TYPE I INTERFERON-MEDIATED DISORDERS

Abstract

The invention provides methods of identifying, diagnosing, treating, and monitoring or prognosing progression of type I IFN-mediated disease or disorder in subjects. The present invention further relates to methods of identifying candidate therapeutic agents for treating a type I interferon-mediated disease or disorder.

Claims

1. A method of treating a type I IFN mediated disease in a subject, comprising administering to the subject a therapeutically effective amount of an anti-IFNAR antibody, wherein the patient is identified as having an elevated interferon protein signature (IFNPS) characterised by elevated protein expression of EPHB2, BLC, LAG-3 and IP-10 in the serum compared to a subject not having the type I IFN mediated disease.

2. The method of claim 1, wherein the anti-IFNAR antibody is anifrolumab and a functional derivative thereof.

3. The method of claim 2, comprising administration of 300 mg anifrolumab, optionally wherein the method comprises intravenous administration of 300 mg anifrolumab every 4 weeks.

4. The method of any preceding claim, wherein treatment supresses the IFNPS.

5. The method of any preceding claim, wherein the type I IFN mediated disease is SLE.

6. The method of claim 5, wherein the treatment results in an improvement of the subject's SLE Disease Activity Index (SLEDAI).

7. The method of claim 5 or 6, wherein the treatment results in an improvement of the subject's Cutaneous Lupus Erthematosus Disease Area and Severity Index (CLASI) activity score.

8. The method of any of claims 1 to 4, wherein the IFN mediated disease is myositis.

9. The method of any preceding claim, wherein the subject is identified as not having an elevated IFNGS signature compared to a subject not having the type IFN mediated disease.

10. The method of any preceding claim, wherein treatment decreases the elevated IFNPS signature.

11. A pharmaceutical composition for use in the treatment of a type I interferon-mediated disease in a subject, wherein the pharmaceutical composition comprises a therapeutically effective amount of an anti-IFNAR antibody and wherein the subject is identified as having an elevated IFN protein signature characterised by elevated EPHB2, BLC, LAG-3 and IP-10 protein expression.

12. The pharmaceutical composition for the use of claim 10, wherein the anti-IFNAR antibody is anifrolumab.

13. The pharmaceutical composition of the use of claim 11, wherein the pharmaceutical composition comprises 300 mg anifrolumab.

14. The pharmaceutical composition for the use of claim 13, wherein the use comprises administration of 300 mg of anifrolumab every four weeks.

15. The pharmaceutical composition for the use of claims 10 to 13, wherein treatment supresses the IFNPS.

16. The method of any of claims 10 to 14, wherein the type I IFN mediated disease is SLE.

17. The pharmaceutical composition for the use of claim 15, wherein the treatment results in an improvement of the subject's SLE Disease Activity Index (SLEDAI).

18. The pharmaceutical composition of the use of claims 16 or 17, wherein the treatment results in an improvement of the subject's Cutaneous Lupus Erthematosus Disease Area and Severity Index (CLASI) activity score.

19. The pharmaceutical composition for the use of claim 10, wherein the IFN mediated disease is myositis.

20. The pharmaceutical composition for the use of any of claims 10-19, wherein the subject is identified as not having an elevated IFNGS signature compared to a subject not having the type IFN mediated disease.

21. An in vitro method for detecting elevated IFN activity in a sample isolated from a subject, the in vitro method comprising quantifying EPHB2, BLC, LAG-3 and IP-10 protein expression in the sample and comparing the protein expression in the sample with EPHB2, BLC, LAG-3 and IP-10 protein expression in a sample from a healthy donor.

22. A method of identifying a subject suitable for treatment of a type I interferon-mediated disease or disorder with a therapeutic agent that modulates type I interferon activity, said method comprising detecting an increased level of a first protein in a sample of the subject and an increased level of a second protein in a sample of the subject, wherein the first protein is EPHB2, wherein the second protein has a gene expression inducible by type I interferon and displays a Pearson correlation coefficient greater than 0.3 versus a type I interferon gene signature, and wherein the increased level of the first protein and the increased level of the second protein is relative to: a) the level of the first protein and the level of the second protein, respectively, in a sample from a tissue or person not having the type I interferon-mediated disease or disorder, or b) the level of one or more control proteins in a sample of the subject.

23. A method of identifying a subject suitable for treatment of a type I interferon-mediated disease or disorder with a therapeutic agent that modulates type I interferon activity comprising: i) detecting an increased level of a first protein in a sample of the subject and an increased level of a second protein in a sample of the subject, wherein the first protein is EPHB2, wherein the second protein has a gene expression inducible by type I interferon and displays a Pearson correlation coefficient greater than 0.3 versus a type I interferon gene signature, and wherein the increased level of the first protein and the increased level of the second protein is relative to: a) the level of the first protein and the level of the second protein, respectively, in a sample from a tissue or person not having the type I interferon-mediated disease or disorder, or b) the level of one or more control proteins in a sample of the subject; and ii) administering the therapeutic agent.

