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Abstract Number: 2875

Molecular Features Define Unique Sjögren’s Syndrome Patient Subsets

Judith A. James1, Joel M. Guthridge2, Hua Chen3, Rufei Lu3, Rebecka L. Bourn3, Alan N. Baer4, Ghaith Noaiseh5, Anne Parke6, Andreea Coca7, Tammy Utset8, Mark C. Genovese9, Teresa Aberle3, Daniel J. Wallace10, Karen Boyle11, Lynette Keyes-Elstein12, Nathalie Franchimont13, Eugene St. Clair14, Virginia Pascual15, Paul J. Utz16 and Kathy L. Sivils2, 1Arthritis & Clinical Immunology Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, 2Arthritis and Clinical Immunology Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, 3Arthritis and Clinical Immunology, Oklahoma Medical Research Foundation, Oklahoma City, OK, 4Medicine (Rheumatology), Johns Hopkins University School of Medicine, Baltimore, MD, 5University of Pittsburgh Medical Center, Pittsburgh, PA, 6University of Connecticut, Farmington, CT, 7University of Rochester Medical Center, Rochester, NY, 8University of Chicago, Chicago, IL, 9Stanford University Medical Center, Palo Alto, CA, 10UCLA, Beverly Hills, CA, 11Rho Federal Systems, Inc, Chapel Hill, NC, 12Rho Federal Systems, Inc., Chapel Hill, NC, 13Biogen, Cambridge, MA, 14Department of Medicine, Duke University Medical Center, Durham, NC, 15Baylor Institute for Immunology Research, Baylor Research Institute, Dallas, TX, 16Medicine, Stanford University School of Medicine, Stanford, CA

Meeting: 2017 ACR/ARHP Annual Meeting

Date of first publication: September 18, 2017

Keywords: Biomarkers, inflammation and interferons

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Session Information

Date: Tuesday, November 7, 2017

Session Title: Sjögren's Syndrome II: Pathogenesis, Autoantibodies and T-Cells

Session Type: ACR Concurrent Abstract Session

Session Time: 4:30PM-6:00PM

Background/Purpose: Immunologic heterogeneity in primary Sjogren’s syndrome (pSS) poses a challenge when selecting a therapeutic for a given patients or when assembling patient cohorts for research or clinical trials. Heterogeneity in the IFN pathways within pSS is established, but little is known about potential variations in other immune pathways that may influence the disease course or response to treatment. This study characterized and clustered pSS patients by molecular phenotypes.

Methods: All pSS patients (n=52) met AECG classification criteria, had at least one systemic manifestation and had stimulated salivary flow of >0.1 mL/min. Patients were assessed for proteomic and genomic markers to enable systems level molecular phenotyping of these patients. Proteomic analysis included 30 serum cytokines, chemokines, soluble receptors which passed stringent quality control measures, and 13 anti-nuclear autoantibodies (anti-dsDNA, chromatin, ribosomal P, Sm, Sm/RNP, RNP, centromere B, Scl-70, and Jo-1) by multiplex, bead-based assay and ELISAs. Correlated gene expression signatures were derived from gene expression microarray data based on the most informative molecular variables by random forest methods.

Results: Expression modules identified three distinct clusters of pSS patients. Cluster 1 showed no significantly elevated gene expression signatures in interferon or inflammation and only modest elevations in platelet or erythrocyte expression profiles. Cluster 2 showed the strongest interferon and inflammation signatures. Patients in Cluster 3 had a moderate interferon signature, but with a weak inflammation signature. Anti-Ro and anti-La responses were present in patients in all three clusters. Cluster 2 showed the highest levels of IP-10, MIG, LIGHT, and BLyS, corresponding to the strong interferon and inflammation signatures. Cluster 3, characterized by a weak inflammatory signature and mixed interferon patterns, showed increased IP-10 compared to Cluster 1, and non-significant increases in IL-2RA, IL-1α, and sEselectin compared to Clusters 1 and 2 (Figure).  

Conclusion: Molecular profiles encompassing interferon, inflammation, and other molecular signatures can be used to separate patients with pSS into distinct groups. Profiles correlating with treatment effects may be useful for clinical trial design or treatment selection.


Disclosure: J. A. James, None; J. M. Guthridge, None; H. Chen, None; R. Lu, None; R. L. Bourn, None; A. N. Baer, Novartis, Boston Pharmaceuticals, and Bristol-Myers, 5; G. Noaiseh, None; A. Parke, None; A. Coca, None; T. Utset, None; M. C. Genovese, None; T. Aberle, None; D. J. Wallace, None; K. Boyle, None; L. Keyes-Elstein, None; N. Franchimont, None; E. St. Clair, Bristol-Myers Squibb, 2,Bristol-Myers Squibb, 5,AbbVie, 5,UpToDate, 7; V. Pascual, None; P. J. Utz, None; K. L. Sivils, None.

To cite this abstract in AMA style:

James JA, Guthridge JM, Chen H, Lu R, Bourn RL, Baer AN, Noaiseh G, Parke A, Coca A, Utset T, Genovese MC, Aberle T, Wallace DJ, Boyle K, Keyes-Elstein L, Franchimont N, St. Clair E, Pascual V, Utz PJ, Sivils KL. Molecular Features Define Unique Sjögren’s Syndrome Patient Subsets [abstract]. Arthritis Rheumatol. 2017; 69 (suppl 10). https://acrabstracts.org/abstract/molecular-features-define-unique-sjogrens-syndrome-patient-subsets/. Accessed April 16, 2021.
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