathematical algorithm to the obtained biomarker levels. In some embodiments, producing an EHI score comprises applying a mathematical algorithm to the biomarker levels. Some embodiments include applying a mathematical algorithm to the detected biomarker levels, thereby producing an EHI score for the patient. Some embodiments include receiving the EHI score produced by the mathematical algorithm. Some embodiments include use of a mathematical algorithm to produce an EHI score from biomarker levels. In some embodiments, the production of the EHI score is performed by a processor and cannot practically be performed in a human mind. For example, in some embodiments, calculations performed by the algorithm cannot be practically performed by the human mind. In some embodiments, the methods described herein provide a significant advantage in computer processing, generation of mucosal healing indices, and patient treatment, over conventional methods. For example, the methods and systems provided herein may provide benefits in patient monitoring over conventional methods of patient monitoring, or aid in speeding up computer processing.

[0058] Various combinations of biomarkers can be used to assess gut inflammation, including endoscopic remission and healing, as detailed above. Such biomarkers can include biomarkers from multiple biological categories, such as angiogenesis, inflammation, immune signaling, matrix remodeling, growth factor, and/or cell adhesion biomarkers, as described above. In some cases, the method includes calculating an EHI based on levels of Ang1, Ang2, CEACAM1, VCAM1, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7.

[0059] In some embodiments, the methods include calculating an EHI based on levels of Ang1, Ang2, VEGFa, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC,

EGF, SCF, IL-7, CRP, SAA1, ADA, TWEAK, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, and/or Fibronectin.

[0060] In some embodiments, the methods include calculating an EHI based on levels of Ang1, Ang2, VEGFa, FGF2, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, AREG, ANXA13, EREG, HB-EGF, HGF, TGFb, IL-7, GM-CSF, IL-1b, IL-2, IL-5, IL-6, IL-10, IL-12/23p40, IL-13, IL-15, IL-17a, IL-17f, IL-22, IL-23, IL-31, IL-33, CRP, SAA1, ADA, TWEAK, IFN-g, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, and Fibronectin.

[0061] In some embodiments, the EHI score incorporates a biomarker measurement. In some embodiments, the biomarker measurement is obtained by an immunoassay such as an ELISA. In some embodiments, the biomarker is compared to a reference or control biomarker measurement. In some embodiments, the biomarker is compared to a reference biomarker measurement. In some embodiments, the biomarker is compared to a control biomarker measurement. In some embodiments, the biomarker is compared to multiple reference or control biomarker measurements. In some embodiments, the biomarker measurement is entered into a model, such as a regression model, relating the to an endoscopic score. In some embodiments, the biomarker measurement is entered into multiple models. The reference or control biomarker measurements can include ranges of values.

[0062] In some embodiments, the reference or control biomarker measurement is from a control patient with a known disease or condition. In some embodiments, the control patient is a pediatric patient. In some embodiments, the control patient is an adult patient. In some embodiments, the control patient has an inflammatory disease. In some embodiments, the control patient has an autoimmune disease. In some embodiments, the control patient does has irritable bowel syndrome. In some embodiments, the control patient has Crohn’s disease. In some embodiments, the control patient has inflammatory bowel disease. In some embodiments, the control patient has ulcerative colitis. In some embodiments, the control patient has an inflammatory bowel disease or irritable bowel syndrome. In some embodiments, the control patient has more than one of the aforementioned diseases. In some embodiments, the control patient has a known stage or severity of one or more of the aforementioned diseases. As such, measurements for biomarkers for a control patient can be correlated to the particular disease, disease stage, or severity of the disease of the control patient. In some cases, biomarkers can be tested for groups of control patients, which can be used to create models of a disease or condition, diseases stages, the severity of a disease or condition, a change in the status or stage of a disease or condition over time and/or in response to a therapy, or the efficacy of a therapy.

[0063] In some embodiments, the reference or control biomarker measurement is from a healthy patient. In some embodiments, the healthy patient is a healthy pediatric patient. In some embodiments, the healthy patient is a healthy adult patient. In some embodiments, the healthy patient does not have an inflammatory disease. In some embodiments, the healthy patient does not have an autoimmune disease. In some embodiments, the healthy patient does not have an irritable bowel syndrome. In some embodiments, the healthy patient does not have Crohn’s disease. In some embodiments, the healthy patient does not have inflammatory bowel disease. In some embodiments, the healthy patient does not have ulcerative colitis. In some embodiments, the healthy patient does not have an inflammatory bowel disease or irritable bowel syndrome. In some embodiments, the healthy patient is a healthy adult patient without one or more of the aforementioned diseases.

[0064] The relationships between the biomarker levels and the endoscopic scoring index, EHI and diagnostic prediction can be derived by any of a number of statistical processes or statistical analysis techniques. In some embodiments, logistic regression is used to derive one or more equations of the mathematical algorithm. In some embodiments, linear regression is used to derive one or more equations of the algorithm. In some embodiments, ordinary least squares regression or unconditional logistic regression is used to derive one or more equations of the algorithm. Some embodiments include a computer system that performs a method described herein, or steps of a method described herein. Some embodiments include a computer-readable medium with instructions for performing all or some of the various steps of the methods and systems provided herein. In some embodiments, the logistic regression comprises backward elimination. In some embodiments, the logistic regression comprises Akike information criterion.

[0065] Some embodiments include developing or training a model. In some embodiments, the model is an algorithm such as an EHI algorithm. In some embodiments, the model is developed by testing candidate biomarkers. In some embodiments, an analytical method validation (AMV) is performed on a biomarker panel. In some embodiments, multiple logistic regression is used to predict endoscopic activity as a function of serum biomarker concentrations. Some embodiments include logarithmic transformation and/or combined through backward elimination with Akaike information criterion (AIC). Biomarkers in an

initial panel can be removed one by one by sequentially reducing the AIC value until a minimum of AIC is reached. In some embodiments, an EHI model is obtained by transforming a logistic function in terms of probability to be in active disease. Some embodiments include transforming a logistic function of each biomarker to a probability such as a probability of being in active disease. Some embodiments include transforming a logistic function of each biomarker to a probability, such as a probability of being in active disease. Some embodiments include combining one or two logistic functions or models to product the probability. Some embodiments include generating an EHI score based on an input of probabilities generated for each biomarker.

[0066] In some embodiments, continuous variables are reported as medians with interquartile ranges (IQR), and compared between groups using the Mann-Whitney test. In some embodiments, categorical variables are reported as numbers (n) and percentages (%), and compared between groups using a Fisher’s exact test. In some embodiments, a Delong method is used to compute a 95% confidence interval (CI) of AUROC, and/or to compare AUROCs of different biomarkers on paired samples. In some embodiments, exact binomial confidence limits are used for the 95% CIs of sensitivity and specificity. In some embodiments, the 95% CIs of PLR and NLR are computed. In some embodiments, a pairwise Wilcoxon rank sum test is used for comparing effect size of different variables. In some embodiments, a p value (e.g. one-sided or two-sided) of 0.05 or lower is considered as significant. In some embodiments, a mixed-effect logistic regression modeling is used for a validation cohort to assess performance of EHI. In some embodiments, effect sizes of SES-CD, CDEIS score, and/or EHI are calculated between baseline and later measurements to assess the responsiveness of those variables (e.g. response: disease status of endoscopic remission or active disease; fixed effect: EHI; e.g. random effect: random intercepts for study subjects). In some embodiments, the underlying data is mostly not normally distributed, and a corresponding median or inter quartile range (IQR) are reported rather than a mean.

[0067] In some embodiments, applying the mathematical algorithm to the biomarker levels comprises using one, two, three, or more models relating the levels of the biomarkers to an endoscopic score. In some embodiments, results are generated from more than one model. In some embodiments, the results comprise a probability such as a probability of a patient (e.g. an adult or pediatric patient) being in active disease and/or a probability of a patient having moderate to severe disease. In some embodiments, the results generated from each of the more than one model are averaged. In some embodiments, producing a Endoscopic Healing Index (EHI) score for the patient comprises using one, two, three, or more models relating the levels of the biomarkers to an endoscopic score. In some embodiments, the mathematical algorithm comprises a model relating the levels of the biomarkers to an endoscopic score. In some embodiments, the mathematical algorithm comprises two or more models relating the levels of the biomarkers to an endoscopic score. In some embodiments, one or more of the models are derived by using classification and regression trees, and/or one or more of the models are derived by using ordinary least squares regression to model diagnostic specificity. In some embodiments, one or more of the models are derived by using random forest learning classification, and/or one or more of the models are derived by using quantile classification. In some embodiments, one or more of the models are derived by using logistic regression to model diagnostic sensitivity, and/or one or more of the models are derived by using logistic regression to model diagnostic specificity. In some embodiments, the use of two or more models provides an unexpected benefit of increasing sensitivity in relating the EHI score to the a CDEIS score. In some embodiments, the use of two or more models provides an unexpected benefit of increasing specificity in relating the biomarkers to the a CDEIS score. In some embodiments, the use of two or more models provides an unexpected benefit of increasing specificity in relating the EHI score to the a CDEIS score.

[0068] In some embodiments, the statistical analyses includes a quantile measurement of one or more biomarkers. Quantiles can be a set of“cut points” that divide a sample of data into groups containing (as far as possible) equal numbers of observations. For example, quartiles can be values that divide a sample of data into four groups containing (as far as possible) equal numbers of observations. The lower quartile is the data value a quarter way up through the ordered data set; the upper quartile is the data value a quarter way down through the ordered data set. Quintiles are values that divide a sample of data into five groups containing (as far as possible) equal numbers of observations. The algorithm can also include the use of percentile ranges of biomarker levels (e.g., tertiles, quartile, quintiles, etc.), or their cumulative indices (e.g., quartile sums of biomarker levels to obtain quartile sum scores (QSS), etc.) as variables in the statistical analyses (just as with continuous variables).

[0069] In some embodiments, the statistical analyses include one or more learning statistical classifier systems. As used herein, the term“learning statistical classifier system” includes a machine learning algorithmic technique capable of adapting to complex data sets

(e.g., panel of biomarkers of interest) and making decisions based upon such data sets. In some embodiments, a single learning statistical classifier system such as a decision/classification tree (e.g., random forest (RF) or classification and regression tree (C&RT)) is used. In some embodiments, a combination of 2, 3, 4, 5, 6, 7, 8, 9, 10, or more learning statistical classifier systems are used, preferably in tandem. Examples of learning statistical classifier systems include, but are not limited to, those using inductive learning (e.g., decision/classification trees such as RF, C&RT, boosted trees, etc.), Probably Approximately Correct (PAC) learning, connectionist learning (e.g., neural networks (NN), artificial neural networks (ANN), neuro fuzzy networks (NFN), network structures, the Cox Proportional-Hazards Model (CPHM), perceptrons such as multi-layer perceptrons, multi-layer feed-forward networks, applications of neural networks, Bayesian learning in belief networks, etc., reinforcement learning (e.g., passive learning in a known environment such as naive learning, adaptive dynamic learning, and temporal difference learning, passive learning in an unknown environment, active learning in an unknown environment, learning action-value functions, applications of reinforcement learning, etc.), and genetic algorithms and evolutionary programming. Other learning statistical classifier systems include support vector machines (e.g., Kernel methods), multivariate adaptive regression splines (MARS), Levenberg-Marquardt algorithms, Gauss-Newton algorithms, mixtures of Gaussians, gradient descent algorithms, and learning vector quantization (LVQ).

[0070] Random forests are learning statistical classifier systems that are constructed using an algorithm developed by Leo Breiman and Adele Cutler. Random forests use a large number of individual decision trees and decide the class by choosing the mode (i.e., most frequently occurring) of the classes as determined by the individual trees.

[0071] Classification and regression trees represent a computer intensive alternative to fitting classical regression models and are typically used to determine the best possible model for a categorical or continuous response of interest based upon one or more predictors. In some embodiments, the statistical methods or models are trained or tested using a cohort of samples (e.g., serological samples) from healthy, CD, or non-CD individuals.

[0072] In certain aspects, one or more equations of the mathematical algorithm are derived to model diagnostic sensitivity, e.g., the proportion of actual positives that are correctly identified as such. For example, one or more equations can be trained using the data to predict an active disease diagnosis versus a remission diagnosis with the measured biomarker levels.

In certain aspects, one or more equations of the mathematical algorithm are derived to model diagnostic specificity, e.g., the proportion of actual negatives that are correctly identified as such. For example, one or more equations can be trained using the data to predict a mild disease or remission diagnosis versus a severe disease or moderate disease diagnosis with the measured biomarker levels. In some embodiments, the mathematical algorithm includes two or more equations, one or more of which are derived to model diagnostic sensitivity, and one or more of which are derived to model diagnostic specificity. In certain aspects, the mathematical algorithm applies one or more diagnostic sensitivity equations prior to applying one or more diagnostic specificity equations in a sequence to generate an EHI score or value. In certain aspects, the mathematical algorithm applies one or more diagnostic specificity equations prior to applying one or more diagnostic sensitivity equations in a sequence to generate an EHI score or value. In some embodiments, the algorithm is trained based on samples with a known CDEIS score and a known concentration of biomarkers.

[0073] Some embodiments of the methods and systems described herein include generating a probability of the patient being in endoscopic remission or active disease by applying a model to at least one biomarker level. In some embodiments, the probability is 0%, 1%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 99%, or 100%. In some embodiments, the probability is 0-10%. In some embodiments, the probability is 10-20%. In some embodiments, the probability is 20-30%. In some embodiments, the probability is 30-40%. In some embodiments, the probability is 40-50%. In some embodiments, the probability is 50-60%. In some embodiments, the probability is 60-70%. In some embodiments, the probability is 70-80%. In some embodiments, the probability is 80-90%. In some embodiments, the probability is 90-100%. Some embodiments include generating a probability for each biomarker. In some embodiments, each biomarker level is multiplied by a separate factor. In some embodiments, the probability for each biomarker level is multiplied by a separate factor. Some embodiments, include generating a probability based on multiple biomarkers (for example, based on 13 biomarkers).

[0074] In some embodiments, at least one biomarker level is weighted. In some embodiments, the weight of a biomarker level is compared to a threshold. In some embodiments, the weight of a biomarker level is assigned by a computer algorithm. In some embodiments, the weight of a biomarker level affects how much a particular biomarker contributes to calculating an EHI score. In some embodiments, the weight of a first biomarker level is less than the weight of a second biomarker level. In such cases, the first biomarker level can be less informative of mucosal healing or the EHI score than the second biomarker. In some embodiments, the weight of a first biomarker level is greater than the weight of a second biomarker level. In such cases, the first biomarker can be more informative of mucosal healing or the EHI score than the second biomarker. In some embodiments, each biomarker is given a separate weight in the mathematical algorithm. For example, the level of one biomarker may have a greater impact on the EHI score than another of biomarker.

[0075] In some embodiments, the weight is 0.01, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2, 3, 4, 5, 6, 7, 8, 9, 10, 50, or 100, in relation to another of the biomarkers. In some embodiments, the weight is 0.01-0.1 in relation to another of the biomarkers. In some embodiments, the weight is 0.1-0.5 in relation to another of the biomarkers. In some embodiments, the weight is 0.5-1 in relation to another of the biomarkers. In some embodiments, the weight is 1-1.5 in relation to another of the biomarkers. In some embodiments, the weight is 1.5-2 in relation to another of the biomarkers. In some embodiments, the weight is 2-10 in relation to another of the biomarkers. In some embodiments, the weight is 10-100 in relation to another of the biomarkers.

[0076] In some embodiments, the a biomarker is weighted such that it contributes 0.01, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2, 3, 4, 5, 6, 7, 8, 9, 10, 50, or 100% of the EHI score.

[0077] Some embodiments of the methods and systems described herein include based on the weight for the probability generated from each biomarker, generating an overall probability of the patient being in endoscopic remission or active disease. In some embodiments, the overall probability is 0%, 1%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 99%, or 100%. In some embodiments, the overall probability is 0-10%. In some embodiments, the overall probability is 10-20%. In some embodiments, the overall probability is 20-30%. In some embodiments, the overall probability is 30-40%. In some embodiments, the overall probability is 40-50%. In some embodiments, the overall probability is 50-60%. In some embodiments, the overall probability is 60-70%. In some embodiments, the overall probability is 70-80%. In some embodiments, the overall probability is 80-90%. In some embodiments, the overall probability is 90-100%.

[0078] Some embodiments include the use of an intermediate value for one or more biomarker levels. In some embodiments, the algorithm converts the level of a biomarker into

an intermediate value for that biomarker. In some embodiments, the algorithm converts the level of multiple biomarkers, or all of the biomarkers, into intermediate values. In some embodiments, the algorithm converts the level of multiple biomarkers into a single intermediate value. For example, in individual intermediate value may be generated by the algorithm for each of one or more of the following groupings of biomarkers: angiogenesis, inflammation, immune signaling, matrix remodeling, growth factor, or cell adhesion. In some embodiments, the intermediate values are converted by the algorithm into the EHI score. In some embodiments, the use of an intermediate value improves the speed of producing the EHI score from the levels, thereby increasing the processing speed of a computer or device implementing the mathematical algorithm. In some embodiments, the use of an intermediate value improves a computer technology or other device.

[0079] Some embodiments include obtaining biomarker levels in a sample from a pediatric patient under 18 years of age and having CD, the biomarkers comprising at least one of Ang1, Ang2, VEGFa, FGF2, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, AREG, ANXA13, EREG, HB-EGF, HGF, TGFb, IL-7, GM-CSF, IL-1b, IL-2, IL-5, IL-6, IL-10, IL-12/23p40, IL-13, IL-15, IL-17a, IL-17f, IL-22, IL-23, IL-31, IL-33, CRP, SAA1, ADA, TWEAK, IFN-g, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, or fibronectin; for each biomarker level, generating a probability of the patient being in endoscopic remission or active disease by applying a model to the biomarker level, the model being derived from a training set of biomarker levels and SES-CD or CDEIS scores using random forest learning classification, logistic regression, quantile classification, ordinary least squares regression, or classification and regression trees; providing a weight for the probability generated from each biomarker; based on the weight for the probability generated from each biomarker, generating an overall probability of the patient being in endoscopic remission or active disease; and multiplying the overall probability by a factor, thereby producing an EHI score for the patient.

[0080] Some embodiments include obtaining biomarker levels in a sample from a pediatric patient under 18 years of age and having CD, the biomarkers comprising at least one of Ang1, Ang2, VEGFa, FGF2, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, AREG, ANXA13, EREG, HB-EGF, HGF, TGFb, IL-7, GM-CSF, IL-1b, IL-2, IL-5, IL-6, IL-10, IL-12/23p40, IL-13, IL-15, IL-17a, IL-17f, IL-22, IL-23, IL-31, IL-33, CRP, SAA1, ADA, TWEAK, IFN-g, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, or

fibronectin; providing a weight for each biomarker level; based on the biomarker levels, and based on the weight for each biomarker level, generating a probability of the patient being in endoscopic remission or active disease by applying a model to the biomarker levels, the model being derived from a training set of biomarker levels and SES-CD or CDEIS scores using random forest learning classification, logistic regression, quantile classification, ordinary least squares regression, or classification and regression trees; based on the weight for the probability generated from each biomarker, generating an overall probability of the patient being in endoscopic remission or active disease; and multiplying the overall probability by a factor, thereby producing an EHI score for the patient.

[0081] The scale of an EHI score can be arbitrary. The scale can be linear or non-linear. In some embodiments, the EHI score has a scale of 01-10 or 0-100. In some embodiments, the EHI score is 1, 10, 20, 30, 40, 50, 60, 70, 80, 90, or 100, or a range of integers defined by any two of the aforementioned integers. In some embodiments, the EHI score is 1-10. In some embodiments, the EHI score is 10-20. In some embodiments, the EHI score is 20-30. In some embodiments, the EHI score is 30-40. In some embodiments, the EHI score is 40-50. In some embodiments, the EHI score is 50-60. In some embodiments, the EHI score is 60-70. In some embodiments, the EHI score is 70-80. In some embodiments, the EHI score is 80-90. In some embodiments, the EHI score is 90-100. In some embodiments, the EHI score is or comprises a factor multiplied by a result or probability of a patient having endoscopically active disease or having moderate to severe disease (as measured by, for example, a CDEIS score). In some embodiments, the factor is 1, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, or 150.

[0082] Some embodiments of the methods described herein include assessing or monitoring mucosal healing based on the biomarker levels. Some embodiments of the methods described herein include assessing or monitoring mucosal healing based on the EHI score. Some embodiments include assessing mucosal healing. In some embodiments, the EHI score or degree of mucosal healing relates to the severity Crohn’s disease symptoms in the patient (e.g. an adult or pediatric patient). In some embodiments, assessing mucosal healing comprises determining that a patient’s mucosa is healing. In some embodiments, assessing mucosal healing comprises determining that a patient’s mucosa is likely healing. In some embodiments, assessing mucosal healing comprises determining that a patient is in clinical remission. In some embodiments, assessing mucosal healing comprises determining that a patient’s mucosa is not healing. In some embodiments, assessing mucosal healing comprises determining that a

patient’s mucosa is likely not healing. For example, assessing mucosal healing may refer to assessing a mucosal inflammation status of the patient, or assessing the mucosal healing status of the patient whether or not the patient’s mucosa is healing. In some embodiments, assessing mucosal healing comprises determining that a patient has clinically active disease.

[0083] Some embodiments include monitoring mucosal healing. In some embodiments, monitoring mucosal healing comprises determining that a patient’s mucosa is healing. In some embodiments, monitoring mucosal healing comprises determining that a patient’s mucosa is likely healing. In some embodiments, monitoring mucosal healing comprises determining that a patient is in clinical remission. In some embodiments, monitoring mucosal healing comprises determining that a patient’s mucosa is not healing. In some embodiments, monitoring mucosal healing comprises determining that a patient’s mucosa is likely not healing. For example, monitoring mucosal healing may refer to monitoring a mucosal inflammation status of the patient, or monitoring the mucosal healing status of the patient whether or not the patient’s mucosa is healing. In some embodiments, monitoring mucosal healing comprises determining that a patient has clinically active disease.

[0084] In some embodiments, the biomarker levels relate to mucosal healing in the subject’s gut mucosa (e.g. an adult or pediatric subject’s gut mucosa). In some embodiments, the EHI score or degree of mucosal healing relates to mucosal healing in the subject’s gut mucosa. In some embodiments, the EHI score or degree of mucosal healing relates to mucosal healing in the subject’s ileum. In some embodiments, the ileum comprises the terminal ileum. In some embodiments, the EHI score or degree of mucosal healing relates to mucosal healing in the subject’s colon. In some embodiments, the EHI score or degree of mucosal healing relates to a degree of mucosal inflammation.

[0085] In some embodiments, the biomarker levels more accurately assess or monitor mucosal healing or a clinical status than another method of assessing or monitoring mucosal healing or the clinical status. In some embodiments, the EHI score more accurately assesses or monitors mucosal healing or a clinical status than another method of assessing or monitoring mucosal healing or the clinical status. For example, the EHI score may more accurately assess mucosal healing or a clinical status than a single biomarker level. In some embodiments, the EHI score more accurately assesses mucosal healing or a clinical status than CRP levels such as CRP serum levels.

[0086] In some embodiments, the EHI score has a scale of 0-100. In some embodiments, the patient (e.g. an adult or pediatric patient) is in remission or has mild endoscopic disease when the EHI is between 0-40. In some embodiments, the patient is in remission or has mild endoscopic disease when the EHI is between 0-20. Some embodiments include determining that the patient is likely to be in remission or have mild endoscopic disease when the EHI score is less than or equal to 40 on a scale from 0 to 100. Some embodiments include identifying the patient as being in remission or having mild endoscopic disease when the EHI score is less than or equal to 40. Some embodiments include determining that the patient is likely to be in remission or have mild endoscopic disease when the EHI score is less than or equal to 20 on a scale from 0 to 100.

[0087] In some embodiments, the patient has endoscopically active disease when the EHI is between 50-100. Some embodiments include determining that the patient is likely to have endoscopically active disease when the EHI score is greater than or equal to 50 on a scale from 0 to 100. Some embodiments include identifying the patient as having endoscopically active disease when the EHI score is greater than or equal to 50.

[0088] In some embodiments, the patient has a moderate probability of having endoscopically active disease when the EHI score is between 40-50. In some embodiments, the patient has a moderate probability of having endoscopically active disease when the EHI score is between 20-50. Some embodiments include determining that the patient has a moderate probability of having endoscopically active disease, or identifying the patient as having a moderate probability of having endoscopically active disease, when the EHI score is between 40 and 50 on a scale from 0 to 100. Some embodiments include determining that the patient has a moderate probability of having endoscopically active disease, or identifying the patient as having a moderate probability of having endoscopically active disease, when the EHI score is between 20 and 50 on a scale from 0 to 100.

[0089] Some embodiments include determining that the patient is in remission or has mild endoscopic disease if the EHI is between 0-40, that the patient has a moderate probability of having endoscopically active disease if the EHI score is between 40-50, and that the patient has endoscopically active disease if the EHI is between 50-100. Some embodiments include determining that the patient is in remission or has mild endoscopic disease if the EHI is between 0-20, that the patient has a moderate probability of having endoscopically active disease if the EHI score is between 20-50, and that the patient has endoscopically active disease if the EHI is between 50-100.

[0090] Some embodiments include determining that the patient is likely to be in remission or have mild endoscopic disease if the EHI is between 0-40, that the patient likely has a moderate probability of having endoscopically active disease if the EHI score is between 40-50, and that the patient likely has endoscopically active disease if the EHI is between 50-100. Some embodiments include determining that the patient is likely to be in remission or have mild endoscopic disease if the EHI is between 0-20, that the patient likely has a moderate probability of having endoscopically active disease if the EHI score is between 20-50, and that the patient likely has endoscopically active disease if the EHI is between 50-100.

[0091] Some embodiments include applying a mathematical algorithm to the of one or more biomarkers as described to produce an EHI for the patient, wherein the EHI has a scale of 0-100, wherein the patient is in remission or has mild endoscopic disease when the EHI is between 0-40, and wherein the patient has endoscopically active disease when the EHI is between 50-100. Some embodiments include applying a mathematical algorithm to the of one or more biomarkers as described to produce an EHI for the patient, wherein the EHI is a scale of 0-100, wherein the patient is in remission or has mild endoscopic disease when the EHI is between 0-20, and wherein the patient has endoscopically active disease when the EHI is between 50-100.