24. An anti-type I interferon antibody or an anti-type I interferon receptor antibody that modulates type I interferon activity for use in the treatment of a type I interferon-mediated disease or disorder in a subject, wherein the subject has been identified by detecting an increased level of a first protein in a sample of the subject and an increased level of a second protein in a sample of the subject, wherein the first protein is EPHB2, wherein the second protein has a gene expression inducible by type I interferon and displays a Pearson correlation coefficient greater than 0.3 versus a type I interferon gene signature, and wherein the increased level of the first protein and the increased level of the second protein is relative to: a) the level of the first protein and the level of the second protein, respectively, in a sample from a tissue or person not having the type I interferon-mediated disease or disorder, or b) the level of one or more control proteins in a sample of the subject.

25. A method of treating a type I interferon-mediated disease or disorder in a subject, the method comprising administering an anti-type I interferon antibody or an anti-type I interferon receptor antibody that modulates type I interferon activity, wherein the subject has been identified by detecting an increased level of a first protein in a sample of the subject and an increased level of a second protein in a sample of the subject, wherein the first protein is EPHB2, wherein the second protein has a gene expression inducible by type I interferon and displays a Pearson correlation coefficient greater than 0.3 versus a type I interferon gene signature, and wherein the increased level of the first protein and the increased level of the second protein is relative to: a) the level of the first protein and the level of the second protein, respectively, in a sample from a tissue or person not having the type I interferon-mediated disease or disorder, or b) the level of one or more control proteins in a sample of the subject.

26. The method of any one of claims 22, 23, or 25, or the antibody for use according to claim 3, further comprising detecting an increased level of at least one other protein in a sample of the subject, wherein the at least one other protein has a gene expression inducible by type I interferon and displays a Pearson correlation coefficient greater than 0.3 versus a type I interferon gene signature; and wherein the increased level of the at least one other protein is relative to: a) the level of the at least one other protein in a sample from a tissue or person not having the type I interferon-mediated disease or disorder, or b) the level of one or more control proteins in a sample of the subject.

27. A method of monitoring or prognosing a type I interferon-mediated disease or disorder progression in a subject comprising: i) identifying a first protein expression level in an initial sample of the subject and at least one other protein expression level in an initial sample of the subject; and ii) identifying the first protein expression level in a further sample of the subject and the at least one other protein expression level in a further sample of the subject; wherein an increase in the expression level of the first protein and an increase in the expression level of the at least one other protein in the further sample relative to the initial sample of the subject prognoses disease progression; or wherein a decrease in the expression level of first protein and a decrease in the expression level of the at least one other protein in the further sample relative to the initial sample of the subject prognoses disease regression; wherein the first protein is EPHB2; and wherein the at least one other protein has a gene expression inducible by type I interferon and displays a Pearson correlation coefficient greater than 0.3 versus a type I interferon gene signature.

28. A method of monitoring a type I interferon-mediated disease or disorder progression in a subject receiving treatment with a therapeutic agent that modulates type I interferon activity comprising: i) identifying a first protein expression level in an initial sample of the subject and at least one other protein expression level in an initial sample of the subject; ii) identifying the first protein expression level in a further sample of the subject and the at least one other protein expression level in a further sample of the subject; iii) administering a therapeutic agent that modulates type I interferon activity to the subject, wherein the therapeutic agent is administered prior to step i) or between steps i) and ii); and iv) comparing the expression levels of the first protein and the at least one other protein in the initial sample of the subject with the expression levels of the first protein and the at least one other protein respectively in the further sample of the subject; wherein a variance in the expression levels of the first protein and the at least one other protein indicates a level of efficacy of the therapeutic agent that modulates type I interferon activity; wherein the first protein is EPHB2; and wherein the at least one other protein has a gene expression inducible by type I interferon and displays a Pearson correlation coefficient greater than 0.3 versus a type I interferon gene signature.

29. A method of identifying a candidate therapeutic agent for treating a type I interferon-mediated disease or disorder comprising: i) identifying a first protein expression level in an initial sample of the subject and at least one other protein expression level in an initial sample of the subject; ii) administering the candidate therapeutic agent to the subject; iii) identifying the first protein expression level in a further sample of the subject and the at least one other protein expression level in a further sample of the subject; and iv) comparing the expression levels of the first protein and the at least one other protein in the initial sample of the subject with the expression levels of the first protein and the at least one other protein, respectively, in the further sample of the subject; wherein a variance in the expression levels of the first protein and the at least one other protein comprising a reduction in the up-regulation of the first protein and the at least one other protein expression levels, respectively, indicates that the agent is a candidate therapeutic agent; wherein the first protein is EPHB2; and wherein the at least one other protein has a gene expression inducible by type I interferon and displays a Pearson correlation coefficient greater than 0.3 versus a type I interferon gene signature.

