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1. (WO2019064294) SLE DISEASE MANAGEMENT
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CLAIMS

1. A method for detecting resolution of systemic lupus erythematosus (SLE) in a subj ect having been diagnosed as having SLE, the method comprising the steps of:

(i) providing a first sample obtained from the subj ect at a first time point and a second sample obtained from the same subject at a second, subsequent time point, wherein said subject has been diagnosed as having SLE at least three years earlier of the second time point and is asymptomatic at said second time point;

(ii) exposing antibodies in each of the two samples to at least four antigens selected from the group consisting of: ssDNA, Sm, DNAse I, Histone III-S, Ro52, Ul snRNP, Collagen III, Apo-SAA, H2a and 01igo21 to detect the respective reactivity patterns of said two samples to the at least four antigens;

(iii) calculating scores based on the reactivity patterns of said two samples by a supervised classification algorithm, in which the lower the score the greater is the probability that said subject is not afflicted with SLE;

(iv) comparing said scores obtained for said two samples, and

(v) determining that said subject has SLE resolution if there is a significant reduction of the score obtained for said second sample compared to the score obtained for said first sample.

2. The method of claim 1, wherein the first time point precedes the second time point by at least ten years.

3. The method of claim 1, wherein said subject has been diagnosed as having SLE at least ten years earlier of said second time point.

4. The method of claim 1, wherein the reactivity of antibodies comprises IgG reactivities, IgM reactivities, or a combination thereof, and wherein the supervised classification algorithm is selected from the group consisting of linear discriminant analysis (LDA), support vector machines (SVMs), logistic regression (LR), and quadratic discriminant analysis (QDA).

5. The method of claim 1, wherein the reactivity pattern comprises reactivities of IgG antibodies to ssDNA, Ul snRNP and Sm, and reactivities of IgM antibodies to Histone III-S, Ul snRNP and 01igo21, and the supervised classification algorithm is LDA, or

wherein the reactivity pattern comprises reactivities of IgG antibodies to ssDNA, Sm, DNAse I, Ro52 and Ul snRNP, and reactivities of IgM antibodies to Histone III-S, and the supervised classification algorithm is SVMs, or

wherein the reactivity pattern comprises reactivities of IgG antibodies to ssDNA, Ul snRNP, Ro52, Collagen III and Apo-SAA, and reactivities of IgM antibodies to Histone III-S, and the supervised classification algorithm is LR, or

wherein the reactivity pattern comprises reactivities of IgG antibodies to ssDNA, Ul snRNP, Sm, Apo-SAA and Ro52, and reactivities of IgM antibodies to H2a, and the supervised classification algorithm is QDA.

6. The method of claim 1, wherein the sample is selected from the group consisting of a serum sample, a plasma sample and a blood sample, and wherein the antigens are used in the form of an antigen probe set, an antigen array, or an antigen chip.

7. The method of claim 1, wherein said subject is undergoing SLE treatment selected from the group consisting of: nonsteroidal anti-inflammatory drugs (NSAIDs), corticosteroids, immunosuppressants, hydroxychloroquine, cyclophosphamide, immunomodulators, and TNF-a inhibitors.

8. The method of claim 1, wherein said scores are calculated in the range of 0 to 1 in which the lower the score the greater is the probability that said subject is not afflicted with SLE, and the significant reduction of said score obtained for said second sample compared to said score obtained for said first sample is of at least 0.1.