[0092] Some embodiments include (a) detecting the of the following biomarkers in a serum sample from the patient: Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7; and (b) applying a mathematical algorithm to the of the biomarkers in step (a) to produce an EHI for the patient, wherein the EHI is a scale of 0-100, wherein the patient is in remission or has mild endoscopic disease when the EHI is between 0-40, and wherein the patient has endoscopically active disease when the EHI is between 50-100.

[0093] In some embodiments, a biomarker level or measurement (for example, an angiogenesis biomarker measurement, an inflammation biomarker measurement, an immune signaling biomarker measurement, a matrix remodeling biomarker measurement, a growth factor biomarker measurement, or a cell adhesion biomarker measurement) is informative of a Crohn's disease endoscopic index of severity (CDEIS) score. In some embodiments, a range of biomarker levels is informative of a CDEIS score. In some embodiments, a biomarker level

above an index or control biomarker level is informative of a CDEIS score. In some embodiments, a biomarker level below an index or control biomarker level is informative of a CDEIS score. In some embodiments, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 biomarker levels are informative of a CDEIS score. In some embodiments, an increase in 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 biomarker levels are informative of a CDEIS score. Alternatively or in addition, in some embodiments, a decrease in 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 biomarker levels are informative of a CDEIS score.

[0094] In some embodiments, CDEIS score is informative or indicative of mucosal healing or inflammation/mucosal disease. In some embodiments, CDEIS Scores CD lesions. In some embodiments, CDEIS score is time-consuming, complicated, and not well suited for routine clinical practice. In some embodiments, the biomarkers and/or EHI score replace or can be used in conjunction with CDEIS score. For example, the biomarkers levels and/or EHI score may be indicative of mucosal healing or inflammation/mucosal disease, and correspond with a CDEIS score or CDEIS score range, but may be easier and faster to generate, and less invasive since they may be obtained without the need for an endoscopy. In some embodiments, CDEIS score has a range of 0 to 44. In some embodiments, CDEIS score comprises a score of 1, 2, 3, 4, 5, or 6 variables. In some embodiments, the variables include presence of deep ulcers. In some embodiments, the variables include presence of superficial ulcers. In some embodiments, the variables include non-ulcerated stenosis. In some embodiments, the variables include ulcerated stenosis. In some embodiments, the variables include proportion of ulcerated surface. In some embodiments, the variables include proportion of ulcerated surface affected by disease. In some embodiments, the ulcers are evaluated based on depth. In some embodiments, the CDEIS score takes into account a number of ileocolonic segments explored as the score summation is divided by the number of segments evaluated.

[0095] In some embodiments, a biomarker level or measurement (for example, an angiogenesis biomarker measurement, an inflammation biomarker measurement, an immune signaling biomarker measurement, a matrix remodeling biomarker measurement, a growth factor biomarker measurement, or a cell adhesion biomarker measurement) is informative of mucosal healing. In some embodiments, a range of biomarker levels is informative of mucosal healing. In some embodiments, a biomarker level above an index or control biomarker level is informative of mucosal healing. In some embodiments, a biomarker level below an index or

control biomarker level is informative of mucosal healing. In some embodiments, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 biomarker levels are informative of mucosal healing. In some embodiments, an increase in a biomarker level is informative of mucosal healing. In some embodiments, a decrease in a biomarker level is informative of mucosal healing. In some embodiments an increase 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 biomarker levels are informative of mucosal healing. Alternatively or in addition, in some embodiments a decrease 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 biomarker levels are informative of mucosal healing.

[0096] In some embodiments, a biomarker level or measurement (for example, an angiogenesis biomarker measurement, an inflammation biomarker measurement, an immune signaling biomarker measurement, a matrix remodeling biomarker measurement, a growth factor biomarker measurement, or a cell adhesion biomarker measurement) is informative of mucosal inflammation. In some embodiments, a range of biomarker levels is informative of mucosal inflammation. In some embodiments, a biomarker level above an index or control biomarker level is informative of mucosal inflammation. In some embodiments, a biomarker level below an index or control biomarker level is informative of mucosal inflammation. In some embodiments, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 biomarker levels are informative of mucosal inflammation. In some embodiments, an increase in a biomarker level is informative of mucosal inflammation. In some embodiments, a decrease in a biomarker level is informative of mucosal inflammation. In some embodiments, an increase in 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 biomarker levels is informative of mucosal inflammation. Alternatively or in addition, in some embodiments, a decrease in 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 biomarker levels is informative of mucosal inflammation.

[0097] In some embodiments, a biomarker level or measurement (for example, an angiogenesis biomarker measurement, an inflammation biomarker measurement, an immune signaling biomarker measurement, a matrix remodeling biomarker measurement, a growth factor biomarker measurement, or a cell adhesion biomarker measurement) is informative of an EHI score. In some embodiments, a range of biomarker levels is informative of an EHI score. In some embodiments, a biomarker level above an index or control biomarker level is informative of an EHI score. In some embodiments, a biomarker level below an index or

control biomarker level is informative of an EHI score. In some embodiments, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 biomarker levels are informative of an EHI score. In some embodiments, an increase in a biomarker level is informative of an EHI score. In some embodiments, a decrease in a biomarker level is informative of an EHI score. In some embodiments an increase in 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 biomarker levels are informative of an EHI score. Alternatively or in addition, in some embodiments a decrease in 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, or 24 biomarker levels are informative of an EHI score.

[0098] In some embodiments, an EHI score is informative of a CDEIS score. In some embodiments, a range of EHI scores is informative of a CDEIS score. In some embodiments, an EHI score above a threshold EHI score is informative of a CDEIS score. In some embodiments, an EHI score below an threshold EHI score is informative of a CDEIS score. In some embodiments, an increase in an EHI score is informative of a CDEIS score. In some embodiments, a decrease in an EHI score is informative of a CDEIS score.

[0099] In some embodiments, an EHI score is informative of mucosal healing. In some embodiments, a range of EHI scores is informative of mucosal healing. In some embodiments, an EHI score above a threshold EHI score is informative of mucosal healing. In some embodiments, an EHI score below an threshold EHI score is informative of mucosal healing. In some embodiments, an increase in an EHI score is informative of mucosal healing. In some embodiments, a decrease in an EHI score is informative of mucosal healing.

[0100] In some embodiments, an EHI score is informative of mucosal inflammation. In some embodiments, a range of EHI scores is informative of mucosal inflammation. In some embodiments, an EHI score above a threshold EHI score is informative of mucosal inflammation. In some embodiments, an EHI score below an threshold EHI score is informative of mucosal inflammation. In some embodiments, an increase in an EHI score is informative of mucosal inflammation. In some embodiments, a decrease in an EHI score is informative of mucosal inflammation.

[0101] In some embodiments, a biomarker measurement (for example, an angiogenesis biomarker measurement, an inflammation biomarker measurement, an immune signaling biomarker measurement, a matrix remodeling biomarker measurement, a growth factor biomarker measurement, or a cell adhesion biomarker measurement) that is less than the

reference or control biomarker measurement is indicative of mucosal healing. In some embodiments, a biomarker measurement that is greater than the reference or control biomarker measurement is indicative of mucosal inflammation. In some embodiments, a biomarker measurement that is less than the reference or control biomarker measurement is incorporated into the score to decrease the EHI score. In some embodiments, a biomarker measurement that is greater than the reference or control biomarker measurement is incorporated into the score to increase the EHI score. In some embodiments, a biomarker measurement that is less than or equal to a reference value is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission. In some embodiments, a biomarker measurement that is less than a reference range is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission. In some embodiments, a biomarker measurement that is less than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score below 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13, or below a range of CDEIS Scores defined by any two of the aforementioned CDEIS Scores. In some embodiments, a biomarker measurement that is greater than a reference value is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a biomarker measurement that is greater than a reference range is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a biomarker measurement that is greater than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or more, or equivalent to a range of CDEIS scores defined by any two of the aforementioned CDEIS Scores. In some embodiments, the EHI score incorporates multiple biomarker measurements.

[0102] In some embodiments, a biomarker measurement (for example, a matrix remodeling biomarker measurement) that is greater than the reference or control biomarker measurement is indicative of mucosal healing. In some embodiments, a biomarker measurement that is less than the reference or control biomarker measurement is indicative of mucosal inflammation. In some embodiments, a biomarker measurement that is greater than the reference or control biomarker measurement is incorporated into the score to decrease the EHI score. In some embodiments, a biomarker measurement that is less than the reference or control biomarker measurement is incorporated into the score to increase the EHI score. In some embodiments, a

biomarker measurement that is greater than or equal to a reference value is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission. In some embodiments, a biomarker measurement that is greater than a reference range is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission. In some embodiments, a biomarker measurement that is greater than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score below 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13, or below a range of CDEIS scores defined by any two of the aforementioned CDEIS scores. In some embodiments, a biomarker measurement that is less than a reference value is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a biomarker measurement that is less than a reference range is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a biomarker measurement that is less than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or more, or equivalent to a range of CDEIS Scores defined by any two of the aforementioned CDEIS scores. In some embodiments, the EHI score incorporates multiple biomarker measurements.

[0103] In some embodiments, a Ang1 biomarker measurement that is less than the reference or control Ang1 biomarker measurement is indicative of mucosal healing. In some embodiments, a Ang1 biomarker measurement that is greater than the reference or control Ang1 biomarker measurement is indicative of mucosal inflammation. In some embodiments, a Ang1 biomarker measurement that is less than the reference or control Ang1 biomarker measurement is incorporated into the score to decrease the EHI score. In some embodiments, a Ang1 biomarker measurement that is greater than the reference or control Ang1 biomarker measurement is incorporated into the score to increase the EHI score. In some embodiments, a Ang1 biomarker measurement that is less than or equal to 451 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission.

[0104] In some embodiments, a Ang1 biomarker level at about 1-200 U/mL is informative of a CDEIS score of 1. In some embodiments, a Ang1 biomarker level at about 201-451 U/mL is informative of a CDEIS score of 2. In some embodiments, a Ang1 biomarker level at about 452-475 U/mL is informative of a CDEIS score of 3. In some embodiments, a Ang1 biomarker level at about 476-500 U/mL is informative of a CDEIS score of 4. In some embodiments, a

Ang1 biomarker level at about 500-550 U/mL is informative of a CDEIS score of 5. In some embodiments, a Ang1 biomarker level at about 550-600 U/mL is informative of a CDEIS score of 6. In some embodiments, a Ang1 biomarker level at about 600-650 U/mL is informative of a CDEIS score of 7. In some embodiments, a Ang1 biomarker level at about 650-700 U/mL is informative of a CDEIS score of 8. In some embodiments, a Ang1 biomarker level at about 700-750 U/mL is informative of a CDEIS score of 9. In some embodiments, a Ang1 biomarker level at about 750-800 U/mL is informative of a CDEIS score of 10. In some embodiments, a Ang1 biomarker level at about 800-850 U/mL is informative of a CDEIS score of 11. In some embodiments, a Ang1 biomarker level at about 850-900 U/mL is informative of a CDEIS score of 12. In some embodiments, a Ang1 biomarker level at about 900-950 U/mL is informative of a CDEIS score of 13. In some embodiments, a Ang1 biomarker level at about 950-1000 U/mL is informative of a CDEIS score of 14. In some embodiments, a Ang1 biomarker level at about 1000-1050 U/mL is informative of a CDEIS score of 15. In some embodiments, a Ang1 biomarker level at about 1050-1100 U/mL is informative of a CDEIS score of 16. In some embodiments, a Ang1 biomarker level at about 1100-1150 U/mL is informative of a CDEIS score of 17. In some embodiments, a Ang1 biomarker level at about 1150-1200 U/mL is informative of a CDEIS score of 18. In some embodiments, a Ang1 biomarker level at about 1200-1250 U/mL is informative of a CDEIS score of 19. In some embodiments, a Ang1 biomarker level at about 1250-1300 U/mL is informative of a CDEIS score of 20. In some embodiments, a Ang1 biomarker level greater than 1300 is informative of a CDEIS score range from about 21 to 44.

[0105] In some embodiments, a Ang1 biomarker measurement that is less than 350, 375, 400, 425, 450, 475, 500, 525, or 550 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission. In some embodiments, a Ang1 biomarker measurement that is less than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score below 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13, or below a range of CDEIS Scores defined by any two of the aforementioned CDEIS Scores. In some embodiments, a Ang1 biomarker measurement that is greater than 451 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a Ang1 biomarker measurement that is greater than 425-475 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe

endoscopic disease activity. In some embodiments, a Ang1 biomarker measurement that is greater than 350, 375, 400, 425, 450, 475, 500, 525, or 550 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a Ang1 biomarker measurement that is greater than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or more, or equivalent to a range of CDEIS scores defined by any two of the aforementioned CDEIS scores.

[0106] In some embodiments, a Ang2 biomarker measurement that is less than the reference or control Ang2 biomarker measurement is indicative of mucosal healing. In some embodiments, a Ang2 biomarker measurement that is greater than the reference or control Ang2 biomarker measurement is indicative of mucosal inflammation. In some embodiments, a Ang2 biomarker measurement that is less than the reference or control Ang2 biomarker measurement is incorporated into the score to decrease the EHI score. In some embodiments, a Ang2 biomarker measurement that is greater than the reference or control Ang2 biomarker measurement is incorporated into the score to increase the EHI score. In some embodiments, a Ang2 biomarker measurement that is less than or equal to 266 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission.

[0107] In some embodiments, a Ang2 biomarker level at about 1-100 U/mL is informative of a CDEIS score of 1. In some embodiments, a Ang2 biomarker level at about 101-266 U/mL is informative of a CDEIS score of 2. In some embodiments, a Ang2 biomarker level at about 267-290 U/mL is informative of a CDEIS score of 3. In some embodiments, a Ang2 biomarker level at about 291-315 U/mL is informative of a CDEIS score of 4. In some embodiments, a Ang2 biomarker level at about 315-365 U/mL is informative of a CDEIS score of 5. In some embodiments, a Ang2 biomarker level at about 365-415 U/mL is informative of a CDEIS score of 6. In some embodiments, a Ang2 biomarker level at about 415-465 U/mL is informative of a CDEIS score of 7. In some embodiments, a Ang2 biomarker level at about 465-515 U/mL is informative of a CDEIS score of 8. In some embodiments, a Ang2 biomarker level at about 515-565 U/mL is informative of a CDEIS score of 9. In some embodiments, a Ang2 biomarker level at about 565-615 U/mL is informative of a CDEIS score of 10. In some embodiments, a Ang2 biomarker level at about 615-665 U/mL is informative of a CDEIS score of 11. In some embodiments, a Ang2 biomarker level at about 665-715 U/mL is informative of a CDEIS score of 12. In some embodiments, a Ang2 biomarker level at about 715-765 U/mL is informative of

a CDEIS score of 13. In some embodiments, a Ang2 biomarker level at about 765-815 U/mL is informative of a CDEIS score of 14. In some embodiments, a Ang2 biomarker level at about 815-865 U/mL is informative of a CDEIS score of 15. In some embodiments, a Ang2 biomarker level at about 865-915 U/mL is informative of a CDEIS score of 16. In some embodiments, a Ang2 biomarker level at about 915-965 U/mL is informative of a CDEIS score of 17. In some embodiments, a Ang2 biomarker level at about 965-1015 U/mL is informative of a CDEIS score of 18. In some embodiments, a Ang2 biomarker level at about 1015-1065 U/mL is informative of a CDEIS score of 19. In some embodiments, a Ang2 biomarker level at about 1065-1115 U/mL is informative of a CDEIS score of 20. In some embodiments, a Ang2 biomarker level greater than 1115 U/mL is informative of a CDEIS score range from 21 to 44.

[0108] In some embodiments, a Ang2 biomarker measurement that is less than 150, 175, 200, 225, 250, 275, 300, 325, or 350 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission. In some embodiments, a Ang2 biomarker measurement that is less than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score below 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13, or below a range of CDEIS Scores defined by any two of the aforementioned CDEIS Scores. In some embodiments, a Ang2 biomarker measurement that is greater than 266 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a Ang2 biomarker measurement that is greater than 240-290 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a Ang2 biomarker measurement that is greater than 150, 175, 200, 225, 250, 275, 300, 325, or 350 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a Ang2 biomarker measurement that is greater than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or more, or equivalent to a range of CDEIS scores defined by any two of the aforementioned CDEIS scores.

[0109] In some embodiments, a CEACAM1 biomarker measurement that is less than the reference or control CEACAM1 biomarker measurement is indicative of mucosal healing. In some embodiments, a CEACAM1 biomarker measurement that is greater than the reference or control CEACAM1 biomarker measurement is indicative of mucosal inflammation. In some

embodiments, a CEACAM1 biomarker measurement that is less than the reference or control CEACAM1 biomarker measurement is incorporated into the score to decrease the EHI score. In some embodiments, a CEACAM1 biomarker measurement that is greater than the reference or control CEACAM1 biomarker measurement is incorporated into the score to increase the EHI score. In some embodiments, a CEACAM1 biomarker measurement that is less than or equal to 208 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission.

[0110] In some embodiments, a CEACAM1 biomarker level at about 1-100 U/mL is informative of a CDEIS score of 1. In some embodiments, a CEACAM1 biomarker level at about 100-208 U/mL is informative of a CDEIS score of 2. In some embodiments, a CEACAM1 biomarker level at about 209-225 U/mL is informative of a CDEIS score of 3. In some embodiments, a CEACAM1 biomarker level at about 226-258 U/mL is informative of a CDEIS score of 4. In some embodiments, a CEACAM1 biomarker level at about 258-308 U/mL is informative of a CDEIS score of 5. In some embodiments, a CEACAM1 biomarker level at about 308-358 U/mL is informative of a CDEIS score of 6. In some embodiments, a CEACAM1 biomarker level at about 358-408 U/mL is informative of a CDEIS score of 7. In some embodiments, a CEACAM1 biomarker level at about 408-458 U/mL is informative of a CDEIS score of 8. In some embodiments, a CEACAM1 biomarker level at about 458-508 U/mL is informative of a CDEIS score of 9. In some embodiments, a CEACAM1 biomarker level at about 508-558 U/mL is informative of a CDEIS score of 10. In some embodiments, a CEACAM1 biomarker level at about 558-608 U/mL is informative of a CDEIS score of 11. In some embodiments, a CEACAM1 biomarker level at about 608-658 U/mL is informative of a CDEIS score of 12. In some embodiments, a CEACAM1 biomarker level at about 658-708 U/mL is informative of a CDEIS score of 13. In some embodiments, a CEACAM1 biomarker level at about 708-758 U/mL is informative of a CDEIS score of 14. In some embodiments, a CEACAM1 biomarker level at about 758-808 U/mL is informative of a CDEIS score of 15. In some embodiments, a CEACAM1 biomarker level at about 808-858 U/mL is informative of a CDEIS score of 16. In some embodiments, a CEACAM1 biomarker level at about 858-908 U/mL is informative of a CDEIS score of 17. In some embodiments, a CEACAM1 biomarker level at about 908-958 U/mL is informative of a CDEIS score of 18. In some embodiments, a CEACAM1 biomarker level at about 958-1008 U/mL is informative of a CDEIS score of 19. In some embodiments, a CEACAM1 biomarker level at about 1008-1058 U/mL is informative of a CDEIS score of 20. In some embodiments, a CEACAM1 biomarker level greater than 1058 U/mL is informative of a CDEIS score range from 21 to 44.

[0111] In some embodiments, a CEACAM1 biomarker measurement that is less than 100, 125, 150, 175, 200, 225, 250, 275, or 300 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission. In some embodiments, a CEACAM1 biomarker measurement that is less than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score below 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13, or below a range of CDEIS Scores defined by any two of the aforementioned CDEIS Scores. In some embodiments, a CEACAM1 biomarker measurement that is greater than 208 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a CEACAM1 biomarker measurement that is greater than 185-235 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a CEACAM1 biomarker measurement that is greater than 100, 125, 150, 175, 200, 225, 250, 275, or 300 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a CEACAM1 biomarker measurement that is greater than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or more, or equivalent to a range of CDEIS scores defined by any two of the aforementioned CDEIS scores.

[0112] In some embodiments, a VCAM1 biomarker measurement that is less than the reference or control VCAM1 biomarker measurement is indicative of mucosal healing. In some embodiments, a VCAM1 biomarker measurement that is greater than the reference or control VCAM1 biomarker measurement is indicative of mucosal inflammation. In some embodiments, a VCAM1 biomarker measurement that is less than the reference or control VCAM1 biomarker measurement is incorporated into the score to decrease the EHI score. In some embodiments, a VCAM1 biomarker measurement that is greater than the reference or control VCAM1 biomarker measurement is incorporated into the score to increase the EHI score. In some embodiments, a VCAM1 biomarker measurement that is less than or equal to 358 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission.

[0113] In some embodiments, a VCAM1 biomarker level at about 1-200 U/mL is informative of a CDEIS score of 1. In some embodiments, a VCAM1 biomarker level at about 200-358 U/mL is informative of a CDEIS score of 2. In some embodiments, a VCAM1 biomarker level at about 359-380 U/mL is informative of a CDEIS score of 3. In some embodiments, a VCAM1 biomarker level at about 381-408 U/mL is informative of a CDEIS score of 4. In some embodiments, a VCAM1 biomarker level at about 408-458 U/mL is informative of a CDEIS score of 5. In some embodiments, a VCAM1 biomarker level at about 458-508 U/mL is informative of a CDEIS score of 6. In some embodiments, a VCAM1 biomarker level at about 508-558 U/mL is informative of a CDEIS score of 7. In some embodiments, a VCAM1 biomarker level at about 558-608 U/mL is informative of a CDEIS score of 8. In some embodiments, a VCAM1 biomarker level at about 608-658 U/mL is informative of a CDEIS score of 9. In some embodiments, a VCAM1 biomarker level at about 658-708 U/mL is informative of a CDEIS score of 10. In some embodiments, a VCAM1 biomarker level at about 708-758 U/mL is informative of a CDEIS score of 11. In some embodiments, a VCAM1 biomarker level at about 758-808 U/mL is informative of a CDEIS score of 12. In some embodiments, a VCAM1 biomarker level at about 808-858 U/mL is informative of a CDEIS score of 13. In some embodiments, a VCAM1 biomarker level at about 858-908 U/mL is informative of a CDEIS score of 14. In some embodiments, a VCAM1 biomarker level at about 908-958 U/mL is informative of a CDEIS score of 15. In some embodiments, a VCAM1 biomarker level at about 958-1008 U/mL is informative of a CDEIS score of 16. In some embodiments, a VCAM1 biomarker level at about 1008-1058 U/mL is informative of a CDEIS score of 17. In some embodiments, a VCAM1 biomarker level at about 1058-1108 U/mL is informative of a CDEIS score of 18. In some embodiments, a VCAM1 biomarker level at about 1108-1158 U/mL is informative of a CDEIS score of 19. In some embodiments, a VCAM1 biomarker level at about 1158-1208 U/mL is informative of a CDEIS score of 20. In some embodiments, a VCAM1 biomarker level greater than 1208 U/mL is informative of a CDEIS score range from 21 to 44.

[0114] In some embodiments, a VCAM1 biomarker measurement that is less than 200, 225, 250, 275, 300, 325, 350, 375, or 400 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission. In some embodiments, a VCAM1 biomarker measurement that is less than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score below 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13, or below a range of CDEIS Scores defined by any two of the aforementioned CDEIS Scores. In some embodiments, a VCAM1 biomarker measurement that is greater than 358 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a VCAM1 biomarker measurement that is greater than 335-385 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a VCAM1 biomarker measurement that is greater than 200, 225, 250, 275, 300, 325, 350, 375, or 400 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a VCAM1 biomarker measurement that is greater than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or more, or equivalent to a range of CDEIS scores defined by any two of the aforementioned CDEIS scores.

[0115] In some embodiments, a CRP biomarker measurement that is less than the reference or control CRP biomarker measurement is indicative of mucosal healing. In some embodiments, a CRP biomarker measurement that is greater than the reference or control CRP biomarker measurement is indicative of mucosal inflammation. In some embodiments, a CRP biomarker measurement that is less than the reference or control CRP biomarker measurement is incorporated into the score to decrease the EHI score. In some embodiments, a CRP biomarker measurement that is greater than the reference or control CRP biomarker measurement is incorporated into the score to increase the EHI score. In some embodiments, a CRP biomarker measurement that is less than or equal to 5 mg/L is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission.

[0116] In some embodiments, a CRP biomarker level at about 1-3 mg/L is informative of a CDEIS score of 1. In some embodiments, a CRP biomarker level at about 4-5 mg/L is informative of a CDEIS score of 2. In some embodiments, a CRP biomarker level at about 6 mg/L is informative of a CDEIS score of 3. In some embodiments, a CRP biomarker level at about 7 mg/L is informative of a CDEIS score of 4. In some embodiments, a CRP biomarker level at about 8 mg/L is informative of a CDEIS score of 5. In some embodiments, a CRP biomarker level at about 9 mg/L is informative of a CDEIS score of 6. In some embodiments, a CRP biomarker level at about 10 mg/L is informative of a CDEIS score of 7. In some

embodiments, a CRP biomarker level at about 11 mg/L is informative of a CDEIS score of 8. In some embodiments, a CRP biomarker level at about 12 mg/L is informative of a CDEIS score of 9. In some embodiments, a CRP biomarker level at about 13 mg/L is informative of a CDEIS score of 10. In some embodiments, a CRP biomarker level at about 14 mg/L is informative of a CDEIS score of 11. In some embodiments, a CRP biomarker level at about 15 mg/L is informative of a CDEIS score of 12. In some embodiments, a CRP biomarker level at about 16 mg/L is informative of a CDEIS score of 13. In some embodiments, a CRP biomarker level at about 17 mg/L is informative of a CDEIS score of 14. In some embodiments, a CRP biomarker level at about 18 mg/L is informative of a CDEIS score of 15. In some embodiments, a CRP biomarker level at about 19 mg/L is informative of a CDEIS score of 16. In some embodiments, a CRP biomarker level at about 20 mg/L is informative of a CDEIS score of 17. In some embodiments, a CRP biomarker level at about 21 mg/L is informative of a CDEIS score of 18. In some embodiments, a CRP biomarker level at about 22 mg/L is informative of a CDEIS score of 19. In some embodiments, a CRP biomarker level at about 23 mg/L is informative of a CDEIS score of 20. In some embodiments, a CRP biomarker level greater than about 24 mg/L is informative of a CDEIS score range from 21 to 44.