30. The method of any one of claims 22, 23, or 25 to 29, or the antibody for use according to claim 3 or claim 5, wherein the second protein and/or the at least one other protein are each independently selected from, ALCAM, Angiopoietin-2, AREG, AXL Receptor Tyrosine Kinase (AXL), b2-Microglobulin, Beta-2-Microglobulin (B2M), C1q, Monocyte Chemotactic Protein 4 (MCP-4), MIP-3b, MCP-1, MCP-3, Monocyte Chemotactic Protein 2 (MCP-2), sCD163, B7-H1, CLM6, CD5L, ST4S6, SCGF-alpha, SCGF-beta, CO8A1, CSF-1, M-CSF R, Cathepsin S, Fractalkine/CX3CL-1, IP-10, I-TAC, BLC, CXCL16, soluble, Monokine Induced by Gamma Interferon (MIG), DLL1, DERM, EMR2, EPHB2, bFGF, VEGF sR3, PHI, TIMD3, Intercellular Adhesion Molecule 1 (ICAM-1), IGFBP-4, IL-13 Ra1, Interleukin-18 (IL-18), IL-18 BPa, Interleukin-1 receptor antagonist (IL-1ra), TCCR, IL-3 Ra, JAG1, KYNU, LAG-3, LDH-H 1, LG3BP, ILT-4, MAPK14, MMP-14, MMP-7, NAGK, Notch-3, Glucocorticoid receptor, PARK7, PD-L2, PDGF-CC, PLPP, NADPH-P450 Oxidoreductase, SAA, a1-Antitrypsin, Sialoadhesin, Siglec-7, SLAF7, Osteopontin, BGH3, TGF-b R III, Tenascin, TNF-a, TNF sR-II, CD30, BAFF, and TS

31. The method of claim 30, or the antibody for use according to claim 30, wherein the level of at least one of (i) the first protein, and (ii) the second protein or the at least one other protein, has an area under the curve (AUC) in SLE v Healthy Donor (HD) of greater 0.5 relative to: a. the level of the first protein, or the level of the second protein or the at least one other protein, respectively, in a sample from a tissue or person not having the type I interferon-mediated disease or disorder, or b. the level of one or more control proteins in a sample of the subject.

32. The method of any one of claims 22, 23, or 25 to 31, or the antibody for use according to any one of claims 24, 26, or 30 to 31, wherein the level of at least one of (i) the first protein, and (ii) the second protein or the at least one other protein is which is at least one standard deviation from the Healthy Donor Mean relative to: a. the level of the first protein, or the level of the second protein or the at least one other protein, respectively, in a sample from a tissue or person not having the type I interferon-mediated disease or disorder, or b. the level of one or more control proteins in a sample of the subject.

33. The method of any one of claims 30 to 32, or the antibody for use according to any one of claims 30 to 32, wherein the second protein and/or the at least one other protein are each independently selected from BLC, LAG-3 and IP-10.

34. The method of any one of claims 22, 23, or 25 to 33, or the antibody for use according to any one of claims 24, 26, or 30 to 33, wherein the second protein and/or the at least one other protein forms part of a biological pathway independent from the biological pathway of the first protein.

35. The method of any one of claims 22, 23, 25 to 28, or 30 to 34, or the antibody for use according to any one of claims 24, 26, or 30 to 34, wherein the level of at least one of: the first protein, and the second protein or the at least one other protein, is increased by at least 10%.

36. The method of any one of claims 22, 23, 25 to 28, or 30 to 34, or the antibody for use according to any one of claims 24, 26, or 30 to 34, wherein the average of: the level of the first protein, and the level of the second protein and/or the level of the at least one other protein, is increased by at least 10%.

37. The method of any one of claims 22, 23, 25 or 28 to 36, wherein the therapeutic agent is an anti-type I interferon antibody or an anti-type I interferon receptor antibody.

38. The method of claim 37, wherein the anti-type I interferon receptor antibody is anifrolumab.

39. The method of claim 37 or the antibody for use according to any one of claims 24 to 5, or 9 to 15, wherein the anti-type I interferon antibody is sifalumimab.

40. The method of any one of claims 22, 23, or 25 to 39, or the antibody for use according to any one of claims 24, 26, 30 to 37, or 39, wherein the subject is in need of treatment of a type I interferon-mediated disease or disorder selected from systemic lupus erythematosus, discoid lupus, lupus nephritis, dermatomyositis, polymyositis, psoriasis, SSc, vasculitis, sarcoidosis, Sjogren's syndrome, and idiopathic inflammatory myositis.

41. The method of claim 40, or the antibody for use according to claim 40, wherein the subject is in need of treatment of systemic lupus erythematosus.

42. A method of recording the output of the methods of claims 22, 23, or 25 to 41 on a readable medium.

43. A method of treating type I IFN-mediated disease in a patient, comprising selecting the patient, treating the patient

Description

[0267] The present invention will now be described in more detail, with reference to the following Figures.

