Unique Sjögren’s syndrome patient subsets defined by molecular features

• Published in: Rheumatology (Oxford, England) England), 2020-04, Vol.59 (4), p.860-868
• Main Authors: James, Judith A, Guthridge, Joel M, Chen, Hua, Lu, Rufei, Bourn, Rebecka L, Bean, Krista, Munroe, Melissa E, Smith, Miles, Chakravarty, Eliza, Baer, Alan N, Noaiseh, Ghaith, Parke, Ann, Boyle, Karen, Keyes-Elstein, Lynette, Coca, Andreea, Utset, Tammy, Genovese, Mark C, Pascual, Virginia, Utz, Paul J, Holers, V. Michael, Deane, Kevin D, Sivils, Kathy L, Aberle, Teresa, Wallace, Daniel J, McNamara, James, Franchimont, Nathalie, St. Clair, E. William
• Format: Article
• Language: English
• Subjects: Adult; Antibodies, Antinuclear - immunology; Autoantibodies - immunology; B-Cell Activating Factor - genetics; B-Cell Activating Factor - immunology; B-Cell Activating Factor - metabolism; Chemokine CXCL10 - genetics; Chemokine CXCL10 - immunology; Chemokine CXCL10 - metabolism; Chemokine CXCL13 - genetics; Chemokine CXCL13 - immunology; Chemokine CXCL13 - metabolism; Chemokine CXCL9 - genetics; Chemokine CXCL9 - immunology; Chemokine CXCL9 - metabolism; Clinical Science; Cytokines - genetics; Cytokines - immunology; Cytokines - metabolism; Enzyme-Linked Immunosorbent Assay; Female; Gene Expression; Gene Regulatory Networks; Humans; Inflammation - genetics; Inflammation - immunology; Inflammation - metabolism; Interferons - genetics; Interferons - immunology; Interferons - metabolism; Interleukin-1alpha - genetics; Interleukin-1alpha - immunology; Interleukin-1alpha - metabolism; Interleukins - genetics; Interleukins - immunology; Interleukins - metabolism; Male; Middle Aged; Models, Statistical; Phenotype; Sjogren's Syndrome - classification; Sjogren's Syndrome - genetics; Sjogren's Syndrome - immunology; Sjogren's Syndrome - metabolism; Tumor Necrosis Factor Ligand Superfamily Member 14 - genetics; Tumor Necrosis Factor Ligand Superfamily Member 14 - immunology; Tumor Necrosis Factor Ligand Superfamily Member 14 - metabolism
• ISSN: 1462-0324; 1462-0332
• DOI: 10.1093/rheumatology/kez335

Abstract Objective To address heterogeneity complicating primary SS (pSS) clinical trials, research and care by characterizing and clustering patients by their molecular phenotypes. Methods pSS patients met American–European Consensus Group classification criteria and had at least one systemic manifestation and stimulated salivary flow of ⩾0.1 ml/min. Correlated transcriptional modules were derived from gene expression microarray data from blood (n = 47 with appropriate samples). Patients were clustered based on this molecular information using an unbiased random forest modelling approach. In addition, multiplex, bead-based assays and ELISAs were used to assess 30 serum cytokines, chemokines and soluble receptors. Eleven autoantibodies, including anti-Ro/SSA and anti-La/SSB, were measured by Bio-Rad Bioplex 2200. Results Transcriptional modules distinguished three clusters of pSS patients. Cluster 1 showed no significant elevation of IFN or inflammation modules. Cluster 2 showed strong IFN and inflammation modular network signatures, as well as high plasma protein levels of IP-10/CXCL10, MIG/CXCL9, BLyS (BAFF) and LIGHT. Cluster 3 samples exhibited moderately elevated IFN modules, but with suppressed inflammatory modules, increased IP-10/CXCL10 and B cell–attracting chemokine 1/CXCL13 and trends toward increased MIG/CXCL9, IL-1α, and IL-21. Anti-Ro/SSA and anti-La/SSB were present in all three clusters. Conclusion Molecular profiles encompassing IFN, inflammation and other signatures can be used to separate patients with pSS into distinct clusters. In the future, such profiles may inform patient selection for clinical trials and guide treatment decisions.