[0117] In some embodiments, a CRP biomarker measurement that is less than 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, or 7 mg/L is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission. In some embodiments, a CRP biomarker measurement that is less than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score below 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13, or below a range of CDEIS Scores defined by any two of the aforementioned CDEIS Scores. In some embodiments, a CRP biomarker measurement that is greater than 5 mg/L is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a CRP biomarker measurement that is greater than 4-6 mg/L is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a CRP biomarker measurement that is greater than 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, or 7 mg/L is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a CRP biomarker measurement that is greater than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or more, or equivalent to a range of CDEIS scores defined by any two of the aforementioned CDEIS scores.

[0118] In some embodiments, a SAA1 biomarker measurement that is less than the reference or control SAA1 biomarker measurement is indicative of mucosal healing. In some embodiments, a SAA1 biomarker measurement that is greater than the reference or control SAA1 biomarker measurement is indicative of mucosal inflammation. In some embodiments, a SAA1 biomarker measurement that is less than the reference or control SAA1 biomarker measurement is incorporated into the score to decrease the EHI score. In some embodiments, a SAA1 biomarker measurement that is greater than the reference or control SAA1 biomarker measurement is incorporated into the score to increase the EHI score. In some embodiments, a SAA1 biomarker measurement that is less than or equal to 16 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission.

[0119] In some embodiments, a SAA1 biomarker level at about 1-9 U/mL is informative of a CDEIS score of 1. In some embodiments, a SAA1 biomarker level at about 10-13 U/mL is informative of a CDEIS score of 2. In some embodiments, a SAA1 biomarker level at about 17 U/mL is informative of a CDEIS score of 3. In some embodiments, a SAA1 biomarker level at about 18-19 U/mL is informative of a CDEIS score of 4. In some embodiments, a SAA1 biomarker level at about 19-22 U/mL is informative of a CDEIS score of 5. In some embodiments, a SAA1 biomarker level at about 22-25 U/mL is informative of a CDEIS score of 6. In some embodiments, a SAA1 biomarker level at about 25-28 U/mL is informative of a CDEIS score of 7. In some embodiments, a SAA1 biomarker level at about 28-31 U/mL is informative of a CDEIS score of 8. In some embodiments, a SAA1 biomarker level at about 31-34 U/mL is informative of a CDEIS score of 9. In some embodiments, a SAA1 biomarker level at about 34-37 U/mL is informative of a CDEIS score of 10. In some embodiments, a SAA1 biomarker level at about 37-40 U/mL is informative of a CDEIS score of 11. In some embodiments, a SAA1 biomarker level at about 40-43 U/mL is informative of a CDEIS score of 12. In some embodiments, a SAA1 biomarker level at about 43-46 U/mL is informative of a CDEIS score of 13. In some embodiments, a SAA1 biomarker level at about 46-49 U/mL is informative of a CDEIS score of 14. In some embodiments, a SAA1 biomarker level at about 49-52 U/mL is informative of a CDEIS score of 15. In some embodiments, a SAA1 biomarker level at about 52-55 U/mL is informative of a CDEIS score of 16. In some embodiments, a SAA1 biomarker level at about 55-58 U/mL is informative of a CDEIS score of 17. In some embodiments, a SAA1 biomarker level at about 58-61 U/mL is informative of a CDEIS score of 18. In some embodiments, a SAA1 biomarker level at about 61-64 U/mL is informative of a CDEIS score of 19. In some embodiments, a SAA1 biomarker level at about 64-67 U/mL is informative of a CDEIS score of 20. In some embodiments, a SAA1 biomarker level greater than 67 U/mL is informative of a CDEIS score range from 21 to 44.

[0120] In some embodiments, a SAA1 biomarker measurement that is less than 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, or 21 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission. In some embodiments, a SAA1 biomarker measurement that is less than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score below 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13, or below a range of CDEIS Scores defined by any two of the aforementioned CDEIS Scores. In some embodiments, a SAA1 biomarker measurement that is greater than 16 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a SAA1 biomarker measurement that is greater than 13-19 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a SAA1 biomarker measurement that is greater than 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, or 21 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a SAA1 biomarker measurement that is greater than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or more, or equivalent to a range of CDEIS scores defined by any two of the aforementioned CDEIS scores.

[0121] In some embodiments, a IL-7 biomarker measurement that is less than the reference or control IL-7 biomarker measurement is indicative of mucosal healing. In some embodiments, a IL-7 biomarker measurement that is greater than the reference or control IL-7 biomarker measurement is indicative of mucosal inflammation. In some embodiments, a IL-7 biomarker measurement that is less than the reference or control IL-7 biomarker measurement is incorporated into the score to decrease the EHI score. In some embodiments, a IL-7 biomarker measurement that is greater than the reference or control IL-7 biomarker measurement is incorporated into the score to increase the EHI score. In some embodiments, a

IL-7 biomarker measurement that is less than or equal to 302 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission.

[0122] In some embodiments, a IL-7 biomarker level at about 1-100 U/mL is informative of a CDEIS score of 1. In some embodiments, a IL-7 biomarker level at about 101-302 U/mL is informative of a CDEIS score of 2. In some embodiments, a IL-7 biomarker level at about 303-325 U/mL is informative of a CDEIS score of 3. In some embodiments, a IL-7 biomarker level at about 326-352 U/mL is informative of a CDEIS score of 4. In some embodiments, a IL-7 biomarker level at about 352-402 U/mL is informative of a CDEIS score of 5. In some embodiments, a IL-7 biomarker level at about 402-452 U/mL is informative of a CDEIS score of 6. In some embodiments, a IL-7 biomarker level at about 452-502 U/mL is informative of a CDEIS score of 7. In some embodiments, a IL-7 biomarker level at about 502-552 U/mL is informative of a CDEIS score of 8. In some embodiments, a IL-7 biomarker level at about 552-602 U/mL is informative of a CDEIS score of 9. In some embodiments, a IL-7 biomarker level at about 602-652 U/mL is informative of a CDEIS score of 10. In some embodiments, a IL-7 biomarker level at about 652-702 U/mL is informative of a CDEIS score of 11. In some embodiments, a IL-7 biomarker level at about 702-752 U/mL is informative of a CDEIS score of 12. In some embodiments, a IL-7 biomarker level at about 752-802 U/mL is informative of a CDEIS score of 13. In some embodiments, a IL-7 biomarker level at about 802-852 U/mL is informative of a CDEIS score of 14. In some embodiments, a IL-7 biomarker level at about 852-902 U/mL is informative of a CDEIS score of 15. In some embodiments, a IL-7 biomarker level at about 902-952 U/mL is informative of a CDEIS score of 16. In some embodiments, a IL-7 biomarker level at about 952-1002 U/mL is informative of a CDEIS score of 17. In some embodiments, a IL-7 biomarker level at about 1002-1052 U/mL is informative of a CDEIS score of 18. In some embodiments, a IL-7 biomarker level at about 1052-1102 U/mL is informative of a CDEIS score of 19. In some embodiments, a IL-7 biomarker level at about 1102-1152 U/mL is informative of a CDEIS score of 20. In some embodiments, a IL-7 biomarker level greater than 1152 U/mL is informative of a CDEIS score range from 21 to 44.

[0123] In some embodiments, a IL-7 biomarker measurement that is less than 200, 225, 250, 275, 300, 325, 350, 375, or 400 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission. In some embodiments, a IL-7 biomarker measurement that is less than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score below 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13, or below a range of CDEIS Scores defined by any two of the aforementioned CDEIS Scores. In some embodiments, a IL-7 biomarker measurement that is greater than 302 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a IL-7 biomarker measurement that is greater than 275-325 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a IL-7 biomarker measurement that is greater than 200, 225, 250, 275, 300, 325, 350, 375, or 400 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a IL-7 biomarker measurement that is greater than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or more, or equivalent to a range of CDEIS scores defined by any two of the aforementioned CDEIS scores.

[0124] In some embodiments, a TGFa biomarker measurement that is less than the reference or control TGFa biomarker measurement is indicative of mucosal healing. In some embodiments, a TGFa biomarker measurement that is greater than the reference or control TGFa biomarker measurement is indicative of mucosal inflammation. In some embodiments, a TGFa biomarker measurement that is less than the reference or control TGFa biomarker measurement is incorporated into the score to decrease the EHI score. In some embodiments, a TGFa biomarker measurement that is greater than the reference or control TGFa biomarker measurement is incorporated into the score to increase the EHI score. In some embodiments, a TGFa biomarker measurement that is less than or equal to 181 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission.

[0125] In some embodiments, a TGFa biomarker level at about 1-80 U/mL is informative of a CDEIS score of 1. In some embodiments, a TGFa biomarker level at about 80-181 U/mL is informative of a CDEIS score of 2. In some embodiments, a TGFa biomarker level at about 182-200 U/mL is informative of a CDEIS score of 3. In some embodiments, a TGFa biomarker level at about 201-231 U/mL is informative of a CDEIS score of 4. In some embodiments, a TGFa biomarker level at about 231-281 U/mL is informative of a CDEIS score of 5. In some embodiments, a TGFa biomarker level at about 281-331 U/mL is informative of a CDEIS score of 6. In some embodiments, a TGFa biomarker level at about 331-381 U/mL is informative of a CDEIS score of 7. In some embodiments, a TGFa biomarker level at about 381-431 U/mL is

informative of a CDEIS score of 8. In some embodiments, a TGFa biomarker level at about 431-481 U/mL is informative of a CDEIS score of 9. In some embodiments, a TGFa biomarker level at about 481-531 U/mL is informative of a CDEIS score of 10. In some embodiments, a TGFa biomarker level at about 531-581 U/mL is informative of a CDEIS score of 11. In some embodiments, a TGFa biomarker level at about 581-631 U/mL is informative of a CDEIS score of 12. In some embodiments, a TGFa biomarker level at about 631-681 U/mL is informative of a CDEIS score of 13. In some embodiments, a TGFa biomarker level at about 681-731 U/mL is informative of a CDEIS score of 14. In some embodiments, a TGFa biomarker level at about 731-781 U/mL is informative of a CDEIS score of 15. In some embodiments, a TGFa biomarker level at about 781-831 U/mL is informative of a CDEIS score of 16. In some embodiments, a TGFa biomarker level at about 831-881 U/mL is informative of a CDEIS score of 17. In some embodiments, a TGFa biomarker level at about 881-931 U/mL is informative of a CDEIS score of 18. In some embodiments, a TGFa biomarker level at about 931-981 U/mL is informative of a CDEIS score of 19. In some embodiments, a TGFa biomarker level at about 981-1031 U/mL is informative of a CDEIS score of 20. In some embodiments, a TGFa biomarker level greater than about 1031 U/mL is informative of a CDEIS score range from 21 to 44.

[0126] In some embodiments, a TGFa biomarker measurement that is less than 100, 125, 150, 175, 200, 225, 250, 275, or 300 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission. In some embodiments, a TGFa biomarker measurement that is less than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score below 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13, or below a range of CDEIS Scores defined by any two of the aforementioned CDEIS Scores. In some embodiments, a TGFa biomarker measurement that is greater than 181 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a TGFa biomarker measurement that is greater than 155-305 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a TGFa biomarker measurement that is greater than 100, 125, 150, 175, 200, 225, 250, 275, or 300 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a TGFa biomarker measurement that is

greater than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or more, or equivalent to a range of CDEIS scores defined by any two of the aforementioned CDEIS scores.

[0127] In some embodiments, a EMMPRIN biomarker measurement that is greater than the reference or control EMMPRIN biomarker measurement is indicative of mucosal healing. In some embodiments, a EMMPRIN biomarker measurement that is less than the reference or control EMMPRIN biomarker measurement is indicative of mucosal inflammation. In some embodiments, a EMMPRIN biomarker measurement that is greater than the reference or control EMMPRIN biomarker measurement is incorporated into the score to decrease the EHI score. In some embodiments, a EMMPRIN biomarker measurement that is less than the reference or control EMMPRIN biomarker measurement is incorporated into the score to increase the EHI score. In some embodiments, a EMMPRIN biomarker measurement that is greater than or equal to 240 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission.

[0128] In some embodiments, a EMMPRIN biomarker level greater than about 300 U/mL is informative of a CDEIS score of 1. In some embodiments, a EMMPRIN biomarker level at about 240-300 U/mL is informative of a CDEIS score of 2. In some embodiments, a EMMPRIN biomarker level at about 238-240 U/mL is informative of a CDEIS score of 3. In some embodiments, a EMMPRIN biomarker level at about 235-237 U/mL is informative of a CDEIS score of 4. In some embodiments, a EMMPRIN biomarker level at about 230-235 U/mL is informative of a CDEIS score of 5. In some embodiments, a EMMPRIN biomarker level at about 225-230 U/mL is informative of a CDEIS score of 6. In some embodiments, a EMMPRIN biomarker level at about 220-225 U/mL is informative of a CDEIS score of 7. In some embodiments, a EMMPRIN biomarker level at about 215-220 U/mL is informative of a CDEIS score of 8. In some embodiments, a EMMPRIN biomarker level at about 210-215 U/mL is informative of a CDEIS score of 9. In some embodiments, a EMMPRIN biomarker level at about 205-210 U/mL is informative of a CDEIS score of 10. In some embodiments, a EMMPRIN biomarker level at about 200-205 U/mL is informative of a CDEIS score of 11. In some embodiments, a EMMPRIN biomarker level at about 195-200 U/mL is informative of a CDEIS score of 12. In some embodiments, a EMMPRIN biomarker level at about 190-195 U/mL is informative of a CDEIS score of 13. In some embodiments, a EMMPRIN biomarker level at about 185-190 U/mL is informative of a CDEIS score of 14. In some embodiments, a

EMMPRIN biomarker level at about 180-185 U/mL is informative of a CDEIS score of 15. In some embodiments, a EMMPRIN biomarker level at about 175-180 U/mL is informative of a CDEIS score of 16. In some embodiments, a EMMPRIN biomarker level at about 170-175 U/mL is informative of a CDEIS score of 17. In some embodiments, a EMMPRIN biomarker level at about 165-170 U/mL is informative of a CDEIS score of 18. In some embodiments, a EMMPRIN biomarker level at about 160-165 U/mL is informative of a CDEIS score of 19. In some embodiments, a EMMPRIN biomarker level at about 155-160 U/mL is informative of a CDEIS score of 20. In some embodiments, a EMMPRIN biomarker level less than about 155 U/mL is informative of a CDEIS score range from 21 to 44.

[0129] In some embodiments, a EMMPRIN biomarker measurement that is greater than 150, 175, 200, 225, 250, 275, 300, 325, or 350 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission. In some embodiments, a EMMPRIN biomarker measurement that is greater than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score below 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13, or below a range of CDEIS Scores defined by any two of the aforementioned CDEIS Scores. In some embodiments, a EMMPRIN biomarker measurement that is less than 240 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a EMMPRIN biomarker measurement that is less than 215-265 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a EMMPRIN biomarker measurement that is less than 150, 175, 200, 225, 250, 275, 300, 325, or 350 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a EMMPRIN biomarker measurement that is less than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or more, or equivalent to a range of CDEIS scores defined by any two of the aforementioned CDEIS scores.

[0130] In some embodiments, a MMP1 biomarker measurement that is less than the reference or control MMP1 biomarker measurement is indicative of mucosal healing. In some embodiments, a MMP1 biomarker measurement that is greater than the reference or control MMP1 biomarker measurement is indicative of mucosal inflammation. In some embodiments,

a MMP1 biomarker measurement that is less than the reference or control MMP1 biomarker measurement is incorporated into the score to decrease the EHI score. In some embodiments, a MMP1 biomarker measurement that is greater than the reference or control MMP1 biomarker measurement is incorporated into the score to increase the EHI score. In some embodiments, a MMP1 biomarker measurement that is less than or equal to 150 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission.

[0131] In some embodiments, a MMP1 biomarker level at about 1-100 U/mL is informative of a CDEIS score of 1. In some embodiments, a MMP1 biomarker level at about 100-150 U/mL is informative of a CDEIS score of 2. In some embodiments, a MMP1 biomarker level at about 151-167 U/mL is informative of a CDEIS score of 3. In some embodiments, a MMP1 biomarker level at about 168-175 U/mL is informative of a CDEIS score of 4. In some embodiments, a MMP1 biomarker level at about 175-200 U/mL is informative of a CDEIS score of 5. In some embodiments, a MMP1 biomarker level at about 200-225 U/mL is informative of a CDEIS score of 6. In some embodiments, a MMP1 biomarker level at about 225-250 U/mL is informative of a CDEIS score of 7. In some embodiments, a MMP1 biomarker level at about 250-275 U/mL is informative of a CDEIS score of 8. In some embodiments, a MMP1 biomarker level at about 275-300 U/mL is informative of a CDEIS score of 9. In some embodiments, a MMP1 biomarker level at about 300-325 U/mL is informative of a CDEIS score of 10. In some embodiments, a MMP1 biomarker level at about 325-350 U/mL is informative of a CDEIS score of 11. In some embodiments, a MMP1 biomarker level at about 350-375 U/mL is informative of a CDEIS score of 12. In some embodiments, a MMP1 biomarker level at about 375-400 U/mL is informative of a CDEIS score of 13. In some embodiments, a MMP1 biomarker level at about 400-425 U/mL is informative of a CDEIS score of 14. In some embodiments, a MMP1 biomarker level at about 425-450 U/mL is informative of a CDEIS score of 15. In some embodiments, a MMP1 biomarker level at about 450-475 U/mL is informative of a CDEIS score of 16. In some embodiments, a MMP1 biomarker level at about 475-500 U/mL is informative of a CDEIS score of 17. In some embodiments, a MMP1 biomarker level at about 500-525 U/mL is informative of a CDEIS score of 18. In some embodiments, a MMP1 biomarker level at about 525-550 U/mL is informative of a CDEIS score of 19. In some embodiments, a MMP1 biomarker level at about 550-575 U/mL is informative of a CDEIS

score of 20. In some embodiments, a MMP1 biomarker level greater than about 575 U/mL is informative of a CDEIS score range from 21 to 44.

[0132] In some embodiments, a MMP1 biomarker measurement that is less than 50, 75, 100, 125, 150, 175, 200, 225, or 250 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission. In some embodiments, a MMP1 biomarker measurement that is less than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score below 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13, or below a range of CDEIS Scores defined by any two of the aforementioned CDEIS Scores. In some embodiments, a MMP1 biomarker measurement that is greater than 150 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a MMP1 biomarker measurement that is greater than 125-175 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a MMP1 biomarker measurement that is greater than 50, 75, 100, 125, 150, 175, 200, 225, or 250 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a MMP1 biomarker measurement that is greater than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or more, or equivalent to a range of CDEIS scores defined by any two of the aforementioned CDEIS scores.

[0133] In some embodiments, a MMP2 biomarker measurement that is greater than the reference or control MMP2 biomarker measurement is indicative of mucosal healing. In some embodiments, a MMP2 biomarker measurement that is less than the reference or control MMP2 biomarker measurement is indicative of mucosal inflammation. In some embodiments, a MMP2 biomarker measurement that is greater than the reference or control MMP2 biomarker measurement is incorporated into the score to decrease the EHI score. In some embodiments, a MMP2 biomarker measurement that is less than the reference or control MMP2 biomarker measurement is incorporated into the score to increase the EHI score. In some embodiments, a MMP2 biomarker measurement that is greater than or equal to 383 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission.

[0134] In some embodiments, a MMP2 biomarker level greater than about 550 U/mL is informative of a CDEIS score of 1. In some embodiments, a MMP2 biomarker level at about

383-550 U/mL is informative of a CDEIS score of 2. In some embodiments, a MMP2 biomarker level at about 378-383 U/mL is informative of a CDEIS score of 3. In some embodiments, a MMP2 biomarker level at about 373-377 U/mL is informative of a CDEIS score of 4. In some embodiments, a MMP2 biomarker level at about 363-373 U/mL is informative of a CDEIS score of 5. In some embodiments, a MMP2 biomarker level at about 353-363 U/mL is informative of a CDEIS score of 6. In some embodiments, a MMP2 biomarker level at about 343-353 U/mL is informative of a CDEIS score of 7. In some embodiments, a MMP2 biomarker level at about 333-343 U/mL is informative of a CDEIS score of 8. In some embodiments, a MMP2 biomarker level at about 323-333 U/mL is informative of a CDEIS score of 9. In some embodiments, a MMP2 biomarker level at about 313-323 U/mL is informative of a CDEIS score of 10. In some embodiments, a MMP2 biomarker level at about 303-313 U/mL is informative of a CDEIS score of 11. In some embodiments, a MMP2 biomarker level at about 293-303 U/mL is informative of a CDEIS score of 12. In some embodiments, a MMP2 biomarker level at about 283-293 U/mL is informative of a CDEIS score of 13. In some embodiments, a MMP2 biomarker level at about 273-283 U/mL is informative of a CDEIS score of 14. In some embodiments, a MMP2 biomarker level at about 263-273 U/mL is informative of a CDEIS score of 15. In some embodiments, a MMP2 biomarker level at about 253-263 U/mL is informative of a CDEIS score of 16. In some embodiments, a MMP2 biomarker level at about 243-253 U/mL is informative of a CDEIS score of 17. In some embodiments, a MMP2 biomarker level at about 233-243 U/mL is informative of a CDEIS score of 18. In some embodiments, a MMP2 biomarker level at about 223-233 U/mL is informative of a CDEIS score of 19. In some embodiments, a MMP2 biomarker level at about 213-223 U/mL is informative of a CDEIS score of 20. In some embodiments, a MMP2 biomarker level less than about 213 U/mL is informative of a CDEIS score range from 21 to 44.

[0135] In some embodiments, a MMP2 biomarker measurement that is greater than 275, 300, 325, 350, 375, 400, 425, 450, 475, or 500 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission. In some embodiments, a MMP2 biomarker measurement that is greater than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score below 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13, or below a range of CDEIS Scores defined by any two of the aforementioned CDEIS Scores. In some embodiments, a MMP2 biomarker measurement that

is less than 383U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a MMP2 biomarker measurement that is less than 360-410 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a MMP2 biomarker measurement that is less than 275, 300, 325, 350, 375, 400, 425, 450, 475, or 500 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a MMP2 biomarker measurement that is less than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or more, or equivalent to a range of CDEIS scores defined by any two of the aforementioned CDEIS scores.

[0136] In some embodiments, a MMP3 biomarker measurement that is less than the reference or control MMP3 biomarker measurement is indicative of mucosal healing. In some embodiments, a MMP3 biomarker measurement that is greater than the reference or control MMP3 biomarker measurement is indicative of mucosal inflammation. In some embodiments, a MMP3 biomarker measurement that is less than the reference or control MMP3 biomarker measurement is incorporated into the score to decrease the EHI score. In some embodiments, a MMP3 biomarker measurement that is greater than the reference or control MMP3 biomarker measurement is incorporated into the score to increase the EHI score. In some embodiments, a MMP3 biomarker measurement that is less than or equal to 85 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission.

[0137] In some embodiments, a MMP3 biomarker level at about 1-40 U/mL is informative of a CDEIS score of 1. In some embodiments, a MMP3 biomarker level at about 40-85 U/mL is informative of a CDEIS score of 2. In some embodiments, a MMP3 biomarker level at about 86-92 U/mL is informative of a CDEIS score of 3. In some embodiments, a MMP3 biomarker level at about 93-100 U/mL is informative of a CDEIS score of 4. In some embodiments, a MMP3 biomarker level at about 100-115 U/mL is informative of a CDEIS score of 5. In some embodiments, a MMP3 biomarker level at about 115-130 U/mL is informative of a CDEIS score of 6. In some embodiments, a MMP3 biomarker level at about 130-145 U/mL is informative of a CDEIS score of 7. In some embodiments, a MMP3 biomarker level at about 145-160 U/mL is informative of a CDEIS score of 8. In some embodiments, a MMP3 biomarker level at about 160-175 U/mL is informative of a CDEIS score of 9. In some

embodiments, a MMP3 biomarker level at about 175-190 U/mL is informative of a CDEIS score of 10. In some embodiments, a MMP3 biomarker level at about 190-205 U/mL is informative of a CDEIS score of 11. In some embodiments, a MMP3 biomarker level at about 205-220 U/mL is informative of a CDEIS score of 12. In some embodiments, a MMP3 biomarker level at about 220-235 U/mL is informative of a CDEIS score of 13. In some embodiments, a MMP3 biomarker level at about 235-250 U/mL is informative of a CDEIS score of 14. In some embodiments, a MMP3 biomarker level at about 250-265 U/mL is informative of a CDEIS score of 15. In some embodiments, a MMP3 biomarker level at about 265-280 U/mL is informative of a CDEIS score of 16. In some embodiments, a MMP3 biomarker level at about 280-295 U/mL is informative of a CDEIS score of 17. In some embodiments, a MMP3 biomarker level at about 295-310 U/mL is informative of a CDEIS score of 18. In some embodiments, a MMP3 biomarker level at about 310-325 U/mL is informative of a CDEIS score of 19. In some embodiments, a MMP3 biomarker level at about 325-340 U/mL is informative of a CDEIS score of 20. In some embodiments, a MMP3 biomarker level greater than about 340 U/mL is informative of a CDEIS score range from 21 to 44.

[0138] In some embodiments, a MMP3 biomarker measurement that is less than 15, 25, 50, 75, 100, 125, 150, 175, or 200 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission. In some embodiments, a MMP3 biomarker measurement that is less than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score below 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13, or below a range of CDEIS Scores defined by any two of the aforementioned CDEIS Scores. In some embodiments, a MMP3 biomarker measurement that is greater than 85 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a MMP3 biomarker measurement that is greater than 60-110 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a MMP3 biomarker measurement that is greater than 15, 25, 50, 75, 100, 125, 150, 175, or 200 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a MMP3 biomarker measurement that is greater than a reference value or reference range is incorporated into the EHI score, as

equivalent to a CDEIS score of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or more, or equivalent to a range of CDEIS scores defined by any two of the aforementioned CDEIS scores.