EXAMPLES

Example 1

Somalogic Measurements Using a Mitigated Protocol

[0268] The SOMAscan multiplex assay consists of 1.3k individual affinity molecules called SOMAmer® (slow off-rate modified DNA aptamer) reagents, each with very high affinity to their protein targets (Rohloff J C et al., Nucleic Acid Ligands With Protein-like Side Chains: Modified Aptamers and Their Use as Diagnostic and Therapeutic Agents. Mol Ther Nucleic Acids 2014;3:e201; Gold L et al., Aptamer-based multiplexed proteomic technology for biomarker discovery. PLoS One. 2010;5:e15004). Prior to the SOMAscan assay, the biological samples were diluted with a sample diluent containing buffers, salts, detergents and competitors. In the case of SLE samples the competitors were a mixture of SomaLogic Polyanionic Competitor, and single and double stranded herring sperm DNA. The diluted biological samples were incubated for 30 min prior to the addition into each well of a 96 well plate containing a mixture of the 1.3k SOMAmer reagents. After the addition, the sample-SOMAmer reagents mixture was incubated for the formation of affinity complexes.

[0269] Two sequential bead-based immobilization and washing steps eliminated unbound or non-specifically bound proteins and the unbound SOMAmer reagents, leaving only protein target-bound SOMAmer reagents. These remaining SOMAmer reagents were isolated, and each reagent was quantified simultaneously on a custom Agilent hybridization array. The number of each SOMAmer measured was quantitatively proportional to the protein concentration in the original sample. Somalogic measurements collected with this mitigated protocol passed QC and no longer increased with anti-dsDNA prevalence (FIG. 1).

[0270] Data Packaging:

[0271] Data standardization procedures were developed to assure data consistency. In the simplest form, normalization procedures controlled for array-to-array variation and were performed in two steps. The first, using a set of hybridization control sequences introduced into the assay eluate prior to hybridization and measured independently for each sample array, which corrected for any systematic effects on the data introduced during the readout phases of the assay. The second normalization scheme used all the SOMAmer signals on a given array to allow for comparison of samples across a plate or within similar groups. It corrected for variation that may be introduced in the course of the SOMAscan assay and natural variation in initial sample concentration that may have occurred. Normalization methods computed scale factors for each sample that was subsequently applied to the signal on the appropriate features within an array. Plate scale and calibration used the endogenous signal from replicate control samples run on each plate and were used to compute scale factors for each plate and for each sequence within a plate to control for plate variation that may have occurred over multiple assay runs.

Example 2

Somalogic Measurements Correlated with Rules Based Medicine Measurements

[0272] To identify correlates of blood protein Type I IFN activity, a set of protein measurements were identified from Rules Based Medicine (RBM) and SOMAscan platforms that correlated with Type I IFN biology in blood microarray and protein measurements. To identify protein correlates of Type I IFN-dependent gene expression 103 proteins were identified, which correlated with the Type I IFN 21 gene signature with a Spearman Correlation>0.3. To identify proteins associated with IFN-dependent protein prevalence, a blind source separation algorithm was used, Principal Components Analysis followed by a Promax rotation, to identify a score strongly correlated with the Type I IFN 21 gene signature and multiple IFN-inducible chemokine protein measurements. 155 proteins correlated with this score with a Spearman R>0.3. When the union of both lists of proteins was examined, a total of 170 protein measurements were found to have an association with Type I IFN biology.