9. The method of claim 1, comprising the steps of:

(i) providing a first sample obtained from the subj ect at a first time point and a second sample obtained from the same subject at a second, subsequent time point, wherein the first time point precedes the second time point by at least ten years, and said subject is asymptomatic at said second time point;

(ii) exposing antibodies in each of the two samples to a plurality of antigens selected from the group consisting of: ssDNA, Sm, DNAse I, Histone III-S, Ro52, Ul snRNP, Collagen III, Apo-SAA, H2a and 01igo21 to detect the respective reactivity patterns of said two samples to the plurality of antigens, and calculating scores, based on the reactivity patterns of said two samples, in which the lower the score the greater is the probability that said subject is not

afflicted with SLE, using a supervised classification algorithm, wherein:

a. the reactivity pattern comprises reactivities of IgG antibodies to ssDNA, Ul snRNP, Ro52, Collagen III and Apo-SAA, and reactivities of IgM antibodies to Histone III-S, and the supervised classification algorithm is logistic regression (LR), or

b. the reactivity pattern comprises reactivities of IgG antibodies to ssDNA, Ul snRNP, Sm, Apo-SAA and Ro52, and reactivities of IgM antibodies to H2a, and the supervised classification algorithm is quadratic discriminant analysis (QDA), or

c. the reactivity pattern comprises reactivities of IgG antibodies to ssDNA, Ul snRNP and Sm, and reactivities of IgM antibodies to Histone III-S, Ul snRNP and 01igo21, and the supervised classification algorithm is linear discriminant analysis (LDA); or

d. the reactivity pattern comprises reactivities of IgG antibodies to ssDNA, Sm, DNAse I, Ro52 and Ul snRNP, and reactivities of IgM antibodies to Histone III-S, and the supervised classification algorithm is support vector machines (SVMs);

) comparing said scores obtained for said two samples, and determining that said subject has SLE resolution if there is a reduction of at least 0.1 in the score obtained for said second sample compared to the score obtained for said first sample.

The method of claim 9, wherein:

a. the reactivity pattern consists of reactivities of IgG antibodies to ssDNA, Ul snRNP, Ro52, Collagen III and Apo-SAA, and reactivities of IgM antibodies to Histone III-S, and the supervised classification algorithm is LR, or

b. the reactivity pattern consists of reactivities of IgG antibodies to ssDNA, Ul snRNP, Sm, Apo-SAA and Ro52, and reactivities of IgM antibodies to H2a, and the supervised classification algorithm is QDA, or

c. the reactivity pattern consists of reactivities of IgG antibodies to ssDNA, Ul snRNP and Sm, and reactivities of IgM antibodies to Histone III-S, Ul snRNP and 01igo21, and the supervised classification algorithm is LDA; or

d. the reactivity pattern consists of reactivities of IgG antibodies to ssDNA, Sm, DNAse I, Ro52 and Ul snRNP, and reactivities of IgM antibodies to Histone III-S, and the supervised classification algorithm is SVMs.

11. The method of claim 9, wherein said scores are calculated in the range of 0 to 1 in which the lower the score the greater is the probability that said subject is not afflicted with SLE, and wherein said classification algorithm is selected from the group consisting of LR, QDA and LDA.

12. The method of any one of claims 1-11, further comprising reducing the dose and/or frequency of treatment or ceasing administration of treatment to said subject determined to have SLE resolution.

13. A method for adjusting treatment in a subject having been diagnosed as having systemic lupus erythematosus (SLE) at least three years earlier, the method comprising the steps of:

(i) providing a first sample obtained from the subj ect at a first time point and a second sample obtained from the same subject at a second, subsequent time point;

(ii) exposing antibodies in each of the two samples to at least four antigens selected from the group consisting of: ssDNA, Sm, DNAse I, Histone III-S, Ro52, Ul snRNP, Collagen III, Apo-SAA, H2a and 01igo21 to detect the respective reactivity patterns of said two samples to the at least four antigens;

(iii) calculating scores based on the reactivity patterns of said two samples by a supervised classification algorithm, wherein the lower the score the greater is the probability that said subject is not afflicted with SLE;

(iv) comparing said scores obtained for said two samples, and

(v) determining that said subject is amenable for treatment adjustment if there is a significant reduction of the score obtained for said second sample compared to the score obtained for said first sample.

14. The method of claim 13, wherein the treatment adjustment comprises reducing the dose and/or frequency of said treatment or ceasing administration of said treatment to said subject.