[0139] In some embodiments, a MMP9 biomarker measurement that is less than the reference or control MMP9 biomarker measurement is indicative of mucosal healing. In some embodiments, a MMP9 biomarker measurement that is greater than the reference or control MMP9 biomarker measurement is indicative of mucosal inflammation. In some embodiments, a MMP9 biomarker measurement that is less than the reference or control MMP9 biomarker measurement is incorporated into the score to decrease the EHI score. In some embodiments, a MMP9 biomarker measurement that is greater than the reference or control MMP9 biomarker measurement is incorporated into the score to increase the EHI score. In some embodiments, a MMP9 biomarker measurement that is less than or equal to 211 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission.

[0140] In some embodiments, a MMP9 biomarker level at about 1-100 U/mL is informative of a CDEIS score of 1. In some embodiments, a MMP9 biomarker level at about 100-211 U/mL is informative of a CDEIS score of 2. In some embodiments, a MMP9 biomarker level at about 212-230 U/mL is informative of a CDEIS score of 3. In some embodiments, a MMP9 biomarker level at about 231-261 U/mL is informative of a CDEIS score of 4. In some embodiments, a MMP9 biomarker level at about 261-311 U/mL is informative of a CDEIS score of 5. In some embodiments, a MMP9 biomarker level at about 311-361 U/mL is informative of a CDEIS score of 6. In some embodiments, a MMP9 biomarker level at about 361-411 U/mL is informative of a CDEIS score of 7. In some embodiments, a MMP9 biomarker level at about 411-461 U/mL is informative of a CDEIS score of 8. In some embodiments, a MMP9 biomarker level at about 461-511 U/mL is informative of a CDEIS score of 9. In some embodiments, a MMP9 biomarker level at about 511-561 U/mL is informative of a CDEIS score of 10. In some embodiments, a MMP9 biomarker level at about 561-611 U/mL is informative of a CDEIS score of 11. In some embodiments, a MMP9 biomarker level at about 611-661 U/mL is informative of a CDEIS score of 12. In some embodiments, a MMP9 biomarker level at about 661-711 U/mL is informative of a CDEIS score of 13. In some embodiments, a MMP9 biomarker level at about 711-761 U/mL is informative of a CDEIS score of 14. In some embodiments, a MMP9 biomarker level at about 761-811 U/mL is informative of a CDEIS score of 15. In some embodiments, a MMP9 biomarker level at about 811-861 U/mL is informative of a CDEIS

score of 16. In some embodiments, a MMP9 biomarker level at about 861-911 U/mL is informative of a CDEIS score of 17. In some embodiments, a MMP9 biomarker level at about 911-961 U/mL is informative of a CDEIS score of 18. In some embodiments, a MMP9 biomarker level at about 961-1011 U/mL is informative of a CDEIS score of 19. In some embodiments, a MMP9 biomarker level at about 1011-1061 U/mL is informative of a CDEIS score of 20. In some embodiments, a MMP9 biomarker level greater than about 1061 U/mL is informative of a CDEIS score range from 21 to 44.

[0141] In some embodiments, a MMP9 biomarker measurement that is less than 100, 125, 150, 175, 200, 225, 250, 275, or 300 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score below 3, or indicative of endoscopic remission. In some embodiments, a MMP9 biomarker measurement that is less than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score below 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13, or below a range of CDEIS Scores defined by any two of the aforementioned CDEIS Scores. In some embodiments, a MMP9 biomarker measurement that is greater than 211 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a MMP9 biomarker measurement that is greater than 185-235 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a MMP9 biomarker measurement that is greater than 100, 125, 150, 175, 200, 225, 250, 275, or 300 U/mL is incorporated into the EHI score, as equivalent to a CDEIS score of 3 or more, or indicative of mild, moderate, or severe endoscopic disease activity. In some embodiments, a MMP9 biomarker measurement that is greater than a reference value or reference range is incorporated into the EHI score, as equivalent to a CDEIS score of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or more, or equivalent to a range of CDEIS scores defined by any two of the aforementioned CDEIS scores.

[0142] In some embodiments, a computer or processor applies a mathematical algorithm to the biomarker levels. In some embodiments, the EHI score is produced by or using a computer or processor. In some embodiments, the computer or processor receives the biomarker scores. In some embodiments, a user enters the biomarker scores, for example into a graphical user interface. In some embodiments, the computer or processor implements the mathematical algorithm to generate the EHI score. In some embodiments, the computer or processor performs or is used to perform one, more, or all steps of the method. In some

embodiments, the computer or processor displays the EHI score. In some embodiments, the computer or processor transmits the EHI score, for example over a network to another computer or processor. Some embodiments include receiving the EHI score.

[0143] In some embodiments, the biomarker levels predict or are used to predict a likelihood of the patient being in remission or having mild endoscopic disease. In some embodiments, the EHI score predicts or is used to predict a likelihood of the patient being in remission or having mild endoscopic disease. In some embodiments, the predicted likelihood of being in remission or having mild endoscopic disease is greater than or equal to 86%. In some embodiments, the predicted likelihood of being in remission or having mild endoscopic disease is greater than or equal to 92%. In some embodiments, the predicted likelihood of being in remission or having mild endoscopic disease is 100%. In some embodiments, the likelihood of the patient being in remission or having mild endoscopic disease is greater than or equal to 86% or 92%, or is 100%. In some embodiments, the likelihood, based on the EHI score, of the patient being in remission or having mild endoscopic disease is greater than or equal to 75%, 76%, 77%, 78%, 79%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99%, or is 100%, or falls within a range defined by any two of the aforementioned percentages. In some embodiments, the remission corresponds to a Crohn's Disease Endoscopic Index of Severity (CDEIS) score of less than 3. In some embodiments, the mild endoscopic disease corresponds to a CDEIS score of less than 3.

[0144] In some embodiments, the biomarker levels predict or are used to predict a likelihood of the patient having endoscopically active disease. In some embodiments, the EHI score predicts or is used to predict a likelihood of the patient having endoscopically active disease. In some embodiments, the predicted likelihood of having endoscopically active disease is greater than or equal to 87%. In some embodiments, the predicted likelihood of having endoscopically active disease is 100%. In some embodiments, the high likelihood of the patient having endoscopically active disease is greater than or equal to 87%, or is 100%. In some embodiments, the likelihood, based on the EHI score, of the patient having endoscopically active disease is greater than or equal to 75%, 76%, 77%, 78%, 79%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99%, or is 100%, or falls within a range defined by any two of the aforementioned percentages. In some embodiments, the endoscopically active disease corresponds to a CDEIS score of greater than or equal to 3.

[0145] In some embodiments, the biomarker levels accurately assesses mucosal healing. In some embodiments, the EHI score accurately assesses mucosal healing. In some embodiments, the EHI score accurately assesses mucosal healing by corresponding with a CDEIS score or endoscopic measurement or CDEIS score. In some embodiments, the EHI score accurately assesses mucosal healing for a period of time. In some embodiments, the EHI score provides an accurate assessment of mucosal healing or corresponds with a CDEIS score over the period of time. In some embodiments, the period of time is 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 months, or more. In some embodiments, the period of time is 1 month. In some embodiments, the period of time is 3 months. In some embodiments, the EHI score corresponds to a CDEIS score within a time window such as 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 months, or more. For example, the EHI score may correspond to a CDEIS score when the endoscopy performed for a CDEIS score and a blood draw performed to obtain a sample for an EHI score occur within 30 or 90 days of each other.

III. OBTAINING BIOMARKER LEVELS

[0146] In some embodiments, the level is an expression level. In some embodiments, the level is a protein level. For example, some embodiments include detecting or measuring a protein level or a protein expression level for each biomarker of the 13 aforementioned biomarkers. In some embodiments, the level is a circulating level such as the level of each biomarker in the blood, serum or plasma of the patient (e.g. an adult or pediatric patient). In some embodiments, a level refers to an amount such as a millimolar (mM), micromolar (µM), or nanomolar (nM) amount. For example, the level of a biomarker may refer to a micromolar amount of the biomarker in a serum sample of the patient. Some embodiments include transmitting the EHI score. Some embodiments include receiving a transmitted EHI score. Some embodiments include transmitting the biomarker levels. Some embodiments include receiving a transmitted biomarker levels.

[0147] In some embodiments, the detecting comprises measuring. In some embodiments, the detecting or measuring comprises performing an assay. In some embodiments, the detecting comprises interpreting the results of an assay. In some embodiments, the assay is or comprises an immunoassay. Examples of immunoassays include enzyme-linked immunoassays (ELISAs), enzyme enhanced reactive immunoassays (CEERs), immunoblots, immunohistochemical assays, turbidity assays, and bead-based immunoassays such as Luminex assays. Examples of immunoassays include competitive, homogeneous

immunoassays, competitive, heterogeneous immunoassays, one-site, noncompetitive immunoassays, and two-site, noncompetitive immunoassays. In some embodiments, one assay or immunoassay is performed for one or more of the biomarkers, and another assay or immunoassay is performed for one or more of the other biomarkers. Some embodiments include a multiplex assay for assessing the levels of multiple biomarkers at once. Some embodiments include a proteomics-based approach such as mass spectrometry, use of a protein chip.

[0148] In some embodiments, the detecting comprises contacting the sample with a binding partner for each of the one or more biomarkers and detecting binding between each biomarker and its respective binding partner. In some embodiments, each binding partner is an antibody. In some embodiments, the detecting comprises performing an immunoassay to assess the level of each of the biomarker.

[0149] Some embodiments of the methods and systems provided herein include obtaining biomarker levels. In some embodiments, the method comprises: receiving biomarker levels, wherein the biomarkers comprise Ang1, Ang2, CEACAM1, VCAM1, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and/or IL-7; and applying a mathematical algorithm to the received biomarker levels, thereby producing a Endoscopic Healing Index (EHI) score for the patient (e.g. an adult or pediatric patient). For example, some embodiments do not include directly measuring any or all of the biomarkers, but include receiving some or all of the levels. It is contemplated that wherever the method includes detecting, the method may alternatively include receiving. In some embodiments, a laboratory technician detects a biomarker level, and provides the level to a receiving party.

[0150] Some embodiments include detecting the level of one or more biomarkers, and receiving the level of one or more other biomarkers. In some embodiments, the receiving comprises receiving information about a biomarker level. In some embodiments, the receiving comprises receiving a report with information about a biomarker level. In some embodiments, the report comprises a printout or a digital file. In some embodiments, the information or report comprises a value for each level.

[0151] Some embodiments include receiving a level for each of one or more biomarkers selected from the group comprising Ang1, Ang2, CEACAM1, VCAM1, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7; and applying a mathematical algorithm to the levels of the one or more biomarkers, thereby producing a Endoscopic Healing Index (EHI) score for the patient. Some embodiments include receiving a level for each of the following biomarkers: Ang1, Ang2, CEACAM1, VCAM1, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7; and applying a mathematical algorithm to the levels of the biomarkers, thereby producing a Endoscopic Healing Index (EHI) score for the patient.

IV. SAMPLES

[0152] Some embodiments of the methods and systems provided herein include providing the sample from a patient (e.g. an adult patient). Some embodiments of the methods and systems provided herein include providing the sample from a patient (e.g. an adult or pediatric patient). In some embodiments, the sample is obtained from a patient. Some embodiments include receiving a patient sample. In some embodiments, the patient has CD. Some embodiments include providing or receiving a sample from a patient with CD. Some embodiments include receiving or providing the sample, and then performing an assay with the sample or otherwise detecting biomarker in the sample. In some embodiments, the providing comprises drawing blood from the patient, or receiving blood drawn from the patient, or drawing or receiving a blood constituent from the patient.

[0153] In some embodiments, the sample is a blood, serum, or plasma sample. In some embodiments, the sample is a blood sample. In some embodiments, the sample is a plasma sample. In some embodiments, the sample is a serum sample. In some embodiments, multiple samples are pooled into a single sample prior to the biomarkers being measured.

[0154] In some embodiments, the sample is a stool sample. In some embodiments, the sample is a saliva sample. In some embodiments, the sample is a urine sample. In some embodiments, the sample is a semen sample. In some embodiments, the sample is a tissue sample. In some embodiments, the sample is a biologic sample such as saliva, sputum, buccal swab sample, serum, plasma, blood, buffy coat, pharyngeal, nasal/nasal pharyngeal or sinus swabs or secretions, throat swabs or scrapings, urine, mucous, feces/stool/excrement, rectal swabs, lesion swabs, chyme, vomit, gastric juices, pancreatic juices, gastrointestinal (GI) tract fluids or solids, semen/sperm, urethral swabs and secretions, cerebral spinal fluid, products of lactation or menstruation, egg yolk, amniotic fluid, aqueous humour, vitreous humour, cervical secretions or swabs, vaginal fluid/secretions/swabs or scrapings, bone marrow samples and aspirates, pleural fluid and effusions, sweat, pus, tears, lymph, bronchial or lung lavage or aspirates, peritoneal effusions, cell cultures and cell suspensions, connective tissue, epithelium, epithelial swabs and smears, mucosal membrane, muscle tissue, placental tissue, biopsies, exudates, organ tissue, nerve tissue, hair, skin, or nails.

[0155] In some embodiments, the sample comprises a 0.5 mL sample. In some embodiments, the sample comprises a 1 mL sample. In some embodiments, the sample comprises a 1.5 mL sample. In some embodiments, the sample comprises a 2 mL sample. In some embodiments, the sample comprises a 2.5 mL sample. In some embodiments, the sample comprises a 3 mL sample. In some embodiments, the sample comprises a 3.5 mL sample. In some embodiments, the sample comprises a 4 mL sample. In some embodiments, the sample comprises a 4.5 mL sample. In some embodiments, the sample comprises a 5 mL sample.

[0156] In some embodiments, the sample comprises a 0.1 mg sample. In some embodiments, the sample comprises a 1 mg sample. In some embodiments, the sample comprises a 10 mg sample. In some embodiments, the sample comprises a 50 mg sample. In some embodiments, the sample comprises a 100 mg sample. In some embodiments, the sample comprises a 200 mg sample. In some embodiments, the sample comprises a 300 mg sample. In some embodiments, the sample comprises a 400 mg sample. In some embodiments, the sample comprises a 500 mg sample. In some embodiments, the sample comprises a 600 mg sample. In some embodiments, the sample comprises a 700 mg sample. In some embodiments, the sample comprises a 800 mg sample. In some embodiments, the sample comprises a 900 mg sample. In some embodiments, the sample comprises a 1000 mg sample.

[0157] In some embodiments, the sample is refrigerated. In some embodiments, the sample is frozen. In some embodiments, the sample is freeze-thawed. In some embodiments, the sample is processed. In some embodiments, the sample is lysed. In some embodiments, the sample is centrifuged. In some embodiments, the sample comprises a protein sample.

V. PATIENTS

[0158] Some embodiments of the methods and systems provided herein relate to a patient. In some embodiments, the patient is an adult patient. In some embodiments, the patient is a pediatric patient. In some embodiments, the patient has an inflammatory condition. In some embodiments, the patient has an inflammatory bowel disease (IBD). In some embodiments, the patient has CD. In some embodiments, the patient has ulcerative colitis. In some embodiments, the patient is being treated with a CD therapy such as a CD drug.

[0159] In some embodiments, the patient is male. In some embodiments, the patient is female.

[0160] In some embodiments, the patient is an adult. In some embodiments, the adult patient is 18 years or older. In some embodiments, the pediatric patient is 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17, or a range defined by any two of the aforementioned integers, years old. In some embodiments, the pediatric patient is 17 years old. In some embodiments, the pediatric patient is 16 years old. In some embodiments, the pediatric patient is 15 years old. In some embodiments, the pediatric patient is 14 years old. In some embodiments, the pediatric patient is 13 years old. In some embodiments, the pediatric patient is 12 years old. In some embodiments, the pediatric patient is 11 years old. In some embodiments, the pediatric patient is 10 years old. In some embodiments, the pediatric patient is 9 years old. In some embodiments, the pediatric patient is 8 years old. In some embodiments, the pediatric patient is 7 years old. In some embodiments, the pediatric patient is 6 years old. In some embodiments, the pediatric patient is 5 years old. In some embodiments, the pediatric patient is 4 years old. In some embodiments, the pediatric patient is 3 years old. In some embodiments, the pediatric patient is 2 years old. In some embodiments, the pediatric patient is 1 year old. In some embodiments, the pediatric patient is 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12, or a range defined by any two of the aforementioned integers, months old. In some embodiments, the pediatric patient is an infant or newborn.

[0161] In some embodiments, the pediatric patient is under 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, or 18 years of age. In some embodiments, the pediatric patient is under 18 years of age. In some embodiments, the pediatric patient is under 17 years of age. In some embodiments, the pediatric patient is under 16 years of age. In some embodiments, the pediatric patient is under 15 years of age. In some embodiments, the pediatric patient is under 14 years of age. In some embodiments, the pediatric patient is under 13 years of age. In some embodiments, the pediatric patient is under 12 years of age. In some embodiments, the pediatric patient is under 11 years of age. In some embodiments, the pediatric patient is under 10 years of age. In some embodiments, the pediatric patient is under 9 years of age. In some embodiments, the pediatric patient is under 8 years of age. In some embodiments, the pediatric patient is under 7 years of age. In some embodiments, the pediatric patient is under 6 years of age. In some embodiments, the pediatric patient is under 5 years of age. In some embodiments, the pediatric patient is under 4 years of age. In some embodiments, the pediatric patient is under 3 years of age. In some embodiments, the pediatric patient is under 2 years of age. In some embodiments, the pediatric patient is under 1 year of age. In some embodiments, the pediatric patient is under 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 months of age. In some embodiments, the pediatric patient is over 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17, years old. In some embodiments, the pediatric patient is over 17 years of age. In some embodiments, the pediatric patient is over 16 years of age. In some embodiments, the pediatric patient is over 15 years of age. In some embodiments, the pediatric patient is over 14 years of age. In some embodiments, the pediatric patient is over 13 years of age. In some embodiments, the pediatric patient is over 12 years of age. In some embodiments, the pediatric patient is over 11 years of age. In some embodiments, the pediatric patient is over 10 years of age. In some embodiments, the pediatric patient is over 9 years of age. In some embodiments, the pediatric patient is over 8 years of age. In some embodiments, the pediatric patient is over 7 years of age. In some embodiments, the pediatric patient is over 6 years of age. In some embodiments, the pediatric patient is over 5 years of age. In some embodiments, the pediatric patient is over 4 years of age. In some embodiments, the pediatric patient is over 3 years of age. In some embodiments, the pediatric patient is over 2 years of age. In some embodiments, the pediatric patient is over 1 year of age. In some embodiments, the pediatric patient is over 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 months of age.

[0162] In some embodiments, the pediatric patient is a human patient. In some embodiments, the pediatric patient is a human under 18 years of age, for example a human 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17 years of age, or a range defined by any two of the aforementioned ages.

[0163] In some embodiments, the patient is a vertebrate. In some embodiments, the patient is a non-human vertebrate. In some embodiments, the patient is an animal. In some embodiments, the patient is a non-human animal. In some embodiments, the patient is a mammal. In some embodiments, the patient is a non-human mammal. In some embodiments, the mammal or non-human mammal is a human, a non-human primate, cattle (such as cow, goat, or sheep), a dog, a cat, or a horse.

VI. COMPANION DIAGNOSTICS AND METHODS OF TREATMENT

[0164] Some embodiments of the methods and systems provided herein include assessing the effect of a CD therapy or treatment based on the biomarker levels. Some embodiments include assessing the effect of a CD therapy or treatment based on the EHI score or EHI score. Some embodiments include initiating, continuing, providing or discontinuing a CD therapy to the patient (e.g. adult or pediatric patient) based on the biomarker levels. Some embodiments

include initiating, continuing, providing or discontinuing a CD therapy to the or adult patient based on the EHI score. Some embodiments include selecting an appropriate CD therapy to the or adult patient based on the biomarker levels. Some embodiments include selecting an appropriate CD therapy to the or adult patient based on the EHI score. In some embodiments, the or adult patient is receiving biologic or non-biologic therapy. In some embodiments, the method assesses mucosal healing by determining the efficacy of the therapy. In some embodiments, the therapy is determined to be effective based on the biomarker levels. In some embodiments, the therapy is determined to be effective based on the EHI score. In some embodiments, the therapy is continued or discontinued based on the assessment. Some embodiments include evaluating the efficacy of a therapy administered to the or adult patient based on the biomarker levels. Some embodiments include evaluating the efficacy of a therapy administered to the or adult patient based on the EHI score. Some embodiments include adjusting the therapy in response to the evaluation.

[0165] Some embodiments include a method of treatment such as a method of treating a CD patient or an adult CD patient. In some embodiments, the method of treatment includes obtaining biomarker levels and providing or initiating a CD therapy based on the biomarker levels in relation to control or index biomarker levels. In some embodiments, the method of treatment includes obtaining biomarker levels and providing or initiating a CD therapy based on a change or trend in biomarker levels over time. In some embodiments, the method of treatment includes obtaining biomarker levels and providing or initiating a CD therapy based on correspondence of the biomarker levels to a Crohn's Disease Endoscopic Index of Severity (CDEIS) score. In some embodiments, the method of treatment includes obtaining a MHI or EHI score and providing or initiating a CD therapy based on the EHI score. In some embodiments, the method of treatment includes obtaining multiple EHI scores and providing or initiating a CD therapy based on a change or trend in the EHI scores over time. In some embodiments, the method of treatment includes obtaining an EHI score and providing or initiating a CD therapy based on correspondence of the EHI score to a CDEIS score.

[0166] In some embodiments, the CD therapy comprises a medication such as an anti-inflammatory medication, a steroid, an immunosuppressant, a nonsteroidal anti-inflammatory drug, a vitamin, or an antibiotic. In some embodiments, the CD therapy comprises a pharmaceutical CD therapy. In some embodiments, the pharmaceutical CD therapy comprises small molecule therapy. In some embodiments, the pharmaceutical CD therapy comprises a

CD biologic. In some embodiments, the pharmaceutical CD therapy comprises an antibody treatment. In some embodiments, the CD therapy comprises a non-biologic CD therapy. In some embodiments, the CD therapy comprises a non-pharmaceutical CD therapy. In some embodiments, the CD therapy comprises any combination of one or more types of a pharmaceutical CD therapy (as described herein), a non-biologic CD therapy, and/or a non-pharmaceutical CD therapy.

[0167] In some embodiments, the CD therapy comprises a CD surgery. In some embodiments, the CD surgery comprises a bowel resection, wherein part of the intestine of a patient is removed. In some embodiments, the CD surgery comprises a colectomy, wherein the entire colon of a patient is removed. In some embodiments, the CD surgery comprises a proctocolectomy, wherein both the rectum and the colon of a patient is removed. In some embodiments, the CD surgery comprises a strictureplasty, wherein a specific disease portion of the small intestine of a patient is widened. In some embodiments, the CD therapy comprises any combination of one or more types of a pharmaceutical CD therapy (as described herein), a non-biologic CD therapy, a non-pharmaceutical CD therapy, and/or one or more types of a CD surgery (as described herein).

[0168] Examples of biologics that may be used as or included in a CD therapy include anti-cytokine and chemokine antibodies such as anti-tumor necrosis factor alpha (TNFa) antibodies. Non-limiting examples of anti-TNFa antibodies include: chimeric monoclonal antibodies such as infliximab, a chimeric IgGl anti-TNFa monoclonal antibody; humanized monoclonal antibodies such as CDP571 and the PEGylated CDP870; fully human monoclonal antibodies such as adalimumab; and p75 fusion proteins such as etanercept; anti-cell adhesion antibodies such as natalizumab, a humanized monoclonal antibody against the cellular adhesion molecule a4-integrin, and MLN-02, a humanized IgGl anti-a4p7-integrin monoclonal antibody; anti-T cell agents; anti-CD3 antibodies such as visilizumab, a humanized IgG2M3 anti-CD3 monoclonal antibody; anti-CD4 antibodies such as priliximab, a chimeric anti-CD4 monoclonal antibody; anti-IL-2 receptor alpha (CD25) antibodies such as daclizumab, a humanized IgGl anti-CD25 monoclonal antibody; basiliximab, a chimeric IgGl anti-CD25 monoclonal antibody; vedolizumab, a humanized antibody against integrin a4b7; ustekinumab, a humanized antibody against IL-12 and IL-23; and combinations thereof.

[0169] In some embodiments, the CD therapy comprises a modulator and/or antagonist of TNF Superfamily Member 15 (TL1A), or the gene encoding TL1A (TNFSF15). In some

embodiments, the modulator of TL1A is an antagonist of TL1A. In some embodiments the CD therapy comprises an inhibitor of TL1A expression or activity. In some cases, the inhibitor of TL1A expression or activity is effective to inhibit TL1A-DR3 binding. In some embodiments, the inhibitor of TL1A expression or activity comprises an allosteric modulator of TL1A. An allosteric modulator of TL1A may indirectly influence the effects of TL1A on DR3, or TR6/DcR3 on TL1A or DR3. The inhibitor of TL1A expression or activity may be a direct inhibitor or indirect inhibitor. Non-limiting examples of an inhibitor of TL1A expression include RNA to protein TL1A translation inhibitors, antisense oligonucleotides targeting the TNFSF15 mRNA (such as miRNAs, or siRNA), epigenetic editing (such as targeting the DNA-binding domain of TNFSF15, or post-translational modifications of histone tails and/or DNA molecules). Non-limiting examples of an inhibitor of TL1A activity include antagonists to the TL1A receptors, (DR3 and TR6/DcR3), antagonists to TL1A antigen, and antagonists to gene expression products involved in TL1A mediated disease. Antagonists as disclosed herein, may include, but are not limited to, an anti-TL1A antibody, an anti- TL1A-binding antibody fragment, or a small molecule. The small molecule may be a small molecule that binds to TL1A or DR3. The anti-TL1A antibody may be monoclonal or polyclonal. The anti-TL1A antibody may be humanized or chimeric. The anti-TL1A antibody may be a fusion protein. The anti-TL1A antibody may be a blocking anti-TL1A antibody. A blocking antibody blocks binding between two proteins, e.g., a ligand and its receptor. Therefore, a TL1A blocking antibody includes an antibody that prevents binding of TL1A to DR3 or TR6/DcR3 receptors. In a non-limiting example, the TL1A blocking antibody binds to DR3. In another example, the TL1A blocking antibody binds to DcR3. In some cases, the anti-TL1A antibody is an anti-TL1A antibody that specifically binds to TL1A.