TABLE-US-00001 TABLE 2 Proteins known to have interferon-inducible transcripts as published within the Interferome database Analyte Name Platform Gene Symbol Biological pathway SOMA-ALCAM SOMA ALCAM inflammation/tissue damage & repair RBM-Angiopoietin-2 RBM ANGPT2 vascular (ANG-2) damage/inflammation/tissue repair SOMA-Angiopoietin-2 SOMA ANGPT2 vascular damage/inflammation/tissue repair SOMA-AREG SOMA AREG vascular damage/inflammation/tissue repair RBM- AXL Receptor RBM AXL dendritic cell/ t cell activation Tyrosine Kinase (AXL) SOMA-b2-Microglobulin SOMA B2M top correlates of IFN21GS RBM-Beta-2-Microglobulin RBM B2M dendritic cell/ t cell activation (B2M) SOMA-C1q SOMA C1QA inflammation/tissue damage & repair RBM-Monocyte RBM CCL13 interferon-inducible chemokine Chemotactic Protein 4 (MCP-4) SOMA-MIP-3b SOMA CCL19 interferon-inducible chemokine SOMA-MCP-1 SOMA CCL2 interferon-inducible chemokine RBM-Monocyte RBM CCL2 interferon-inducible chemokine Chemotactic Protein 1 (MCP-1) RBM-Macrophage RBM CCL23 interferon-inducible chemokine inflammatory protein 3 beta (MIP-3 beta) SOMA-MCP-3 SOMA CCL7 interferon-inducible chemokine RBM-Monocyte RBM CCL8 top correlates of IFN21GS Chemotactic Protein 2 (MCP-2) SOMA-sCD163 SOMA CD163 inflammation/tissue damage & repair SOMA-B7-H1 SOMA CD274 top correlates of IFN21GS SOMA-CLM6 SOMA CD300C inflammation/tissue damage & repair SOMA-CD5L SOMA CD5L inflammation/tissue damage & repair RBM-CD5 Antigen-like RBM CD5L inflammation/tissue damage & repair (CD5L) SOMA-ST4S6 SOMA CHST15 inflammation/tissue damage & repair SOMA-SCGF-alpha SOMA CLEC11A dendritic cell/ t cell activation SOMA-SCGF-beta SOMA CLEC11A dendritic cell/ t cell activation SOMA-CO8A1 SOMA COL8A1 inflammation/tissue damage & repair RBM-Macrophage Colony- RBM CSF1 inflammation/tissue damage & repair Stimulating Factor 1 (M-CSF) SOMA-CSF-1 SOMA CSF1 inflammation/tissue damage & repair SOMA-M-CSF R SOMA CSF1R inflammation/tissue damage & repair SOMA-Cathepsin S SOMA CTSS inflammation/tissue damage & repair SOMA- SOMA CX3CL1 interferon-inducible chemokine Fractalkine/CX3CL-1 RBM-Interferon gamma RBM CXCL10 interferon-inducible chemokine Induced Protein 10 (IP-10) SOMA-IP-10 SOMA CXCL10 interferon-inducible chemokine SOMA-I-TAC SOMA CXCL11 interferon-inducible chemokine RBM-Interferon-inducible RBM CXCL11 interferon-inducible chemokine T-cell alpha chemoattractant (ITAC) SOMA-BLC SOMA CXCL13 B cell survival/differentiation RBM-B Lymphocyte RBM CXCL13 B cell survival/differentiation Chemoattractant (BLC) SOMA-CXCL16, soluble SOMA CXCL16 inflammation/tissue damage & repair RBM-Monokine Induced RBM CXCL9 interferon-inducible chemokine by Gamma Interferon (MIG) SOMA-DLL1 SOMA DLL1 B cell survival/differentiation SOMA-DERM SOMA DPT inflammation/tissue damage & repair SOMA-EMR2 SOMA EMR2 inflammation/tissue damage & repair SOMA-EPHB2 SOMA EPHB2 top correlate of IFN21G5 SOMA-bFGF SOMA FGF2 inflammation/tissue damage & repair SOMA-VEGF sR3 SOMA FLT4 inflammation/tissue damage & repair SOMA-PHI SOMA GPI inflammation/tissue damage & repair SOMA-TIMD3 SOMA HAVCR2 dendritic cell/ t cell activation RBM-Intercellular RBM ICAM1 dendritic cell/ t cell activation Adhesion Molecule 1 (ICAM-1) SOMA-IGFBP-4 SOMA IGFBP4 inflammation/tissue damage & repair SOMA-IL-13 Ra1 SOMA IL13RA1 dendritic cell/ t cell activation RBM-Interleukin-18 (IL-18) RBM IL18 dendritic cell/ t cell activation SOMA-IL-18 BPa SOMA IL18BP dendritic cell/ t cell activation RBM-Interleukin-1 RBM IL1RN inflammation/tissue damage & repair receptor antagonist (IL-1ra) SOMA-TCCR SOMA IL27RA dendritic cell/ t cell activation SOMA-IL-3 Ra SOMA IL3RA dendritic cell/ t cell activation SOMA-JAG1 SOMA JAG1 inflammation/tissue damage & repair SOMA-KYNU SOMA KYNU inflammation/tissue damage & repair SOMA-LAG-3 SOMA LAG3 dendritic cell/ t cell activation SOMA-LDH-H 1 SOMA LDHB dendritic cell/ t cell activation SOMA-LG3BP SOMA LGALS3BP inflammation/tissue damage & repair SOMA-ILT-4 SOMA LILRB2 inflammation/tissue damage & repair SOMA-MAPK14 SOMA MAPK14 inflammation/tissue damage & repair SOMA-MMP-14 SOMA MMP14 inflammation/tissue damage & repair SOMA-MMP-7 SOMA MMP7 inflammation/tissue damage & repair RBM-Matrix RBM MMP7 inflammation/tissue damage & repair Metalloproteinase-7 (MMP-7) SOMA-NAGK SOMA NAGK inflammation/tissue damage & repair SOMA-Notch-3 SOMA NOTCH3 inflammation/tissue damage & repair SOMA-Glucocorticoid SOMA NR3C1 dendritic cell/ t cell activation receptor SOMA-PARK7 SOMA PARK7 dendritic cell/ t cell activation SOMA-PD-L2 SOMA PDCD1LG2 dendritic cell/ t cell activation SOMA-PDGF-CC SOMA PDGFC inflammation/tissue damage & repair SOMA-PLPP SOMA PDXP inflammation/tissue damage & repair SOMA-NADPH-P450 SOMA POR inflammation/tissue damage & repair Oxidoreductase SOMA-SAA SOMA SAA1 inflammation/tissue damage & repair SOMA-a1-Antitrypsin SOMA SERPINA1 inflammation/tissue damage & repair SOMA-Sialoadhesin SOMA SIGLEC1 inflammation/tissue damage & repair SOMA-Siglec-7 SOMA SIGLEC7 inflammation/tissue damage & repair SOMA-SLAF7 SOMA SLAMF7 B cell survival/differentiation RBM-Osteopontin RBM SPP1 inflammation/tissue damage & repair SOMA-BGH3 SOMA TGFBI inflammation/tissue damage & repair SOMA-TGF-b R III SOMA TGFBR3 dendritic cell/ t cell activation SOMA-Tenascin SOMA TNC inflammation/tissue damage & repair SOMA-TNF-a SOMA TNF dendritic cell/ t cell activation RBM-Tumor necrosis RBM TNFRSF1B inflammation/tissue damage & repair factor receptor 2 (TNFR2) SOMA-TNF sR-II SOMA TNFRSF1B inflammation/tissue damage & repair SOMA-CD30 SOMA TNFRSF8 dendritic cell/ t cell activation RBM-B cell-activating RBM TNFSF13B B cell survival/differentiation factor (BAFF) SOMA-BAFF SOMA TNFSF13B B cell survival/differentiation SOMA-TS SOMA TYMS inflammation/tissue damage & repair

