Judith A James1,2,3, Joel M Guthridge1,2, Hua Chen1, Rufei Lu1,2, Rebecka L Bourn1, Krista Bean1, Melissa E Munroe1, Miles Smith1, Eliza Chakravarty1, Alan N Baer4, Ghaith Noaiseh5, Ann Parke6, Karen Boyle7, Lynette Keyes-Elstein7, Andreea Coca8, Tammy Utset9, Mark C Genovese10, Virginia Pascual11, Paul J Utz10, V Michael Holers12, Kevin D Deane12, Kathy L Sivils1, Teresa Aberle1, Daniel J Wallace13, James McNamara14, Nathalie Franchimont15, E William St Clair16. 1. Arthritis and Clinical Immunology, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA. 2. Department of Medicine. 3. Department of Pathology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA. 4. Division of Rheumatology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. 5. Division of Rheumatology and Clinical Immunology, Department of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, USA. 6. Division of Rheumatic Diseases, University of Connecticut, Farmington, CT, USA. 7. Rho Federal Systems Division, Chapel Hill, NC, USA. 8. Department of Medicine, University of Rochester Medical Center, Rochester, NY, USA. 9. Department of Medicine, University of Chicago, Chicago, IL, USA. 10. Immunology and Rheumatology, Stanford University School of Medicine, Stanford, CA, USA. 11. Drukier Institute for Children's Health, Weill Cornell Medicine, New York, NY, USA. 12. Division of Rheumatology, University of Colorado School of Medicine, Aurora,CO, USA. 13. Department of Medicine, Cedars-Sinai Medical Center, West Hollywood, CA, USA. 14. Division of Allergy, Immunology, and Transplantation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA. 15. Biogen, Cambridge, MA, USA. 16. Division of Rheumatology and Immunology, Department of Medicine, Duke University School of Medicine, Durham, NC, USA.
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.
OBJECTIVE: To address heterogeneity complicating primary SS (pSS) clinical trials, research and care by characterizing and clustering patients by their molecular phenotypes. METHODS:pSSpatients 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 pSSpatients. 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.
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