[0170] In some embodiments, the CD therapy comprises a modulator and/or antagonist of TNFa. In some embodiments, the modulator of TNFa is an antagonist of TNFa. In some embodiments the CD therapy comprises an inhibitor of TNFa expression or activity. In some cases, the inhibitor of TNFa expression or activity is effective to inhibit TNFa-receptor binding. Non-limiting examples of receptors for TNFa include TNFR1 and/or TNFR2. In some embodiments, the inhibitor of TNFa expression or activity comprises an allosteric modulator of TNFa. An allosteric modulator of TNFa may indirectly influence the effects of TNFa on a respective receptor. The inhibitor of TNFa expression or activity may be a direct inhibitor or indirect inhibitor. Non-limiting examples of an inhibitor of TNFa expression include RNA to protein TNFa translation inhibitors, antisense oligonucleotides targeting the TNFa mRNA, epigenetic editing, or post-translational modifications of histone tails and/or DNA molecules. Non-limiting examples of an inhibitor of TNFa activity include antagonists to TNFa and/or respective TNFa receptors, antagonists to TNFa antigen, and antagonists to gene expression products involved in TNFa mediated disease. Antagonists as disclosed herein, may include, but are not limited to, an anti- TNFa antibody, an anti- TNFa-binding antibody fragment, or a small molecule. The small molecule may be a small molecule that binds to TNFa and/or a respective TNFa receptor. The anti- TNFa antibody may be monoclonal or polyclonal. The anti- TNFa antibody may be humanized or chimeric. The anti- TNFa antibody may be a fusion protein. The anti- TNFa antibody may be a blocking anti- TNFa antibody. A blocking antibody blocks binding between two proteins, e.g., a ligand and its receptor. Therefore, a TNFa blocking antibody includes an antibody that prevents binding of TNFa to a corresponding receptor. In a non-limiting example, the TNFa blocking antibody binds to a respective TNFa receptor, such as TNFR1 and/or TNFR2. In some cases, the anti- TNFa antibody is an anti- TNFa antibody that specifically binds to TNFa.

[0171] In some embodiments, the anti- TNFa antibody is introduced into a patient by injection. In some embodiments, the injection of the anti- TNFa antibody is administered subcutaneously. In some embodiments, the injection of an anti- TNFa antibody is administered into a patient’s abdomen and/or thigh. Non-limiting examples of TNFa antagonists include infliximab and/or adalimumab. In some cases, a dosage for an anti- TNFa antibody, such as infliximab, can range from an initial dosage ranging from 3-5 mg/kg every 2 -4 weeks for the first 6 weeks, followed by a dosage ranging from 5-10 mg every 4-8 weeks. In some embodiments, a dosage for an anti- TNFa antibody, such as adalimumab, can range from 30mg to 50mg every other week.

[0172] In some embodiments, the CD therapy comprises a modulator and/or antagonist of IL-12 and/or IL-23. In some embodiments, the modulator of IL-12 and/or IL-23 is an antagonist of IL-12 and/or IL-23. In some embodiments the CD therapy comprises an inhibitor of IL-12 and/or IL-23 expression or activity. In some cases, the inhibitor of IL-12 and/or IL-23 expression or activity is effective to inhibit binding between a receptor and IL-12 and/or IL-23. Non-limiting examples of a receptor for IL-12 and/or IL-23 include IL-12R-b1 and/or IL-12R-b2. In some embodiments, the inhibitor of IL-12 and/or IL-23 expression or activity comprises an allosteric modulator of IL-12 and/or IL-23. An allosteric modulator of IL-12 and/or IL-23 may indirectly influence the effects of IL-12 and/or IL-23 on a respective receptor. The inhibitor of IL-12 and/or IL-23 expression or activity may be a direct inhibitor or indirect inhibitor. Non-limiting examples of an inhibitor of IL-12 and/or IL-23 expression include RNA to protein IL-12 and/or IL-23 translation inhibitors, antisense oligonucleotides targeting the IL-12 and/or IL-23 mRNA, epigenetic editing, or post-translational modifications of histone tails and/or DNA molecules. Non-limiting examples of an inhibitor of IL-12 and/or IL-23 activity include antagonists to the IL-12 and/or IL-23 and/or respective IL-12 and/or IL-23 receptors, antagonists to IL-12 and/or IL-23 antigen, and antagonists to gene expression products involved in IL-12 and/or IL-23 mediated disease. Antagonists as disclosed herein, may include, but are not limited to, an anti- IL-12 and/or IL-23 antibody, an anti- IL-12 and/or IL-23 -binding antibody fragment, or a small molecule. The small molecule may be a small molecule that binds to IL-12 and/or IL-23 or a corresponding receptor. The anti- IL-12 and/or IL-23 antibody may be monoclonal or polyclonal. The anti- IL-12 and/or IL-23 antibody may be humanized or chimeric. The anti- IL-12 and/or IL-23 antibody may be a fusion protein. The anti- IL-12 and/or IL-23 antibody may be a blocking anti- IL-12 and/or IL-23 antibody. A blocking antibody blocks binding between two proteins, e.g., a ligand and its receptor. Therefore, a IL-12 and/or IL-23 blocking antibody includes an antibody that prevents binding of IL-12 and/or IL-23 to a respective receptor. In a non-limiting example, the IL-12 and/or IL-23 blocking antibody binds to IL-12R-b1. In another example, the IL-12 and/or IL-23 blocking antibody binds to IL-12R-b2. In some cases, the anti- IL-12 and/or IL-23 antibody is an anti-IL-12 and/or IL-23 antibody that specifically binds to IL-12 and/or IL-23.

[0173] In some embodiments, the anti- IL-12 and/or IL-23 antibody is introduced into a patient by injection. In some embodiments, the injection of anti- IL-12 and/or IL-23 antibody is administered intravenously. In some embodiments, the injection of the anti- IL-12 and/or IL-23 antibody is administered subcutaneously. A non-limiting example of an IL-12 and/or IL-23 antagonist includes ustekinumab. In some cases, a dosage for an anti- IL-12 and/or IL-23 antibody, such as ustekinumab, can include an initial dosage ranging from 260 mg to 520 mg, wherein the weight of the patient is considered. In a non-limiting example, a patient weighing 55kg or less is administered with an initial dosage of an anti- IL-12 and/or IL-23 antibody ranging from 250– 275mg. In a non-limiting example, a patient weighing 55kg to 85kg is administered with an initial dosage of an anti- IL-12 and/or IL-23 antibody ranging from 375 – 400mg. In a non-limiting example, a patient weighing 85kg or more is administered with an

initial dosage of an anti- IL-12 and/or IL-23 antibody ranging from 500 - 540mg. In some embodiments, the initial dosage of an anti- IL-12 and/or IL-23 antibody is administered intravenously. In some embodiments, a dosage of an anti- IL-12 and/or IL-23 antibody ranges from 80– 100 mg every 8 weeks after the initial dosage.

[0174] In some embodiments, the CD therapy comprises a modulator and/or antagonist of a4b7. In some embodiments, the modulator of a4b7 is an antagonist of a4b7. In some embodiments the CD therapy comprises an inhibitor of a4b7 expression or activity. In some cases, the inhibitor of a4b7 expression or activity is effective to inhibit binding of a4b7 with a a4b7 receptor. In some embodiments, the inhibitor of a4b7 expression or activity comprises an allosteric modulator of a4b7. An allosteric modulator of a4b7 may indirectly influence the effects of a4b7 on corresponding receptors. The inhibitor of a4b7 expression or activity may be a direct inhibitor or indirect inhibitor. Non-limiting examples of an inhibitor of a4b7 expression include RNA to protein a4b7 translation inhibitors, antisense oligonucleotides targeting the a4b7 mRNA, epigenetic editing, or post-translational modifications of histone tails and/or DNA molecules. Non-limiting examples of an inhibitor of a4b7 activity include antagonists to the a4b7 and/or a4b7 receptors, antagonists to a4b7 antigen, and antagonists to gene expression products involved in a4b7 mediated disease. Antagonists as disclosed herein, may include, but are not limited to, an anti- a4b7 antibody, an anti- a4b7-binding antibody fragment, or a small molecule. The small molecule may be a small molecule that binds to a4b7 or a respective receptor. The anti- a4b7 antibody may be monoclonal or polyclonal. The anti-a4b7 antibody may be humanized or chimeric. The anti- a4b7 antibody may be a fusion protein. The anti- a4b7 antibody may be a blocking anti- a4b7 antibody. A blocking antibody blocks binding between two proteins, e.g., a ligand and its receptor. Therefore, a a4b7 blocking antibody includes an antibody that prevents binding of a4b7 to corresponding receptor(s). In some cases, the anti- a4b7 antibody is an anti- a4b7 antibody that specifically binds to a4b7.

[0175] In some embodiments, the anti- a4b7 antibody is introduced into a patient by injection. In some embodiments, the injection of an anti- a4b7 antibody is administered intravenously. A non-limiting example of an a4b7 antagonist includes vedolizumab. In some cases, a dosage for an anti- a4b7 antibody, such as vedolizumab, can include a dosage ranging from 275mg to 325mg every 8 weeks after an initial dosage treatment. In some embodiments, an initial dosage treatment for an anti- a4b7 antibody ranges from administering 275mg to 325mg at weeks 0, 2, and 6 of a treatment.

[0176] Examples of conventional drugs that could be used as or included in a CD therapy include, without limitation, aminosalicylates (e.g., mesalazine, sulfasalazine, and the like), corticosteroids (e.g., prednisone), thiopurines (e.g., azathioprine, 6-mercaptopurine, and the like), methotrexate, free bases thereof, pharmaceutically acceptable salts thereof, derivatives thereof, analogs thereof, and combinations thereof.

[0177] In some embodiments, providing or discontinuing one or more types of CD therapy (as described herein) is based on an EHI score. In some instances, one or more types of a CD therapy is continued or discontinued in response to an increase in biomarker levels as compared to an index, control, or previously measured bio-marker level. In some instances, one or more types of a CD therapy is continued or discontinued in response to a decrease in biomarker levels as compared to an index, control, or previously measured bio-marker level. In some instances, one or more types of a CD therapy is continued or discontinued in response to a lack of change over time in biomarker levels. In some instances, one or more types of a CD therapy is continued or discontinued in response to a lack of change over time in an EHI score. In some instances, one or more types of a CD therapy is discontinued in response to an increase in an EHI score as compared to an index, control, or previously calculated EHI score. In some instances, one or more types of a CD therapy is continued in response to a decrease in an EHI score as compared to an index, control, or previously calculated EHI score.

[0178] In some instances, a respective dosage of one or more types of a CD therapy (e.g., pharmaceutical CD therapy) is increased or decreased in response to an increase in biomarker levels as compared to an index, control, or previously measured bio-marker level. In some instances, a respective dosage of one or more types of a CD therapy (e.g., pharmaceutical CD therapy) is increased or decreased in response to a decrease in biomarker levels as compared to an index, control, or previously measured bio-marker level. In some instances, a respective dosage of one or more types of a CD therapy (e.g., pharmaceutical CD therapy) is increased or decreased in response to a lack of change over time in biomarker levels. In some instances, a respective dosage of one or more types of a CD therapy (e.g., pharmaceutical CD therapy) is increased or decreased in response to a lack of change over time in an EHI score. In some instances, a respective dosage of one or more types of a CD therapy (e.g., pharmaceutical CD therapy) is increased in response to an increase in an EHI score as compared to an index, control, or previously calculated EHI score. In some instances, a respective dosage of one or more types of a CD therapy (e.g., pharmaceutical CD therapy) is decreased in response to a decrease in an EHI score as compared to an index, control, or previously calculated EHI score.

[0179] In some instances, the frequency of a respective dosage of one or more types of a CD therapy is increased or decreased in response to an increase in biomarker levels as compared to an index, control, or previously measured bio-marker level. In some instances, the frequency of a respective dosage of one or more types of a CD therapy is increased or decreased in response to a decrease in biomarker levels as compared to an index, control, or previously measured bio-marker level. In some instances, the frequency of a respective dosage of one or more types of a CD therapy is increased or decreased in response to a lack of change over time in biomarker levels. In some instances, the frequency of a respective dosage of one or more types of a CD therapy is increased or decreased in response to a lack of change over time in an EHI score. In some instances, the frequency of a respective dosage of one or more types of a CD therapy is increased in response to an increase in an EHI score as compared to an index, control, or previously calculated EHI score. In some instances, the frequency of a respective dosage of one or more types of a CD therapy is decreased in response to a decrease in an EHI score as compared to an index, control, or previously calculated EHI score.

[0180] In some embodiments, the method assesses mucosal healing. In some embodiments, the method assesses mucosal healing by predicting or monitoring the mucosal status in the patient (e.g. adult or pediatric patient). In some embodiments, the method assesses mucosal healing at a colonic, ileocolonic, and/or ileal disease location in the patient. In some embodiments, the method assesses mucosal healing in the patient after surgery. In some embodiments, the method assesses mucosal healing by identifying post-operative, endoscopic recurrence in the patient.

[0181] Some embodiments include monitoring mucosal healing. For example, multiple EHI scores may be generated over time to monitor the patient (e.g. adult or pediatric patient). Some embodiments include detecting, in a second sample taken from the patient with CD at a second time, a level of each of the one or more biomarkers, and applying the mathematical algorithm to the detected levels of the second sample, thereby producing a second EHI score for the patient.

[0182] In some embodiments, the biomarker levels are obtained multiple times. In some embodiments, monitoring the patient’s mucosal healing comprises generating a first and a second EHI score. In some embodiments, monitoring the patient’s mucosal healing comprises generating 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more EHI scores, or a range of EHI scores defined by any two of the aforementioned numbers of EHI scores.

[0183] In some embodiments, monitoring the patient’s mucosal healing comprises generating two or more EHI scores based on biomarkers in the patient’s serum at two or more times. In some embodiments, each EHI score is generated from a separate serum sample taken from the patient. In some embodiments, each separate serum sample is taken from the patient 1, 2, 3, 4, 5, 10, 15, 20, 25, or 30, or a range defined by any two of the aforementioned integers, days apart. In some embodiments, each separate serum sample is taken from the patient 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12, or a range defined by any two of the aforementioned integers, months apart. In some embodiments, each separate serum sample is taken from the patient 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10, or a range defined by any two of the aforementioned integers, years apart.

[0184] In some embodiments, monitoring the patient’s mucosal healing comprises monitoring the patient’s mucosal healing during the course of a therapy or drug treatment. In some embodiments, the therapy comprises a CD therapy as described herein. In some embodiments, the monitoring begins prior to initiation of the therapy. In some embodiments, the monitoring begins after initiation of the therapy. In some embodiments, the monitoring continues throughout the term of the therapy. In some embodiments, the therapy continues over the course of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, months, or over a range of months defined by any two of the aforementioned integers. In some embodiments, the therapy continues over the course of 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 years, or more, or over a range of years defined by any two of the aforementioned integers. In some embodiments, the therapy is provided to the subject 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 50, or 100 times, or more, or a range of times defined by any two of the aforementioned integers.

[0185] Disclosed herein, in certain embodiments, are methods of evaluating the efficacy of a therapy administered to a patient (e.g. adult or pediatric patient) with CD. Some embodiments include providing a serum sample from the patient. Some embodiments include detecting in the serum sample an expression level of each of one or more biomarkers selected from the group comprising Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7. Some embodiments include applying a mathematical algorithm to the expression levels of the one or more biomarkers, thereby producing an EHI score for the patient. Some embodiments include adjusting the therapy in response to the EHI

score. In some embodiments, the pediatric patient is a human under 18 years of age, for example, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17 years of age, or a range defined by any two of the aforementioned ages. In some embodiments, the one or more biomarkers comprise 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13 (for example, all 13) of the biomarkers selected from the group comprising Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7. In some embodiments, the adjusting comprises decreasing subsequent doses of the therapy when the EHI score is less than or equal to 40 on a scale from 0 to 100. In some embodiments, the adjusting comprises increasing subsequent doses of the therapy when the EHI score is greater than or equal to 50 on a scale from 0 to 100. In some embodiments, the therapy comprises one or more biologic agents, conventional drugs, nutritional supplements, or combinations thereof.

[0186] Disclosed herein, in certain embodiments, are methods of treating Crohn's disease in a patient (e.g. adult or pediatric patient). Some embodiments include obtaining a serum sample from a patient. Some embodiments include detecting in the serum sample an expression level of each of one or more biomarkers selected from the group comprising Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7. Some embodiments include applying a mathematical algorithm to the expression levels of the one or more biomarkers, thereby producing an EHI score for the patient. Some embodiments include diagnosing the patient with a high probability of having endoscopically active disease when the EHI score is greater than or equal to 50 on a scale from 0 to 100. Some embodiments include administering an effective amount of a therapeutic agent to the diagnosed patient. In some embodiments, the pediatric patient is a human under 18 years of age, for example, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17 years of age, or a range defined by any two of the aforementioned ages. In some embodiments, the one or more biomarkers comprise 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13 (for example, all 13) of the biomarkers selected from the group comprising Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7. In some embodiments, the therapeutic agent comprises one or more biologic agents, conventional drugs, nutritional supplements, or combinations thereof.

[0187] Some additional embodiments have been described for patients (e.g. adults) in PCT Application No: PCT/IB2018/053923, filed May 31, 2018, which is incorporated herein by

reference in its entirety. Some embodiments include methods described therein for adults, but for a pediatric patient.

VII. SYSTEMS

[0188] Disclosed herein, in some embodiments, is a system for evaluating a sample from a patient (e.g. adult or pediatric patient) with Crohn’s disease (CD). The system is configured to implement the methods described in this disclosure, including, but not limited to producing a Endoscopic Healing Index (EHI) or EHI. Some embodiments include a central computing environment. Some embodiments include an input device operatively connected to said central computing environment. In some embodiments, said input device is configured to receive biomarker levels. In some embodiments, the biomarkers comprise Ang1, Ang2, CEACAM1, VCAM1, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and/or IL-7. Some embodiments include a trained algorithm executed by said central computing environment. In some embodiments, the trained algorithm is configured to use the biomarker levels to produce a Endoscopic Healing Index (EHI) score. Some embodiments include an output device operatively connected to said central computing environment. In some embodiments, said output device is configured to provide information comprising the EHI score to a user.

[0189] In some instances, the system comprises a central processing unit (CPU), memory (e.g., random access memory, flash memory), electronic storage unit, computer program, communication interface to communicate with one or more other systems, and any combination thereof. In some instances, the system is coupled to a computer network, for example, the Internet, intranet, and/or extranet that is in communication with the Internet, a telecommunication, or data network. In some embodiments, the system comprises a storage unit to store data and information regarding any aspect of the methods described in this disclosure. Various aspects of the system are a product or article or manufacture.

[0190] One feature of a computer program includes a sequence of instructions, executable in the digital processing device’s CPU, written to perform a specified task. In some embodiments, computer readable instructions are implemented as program modules, such as functions, features, Application Programming Interfaces (APIs), data structures, and the like, that perform particular tasks or implement particular abstract data types. In light of the disclosure provided herein, those of skill in the art will recognize that a computer program may be written in various versions of various languages.

[0191] The functionality of the computer readable instructions are combined or distributed as desired in various environments. In some instances, a computer program comprises one sequence of instructions or a plurality of sequences of instructions. A computer program may be provided from one location. A computer program may be provided from a plurality of locations. In some embodiment, a computer program includes one or more software modules. In some embodiments, a computer program includes, in part or in whole, one or more web applications, one or more mobile applications, one or more standalone applications, one or more web browser plug-ins, extensions, add-ins, or add-ons, or combinations thereof.

A. Web application

[0192] In some embodiments, a computer program includes a web application. In light of the disclosure provided herein, those of skill in the art will recognize that a web application may utilize one or more software frameworks and one or more database systems. A web application, for example, is created upon a software framework such as Microsoft® .NET or Ruby on Rails (RoR). A web application, in some instances, utilizes one or more database systems including, by way of non-limiting examples, relational, non-relational, feature oriented, associative, and XML database systems. Suitable relational database systems include, by way of non-limiting examples, Microsoft® SQL Server, mySQL™, and Oracle®. Those of skill in the art will also recognize that a web application may be written in one or more versions of one or more languages. In some embodiments, a web application is written in one or more markup languages, presentation definition languages, client-side scripting languages, server-side coding languages, database query languages, or combinations thereof. In some embodiments, a web application is written to some extent in a markup language such as Hypertext Markup Language (HTML), Extensible Hypertext Markup Language (XHTML), or eXtensible Markup Language (XML). In some embodiments, a web application is written to some extent in a presentation definition language such as Cascading Style Sheets (CSS). In some embodiments, a web application is written to some extent in a client-side scripting language such as Asynchronous Javascript and XML (AJAX), Flash® Actionscript, Javascript, or Silverlight®. In some embodiments, a web application is written to some extent in a server-side coding language such as Active Server Pages (ASP), ColdFusion®, Perl, Java™, JavaServer Pages (JSP), Hypertext Preprocessor (PHP), Python™, Ruby, Tcl, Smalltalk, WebDNA®, or Groovy. In some embodiments, a web application is written to some extent in a database query language such as Structured Query Language (SQL). A web application may

integrate enterprise server products such as IBM® Lotus Domino®. A web application may include a media player element. A media player element may utilize one or more of many suitable multimedia technologies including, by way of non-limiting examples, Adobe® Flash®, HTML 5, Apple® QuickTime®, Microsoft® Silverlight®, Java™, and Unity®.

B. Mobile application

[0193] In some instances, a computer program includes a mobile application provided to a mobile digital processing device. The mobile application may be provided to a mobile digital processing device at the time it is manufactured. The mobile application may be provided to a mobile digital processing device via the computer network described herein.

[0194] A mobile application is created by techniques known to those of skill in the art using hardware, languages, and development environments known to the art. Those of skill in the art will recognize that mobile applications may be written in several languages. Suitable programming languages include, by way of non-limiting examples, C, C++, C#, Featureive-C, Java™, Javascript, Pascal, Feature Pascal, Python™, Ruby, VB.NET, WML, and XHTML/HTML with or without CSS, or combinations thereof.

[0195] Suitable mobile application development environments are available from several sources. Commercially available development environments include, by way of non-limiting examples, AirplaySDK, alcheMo, Appcelerator®, Celsius, Bedrock, Flash Lite, .NET Compact Framework, Rhomobile, and WorkLight Mobile Platform. Other development environments may be available without cost including, by way of non-limiting examples, Lazarus, MobiFlex, MoSync, and Phonegap. Also, mobile device manufacturers distribute software developer kits including, by way of non-limiting examples, iPhone and iPad (iOS) SDK, Android™ SDK, BlackBerry® SDK, BREW SDK, Palm® OS SDK, Symbian SDK, webOS SDK, and Windows® Mobile SDK.

[0196] Those of skill in the art will recognize that several commercial forums are available for distribution of mobile applications including, by way of non-limiting examples, Apple® App Store, Android™ Market, BlackBerry® App World, App Store for Palm devices, App Catalog for webOS, Windows® Marketplace for Mobile, Ovi Store for Nokia® devices, Samsung® Apps, and Nintendo® DSi Shop.

C. Standalone application

[0197] In some embodiments, a computer program includes a standalone application, which is a program that may be run as an independent computer process, not an add-on to an existing process, e.g., not a plug-in. Those of skill in the art will recognize that standalone applications are sometimes compiled. In some instances, a compiler is a computer program(s) that transforms source code written in a programming language into binary feature code such as assembly language or machine code. Suitable compiled programming languages include, by way of non-limiting examples, C, C++, Featureive-C, COBOL, Delphi, Eiffel, Java™, Lisp, Python™, Visual Basic, and VB .NET, or combinations thereof. Compilation may be often performed, at least in part, to create an executable program. In some instances, a computer program includes one or more executable complied applications.

D. Web browser plug-in

[0198] A computer program, in some aspects, includes a web browser plug-in. In computing, a plug-in, in some instances, is one or more software components that add specific functionality to a larger software application. Makers of software applications may support plug-ins to enable third-party developers to create abilities which extend an application, to support easily adding new features, and to reduce the size of an application. When supported, plug-ins enable customizing the functionality of a software application. For example, plug-ins are commonly used in web browsers to play video, generate interactivity, scan for viruses, and display particular file types. Those of skill in the art will be familiar with several web browser plug-ins including, Adobe® Flash® Player, Microsoft® Silverlight®, and Apple® QuickTime®. The toolbar may comprise one or more web browser extensions, add-ins, or add-ons. The toolbar may comprise one or more explorer bars, tool bands, or desk bands.

[0199] In view of the disclosure provided herein, those of skill in the art will recognize that several plug-in frameworks are available that enable development of plug-ins in various programming languages, including, by way of non-limiting examples, C++, Delphi, Java™, PHP, Python™, and VB .NET, or combinations thereof.

[0200] In some embodiments, Web browsers (also called Internet browsers) are software applications, designed for use with network-connected digital processing devices, for retrieving, presenting, and traversing information resources on the World Wide Web. Suitable web browsers include, by way of non-limiting examples, Microsoft® Internet Explorer®,

Mozilla® Firefox®, Google® Chrome, Apple® Safari®, Opera Software® Opera®, and KDE Konqueror. The web browser, in some instances, is a mobile web browser. Mobile web browsers (also called mircrobrowsers, mini-browsers, and wireless browsers) may be designed for use on mobile digital processing devices including, by way of non-limiting examples, handheld computers, tablet computers, netbook computers, subnotebook computers, smartphones, music players, personal digital assistants (PDAs), and handheld video game systems. Suitable mobile web browsers include, by way of non-limiting examples, Google® Android® browser, RIM BlackBerry® Browser, Apple® Safari®, Palm® Blazer, Palm® WebOS® Browser, Mozilla® Firefox® for mobile, Microsoft® Internet Explorer® Mobile, Amazon® Kindle® Basic Web, Nokia® Browser, Opera Software® Opera® Mobile, and Sony® PSP™ browser.