Example 4

Independent Confirmation of IFNPS Components by Microarray and Rules Based Medicine (RBM)

[0273] As an example of the utility of these 170 proteins, we then set out to identify a small subset that could be used to generate summary score for blood Type I IFN activity. We first filtered the 170 proteins to a list of 87 protein measurements from 75 unique proteins, 20 originating from Rules based Medicine and 67 from SOMAscan platforms, known to have interferon-inducible transcripts as published within the Interferome database. We then used LASSO regression to select a small subset of SOMAscan measurements for use as a summary score. Protein measurements generated in 2013 and 2014 from the NIH-SLE cohort were used as training data to fit the linear model. Protein measurements generated in 2015 were used to validate the model. The shrinkage parameter, λ, and the number of top pearson correlates of the IFN21GS, k, to include in the LASSO model were chosen based on the values that minimized Mean Squared Error (MSE) with the Type I IFN 21 gene signature after 10 iterations of 5-fold cross validation. A linear combination of the top 4 protein correlates of the IFN21GS optimally predicted the IFN21GS in the training set. We refit the model composed of 4 proteins using Ordinary Least Squares (OLS) regression to derive the final coefficient estimates. All protein measurements were log.sub.2 transformed, then scaled to the mean and standard deviation of the respective HD distribution in the training and test sets prior to fitting linear models.

Example 5

IFNPS Correlates with SLE Global Disease Activity (SLEDAI)

[0274] Scatterplots displaying correlation between IFNGS and SLEDAI and 4 protein type I IFN signature and SLEDAI of SLE patients are presented in FIG. 6. AUC of IFNGS and IFNPS discriminated SLE patients with and without specific SLE symptoms (FIG. 6B). Scatterplot displaying relationship between the IFNGS and the 4 protein type I IFN signature in non-lymphopenic and lymphopenic SLE patients are presented in FIG. 6C.

Example 6

IFNPS Correlates with SLEDAI in Both Lymphopenic and Non-Lymphopenic SLE Patients

[0275] Correlations between IFNGS and SLEDAI and 4 protein type I IFN signature and SLEDAI in non-lymphopenic and lymphopenic SLE patients were obtained, as shown in FIG. 6C.

[0276] All statistical analysis was conducted in R 3.1.1. Pairwise correlations were calculated using the non-parametric Spearman's correlation unless otherwise stated. Pairwise comparisons were calculated using the non-parametric Mann-Whitney U Test. The R glmnet package was used to fit the LASSO model.

[0277] To conclude, in a cohort of 82 SLE patients and 48 healthy donors, the protein signature was found elevated above healthy donors for most of IFNGS test-high patients (49/55, 89%) and also for a subgroup of IFNGS test-low patients (7/27, 26%) (FIG. 5). The protein signature correlated with global disease activity (median SLEDAI score of 4 for the cohort) in both lymphopenic and non-lymphopenic patients (FIG. 6). Significant associations with skin involvement, low complement, anti DNA auto-antibodies, and thrombocytopenia were also observed. In sum, our results suggest blood derived protein measurements can complement validated gene signatures to monitor type I IFN activity.