15. The method of claim 13 or 14, further comprising adjusting treatment in said subject determined to be amenable for treatment adjustment.

16. The method of claim 13, wherein the first time point precedes the second time point by at least ten years and/or wherein said subject has been diagnosed as having SLE at least ten years earlier.

17. The method of claim 13, wherein said subject is asymptomatic at the second time point.

18. The method of claim 13, wherein the supervised classification algorithm is selected from the group consisting of support vector machines (SVMs), logistic regression (LR), quadratic discriminant analysis (QDA), and linear discriminant analysis (LDA), and the reactivity of antibodies comprises IgG reactivities, IgM reactivities, or a combination thereof.

19. The method of claim 16, wherein the reactivity pattern comprises reactivities of IgG antibodies to ssDNA, Sm, DNAse I, Ro52 and Ul snRNP, and reactivities of IgM antibodies to Histone III-S, and the supervised classification algorithm is SVMs.

20. The method of claim 13, wherein the reactivity pattern comprises reactivities of IgG antibodies to ssDNA, Ul snRNP, Ro52, Collagen III and Apo-SAA, and reactivities of IgM antibodies to Histone III-S, and the supervised classification algorithm is LR, or

wherein the reactivity pattern comprises reactivities of IgG antibodies to ssDNA, Ul snRNP, Sm, Apo-SAA and Ro52, and reactivities of IgM antibodies to H2a, and the supervised classification algorithm is QDA, or

wherein the reactivity pattern comprises reactivities of IgG antibodies to ssDNA, Ul snRNP and Sm, and reactivities of IgM antibodies to Histone III-S, Ul snRNP and 01igo21, and the supervised classification algorithm is LDA.

21. The method of claim 13, wherein the sample is selected from the group consisting of a serum sample, a plasma sample and a blood sample, and wherein the antigens are used in the form of an antigen probe set, an antigen array, or an antigen chip.

22. The method of any one of claims 13-15, wherein said treatment is selected from the group consisting of: nonsteroidal anti-inflammatory drugs (NSAIDs), corticosteroids, immunosuppressants, hydroxychloroquine, cyclophosphamide, immunomodulators, and

T F-α inhibitors.

23. The method of claim 22, wherein said treatment is selected from the group consisting of: NSAIDs, corticosteroids, myfortic, Methotrexate, Imuran, Abatacept, Hizentra, Gammagard, Octagam, Privigen, Arava, Plaquenil, Cyclophosphamide, Benlysta, Rituximab and Orenica.

24. The method of claim 13, wherein said scores are calculated in the range of 0 to 1 in which the lower the score the greater is the probability that said subject is not afflicted with SLE, and the significant reduction of said score obtained for said second sample compared to said score obtained for said first sample is of at least 0.1.

25. The method of claim 13, comprising the steps of:

(i) providing a first sample obtained from the subject at a first time point and a second sample obtained from the same subject at a second, subsequent time point, wherein the first time point precedes the second time point by at least ten years;

(ii) exposing antibodies in each of the two samples to a plurality of antigens selected from the group consisting of: ssDNA, Sm, DNAse I, Histone III-S, Ro52, Ul snR P,

Collagen III, Apo-SAA, H2a and 01igo21 to detect the respective reactivity patterns of said two samples to the plurality of antigens, and calculating scores based on the reactivity patterns of said two samples, in which the lower the score the greater is the probability that said subject is not afflicted with SLE, using a supervised classification algorithm, wherein:

a. the reactivity pattern comprises reactivities of IgG antibodies to ssDNA, Ul snRNP, Ro52, Collagen III and Apo-SAA, and reactivities of IgM antibodies to Histone III-S, and the supervised classification algorithm is logistic regression (LR), or

b. the reactivity pattern comprises reactivities of IgG antibodies to ssDNA, Ul snRNP, Sm, Apo-SAA and Ro52, and reactivities of IgM antibodies to H2a, and the supervised classification algorithm is quadratic discriminant analysis (QDA), or

c. the reactivity pattern comprises reactivities of IgG antibodies to ssDNA, Ul snRNP and Sm, and reactivities of IgM antibodies to Histone III-S, Ul snRNP and 01igo21, and the supervised classification algorithm is

linear discriminant analysis (LDA); or

d. the reactivity pattern comprises reactivities of IgG antibodies to ssDNA, Sm, DNAse I, Ro52 and Ul snRNP, and reactivities of IgM antibodies to Histone III-S, and the supervised classification algorithm is support vector machines (SVMs);