E. Software module

[0201] The medium, method, and system disclosed herein frequently comprise one or more softwares, servers, and database modules, or use of the same. In view of the disclosure provided herein, software modules may be created by techniques known to those of skill in the art using machines, software, and languages known to the art. The software modules disclosed herein may be implemented in a multitude of ways. In some embodiments, a software module comprises a file, a section of code, a programming feature, a programming structure, or combinations thereof. A software module may comprise a plurality of files, a plurality of sections of code, a plurality of programming features, a plurality of programming structures, or combinations thereof. By way of non-limiting examples, the one or more software modules comprise a web application, a mobile application, and/or a standalone application. Software modules may be in one computer program or application. Software modules may be in more than one computer program or application. Software modules may be hosted on one machine. Software modules may be hosted on more than one machine. Software modules may be hosted on cloud computing platforms. Software modules may be hosted on one or more machines in one location. Software modules may be hosted on one or more machines in more than one location.

F. Database

[0202] The medium, method, and system disclosed herein can comprise one or more databases, or use of the same. In view of the disclosure provided herein, those of skill in the art will recognize that many databases are suitable for storage and retrieval of geologic profile, operator activities, division of interest, and/or contact information of royalty owners. Suitable databases include, by way of non-limiting examples, relational databases, non-relational databases, feature oriented databases, feature databases, entity-relationship model databases, associative databases, and XML databases. In some embodiments, a database is internet-based. In some embodiments, a database is web-based. In some embodiments, a database is cloud computing-based. A database may be based on one or more local computer storage devices.

G. Data transmission

[0203] The subject matter described herein, including methods for detecting a particular CD subtype, are configured to be performed in one or more facilities at one or more locations. Facility locations are not limited by country and include any country or territory. In some instances, one or more steps are performed in a different country than another step of the method. In some instances, one or more steps for obtaining a sample are performed in a different country than one or more steps for detecting the presence or absence of a particular CD subtype from a sample. In some embodiments, one or more method steps involving a computer system are performed in a different country than another step of the methods provided herein. In some embodiments, data processing and analyses are performed in a different country or location than one or more steps of the methods described herein. In some embodiments, one or more articles, products, or data are transferred from one or more of the facilities to one or more different facilities for analysis or further analysis. An article includes, but is not limited to, one or more components obtained from a subject, e.g., processed cellular material. Processed cellular material includes, but is not limited to, cDNA reverse transcribed from RNA, amplified RNA, amplified cDNA, sequenced DNA, isolated and/or purified RNA, isolated and/or purified DNA, and isolated and/or purified polypeptide. Data includes, but is not limited to, information regarding the stratification of a subject, and any data produced by the methods disclosed herein. In some embodiments of the methods and systems described herein, the analysis is performed and a subsequent data transmission step will convey or transmit the results of the analysis.

[0204] In some embodiments, any step of any method described herein is performed by a software program or module on a computer. In additional or further embodiments, data from any step of any method described herein is transferred to and from facilities located within the same or different countries, including analysis performed in one facility in a particular location and the data shipped to another location or directly to an individual in the same or a different country. In additional or further embodiments, data from any step of any method described herein is transferred to and/or received from a facility located within the same or different countries, including analysis of a data input, such as genetic or processed cellular material, performed in one facility in a particular location and corresponding data transmitted to another location, or directly to an individual, such as data related to the diagnosis, prognosis, responsiveness to therapy, or the like, in the same or different location or country.

H. Business method using a computer

[0205] The methods described herein may utilize one or more computers. The computer may be used for managing customer and sample information such as sample or customer tracking, database management, analyzing molecular profiling data, analyzing cytological data, storing data, billing, marketing, reporting results, storing results, or a combination thereof. The computer may include a monitor or other graphical interface for displaying data, results, billing information, marketing information (e.g. demographics), customer information, or sample information. The computer may also include means for data or information input. The computer may include a processing unit and fixed or removable media or a combination thereof. The computer may be accessed by a user in physical proximity to the computer, for example via a keyboard and/or mouse, or by a user that does not necessarily have access to the physical computer through a communication medium such as a modem, an internet connection, a telephone connection, or a wired or wireless communication signal carrier wave. In some cases, the computer may be connected to a server or other communication device for relaying information from a user to the computer or from the computer to a user. In some cases, the user may store data or information obtained from the computer through a communication medium on media, such as removable media. It is envisioned that data relating to the methods can be transmitted over such networks or connections for reception and/or review by a party. The receiving party can be but is not limited to an individual, a health care provider or a health care manager. In one embodiment, a computer-readable medium includes a medium suitable for transmission of a result of an analysis of a biological sample, such as exosome bio-signatures. The medium can include a result regarding an exosome bio-signature of a subject, wherein such a result is derived using the methods described herein.

[0206] The entity obtaining biomarker levels or producing an EHI or EHI may enter sample information into a database for the purpose of one or more of the following: inventory tracking, assay result tracking, order tracking, customer management, customer service, billing, and sales. Sample information may include, but is not limited to: customer name, unique customer identification, customer associated medical professional, indicated assay or assays, assay results, adequacy status, indicated adequacy tests, medical history of the individual, preliminary diagnosis, suspected diagnosis, sample history, insurance provider, medical provider, third party testing center or any information suitable for storage in a database. Sample history may include but is not limited to: age of the sample, type of sample, method of acquisition, method of storage, or method of transport.

[0207] The database may be accessible by a customer, medical professional, insurance provider, or other third party. Database access may take the form of electronic communication such as a computer or telephone. The database may be accessed through an intermediary such as a customer service representative, business representative, consultant, independent testing center, or medical professional. The availability or degree of database access or sample information, such as assay results, may change upon payment of a fee for products and services rendered or to be rendered. The degree of database access or sample information may be restricted to comply with generally accepted or legal requirements for patient or customer confidentiality.

VIII. DEFINITIONS

[0208] In some embodiments,“mucosal healing” refers to restoration of normal mucosal appearance of a previously inflamed region, and complete or substantial absence of ulceration and/or inflammation at the endoscopic and/or microscopic levels. In some embodiments, mucosal healing includes repair and restoration of the mucosa, submucosa, and muscularis layers. Mucosal healing can also include neuronal and lymphangiogenic elements of the intestinal wall.“Mucosal healing” is also used herein, in some cases, to refer to the presence or absence of mucosal healing, or to a level of mucosal healing or inflammation/disease, regardless of whether the mucosa is actually healing or not.“Assessing mucosal healing” may include assessing a mucosal inflammation status, regardless of whether the mucosa is healing or not healing (e.g. inflamed).“Monitoring mucosal healing” may include monitoring a mucosal inflammation status, regardless of whether the mucosa is healing or not healing (e.g. inflamed).

[0209] “Endoscopic Healing Index,”“EHI,”“Endoscopic Healing Index score,”“EHI score,”“Mucosal Healing Index,”“Mucosal Healing Index score,”“MHI,” and“MHI score,”

are used interchangeably and refer, in some embodiments, to an empirically derived index that is derived based on an analysis of relevant biomarkers. In some embodiments, the measured concentrations of the biomarkers are transformed into the index by a computer. In some embodiments, the transformation is made by an algorithm resident on a computer. In some embodiments, the index is a synthetic or human derived output, score, or cut off value(s), which express the biological data in numerical terms. The index can be used to determine or make or aid in making a clinical decision. An EHI can be measured multiple instances over the course of time. In some embodiments, the algorithm is trained with known samples and thereafter validated with samples of known identity. In some embodiments, the index is based on an endoscopic measurement such as a CDEIS score.

[0210] Throughout this application, various embodiments may be presented in a range format. It should be understood that the description in range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the disclosure. Accordingly, the description of a range should be considered to have specifically disclosed all the possible subranges as well as individual numerical values within that range. For example, description of a range such as from 1 to 6 should be considered to have specifically disclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numbers within that range, for example, 1, 2, 3, 4, 5, and 6. This applies regardless of the breadth of the range.

[0211] As used in the specification and claims, the singular forms“a”,“an” and“the” include plural references unless the context clearly dictates otherwise. For example, the term “a sample” includes a plurality of samples, including mixtures thereof.

[0212] As used herein, the terms“treatment” or“treating” are used in reference to a pharmaceutical or other intervention regimen for obtaining beneficial or desired results in the recipient. A therapeutic benefit may refer to eradication or amelioration of symptoms or of an underlying disorder being treated. Also, a therapeutic benefit can be achieved with the eradication or amelioration of one or more of the physiological symptoms associated with the underlying disorder such that an improvement is observed in the subject, notwithstanding that the subject may still be afflicted with the underlying disorder.

[0213] The terms“determining,”“measuring,”“evaluating,”“assessing,”“assaying,” and “analyzing” are often used interchangeably herein to refer to forms of measurement. The terms include determining if an element is present or not (for example, detection). These terms can include quantitative, qualitative or quantitative and qualitative determinations. Assessing can be relative or absolute.“Detecting the presence of” can include determining the amount of something present in addition to determining whether it is present or absent depending on the context.

[0214] The terms“subject,”“individual,” or“patient” are often used interchangeably herein. A“subject” can be a biological entity containing expressed genetic materials. The biological entity can be a plant, animal, or microorganism, including, for example, bacteria, viruses, fungi, and protozoa. The subject can be tissues, cells and their progeny of a biological entity obtained in vivo or cultured in vitro. The subject can be a mammal. The mammal can be a human. The subject may be diagnosed or suspected of being at high risk for a disease. In some cases, the subject is not necessarily diagnosed or suspected of being at high risk for the disease.

[0215] As used herein, the term“about” a number refers to that number plus or minus 10% of that number. The term“about” a range refers to that range minus 10% of its lowest value and plus 10% of its greatest value.

IX. ENUMERATED EMBODIMENTS

[0216] Disclosed herein, in some embodiments, are the following:

1. A method for assessing or monitoring mucosal healing in an adult or pediatric patient with Crohn’s Disease (CD), the method comprising:

detecting biomarker levels in a sample from the patient with CD, wherein the biomarkers comprise Ang1, Ang2, VEGFa, FGF2, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, AREG, ANXA13, EREG, HB-EGF, HGF, TGFb, IL-7, GM-CSF, IL-1b, IL-2, IL-5, IL-6, IL-10, IL-12/23p40, IL-13, IL-15, IL-17a, IL-17f, IL-22, IL-23, IL-31, IL-33, CRP, SAA1, ADA, TWEAK, IFN-g, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, or Fibronectin; and

producing a Endoscopic Healing Index (EHI) score for the patient based on the detected biomarker levels.

2. The method of embodiment 1, wherein the pediatric patient is a human under 18 years of age, for example, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17 years of age, or a range defined by any two of the aforementioned ages.

3. The method of embodiment 1 or 2, wherein the biomarkers comprise 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13 (for example, all 13) of the following biomarkers: Angl, Ang2,

CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7.

4. The method of any one of embodiments 1-3, wherein the detecting comprises contacting the sample with binding partners for the biomarkers and detecting binding between the biomarkers and their respective binding partners.

5. The method of embodiment 4, wherein the binding partners are antibodies.

6. The method of any one of embodiments 1-5, further comprising: determining that the patient is in remission or has mild endoscopic disease, or is likely to be in remission or have mild endoscopic disease, when the EHI score is less than or equal to 40 on a scale from 0 to 100.

7. The method of one embodiment 6, wherein the likelihood of the patient being in remission or having mild endoscopic disease is greater than or equal to 86% or 92%, or is 100%.

8. The method of embodiment 6 or 7, wherein the remission corresponds to a Crohn's Disease Endoscopic Index of Severity (CDEIS) score of less than 3.

9. The method of any one of embodiments 1-8, further comprising: determining that the patient is likely to have an endoscopically active disease when the EHI score is greater than or equal to 50 on a scale from 0 to 100.

10. The method of embodiment 9, wherein the high likelihood of the patient having endoscopically active disease is greater than or equal to 87%, or is 100%.

11. The method of embodiment 9 or 10, wherein the endoscopically active disease corresponds to a CDEIS score of greater than or equal to 3.

12. The method of any one of embodiments 1-11, further comprising: determining that the patient has a moderate probability of having endoscopically active disease when the EHI score is between 40 and 50 on a scale from 0 to 100.

13. The method of any one of embodiments 1-12, wherein producing a Endoscopic Healing Index (EHI) score for the patient based on the detected biomarker levels comprises applying a mathematical algorithm to the detected biomarker levels.

14. The method of any one of embodiments 1-12, wherein the mathematical algorithm comprises two or more models relating biomarker levels to an endoscopic score.

15. The method of embodiment 14, wherein one or more of the two or more models are derived by using classification and regression trees, and/or one or more of the two or more models are derived by using ordinary least squares regression to model diagnostic specificity. 16. The method of embodiment 14 or 15, wherein one or more of the two or more models are derived by using random forest learning classification, and/or one or more of the two or more models are derived by using quantile classification.

17. The method of any one of embodiments 14-16, wherein one or more of the two or more models are derived by using logistic regression to model diagnostic sensitivity, and/or one or more of the two or more models are derived by using logistic regression to model diagnostic specificity.

18. The method of any one of embodiments 1-17, further comprising providing the sample from a patient with CD.

19. The method of any one of embodiments 1-18, wherein the sample is a serum sample. 20. The method of any one of embodiments 1-19, further comprising providing, modifying or discontinuing a CD therapy to the patient based on the EHI score.

21. The method of any one of embodiments 1-20, wherein the patient is receiving biologic or non-biologic therapy.

22. The method of embodiment 21, wherein the method assesses mucosal healing by determining the efficacy of the therapy.

23. The method of any one of embodiments 1-22, wherein the method assesses mucosal healing at a colonic, ileocolonic, and/or ileal disease location in the patient.

24. The method of any one of embodiments 1-23, wherein the method assesses mucosal healing in the patient after surgery.

25. The method of embodiment 24, wherein the method assesses mucosal healing by identifying post-operative, endoscopic recurrence in the patient.

26. The method of any one of embodiments 1-25, further comprising monitoring the mucosal status in the patient based on the EHI score.

27. The method of any one of embodiments 1-26, further comprising detecting, in a second sample taken from the patient with CD at a second time, a second level of each biomarker, and applying the mathematical algorithm to the detected biomarker levels of the second sample, thereby producing a second EHI score for the patient.

28. A method of detecting biomarkers levels in a patient (e.g. adult or pediatric patient) with Crohn's disease, wherein the biomarkers comprise Ang1, Ang2, VEGFa, FGF2, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, AREG, ANXA13, EREG, HB-EGF, HGF, TGFb, IL-7, GM-CSF, IL-1b, IL-2, IL-5, IL-6, IL-10, IL-12/23p40, IL-13, IL-15, IL-17a, IL-17f, IL-22, IL-23, IL-31, IL-33, CRP, SAA1, ADA, TWEAK, IFN-g, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, and/or Fibronectin, the method comprising:

obtaining a serum sample from the patient; and

detecting the biomarkers levels in the serum sample by contacting the serum sample with binding partners for the biomarkers and detecting binding between the biomarkers and their respective binding partners.

29. The method of embodiment 28, wherein the binding partners are an antibodies.

30. The method of embodiment 28 or 29, wherein the pediatric patient is a human under 18 years of age, for example, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17 years of age, or a range defined by any two of the aforementioned ages.

31. The method of any one of embodiments 28-30, wherein the biomarkers comprise 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13 (for example, all 13) of the following biomarkers: Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7.

32. A method of evaluating the efficacy of a therapy administered to a patient (e.g. adult or pediatric patient) with CD, the method comprising:

providing a serum sample from the patient;

detecting biomarker levels in the serum sample, wherein the biomarkers comprise Ang1, Ang2, VEGFa, FGF2, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, AREG, ANXA13, EREG, HB-EGF, HGF, TGFb, IL-7, GM-CSF, IL-1b, IL-2, IL-5, IL-6, IL-10, IL-12/23p40, IL-13, IL-15, IL-17a, IL-17f, IL-22, IL-23, IL-31, IL-33, CRP, SAA1, ADA, TWEAK, IFN-g, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, and/or Fibronectin;

applying a mathematical algorithm to the biomarker levels, thereby producing an EHI score for the patient; and

adjusting the therapy in response to the EHI score.

33. The method of embodiment 32, wherein the pediatric patient is a human under 18 years of age, for example, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17 years of age, or a range defined by any two of the aforementioned ages.

34. The method of embodiment 32 or 33, wherein the biomarkers comprise 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13 (for example, all 13) of the following biomarkers: Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7.

35. The method of any one of embodiments 32-34, wherein the adjusting comprises decreasing subsequent doses of the therapy when the EHI score is less than or equal to 40 on a scale from 0 to 100.

36. The method of any one of embodiments 32-35, wherein the adjusting comprises increasing subsequent doses of the therapy when the EHI score is greater than or equal to 50 on a scale from 0 to 100.

37. The method of any one of embodiments 32-36, wherein the therapy comprises one or more biologic agents, conventional drugs, nutritional supplements, or combinations thereof. 38. A method of treating Crohn's disease in a pediatric or adult patient, the method comprising:

obtaining a serum sample from a patient;

detecting biomarker levels in the serum sample, wherein the biomarkers comprise Ang1, Ang2, VEGFa, FGF2, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, AREG, ANXA13, EREG, HB-EGF, HGF, TGFb, IL-7, GM-CSF, IL-1b, IL-2, IL-5, IL-6, IL-10, IL-12/23p40, IL-13, IL-15, IL-17a, IL-17f, IL-22, IL-23, IL-31, IL-33, CRP, SAA1, ADA, TWEAK, IFN-g, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, and/or Fibronectin;

applying a mathematical algorithm to the biomarker levels, thereby producing an EHI score for the patient;

diagnosing the patient with a high probability of having endoscopically active disease when the EHI score is greater than or equal to 50 on a scale from 0 to 100; and

administering an effective amount of a therapeutic agent to the diagnosed patient.

39. The method of embodiment 38 wherein the pediatric patient is a human under 18 years of age, for example, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17 years of age, or a range defined by any two of the aforementioned ages.

40. The method of embodiment 38 or 39, wherein the biomarkers comprise 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13 (for example, all 13) of the following biomarkers: Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7.

41. The method of any one of embodiments 38-40, wherein the therapeutic agent comprises one or more biologic agents, conventional drugs, nutritional supplements, or combinations thereof.

42. A method of assessing or monitoring mucosal healing in a patient comprising generating an EHI score for the patient based on a set of biomarker levels.

43. The method of any one of embodiments 1-42, wherein the biomarkers comprise Ang1, Ang2, VEGFa, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, IL-7, CRP, SAA1, ADA, TWEAK, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, and/or Fibronectin.

44. The method of any one of embodiments 1-43, wherein the biomarkers comprise Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, or IL-7.

45. The method of any one of embodiments 1-44, wherein the biomarkers comprise Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7.

X. FURTHER EMBODIMENTS

[0217] Disclosed herein, in some embodiments, are the following:

1. A computer system for evaluating a sample from an adult or pediatric patient with Crohn’s disease (CD), the system comprising:

a central computing environment;

an input device operatively connected to said central computing environment, wherein said input device is configured to receive biomarker levels, wherein the biomarkers comprise Ang1, Ang2, VEGFa, FGF2, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, AREG, ANXA13, EREG, HB-EGF, HGF, TGFb, IL-7, GM-CSF, IL-1b, IL-2, IL-5, IL-6, IL-10, IL-12/23p40, IL-13, IL-15, IL-17a, IL-17f, IL-22, IL-23, IL-31, IL-33, CRP, SAA1, ADA, TWEAK, IFN-g, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, or Fibronectin;

a trained algorithm executed by said central computing environment, wherein the trained algorithm is configured to use the biomarker levels to produce a Endoscopic Healing Index (EHI) score; and

an output device operatively connected to said central computing environment, wherein said output device is configured to provide information comprising the EHI score to a user. 2. The computer system of embodiment 1, wherein the pediatric patient is a human under 18 years of age, for example, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17 years of age, or a range defined by any two of the aforementioned ages.

3. The computer system of embodiment 1 or 2, wherein the biomarkers comprise 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13 (for example, all 13) of the following biomarkers: Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7.

4. The computer system of any one of embodiments 1-3, wherein the biomarker levels are detected by contacting the sample with binding partners for the biomarkers and detecting binding between the biomarkers and their respective binding partners.

5. The computer system of embodiment 4, wherein the binding partners are antibodies. 6. The computer system of any one of embodiments 1-5, wherein the information further comprises an indication that the patient is in remission or has mild endoscopic disease, or is likely to be in remission or have mild endoscopic disease, when the EHI score is less than or equal to 40 on a scale from 0 to 100.

7. The computer system of one embodiment 6, wherein the likelihood of the patient being in remission or having mild endoscopic disease is greater than or equal to 86% or 92%, or is 100%.

8. The computer system of embodiment 6 or 7, wherein the remission corresponds to a Crohn's Disease Endoscopic Index of Severity (CDEIS) score of less than 3.

9. The computer system of any one of embodiments 1-8, wherein the information further comprises an indication that the patient is likely to have an endoscopically active disease when the EHI score is greater than or equal to 50 on a scale from 0 to 100.

10. The computer system of embodiment 9, wherein the high likelihood of the patient having endoscopically active disease is greater than or equal to 87%, or is 100%.

11. The computer system of embodiment 9 or 10, wherein the endoscopically active disease corresponds to a CDEIS score of greater than or equal to 3.

12. The computer system of any one of embodiments 1-11, wherein the information further comprises an indication that the patient has a moderate probability of having endoscopically active disease when the EHI score is between 40 and 50 on a scale from 0 to 100.

13. The computer system of any one of embodiments 1-12, wherein the trained algorithm comprises a mathematical algorithm that is applied to the received biomarker levels.

14. The computer system of any one of embodiments 1-12, wherein the mathematical algorithm comprises two or more models relating biomarker levels to an endoscopic score. 15. The computer system of embodiment 14, wherein one or more of the two or more models are derived by using classification and regression trees, and/or one or more of the two or more models are derived by using ordinary least squares regression to model diagnostic specificity.

16. The computer system of embodiment 14 or 15, wherein one or more of the two or more models are derived by using random forest learning classification, and/or one or more of the two or more models are derived by using quantile classification.

17. The computer system of any one of embodiments 14-16, wherein one or more of the two or more models are derived by using logistic regression to model diagnostic sensitivity, and/or one or more of the two or more models are derived by using logistic regression to model diagnostic specificity.

18. The computer system of any one of embodiments 1-17, wherein the sample is provided from a patient with CD.

19. The computer system of any one of embodiments 1-18, wherein the sample is a serum sample.

20. The computer system of any one of embodiments 1-19, wherein the information further comprises a recommendation to provide, modify or discontinue a CD therapy to the patient based on the EHI score.

21. The computer system of any one of embodiments 1-20, wherein the patient is receiving biologic or non-biologic therapy.

22. The computer system of embodiment 21, wherein the information further comprises an assessment of mucosal healing based on the efficacy of the therapy.

23. The computer system of any one of embodiments 1-22, wherein the mucosal healing relates to mucosal healing at a colonic, ileocolonic, and/or ileal disease location in the patient. 24. The computer system of any one of embodiments 1-23, wherein the computer system assesses mucosal healing in the patient after surgery.

25. The computer system of embodiment 24, wherein the computer system assesses mucosal healing by identifying post-operative, endoscopic recurrence in the patient.

26. The computer system of any one of embodiments 1-25, configured to produce multiple EHI scores, and wherein the information comprises a monitoring report for the patient’s mucosal healing over time.

27. The computer system of any one of embodiments 1-26, wherein the biomarkers comprise Ang1, Ang2, VEGFa, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, IL-7, CRP, SAA1, ADA, TWEAK, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, and/or Fibronectin.

28. The computer system of any one of embodiments 1-27, wherein the biomarkers comprise Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, or IL-7.

29. The computer system of any one of embodiments 1-28, wherein the biomarkers comprise Angl, Ang2, CEACAMl, VCAMl, TGFa, CRP, SAAl, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7.

XI. EXAMPLES

[0218] The following examples are included for illustrative purposes only and are not intended to limit the scope of the invention.

Example 1: Development and Validation of a Test to Monitor Mucosal Healing or Inflammation in Adult Patients with Crohn’s Disease

Methods

[0219] Patient Selection: Adult CD patients (³18 years) were included if they had: (A) a confirmed diagnosis of CD based on clinical, endoscopic, and histologic data; (B) documented endoscopic disease activity; and (C) sufficient volume of serum sample available for testing. For the validation cohorts we required samples to be available within +/- 45 days of endoscopy. Patients selected for this study were not excluded based on current or prior therapies, prior bowel surgeries, or the presence of an ostomy (ileostomy or colostomy).

[0220] Cohorts: The study consisted of 3 independent cohorts of prospectively collected, retrospectively analyzed samples for training and validation. The training cohort included samples obtained from prospectively recruited convenience sampling biobanks between June 2006 - August 2015 at University of Padua (U Padua), Italy (Jul 2011-Mar 2014); Mount Sinai Hospital, Toronto, Canada (Oct 2008– Aug 2015); University of California San Diego (UCSD, Jun 2014– May 2015), USA; and the STORI clinical trial (GETAID, France, Jun 2006– Jan 2007). Validation cohort 1 included samples collected during the prospective TAILORIX clinical trial (July 2012– September 2015). These included baseline, week 12, and week 54 samples from 116 biologic naïve CD patients recruited from 27 centers in Belgium, France and the Netherlands. Validation cohort 2 included samples collected prospectively from a tertiary referral center in San Diego, USA (UCSD, June 2014– January 2018), which were distinct from those included from this institution in the training cohort.

[0221] Clinical Data Variables: Data on available variables of interest included patient characteristics (age, gender; ethnicity), disease characteristics (prior surgeries, disease-related complications, Montreal phenotype classification), current and prior treatments (corticosteroids, immunosuppressives, biologics), and clinical disease activity (patient reported outcomes (PRO2) or Crohn’s Disease Activity Index (CDAI)).