Example 7

IFNPS Identifies a New Subset of Patients with Evidence of Type I IFN Activity

[0278] In patients with SLE, the IFNGS displays a bimodal distribution and can be used to separate patients into two subgroups: those with high IFNGS (IFNGS-high) and those with low levels (IFNGS-low). The prevalence of the IFNPS in HD with both IFNGS-high and IFNGS-low patients with SLE was compared. It was found that IFNPS was strongly elevated in all patients with SLE. Of patients with SLE, 68% displayed an IFNPS>2 standard deviations from the HD mean (AUC=0.93, p<0.001). Surprisingly, the IFNPS was also significantly elevated in IFNGS-low patients with SLE (AUC=0.86, p<0.001), and a subset of 26% of IFNGS-low patients with SLE who similarly displayed an IFNPS>2 standard deviations from the HD mean was identified (FIG. 3). IFNPS can therefore be used to identify a unique subset of patients with potentially high type I IFN activity and low levels of IFN-inducible genes in the blood.

Example 8

IFNPS and IFNGS Correlate with Global Disease Activity in SLE

[0279] The association between the IFNPS and composite disease activity in the training set was characterised to determine if the IFNPS correlates with overall disease activity. The Spearman's correlation of the IFNPS and IFNGS with the SLE Disease Activity Index (SLEDAI) was calculated, an assessment of SLE disease activity across multiple organ systems. It was surprisingly found that IFNPS shared a Spearman's correlation of 0.45 (p<0.001) with SLEDAI, while the IFNGS displayed a Spearman's correlation of 0.19 (p=0.029) with SLEDAI, suggesting the IFNPS could serve as a useful biomarker of composite disease in SLE (FIG. 6A).

[0280] The prevalence of the IFNPS and IFNGS in patients positive and negative for each SLEDAI component was examined. Both the IFNGS and IFNPS were significantly elevated in patients who presented with rash, low complement and anti-dsDNA autoantibodies. The IFNPS was also significantly elevated in thrombocytopenic patients with SLE, and the IFNGS displayed a similar trend. The IFNPS also displayed numerical elevation in leukopenic patients with SLE (FIG. 6B). The IFNPS significantly correlates with SLEDAI in both lymphopenic and non-lymphopenic patients with SLE (p<0.05), providing further evidence that the signature reflects tissue biology that is insensitive to blood compositional changes (FIG. 6c).

[0281] To determine whether these findings could be reproduced in an independent cohort of patients with moderate to severe disease, the association between the IFNPS and SLEDAI composite score in both lymphopenic and non-lymphopenic patients in the MUSE cohort was assessed. There was significant association between IFNPS and hypocomplementemia, increased anti-dsDNA, and leukopenia in this cohort ( ). In two thrombocytopenic patients The IFNPS displayed a positive correlation with Cutaneous Lupus Erythematosus Disease Area and Severity Index (CLASI) activity score (Spearman's r=0.21, p<0.001), an alternative measure of cutaneous disease activity, confirming the association between IFNPS and SLE cutaneous involvement.

[0282] In summary, the IFNPS reflects inflammation across multiple organ systems in patients with SLE, making the IFNPS a surprisingly useful biomarker of composite disease activity.

Example 9

IFNPS is Associated with the Type I IFN Pathway

[0283] Type I and type II IFNs have distinct roles in amplifying immune response but induce largely overlapping transcriptional changes in cells. Moreover, type II IFNs are directly inducible by type I IFNs. For these reasons, distinguishing between both types of responses while monitoring human disease is challenging. To verify that the IFNPS we identified is reflecting type I IFN—and not type II IFN-associated biology, the correlation between IFNPS and transcription of several components of IFN-γ-inducible gene signatures, IRF1, CXCL9, and SLAMF8,39,41 was measured, and therefore was found to be no correlation between the IFNPS and these genes in samples from patients with either SLE or myositis. In contrast, the IFNPS correlated with all four components of a type I IFN-inducible gene signature, IFI44L, IFI27, RSAD2, and IFI44, demonstrating that the IFNPS is directly induced by type I IFNs and not type II IFNs.

[0284] To further evaluate whether the IFNPS is specifically induced by type I IFNs, we investigated whether the IFNPS is suppressed by neutralisation of IFNAR, the receptor necessary for type I IFN signalling. The IFNPS of patients with SLE before and after treatment with anifrolumab, a monoclonal antibody that neutralises IFNAR, was monitored. We found that the IFNPS was significantly decreased at Days 169 and 365 compared with Day 1 (p<0.001) in the anifrolumab 300-mg treatment group. In contrast, the IFNPS displayed no significant changes from baseline in the placebo group (p>0.05; FIG. 7a). Changes in the IFNPS from Day 1 to Days 169 and 365 were also significant when compared between the anifrolumab 300-mg group and placebo group (FIG. 7b). Therefore, the IFNPS was specifically suppressed following IFNAR neutralisation with anifrolumab, demonstrating that the IFNPS reflects biology induced by type I IFN.