(iii) comparing said scores obtained for said two samples, and

(iv) determining that said subject is amenable for treatment adjustment if there is a reduction of at least 0.1 in the score obtained for said second sample compared to the score obtained for said first sample.

26. The method of claim 13, comprising the steps of:

(i) providing a first sample obtained from the subject at a first time point and a second sample obtained from the same subject at a second, subsequent time point, wherein the first time point precedes the second time point by at least ten years;

(ii) exposing antibodies in each of the two samples to a plurality of antigens selected from the group consisting of: ssDNA, Sm, DNAse I, Histone III-S, Ro52, Ul snRNP, Collagen III, Apo-SAA, H2a and 01igo21 to detect the respective reactivity patterns of said two samples to the plurality of antigens, and calculating scores based on the reactivity patterns of said two samples by a supervised classification algorithm, wherein:

a. the reactivity pattern comprises reactivities of IgG antibodies to ssDNA, Ul snRNP, Ro52, Collagen III and Apo-SAA, and reactivities of IgM antibodies to Histone III-S, and the supervised classification algorithm is logistic regression (LR), or

b. the reactivity pattern comprises reactivities of IgG antibodies to ssDNA, Ul snRNP, Sm, Apo-SAA and Ro52, and reactivities of IgM antibodies to H2a, and the supervised classification algorithm is quadratic discriminant analysis (QDA), or

c. the reactivity pattern comprises reactivities of IgG antibodies to ssDNA, Ul snRNP and Sm, and reactivities of IgM antibodies to Histone III-S, Ul

snRNP and 01igo21, and the supervised classification algorithm is linear discriminant analysis (LDA);

(iii) comparing said scores obtained for said two samples, and further comparing the score obtained for said second sample to a pre-determined threshold score, wherein said scores are calculated in the range of 0 to 1 and the predetermined threshold score is 0.18; and

(iv) determining that said subject is amenable for treatment adjustment if there is a significant reduction of the score obtained for said second sample compared to the score obtained for said first sample, and if said score obtained for said second sample is within two standard deviations (SD) of said pre-determined threshold score.

27. The method of claim 25, wherein:

a. the reactivity pattern consists of reactivities of IgG antibodies to ssDNA, Ul snRNP, Ro52, Collagen III and Apo-SAA, and reactivities of IgM antibodies to Histone III- S, and the supervised classification algorithm is LR, or

b. the reactivity pattern consists of reactivities of IgG antibodies to ssDNA, Ul snRNP, Sm, Apo-SAA and Ro52, and reactivities of IgM antibodies to H2a, and the supervised classification algorithm is QDA, or

c. the reactivity pattern consists of reactivities of IgG antibodies to ssDNA, Ul snRNP and Sm, and reactivities of IgM antibodies to Histone III-S, Ul snRNP and 01igo21, and the supervised classification algorithm is LDA; or

d. the reactivity pattern consists of reactivities of IgG antibodies to ssDNA, Sm, DNAse I, Ro52 and Ul snRNP, and reactivities of IgM antibodies to Histone III-S, and the supervised classification algorithm is SVMs.

28. The method of any one of claims 25-27, wherein said treatment is selected from the group consisting of: NSAIDs, corticosteroids, immunosuppressants, hydroxychloroquine, cyclophosphamide, immunomodulators, and TNF-a inhibitors and said method comprises reducing the dose and/or frequency of said treatment or ceasing administration of said treatment to said subject.