[0222] Endoscopic Healing Definitions: Endoscopic remission (ER) was defined as a total simple endoscopic score for CD (SES-CD) of £ 2 and £ 1 in each segment (in the two validation cohorts) or a total Crohn’s Disease Endoscopic Index of Severity (CDEIS) score <3 (in the training cohort). Consequently, active disease (AD) was defined as CDEIS score ³ 3 or SES-CD > 2 or SESCD = 2 if only one segment had a score of 2 with a score of 0 in the remaining segments. Endohistopathologic healing (EHPH) was defined as achieving both ER and histologic remission (Global Histologic Disease Activity (GHAS) £ 2). Endoscopic scores were derived using either the SES-CD or the CDEIS score. Scoring was done locally by site investigators at the time of endoscopy in all datasets except TAILORIX where endoscopies were scored by blinded central readers. In the derivation-training cohort all SES-CD scores were converted to CDEIS scores for consistency during training (FIG. 6). Histologic disease activity assessments were available in validation cohort 2 and were done by a pathologist with expertise in gastrointestinal pathology and IBD (M.V.) who was blinded to endoscopy scores. Four biopsies were taken from each intestinal segment (using segments identical to those used to calculate SES-CD score) with matching endoscopic scores. Biopsies were taken from the

most active endoscopic area, and if no active inflammation was observed then random biopsies were taken.

[0223] Sample Storage and Testing: All serum samples and fecal samples were frozen within 24 hours of collection to avoid degradation or loss in biomarkers, and kept frozen at -80 degrees Celsius until testing. Thawed serum and stool samples were tested for all biomarkers in a randomized manner with clinical data blinded to the operator.

[0224] Serum CRP was tested using a turbidity assay (hsCRP, Beckman Coulter, Brea, CA). Other serum biomarkers were measured via multiplexed fluorescent immunoassays. Serum specimens were added to a mixture of color-coded beads, which were pre-coated with analyte-specific capture antibodies. Biotinylated detection antibodies specific to the target analytes were then added to form an antibody-antigen sandwich. Afterwards phycoerythrin (PE)-conjugated streptavidin was added, which bound to the biotinylated detection antibodies. The magnitude of the PE-derived signal, which was directly proportional to the amount of target analyte in the sample, was then detected in a flow-based instrument. Values of FC from the STORI trial and the TAILORIX trial were used directly without retesting. Values of FC in Validation cohort 2 were measured using the QUANTA Lite® Calprotectin Extended Range assay (Inova Diagnostics, San Diego, CA).

[0225] EHI Development: Preliminary serum biomarker candidates were identified from literature review and assessed by the strength of the corresponding evidence, the relevance of their biological functions to CD, and the involvement of their signal pathways in CD pathogenesis (Table 5). Assays were then developed for the selected biomarker candidates and evaluated for their analytical performance. Biomarker candidates whose assays showed poor analytical reproducibility, low detection rate in serum specimens, and/or lack of correlation to disease severity in preliminary studies (data not shown) were eliminated from further consideration as training progressed to validation. As candidate biomarkers were tested, new panels were developed with progressively fewer target biomarkers.

[0226] A panel with 47 biomarkers included: Ang1, Ang2, VEGFa, FGF2, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, AREG, ANXA13, EREG, HB-EGF, HGF, TGFb, IL-7, GM-CSF, IL-1b, IL-2, IL-5, IL-6, IL-10, IL-12/23p40, IL-13, IL-15, IL-17a, IL-17f, IL-22, IL-23, IL-31, IL-33, CRP, SAA1, ADA, TWEAK, IFN-g, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, and Fibronectin.

[0227] This was further reduced to a panel with 24 biomarkers, including Ang1, Ang2, VEGFa, CEACAM1, VCAM1, Alcam, a4b7, ICAM-1, MAdCAM, TGFa, BTC, EGF, SCF, IL-7, CRP, SAA1, ADA, TWEAK, EMMPRIN, MMP-1, MMP-2, MMP-3, MMP-9, and Fibronectin. Subsequent validation was performed on this 24-analyte panel, which showed that this panel correlated with clinical disease.

[0228] A panel with 13 analytes was shown to correlate with clinical disease. This panel included Ang1, Ang2, CEACAM1, VCAM1, TGFa, CRP, SAA1, MMP-1, MMP-2, MMP-3, MMP-9, EMMPRIN, and IL-7. An analytical method validation (AMV) was also performed on the 13-biomarker panel.

[0229] Multiple logistic regression method was used to predict endoscopic activity as a function of serum biomarker concentrations proposed as continuous predictors after logarithmic transformation and combined through backward elimination with Akaike information criterion (AIC). Biomarkers were removed one by one by sequentially reducing the AIC value until a minimum of AIC was reached, using standard settings in JMP (version 12.0; SAS Institute, Cary, NC). EHI was obtained by transforming the logistic function in terms of probability to be in active disease. A small fraction of patients (11.5%) contributed more than one sample in the training cohort. Samples from same patients were treated as independent samples, an imperfection limited to the training cohort.

[0230] Endpoints: A primary aim was to assess the sensitivity (proportion of patients above a specific EHI limit among patients with active disease (SES-CD>2 or SES-CD=2 if only one segment has a score of 2 with a score of 0 in the remaining segments)) and specificity (proportion of patients below a specific EHI limit among patients in endoscopic remission (SES-CD) of £ 2 and £ 1 in each segment)) of the EHI at various cut-offs for identifying the presence of endoscopic inflammation. Secondary aims were to explore the diagnostic accuracy of the EHI at various cut-offs for identifying the presence of endohistopathologic inflammation, and to compare the diagnostic accuracy of EHI to CRP and FC. Positive likelihood ratio (PLR), negative likelihood ratio (NLR), positive predictive value (PPV), negative predictive value (NPV) and area under the receiver operating characteristic (ROC) curve (AUROC) were used as secondary measures to assess the performance of EHI. Finally, the responsiveness of EHI was assessed as compared to endoscopy, CRP, and FC, to assess its utility as a tool for monitoring endoscopic disease activity in patients with CD.

[0231] Statistical Analysis: The Delong method was used for computing the 95% confidence interval (CI) of AUROC and for comparing AUROCs of different biomarkers on paired samples. Exact binomial confidence limits were used for the 95% CIs of sensitivity and specificity. The 95% CIs of PLR and NLR were computed. Pairwise Wilcoxon rank sum test was used for comparing effect size of different variables. A p value (two-sided) of 0.05 or lower was considered as significant. All data analysis was carried out using JMP (version 12.0; SAS Institute, Cary, NC) or R (version 3.3.2). A mixed-effect logistic regression modeling was utilized for Validation cohort 1 to assess the performance of EHI, CRP and FC effect sizes of SES-CD, CDEIS score, EHI, FC and CRP were calculated between baseline and week 12 and between baseline and week 54 to assess the responsiveness of those variables.

[0232] Continuous variables were reported as medians with interquartile ranges (IQR), and compared between groups using the Mann-Whitney test. Categorical variables are reported as numbers (n) and percentages (%), and compared between groups using the Fisher’s exact test. The Delong method was used for computing the 95% confidence interval (CI) of AUROC and for comparing AUROCs of different biomarkers on paired samples. Exact binomial confidence limits were used for the 95% CIs of sensitivity and specificity. The 95% CIs of PLR and NLR were computed. Pairwise Wilcoxon rank sum test was used for comparing effect size of different variables. A p value (two-sided) of 0.05 or lower was considered as significant. All data analysis was carried out using JMP (version 12.0; SAS Institute, Cary, NC) or R (version 3.3.2).

[0233] For validation of cohort 1, where longitudinal samples were available, a mixed-effect logistic regression modeling was utilized to assess the performance of EHI, CRP and FC (response: disease status of endoscopic remission or active disease; fixed effect: EHI, CRP or FC; random effect: random intercepts for study subjects). The values of CRP and FC were first logarithmic transformed in the modeling. For samples whose FC test result was 0, the corresponding FC values were set to 10 mg/g, which was well below the minimal nonzero FC value of 31 mg/g observed in the cohort. Subsequently, effect sizes of SES-CD, CDEIS score, EHI, FC and CRP were calculated between baseline and week 12 and between baseline and week 54 to assess the responsiveness of those variables. Since the underlying data were mostly not normally distributed, the corresponding median and inter quartile range (IQR) were reported instead of the mean.

[0234] Sample Size Calculation: No sample size calculation was performed on the training cohort. EHI had a sensitivity of 90% at the threshold of 20 and a specificity of 95% at the threshold of 50 in the training cohort. An aim was to validate such performance in the validation cohorts with precisions such that the corresponding one-sided lower 95% confidence limits of sensitivity and specificity were ³80% and ³85%, respectively. Based on exact binomial confidence limits, a minimal of 57 samples from CD patients with active disease (AD) and a minimal of 40 samples from CD patients in ER were needed for the validation study.

Results

[0235] Patient Demographics: Serum samples from a total of 589 patients were used (Table 6) distributed across the training and two distinct validation cohorts without any sample overlap among the training and validation cohorts. The flow chart describing the patients and samples used in the two validation cohorts is shown in FIG. 7A and FIG. 7B. All validation samples used in this study were obtained ± 45 days of endoscopy with ~66% (311/470) of samples collected on the same day as the endoscopy: Validation cohort 1: 123/275 (44.7%), Validation cohort 2: 188/195 (96.4%).90.1% of the training samples were also obtained ± 45 days of endoscopy with 43.9% (147/335) samples collected on the same day as the endoscopy. Median elapse from endoscopy to sample collection was 0 (day, IQR: 0-14.5) in the training cohort.

[0236] The training cohort included 278 patients with a total of 335 endoscopy visits. (Table 7) Median age was 30.0 years (IQR: 24.9-40.0) with 46.0% females. Median disease duration was 4 years (IQR: 3.0-12.5). Validation cohort 1 included 116 patients with a median age of 30.2 years (IQR: 22.4-45.2) and 59.5% females. The cohort included a total of 275 endoscopy visits distributed at baseline (102 visits), weeks 12 (98 visits) and 54 (75 visits). FC was available at the same time points (Table 8). Validation cohort 2 included 195 patients with one endoscopy visit per patient. Median age of the cohort was 38.5 years (IQR: 28.0-52.0) with 49.7% females. A sub-cohort of validation cohort 2 (N=81) patients also had paired fecal calprotectin values obtained from stool samples collected within 45 days of endoscopy (Table 9).

[0237] The two validation cohorts differed significantly in baseline age (30.2 vs. 38.5 years, p<0.001), disease duration (0.7 vs. 11.0 years, p<0.001), disease phenotype (Non-stricturing, non-penetrating 73% vs.58%, p=0.006), prior IBD related bowel surgery (10% vs. 46%, p<0.001) and prior biologic exposure (0% vs.77%, p<0.001). The median SES-CD (6.0

vs.3.0, p<0.001) and FC (336 vs.55, p<0.001) were significantly higher in validation cohort 1, with comparable CRP values (2.5 vs.2.6, p=0.460). All disease locations were represented in the training and both validation cohorts.

[0238] Training of the Endoscopic Healing Index (EHI): The 47 markers evaluated for the development of EHI are listed in Table 5. The panel of 24 biomarkers were surprisingly effectual as indicators of mucosal healing and/or inflammation. Eleven markers were further eliminated during logistic regression analyses as they did not enhance the performance of EHI. The lack of an enhancement of performance in indicating mucosal healing of the 11 biomarkers that were further eliminated surprisingly indicates that these 11 biomarkers may be used in place of other biomarkers in an EHI. For example, biomarkers in Table 5 marked with a superscripted 1 may in some instances replace one another within the same biomarker grouping (such as angiogenesis, cell adhesion, growth factors, immune modulation, inflammation, or matrix remodeling), or replace other biomarkers within the same grouping that are used in an EHI, to produce an EHI indicative of mucosal healing. The final EHI model included serum concentrations of 13 biomarkers: angiopoietin 1 (ANG1) and 2 (ANG2), carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1), C-reactive protein (CRP), serum amyloid A1 (SAA1), Interleukin-7 (IL7), transforming growth factor alpha (TGFa), vascular cell adhesion molecule 1 (VCAM1), extracellular matrix metalloproteinase inducer (EMMPRIN), and matrix metalloproteinase-1 (MMP1), -2 (MMP2), -3 (MMP3), and -9 (MMP9).

[0239] EHI was constructed as a scale of 0– 100 arbitrary units of EHI activity, a higher score indicating more severe disease activity. Analytical reproducibility of EHI was established using Deming regression (FIG. 8) with a slope of 1.005 (95% CI: 0.926– 1.087) and an intercept of -0.298 (95% CI: -2.790– 2.144).

[0240] AUROC of EHI for distinguishing AD from ER in the training cohort was 0.748 (95% CI: 0.696– 0.800). Sensitivity and specificity of EHI was evaluated at increasing cut-offs from 20-50 (Table 10), covering the clinically relevant region (from high sensitivity to high specificity) as observed in the training cohort. EHI demonstrated a sensitivity and specificity of 90.3% (95% CI: 85.0– 94.3) and 95.0% (90.3– 97.8) at cut-offs 20 and 50, respectively, in the training cohort.

[0241] Validation Cohort 1: The median global endoscopic SES-CD score with corresponding median EHI values were 15.0 (IQR 9.0-22.0) and 55.5 (IQR 42.0-72.8) at

baseline, 4.0 (IQR: 2.0-8.0) and 33.5 (IQR 23.0-41.8) at week 12, 1.0 (IQR: 0.0-3.0) and 25.0 (IQR 19.0-37.5) at week 52, respectively. The prevalence of ER among patients with paired endoscopy and serum samples in validation cohort 1 was 0% at baseline, 26.5% at week 12, and 60% at week 52. AUROC for distinguishing AD from ER was 0.962 (95% CI: 0.942– 0.982) (FIG.3A). Sensitivity for ruling out endoscopic inflammation at an EHI cut-off £20 was 97.1% (95% CI: 93.7– 98.9) (Table 1). At EHI cut-offs 40 and 50, the specificity for ruling in AD was 100% (95% CI: 94.9– 100.0). At a cut-off of 30, sensitivity and specificity for endoscopic inflammation was 84.8% (95% CI: 79.1-89.4) and 91.5% (95% CI: 82.5-96.8), respectively. The positive likelihood ratios (PLR) for detecting AD demonstrated a steady increase from 3.132 (95% CI: 2.212-4.436) to infinity with increasing EHI cut-offs while the negative likelihood ratios (NLR) were no greater than 0.627 (95%CI: 0.564-0.697). Prevalence of AD at EHI ³50 was 100% and the prevalence of ER at EHI<20 was 89.1% (FIG.7A and FIG.7B).

[0242] Validation Cohort 2: The median global SES-CD score was 3.0 (IQR 0.0-6.5) and the median EHI value was 32 (IQR 19.5-46.5). Prevalence of ER was 42.1% (82/195). AUROC of EHI for distinguishing AD from ER was 0.693 (0.619– 0.767) (FIG.1B). Sensitivity was the highest at an EHI cut-off 20 at 83.2% (95% CI: 75.0– 89.6) (Table 1). The specificity of the test progressively increased with increasing EHI cut-offs, and at an EHI cut-off of 50 the specificity was observed to be 87.8% (95% CI: 78.7– 94.0). Prevalence of AD at EHI ³50 was 77.3% and the prevalence of ER at EHI<20 was 61.2% (FIG.7A and FIG.7B). PPV and NPV in Validation cohorts 1 and 2 at EHI cut-offs 20 and 50 were calculated at assumed AD prevalence ranging from 5-75% (Table 2). Presence or absence of prior IBD-related surgeries did not impact the performance of EHI (AUROC in patients with prior surgery (FIG.9): 0.699 (95% CI: 0.588– 0.811); AUROC in patients without prior surgery: 0.680 (95% CI: 0.578– 0.782), p=0.801). Paired histology data was available for a subset of Validation cohort 2 (N = 79) patients. The AUROC estimate of EHI for distinguishing endohistopathologic healing (defined as endoscopic remission + histologic remission) from active endoscopic or histologic disease was 0.666 (95% CI: 0.536– 0.797) (FIG.10).

[0243] Diagnostic Performance of EHI by Disease Location and Phenotype: The AUROC of EHI for distinguishing AD vs ER was not significantly different across disease locations in both validation cohorts (FIG.11A and FIG.11B; pairwise P³0.171 and P³0.292, respectively). EHI performance was also comparable across disease behaviors B1, B2, B3 (FIG.12A and FIG.12B).

[0244] Sensitivity and specificity in each location were evaluated at cut-offs that had a high performance in both validation cohort 1 (Table 11) and validation cohort 2 (Table 12). In validation cohort 1, an EHI cut-off of 20 demonstrated a high sensitivity when the cohort was limited to L1 disease (98.1%; 95% CI: 89.7– 100.0%), L2 disease (100%, 95% CI: 88.4– 100.0%) or L3 disease (95.7%; 95% CI: 90.1– 98.6%). The specificity at EHI cut-offs 40 and 50 was 100% regardless of the disease location. Similarly, in validation cohort 2, sensitivity and specificity at cut-offs 20 and 50, respectively, by disease location was as follows: L1 (sensitivity = 84.6%, specificity = 100.0%), L2 (sensitivity = 78.9%, specificity = 79.3%) and L3 (sensitivity = 85.1%, specificity = 86.2%).

[0245] Comparison of EHI to CRP: AUROC of EHI to distinguish active endoscopic disease from ER was significantly higher than that of CRP alone in Validation cohort 1 (EHI = 0.962; 95% CI: 0.942– 0.982, CRP = 0.876; 95% CI: 0.835– 0.916, p<0.001) (FIG.3A and FIG.3B). In Validation cohort 2, AUROC of EHI was numerically better than CRP but did not reach significance (EHI = 0.693; 95% CI: 0.619– 0.767, CRP = 0.624; 95% CI: 0.544– 0.704, p=0.109). Diagnostic performance of EHI was also significantly better than the corresponding AUROC of CRP in the training cohort (EHI vs CRP: 0.748 vs.0.604; p<0.001). CRP cut-off of 5 mg/L had a sensitivity of 41.7– 44.3% in both validation cohorts 1 and 2 (Table 3 and Table 4). At a cut-off of 20, EHI had a sensitivity of 91.7– 96.2%. PPV and NPV in Validation cohorts 1 and 2 at CRP cut-offs 3 and 5mg/L were calculated at assumed AD prevalence ranging from 5-75% (Table 4) and compared to that of EHI.

[0246] Comparison of EHI to FC: A total of 247 FC assessments were available in Validation cohort 1 (FIG. 4A and FIG.4B), and 81 paired stool samples were available in Validation cohort 2, for comparison between EHI and FC. The sub-cohorts with and without FC available from validation cohort 2 were comparable for all baseline characteristics (Table 9) although a hidden bias cannot be ruled out. The diagnostic accuracy of EHI was not significantly different from that of FC in either of the two validation cohorts; in Validation cohort 1 it was numerically superior to FC (EHI vs FC: AUROC 0.950 vs 0.923, p=0.147) but numerically inferior in Validation cohort 2 (EHI vs FC: AUROC 0.803 vs 0.854, p=0.298). A FC cut-off of 50 mg/g had 100% sensitivity in validation cohort 1, and 75% sensitivity in validation cohort 2. Corresponding sensitivity for EHI at a cut-off of 20 was 96% in validation cohort 1 and 92% in validation cohort 2. A FC cut-off of 250 mg/g had 89% specificity in validation cohort 1, and 100% specificity in validation cohort 2. Corresponding specificity for EHI at a cut-off of 50 was 100% in validation cohort 1 and 91% in validation cohort 2. (Table 3 and Table 4) PPV and NPV in Validation cohorts 1 and 2 at FC cut-offs 50 and 250 mg/g were calculated at assumed AD prevalence ranging from 5-75% (Table 2) and compared to that of EHI.

[0247] Responsiveness of EHI: Endoscopy paired, longitudinal serum samples were available from 97 patients in Validation cohort 1. Effect sizes (ES) were calculated between baseline and week 12 (n = 70 patients; FIG. 5A) and between baseline and week 54 (n = 59 patients; FIG. 5B) for the 2 endoscopic indices (SES-CD and CDEIS score) and the 3 biomarkers (EHI, CRP, FC). Between baseline and week 12, median ES of EHI (1.10, IQR 0.52– 1.83) was numerically better than that of FC (0.96, IQR 0.43– 1.96, p=0.423) and significantly better than that of CRP (0.26, IQR 0.11– 0.51, p<0.001). Similar results were noted between baseline and week 54 where median ES of EHI (1.64, IQR 0.65– 2.29) was numerically better than that of FC (1.16, IQR 0.51– 2.32, p=0.574) and significantly better than that of CRP (0.21, IQR 0.09– 0.56, p<0.001). Between both time intervals, median ES of EHI was on par with those of the endoscopic scores and mirrored changes in SES-CD and CDEIS score (SES-CD between weeks 0-12: 1.53, IQR 0.67– 2.23, p=0.077; SES-CD between weeks 0-54: 1.87, IQR 0.93– 2.67, p=0.069; CDEIS score between weeks 0-12: 1.29, IQR 0.80– 2.25, p=0.182; CDEIS score between weeks 0-54: 1.50, IQR 0.81– 2.17, p=0.997).

Tables

[0248] Table 1 shows diagnostic accuracy of EHI in accordance with some embodiments. The table includes: True Positives (TPs), True Negatives (TNs), Sensitivity, Specificity, Positive Likelihood Ratio (PLR) and Negative Likelihood Ratio (NLR) of Endoscopic Healing Index (EHI) in Distinguishing AD vs ER in Validation Cohort 1 and Validation Cohort 2.

[0249] Table 2 comparatively shows PPV and NPV of EHI, CRP and FC. The table includes: Sensitivity, Specificity, Positive Predictive Value (PPV) and Negative Predictive Value (NPV) of Endoscopic Healing Index (EHI), CRP and FC in Distinguishing Endoscopic Remission versus Active Disease in the Two Validation Cohorts under Different Possible Prevalence of Active Disease.

[0250] Table 3 shows comparative diagnostic accuracy of EHI to CRP and FC in Validation Cohort 1. The table includes: True Positives (TPs), True Negatives (TNs),

Sensitivity, Specificity, Positive Likelihood Ratio (PLR) and Negative Likelihood Ratio (NLR) of Endoscopic Healing Index (EHI), C-Reactive Protein (CRP) and Fecal Calprotectin (FC) in Distinguishing AD (n=183) vs ER (n=64) in the FC Sub-Cohort of Validation 1.

[0251] Table 4 shows comparative diagnostic accuracy of EHI to CRP and FC in Validation Cohort 2. The table includes: True Positives (TPs), True Negatives (TNs), Sensitivity, Specificity, Positive Likelihood Ratio (PLR) and Negative Likelihood Ratio (NLR) of Endoscopic Healing Index (EHI), C-Reactive Protein (CRP) and Fecal Calprotectin (FC) in Distinguishing AD (n=48) vs ER (n=33) in the FC Sub-Cohort of Validation 2.

[0252] Table 5 provides details about biomarkers, in accordance with some embodiments. P values are labeled as follows: ***p<0.001, **0.001<p<0.01, *0.01<p<0.05.

[0253] Table 6 provides details about subject and sample characteristics of study cohorts, in accordance with some embodiments.

[0254] Table 7 provides details about subject and sample characteristics of a training cohort, in accordance with some embodiments.

[0255] Table 8 provides details about subject and sample characteristics of Validation Cohort 1.

[0256] Table 9 provides details about subject and sample characteristics of Validation Cohort 2 and sub-cohorts with or without fecal calprotectin.

[0257] Table 10 provides details about true positives, true negatives, sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of EHI in distinguishing active disease vs endoscopic remission by disease location in a training cohort.

[0258] Table 11 provides details about true positives, true negatives, sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of EHI in distinguishing active disease vs endoscopic remission by disease location in Validation Cohort 1.

[0259] Table 12 provides details about true positives, true negatives, sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of EHI in distinguishing active disease vs endoscopic remission by disease location in Validation Cohort 2.

Table 1

Table 2

Sensitivity, Specificity, Positive Predictive Value (PPV) and Negative Predictive Value (NPV) of endoscopic Healing Index (EHI), CRP and FC in Distinguishing Endoscopic Remission versus Active Disease in the Two Validation Cohorts under Different Possible Prevalence of Active Disease.