[0285] FIG. 1: Circulating proteins provide largely distinct data from that found in whole blood gene expression. Density plots displaying spearman correlation of paired RBM and HGU133 Plus 2.0 measurements in 50 HD and 143 SLE samples. Analysis limited to RBM analytes where 75% of measurements were above LLOQ in the specific sample group. Somalogic measurements collected with new mitigated protocol pass QC and no longer increase with anti-dsDNA prevalence. Boxplots displaying global signal distribution of 1129 protein measurements generated using the standard Somalogic protocol (A) and mitigation protocol (B) from serum samples isolated from 143 SLE samples and 50 HD. The min, first quartile, median, third quartile, and max RFU per sample are indicated on each boxplot. Anti-dsDNA prevalence for each sample is plotted in green C. Sample specific median scaling factors used for plate median normalisation in SLE and HD. Samples with a sample scaling factor less than 0.4 signifying a median RFU 2.5 times greater than plate median RFU failed quality control.

[0286] Mitigated protocol improves correlation with Rules Based Medicine measurements. Density plots displaying spearman correlation of paired RBM and Somalogic measurements in the 50 HD, anti-dsDNA− SLE samples, and anti-dsDNA+ SLE samples generated from both the standard and mitigated protocol. Only RBM analytes where 75% of measurements were above LLOQ in the specific sample group were used in correlation analysis.

[0287] Majority of analytes display high reproducibility. A. Reproducibility of RFU of samples run within same plate on same day (A) and on different plates on different days (B) under mitigation protocol. Boxplots represent the 10.sup.th and 90.sup.th percentile, interquartile range, and median distribution of CVs among the three replicate experiments of the HD, anti-dsDNA− SLE, and anti-dsDNA+ SLE sample.

[0288] FIG. 2: Identification of an Interferon Protein Signature (IFNPS). A. Venn-diagram displaying selection of protein measurements used for feature selection in LASSO regression. 34 Somalogic protein measurements displayed a Pearson correlation>0.3 versus the IFNGS and were known to have gene expression inducible by type I IFN through in vitro or in vivo human experiments. B. Average Pearson correlation of type I IFN protein scores predicted through 10 iterations of 5 fold cross validation with the IFNGS varying the number of features input into the LASSO regression model. Optimal value of λ was also chosen through 10 iterations of 5 fold cross validation. Feature selection was restricted to proteins with positive independent associations to the IFNGS. Proteins were scaled to the HD mean and standard deviation prior to fitting the LASSO regression model. C. Regression coefficients from 4 protein signature refit to the IFNα/β 21-gene signature with ordinary least squares regression D. Scatterplot displaying concordance between 4 protein type I IFN signature and the IFNGS. R value calculated using Pearson correlation.

[0289] Independent confirmation of IFNPS components by microarray and Rules Based Medicine (RBM). Validation of components of Somalogic measurements of 4 protein type I IFN signature in independent platforms. For each component of the signature, pairwise Spearman correlation between the Somalogic measurements and protein measurements through RBM or paired gene expression measured by microarray are reported. All correlations were significant (p<0.001) except the correlation between Somalogic BLC protein measurements and BLC gene expression measurements reported by the HGU133 Plus 2.0 microarray.

[0290] FIG. 3: IFNPS elevated above healthy donors for most IFNGS test-high patients (89%) and also for a subgroup of IFNGS test-low patients (26%). A Density plots displaying prevalence of 21 gene IFNα/β signature in SLE and HD. B. 4 protein type I IFN signature in HD and SLE patients. C. Prevalence of IFNα/β gene signature in HD and SLE patients with low and high prevalence of IFNα/β gene signature. D. Prevalence of type I IFN protein signature in HD and SLE patients with low and high prevalence of IFNα/β gene signature. Statistical comparisons between each group of SLE patients and HD were reported with the Area Under the Curve (AUC) and p-value reported from the Mann-Whitney U Test.

[0291] FIG. 6: IFNPS correlates with SLE global disease activity (SLEDAI). Scatterplots displaying correlation between IFNGS and SLEDAI (A) and 4 protein type I IFN signature and SLEDAI in SLE patients. B. AUC of IFNGS and IFNPS in discriminating SLE patients with and without specific SLE symptoms. Threshold for Leukopenia<3000 WBC/μl. P-values reported using Mann-Whitney U test (*** p<0.001, ** p<0.01, * p<0.05, p<0.10).

[0292] FIG. 6. cont: IFNPS correlates with SLEDAI in both lymphopenic and non-lymphopenic SLE patients. C. Scatterplot displaying relationship between the IFNGS and the 4 protein type I IFN signature in non-lymphopenic and B. lymphopenic SLE patients. Threshold for Lymphopenia<1000 Lymphocytes/μl. Regression line between both signatures fit using ordinary least squares regression. Correlation coefficient and p-value reported using Spearman's correlation.