Validation 1 Validation 2 Validation 1 Validation 2 Sensitivity 0.962 0.917 0.355 0.354 Specificity 0.641 0.424 1.000 0.909 Prevalence PPV NPV PPV NPV PPV NPV PPV NPV 0.05 0.124 0.997 0.077 0.990 1.000 0.967 0.170 0.964 0.25 0.472 0.981 0.347 0.939 1.000 0.823 0.565 0.808 0.40 0.641 0.962 0.515 0.885 1.000 0.699 0.722 0.679 0.60 0.801 0.918 0.705 0.773 1.000 0.508 0.854 0.484 0.75 0.889 0.849 0.827 0.630 1.000 0.341 0.921 0.319

Validation 1 Validation 2 Validation 1 Validation 2 Sensitivity 0.596 0.625 0.443 0.417 Specificity 0.938 0.636 0.969 0.727 Prevalence PPV NPV PPV NPV PPV NPV PPV NPV 0.05 0.336 0.978 0.083 0.970 0.429 0.971 0.074 0.960 0.25 0.762 0.874 0.364 0.836 0.826 0.839 0.337 0.789 0.40 0.865 0.777 0.534 0.718 0.905 0.723 0.505 0.652 0.60 0.935 0.608 0.720 0.531 0.955 0.537 0.696 0.454 0.75 0.966 0.436 0.837 0.361 0.977 0.367 0.821 0.294

Validation 1 Validation 2 Validation 1 Validation 2 Sensitivity 1.000 0.750 0.683 0.438 Specificity 0.063 0.788 0.891 1.000 Prevalence PPV NPV PPV NPV PPV NPV PPV NPV 0.05 0.053 1.000 0.157 0.984 0.248 0.982 1.000 0.971 0.25 0.262 1.000 0.541 0.904 0.676 0.894 1.000 0.842 0.40 0.416 1.000 0.702 0.825 0.807 0.808 1.000 0.727 0.60 0.616 1.000 0.841 0.678 0.904 0.652 1.000 0.543 0.75 0.762 1.000 0.914 0.512 0.949 0.484 1.000 0.372

Table 3

Table 4

Table 5

Table 6

Subject and Sample Characteristics of the Study Cohortsa

Characteristics Training Validation 1 Validation 2 P valueb P valueb P valueb

(TAILORIX) (UCSD) (Training (Training (Validation vs vs 1 vs 2) Validation Validation

Subjects

n 278 116 195

Age (years) 30.0 (24.9- 30.2 (22.4-45.2) 38.5 (28.0- 0.842 <0.001 <0.001

40.0)[2] 52.0)[17]

Female sex 128 (46.0) 69 (59.5) 92 (49.7)(10) 0.020 0.449 0.123 Race/Ethnicity - 0.039 - African 5 (1.8) - 5 (2.6)

American

Asian 14 (5.0) - 3 (1.5)

White 160 (57.6) - 125 (64.1)

Hispanic 5 (1.8) - 8 (4.1)

Other 5 (1.8) - 0 (0.0)

Unknown 89 (32.0) - 54 (27.7)

CD duration 4.0 (3.0- 0.7 (0.1-6.9) 11.0 (5.0- 0.002 0.018 <0.001 (years) 12.5)[260] 19.0)[16]

Age at diagnosis [100] [12] <0.001 0.017 <0.001 (years)

A1: £16 55 (30.9) 6 (5.2) 49 (26.8)

A2: 17-40 106 (59.6) 86 (74.1) 97 (53.0)

A3: >40 17 (9.6) 24 (20.7) 37 (20.2)

CD location [100] [5] [5] 0.738 <0.001 0.002 L1: Ileal 43 (24.2) 27 (24.3) 47 (24.7)

L2: 26 (14.6) 20 (18.0) 67 (35.3)

Colonic

L3: 109 (61.2) 64 (57.7) 76 (40.0)

Ileocolonic

CD behavior [186] [5] [1] <0.001 <0.001 0.006 B1: Non- 26 (28.3) 81 (73.0) 112 (57.7)

stricturing,

non- penetrating

B2: Stricturing 57 (62.0) 17 (15.3) 31 (16.0)

B3: Penetrating 9 (9.8) 13 (11.7) 51 (26.3)

Perianal disease 29 (17.5)[112] 31 (27.9)[5] 21 (10.8) 0.052 0.069 <0.001 modifier

Biologic - 0 (0) 139 (77.2)[15] - - <0.001 medication use

History of IBD - 12 (10.3) 90 (46.2) - - <0.001 related surgery

Samples

n 335 275 195

Endoscopic 159 (47.5) 71 (25.8) 82 (42.1) <0.001 0.241 <0.001 remissionc

CDEIS 2.8 (0.2- 4.4 (0.8-9.1) - 0.016 - - 6.0)[202]

SES-CD 6.0 (1.0- 6.0 (2.0-12.0) 3.0 (0.0-6.5) 0.321 <0.001 <0.001 12.0)[133]

CRP (mg/L) 2.0 (0.7-6.5) 2.5 (0.5-7.2) 2.6 (0.7-7.1) 0.586 0.172 0.460 Fecal calprotectin 50.8 (30.1- 336.0 (100.0- 55.0 (0.0- <0.001 0.086 <0.001 (µg/g) 270.3)[273] 1197.5)[28] 251.1)[114]

EHI 32 (20-44) 38 (25-53) 32 (19.5-46.5) 0.001 0.752 0.006 aContinuous variables are reported as median (inter-quartile range), categorical variables are reported as n (%), and numbers of missing data, if any, are listed inside brackets ([n]).

bBased on Mann-Whitney test for continuous variables and Fisher’s exact test for categorical variables.

cOn the training cohort, SES-CD scores were first converted to CDEIS scores by: CDEIS = 0.1569 + 0.6744^SES-CD (see Supplementary Figure 1).

Endoscopic remission was then defined as either original or converted CDEIS score < 3. On validation cohorts, endoscopic remission was defined as a total SES-CD of £ 2 and £ 1 in each segment.

Table 7

Subject and Sample Characteristics of the Study Cohortsa

Characteristics Total U Padua, Italy MSH, Toronto STORI UCSD Subjects

n 278 18 146 83 31 Age (years) 30.0 (24.9-40.0)[2] 34.5 (26.5-51.5) 29.0 (23.0-39.2)[12] 31.6 (25.6-39.2) 30.0 (23.5-45.0) Female sex 128 (46.0) 5 (27.8) 63 (43.2) 45 (54.2) 15 (48.4) Race/Ethnicity

African American 5 (1.8) 0 (0.0) 5 (3.4) - 0 (0.0) Asian 14 (5.0) 0 (0.0) 13 (8.9) - 1 (3.2) White 160 (57.6) 18 (100.0) 115 (78.8) - 27 (87.1) Hispanic 5 (1.8) 0 (0.0) 3 (2.1) - 2 (6.5) Other 5 (1.8) 0 (0.0) 4 (2.7) - 1 (3.2) Unknown 89 (28.7) 0 (0.0) 6 (4.1) - 0 (0.0) Disease duration (years) 4.0 (3.0-12.5)[260] 4.0 (3.0-12.5) - - - Age at diagnosis (years) [100] [17] [83]

A1: £16 55 (30.9) 0 (0.0) 47 (36.4) - 8 (25.8) A2: 17-40 106 (59.6) 13 (72.2) 74 (57.4) - 19 (61.3) A3: >40 17 (9.6) 5 (27.8) 8 (6.2) - 4 (12.9) CD location [100] [17] [83]

L1: Ileal 43 (24.2) 9 (50.0) 27 (20.9) - 7 (22.6) L2: Colonic 26 (14.6) 3 (16.7) 11 (8.5) - 12 (38.7) L3: Ileocolonic 109 (61.2) 6 (33.3) 91 (70.5) - 12 (38.7) CD behavior [186] [102] [83] [1] B1: Non- 26 (28.3) 7 (38.9) 0 (0.0) - 19 (63.3) stricturing,

Non-penetrating

B2: Stricturing 57 (62.0) 6 (33.3) 44 (100.0) - 7 (23.3) B3: Penetrating 9 (9.8) 5 (27.8) 0 (0.0) - 4 (13.3) Perianal disease 29 (17.5)[112] 2 (11.1) 25 (17.1) - 2 (100)[29] modifier

Samples

n 335 50 157 83 45 Endoscopic Remissionb 159 (47.5) 5 (10.0) 67 (42.7) 63 (75.9) 24 (53.3) CDEIS 2.8 (0.2-6.0)[202] 6.6 (4.0-17.6) - 0.7 (0.0-2.8) - SES-CD 6.0 (1.0-12.0)[133] - 6.0 (2.0-12.0) - 4.0 (0.0-9.0) CDAI 59.5 (24.2-123.8)[205] 147.0 (120.0-240.0)[3] - 36.5 (17.2-61.1) - CRP (mg/L) 2.0 (0.7-6.5) 1.3 (0.6-4.4) 3.6 (1.0-6.5) 1.4 (0.6-2.7) 2.0 (0.6-3.9) Fecal calprotectin 50.8 (30.1-270.3)[273] - - 50.8 (30.1- -

aContinuous variables are reported as median (inter-quartile range), categorical variables are reported as n (%), and numbers of

missing data, if any, are listed inside brackets ([n]).

bSES-CD scores were first converted to CDEIS scores by: CDEIS = 0.1569 + 0.6744*SES-CD (see Supplementary Figure 1).

Disease activity status was defined by either original or converted CDEIS scores as remission (CDEIS < 3) or active (CDEIS ³ 3).

Table 8

Subject and Sample Characteristics of the Study Cohort 1a

Characteristics Total Baseline Week 12 Week 54 Subjectsb

n 116 102 98 75 Age (years) 30.2 (22.4-45.2) 30.9 (24.1-45.6) 30.9 (22.9-45.7) 30.4 (23.1-44.5) Female sex 69 (59.5) 61 (59.8) 58 (59.2) 43 (57.3) CD duration (years) 0.7 (0.1-6.9) 0.9 (0.1-7.3) 0.5 (0.1-6.1) 0.5 (0.0-5.6) Age at diagnosis (years)

A1: £16 6 (5.2) 5 (4.9) 3 (3.1) 3 (4.0) A2: 17-40 86 (74.1) 77 (75.5) 72 (73.5) 55 (73.3) A3: >40 24 (20.7) 20 (19.6) 23 (23.5) 17 (22.7) CD location [5] [3] [4] [1] L1: Ileal 27 (24.3) 26 (26.3) 23 (24.5) 18 (24.3) L2: Colonic 20 (18.0) 16 (16.2) 17 (18.1) 16 (21.6) L3: Ileocolonic 64 (57.7) 57 (57.6) 54 (57.4) 40 (54.1) CD behavior [5] [3] [4] [1] B1: Non-stricturing, 81 (73.0) 73 (73.7) 69 (73.4) 52 (70.3) Non-penetrating

B2: Stricturing 17 (15.3) 16 (16.2) 13 (13.8) 13 (17.6) B3: Penetrating 13 (11.7) 10 (10.1) 12 (12.8) 9 (12.2) Perianal disease modifier 31 (27.9)[5] 26 (26.3.)[3] 25 (26.6)[4] 21 (28.4)[1] History of IBD related surgery 12 (10.3) 12 (11.8) 8 (8.2) 4 (5.3) Samples

n 275 102 98 75 Endoscopic remissionc 71 (25.8) 0 (0.0) 26 (26.5) 45 (60.0) CDEIS 4.4 (0.8-9.1) 10.0 (7.4-16.0) 3.0 (0.7-5.2) 0.1 (0.0-2.6) SES-CD 6.0 (2.0-12.0) 15.0 (9.0-22.0) 4.0 (2.0-8.0) 1.0 (0.0-3.0) CDAI 166.0 (72.5-261.0) 279.5 (233.0-321.8) 112.0 (58.5-181.5)[3] 66.5 (39.8-115.2)[1]

[4]

CRP (mg/L) 2.5 (0.5-7.2) 8.2 (3.5-14.3) 0.9 (0.3-3.5) 0.8 (0.3-2.5) Fecal calprotectin (µg/g) 336.0 (100.0- 1462.5 (709.4-1800.0)[6] 122.0 (100.0-430.5)[17] 105.2 (100.0-215.8)[5]

1197.5)[28]

EHI 38.0 (25.0-53.0) 55.5 (42.0-72.8) 33.5 (23.0-41.8) 25.0 (19.0-37.5) aContinuous variables are reported as median (inter-quartile range), categorical variables are reported as n (%), and numbers of missing data, if any, are listed inside brackets ([n]).

bSubjects in the three time points were subsets of the full cohort that contributed the corresponding samples.

cEndoscopic remission was defined as a total of SES-CD of £ 2 and £ 1 in each segment.

Table 9

Subject and Sample Characteristics of Validation Cohort 2 and Sub-Cohorts with or without Fecal Calprotectina Characteristics Full Cohort Sub-Cohort Sub-Cohort P Valueb

(with Calprotectin) (without Calprotectin) n 195 81 114

Age (years) 38.5 (28.0-52.0)[17] 37.0 (28.0-47.0)[9] 39.0 (28.0-53.8)[8] 0.603 Female sex 92 (49.7)[10] 36 (48.0)[6] 56 (50.9)[4] 0.765 Race/Ethnicity <0.001 African American 5 (2.6) 1 (1.2) 4 (3.5)

Asian 3 (1.5) 2 (2.5) 1 (0.9)

White 125 (64.1) 33 (40.7) 92 (80.7)

Hispanic 8 (4.1) 3 (3.7) 5 (4.4)

Unknown 54 (27.7) 42 (51.9) 12 (10.5)

CD duration (years) 11.0 (5.0-19.0)[16] 11.0 (5.0-20.0)[8] 11.0 (5.0-18.0)[8] 0.684 Age at diagnosis (years) [12] [8] [4] 0.530 A1: £16 49 (26.8) 22 (30.1) 27 (24.5)

A2: 17-40 97 (53.0) 39 (53.4) 58 (52.7)

A3: >40 37 (20.2) 12 (16.4) 25 (22.7)

CD location [5] [3] [2] 0.566 L1: Ileal 47 (24.7) 22 (28.2) 25 (22.3)

L2: Colonic 67 (35.3) 28 (35.9) 39 (34.8)

L3: Ileocolonic 76 (40.0) 28 (35.9) 48 (42.9)

CD behavior [1] [1] 0.444 B1: Non-stricturing, 112 (57.7) 51 (63.0) 61 (54.0)

Non-penetrating

B2: Stricturing 31 (16.0) 12 (14.8) 19 (16.8)

B3: Penetrating 51 (26.3) 18 (22.2) 33 (29.2)

Perianal disease modifier 21 (10.8) 11 (13.6) 10 (8.8) 0.350 Biological medication use 139 (77.2)[15] 59 (76.6)[4] 80 (77.7)[11] 1.000 History of IBD related 90 (46.2) 33 (40.7) 57 (50.0) 0.244 surgery

Endoscopic remissionc 82 (42.1) 33 (40.7) 49 (43.0) 0.771 Endohistopathologic 23 (29.1)[116] 11 (28.9)[43] 12 (29.3)[73] 1.000 healingd

SES-CD 3.0 (0.0-6.5) 3.0 (0.0-7.0) 3.0 (0.0-6.0) 0.609 CDAI PRO 2 7.7 (2.9-15.5)[39] 6.9 (2.4-15.4)[10] 8.3 (3.7-15.4)[29] 0.457 GHAS 3.0 (1.0-6.0)[116] 3.0 (1.0-6.0)[43] 4.0 (1.0-6.0)[73] 0.886 CRP (mg/L) 2.6 (0.7-7.1) 3.2 (0.7-7.5) 2.4 (0.8-6.2) 0.476 Fecal calprotectin (µg/g) 55.0 (0.0-251.1)[114] 55.0 (0.0-251.1) - - EHI 32 (19.5-46.5) 32 (21-47) 32.0 (19.0-46.0) 0.576 aContinuous variables are reported as median (inter-quartile range), categorical variables are reported as n (%), and numbers of missing data, if any, are listed inside brackets ([n]).

bBased on Mann-Whitney test for continuous variables and Fisher’s exact test for categorical variables.

cEndoscopic remission was then defined as a total SES-CD of £ 2 and £ 1 in each segment.

dEndohistopathologic healing was defined as achieving both endoscopic remission and histologic remission (GHAS £ 2).

Table 10

Table 11

True Positives (TPs), True Negatives (TNs), Sensitivity, Specificity, Positive Likelihood Ratio (PLR) and Negative Likelihood Ratio (NLR) of endoscopic Healing Index (EHI) in Distinguishing Active Disease (AD) vs Endoscopic Remission (ER) by Disease Location in Validation Cohort 1

CD EHI MLG TPs TNs Sensitivity Specificity PLR NLR Location Threshold Probabilitya (n) (n) (%)(95% CI) (%)(95% CI) (95%) (95% CI) All 20 0.550 198 49 97.1 69.0 3.13 0.04 ER (n=71) (93.7-98.9) (56.9-79.5) (2.21-4.44) (0.02-10) AD (n=204) 30 0.746 173 65 84.8 91.5 10.04 0.17

(79.1-89.4) (82.5-96.8) (4.66-21.63) (0.12-0.23) 40 0.876 118 71 57.8 100.0 infinity 0.42

(50.7-64.7) (94.9-100.0) (0.36-0.50) 50 0.945 76 71 37.3 100.0 infinity 0.63

(30.6-44.3) (94.9-100.0) (0.56-0.70) L1 20 0.550 51 12 98.1 80.0 4.90 0.02 ER (n=15) (89.7-100.0) (51.9-95.7) (1.78-13.50) (0.00-0.17) AD (n=52) 30 0.746 48 14 92.3 93.3 13.85 0.08

(81.5-97.9) (68.1-99.8) (2.08-92.12) (0.03-0.21) 40 0.876 29 15 55.8 100.0 infinity 0.44

(41.3-69.5) (78.02-100.0) (0.33-0.60) 50 0.945 17 15 32.7 100.0 infinity 0.67

(20.3-47.1) (78.2-100.0) (0.56-0.81) L2 20 0.550 30 12 100.0 63.2 2.71 0.00 ER (n=19) (88.4-100.0) (38.4-83.7) (1.51-4.89) (0.00- ) AD (n=30) 30 0.746 23 18 76.7 94.7 14.57 0.25

(57.7-90.1) (74.0-99.9) (2.14-99.15) (0.13-0.48) 40 0.876 17 19 56.7 100.0 infinity 0.43

(37.4-74.5) (82.4-100.0) (0.29-0.65) 50 0.945 13 19 43.3 100.0 infinity 0.57

(25.5-62.6) (82.4-100.0) (0.41-0.78) L3 20 0.550 110 25 95.7 69.4 3.13 0.06 ER (n=36) (90.1-98.6) (51.9-83.7) (1.91-5.13) (0.03-00.15) AD (n=115) 30 0.746 96 32 83.5 88.9 7.51 0.19

(75.4-89.7) (73.9-96.9) (2.97-18.99) (0.12-0.29) 40 0.876 67 36 58.3 100.0 infinity 0.42

(48.7-67.4) (90.3-100.0) (0.34-0.52) 50 0.945 43 36 37.4 100.0 infinity 0.63

aThe population-averaged probability from the mixed logistic regression (MLG) model.

Discussion

[0260] In this example, a novel 13-biomarker panel serum-based assay (EHI) was developed and validated that detects mucosal inflammation in CD. The EHI was validated in 2 independent cohorts representing both early disease and biologic naive CD patients and longer duration CD patients with prior bowel surgeries, disease-related complications, and multiple biologic exposures. Across both cohorts EHI was observed to have an overall favorable

diagnostic accuracy for identifying endoscopic inflammation, and in the second validation cohort an early exploratory analysis observed it to have a reasonable diagnostic accuracy for identifying histologic inflammation. Based on these data a cut-off of 20 was observed to have a high sensitivity for ruling out endoscopic inflammation and a cut-off of 50 was observed to have a high specificity for ruling in endoscopic inflammation. The sensitivity of CRP was consistently poor across both validation cohorts indicating that CRP may be unreliable by itself for ruling out endoscopic inflammation. Most notably, the diagnostic accuracy of EHI was consistent across disease locations and disease phenotypes, and its performance was comparable to that of FC and superior to CRP alone.

[0261] Many CD patients prefer blood based testing over fecal testing, but there were no routinely available blood based tests with a diagnostic performance comparable to that of FC. A study examined the diagnostic accuracy of serum calprotectin for differentiating IBD from healthy controls, and although serum calprotectin had a favorable diagnostic accuracy for identifying IBD (AUC 0.87, 95% CI 0.78-0.97), it was still less accurate than FC (AUC 0.99, 95% CI 0.87-1.00, p=0.01). This study is therefore novel and inventive in relation to current tests available for monitoring CD patients.

[0262] When comparing EHI to FC come observations from are notable. First, the sensitivity and specificity of EHI at cut offs of 20 and 50 respectively remained consistent across both validation cohorts (92-96% and 91-100%). Although the specificity of FC at a cut-off of 250 mg/g remained stable between validation cohorts (89-100%), the sensitivity of FC at a cut-off of 50 mg/g was quite different between validation cohort 1 (an early disease biologic naive population; 100%) and validation cohort 2 (routine practice, longer duration, biologic exposed population; 75%). Second, the diagnostic accuracy of EHI was consistent across disease locations and phenotypes. Prior literature has demonstrated that the diagnostic performance of FC varies by disease location, and even in the presence of very large ulcers ileal CD patients may not have markedly elevated FC levels. Furthermore, the presence of perianal fistulas even in the absence of colonic inflammation leads to elevated FC. Third, one limitation of FC is the variability across platforms, collection techniques, and timing of sample collection, which have downstream implications on the diagnostic performance of FC. EHI was built to ensure reproducibility and consistency in performance, which was observed throughout the validation process.

[0263] EHI performance was consistent as compared to other serum markers across various endoscopic active disease prevalence in patients with established CD that ranged from 5-75%. At a threshold of 20, EHI had a high NPV (84.9-99.7%) in validation cohort 1 across disease prevalence of 5-75% and an NPV of 63-99% in validation cohort 2. In contrast NPV of CRP decreased with increasing disease prevalence and was as low as 29% at a cut-off of 5mg/l in validation cohort 2 indicating that CRP is a poor marker to rule out active disease. Performance of FC was better than CRP with a better NPV at a cut-off of 50 µg/g which was comparable to or lower than that of EHI 20.

[0264] The study in this example had several strengths, including the multi-center multi-national collaboration with varying patient populations and disease characteristics, availability of both endoscopic and histologic disease activity assessments, comparative accuracy assessments against both FC and CRP, and longitudinal comparisons for responsiveness in a prospective clinical trial.

[0265] In conclusion, a serum-based assay with a favorable diagnostic accuracy for identifying mucosal inflammation was developed and validated, which is comparable to FC. The serum-based assay was responsive to changes in endoscopic disease activity and accuracy was consistent across sub-groups. This test bridges current gaps in monitoring patients with CD.

Example 2: Difficulty Assessing Mucosal Healing in a Pediatric Patient without an EHI Score

[0266] A pediatric patient presents with Crohn’s disease (CD) symptoms. A physician performs an endoscopy and diagnoses the patient as having endoscopically active disease. The physician treats the patient with a CD therapy. Three months later, the patient has reduced symptoms. The physician is reluctant to perform an invasive test on the pediatric subject to assess mucosal healing, but is unable to perform a noninvasive test to assess the patient’s mucosal healing because no such noninvasive test is available for pediatric subjects.

Example 3: Assessing Mucosal Healing in Children with Ileocolonic Crohn’s Disease using EHI Scores

[0267] EHI scores were generated from serum samples of pediatric patients enrolled in a prospective study that included looking at pharmacokinetics of infliximab in pediatric Crohn’s disease patients. A subset of these pediatric patients had an endoscopic evaluation near the time of blood collection. Imaging studies were used to support endoscopic findings. Patients who received infliximab during the time between the endoscopy and the blood sample were excluded. Endoscopy was scored independently by two experienced pediatric gastroenterologist as either no, mild or moderate/severe inflammation in the terminal ileum (TI) and colon, respectively. Mucosal healing was defined as no inflammation in the TI or colon.

[0268] EHI scores were identified in 14 pediatric CD patients (57% male; median age 12). Test samples were taken from all patients within 90 days of an endoscopy. The median time between endoscopy and blood collection was 28 days (range 3 to 83 days). Magnetic resonance and computed tomography enterography were used to support endoscopic findings.

[0269] Patient characteristics are shown in Table 13. Five patients achieved mucosal healing with no inflammation in TI or colon whereas 9 patients had moderate/severe endoscopic disease in TI and/or colon.


[0270] Median EHI scores were significantly lower in those patients in endoscopic remission (19 [4-49]) as compared to those with moderate-severe active endoscopic disease (74 [49-97]) (P < 0.0001*) (FIG.1A).

[0271] A subset of pediatric patients had test samples taken within 30 days of endoscopy. Details for these patients are shown in Table 14, and results are included in FIG.1B.

Table 14. Patient Characteristics for Subset within 30 days of Endoscopy


[0272] In the subset of pediatric patients who had test samples taken within 30 days of endoscopy, median EHI scores were significantly lower in those patients in endoscopic remission (13 [3-19]) as compared to those with moderate-severe active endoscopic disease (82 [73-97]) (P < 0.0001*) (FIG.1B). The difference was even more striking among this subset of pediatric patients than the overall population of pediatric patients enrolled in the study.

[0273] Overall, EHI scores successfully assessed clinical remission and mucosal healing in pediatric CD patients such as those with ileocolonic disease. EHI scores were predictive within 30 or 90 days of an endoscopy. EHI scores between about 65 and 85 successfully assessed moderate or severe endoscopic disease. EHI scores between about 75 and 90 successfully assessed moderate or severe endoscopic disease. EHI scores between about 70 and 100 successfully assessed moderate or severe endoscopic disease. EHI scores between about 80 and 100 successfully assessed moderate or severe endoscopic disease. EHI scores between about 5 and 35 successfully assessed clinical remission and mucosal healing. EHI scores between about 4 and 20 successfully assessed clinical remission and mucosal healing. EHI scores between about 5 and 50 successfully assessed clinical remission and mucosal healing. Thus, EHI scores are useful for noninvasive assessment of mucosal status in children with CD.

Example 4: Difficulty Monitoring Mucosal Healing in a Pediatric Patient without an EHI Score

[0274] A pediatric patient presents with Crohn’s disease (CD) symptoms. A physician performs an endoscopy and diagnoses the patient as having endoscopically active disease. A month later, the patient has worsened symptoms. The physician is unable to perform a second endoscopy because doing so would put the subject at risk of causing mucosal damage by the endoscopy. Therefore, the physician is unable to fully monitor the pediatric subject.

Example 5: Longitudinal Monitoring of Pediatric Patients with EHI Scores

[0275] A case study was performed on a pediatric patient to perform longitudinal monitoring using EHI scores. The case study included a 16-year-old male pediatric patient with CD. At the beginning of the study (week 0), the pediatric patient had moderate to severe disease as indicated by endoscopy, and an EHI score of 82. Serum CRP levels in the patient were 5.5 mg/L at week 0.

[0276] This patient was followed for 22 weeks and treated with infliximab (IFX) during that time. Data for the patient are shown in FIG.2, Table 15, and Table 16. Serum IFX levels in the patient were 12 µg/L at week 22. Serum anti-drug antibodies (ATI) were undetectable throughout the 22-week period. Serum CRP levels in the patient were 1.8 mg/L at week 22. The EHI score for the patient remained high at > 50 from weeks 0 to 22 even though CRP levels were low. The EHI score reflected the clinical and therapeutic profile of this pediatric patient better than CRP alone. Thus, in some embodiments, an EHI score is used to monitor and assess mucosal healing in a pediatric patient, and is advantageous over existing methods of monitoring and assessing mucosal healing in pediatric patients.

Example 6: Providing a Sample from a Patient

[0277] A 2 mL serum sample is obtained from a pediatric patient by a medical professional, and placed in a test tube. The test tube is refrigerated at 4°C, and then shipped with a cold pack to a diagnostic laboratory. The diagnostic laboratory receives the test tube, and refrigerates the sample. The diagnostic laboratory measures biomarkers in the sample within 3 days of receiving the sample. The biomarkers are measured within 14 days after the medical professional obtains the sample, and the sample is refrigerated without being allowed to sit at ambient room temperature for more than 24 hours during that time.

[0278] While preferred embodiments of the present invention have been shown and described herein, it will be obvious to those skilled in the art that such embodiments are provided by way of example only. Numerous variations, changes, and substitutions will now occur to those skilled in the art without departing from the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in practicing the invention. It is intended that the following claims define the scope of the invention and that methods and structures within the scope of these claims and their equivalents be covered thereby.

[0279] The section headings used herein are for organizational purposes only and are not to be construed as limiting the subject matter described.