Discovery and Characterization of Genetic Risk Loci in Sjogren's Syndrome

The Sjögren's Genetics Network (SGENE) is an international collaboration focused on identifying and understanding the genetic variations that influence Sjögren's pathology. Collectively, SGENE collaborators from 26 different sites (5 in the United States; 21 in foreign countries) have recruited a large cohort of geographically diverse participants of European ancestry. Participants underwent extensive medical assessment for Sjögren's Disease (formerly Sjögren's Syndrome) using internationally accepted American-European Consensus Group (AECG) classification criteria or the American College of Rheumatology/European League Against Rheumatism classification criteria. Recruitment, sample collection, and genotyping were performed at unique SGENE sites in compliance with local institutional review board approval. High-density SNP genotyping data were collated by the Oklahoma Medical Research Foundation (OMRF) and used to perform a GWAS of Sjögren's of European ancestry. Data quality control, GWAS imputation using the Haplotype Reference Consortium, panel version 1.1, and dbGaP preparation/posting were also performed at the OMRF. To facilitate research focused on understanding the genetics of Sjögren's Disease, the Genomic Summary Results from this GWAS are being made available herein (n=3232 Sjögren's cases; n=8962 healthy controls). To achieve adequate case-to-control ratios for the GWAS analyses, population-based control GWAS data were obtained from dbGaP (phs000428; phs000196; phs000187; phs000672. In accordance with IRB approval, subject consents, and data sharing restrictions, we have made available the individual-level genotyping data for a subset of Sjögren's cases (n=1,244) that were genotyped at the OMRF. Bulk RNA-sequencing was also performed using total RNA extracted from peripheral whole blood samples from a subset of Sjögren's cases classified by status of Ro autoantibody (Ro-positive n=27; Ro-negative n=23) and healthy controls (n=27). In accordance with IRB approval, subject consents, and data sharing restrictions, we have made available the individual-level transcriptomic sequences as a subset of this cohort. SmartSeq2 manual single cell RNA-sequencing (scRNA-seq) data was also generated from a subset of Sjögren's cases classified by status of Ro autoantibody (Ro positive n=9, Ro negative n=12) and from individuals with non-Sjögren's sicca syndrome (n=11). In accordance with IRB approval, subject consents, and data sharing restrictions, we have made available the individual-level transcriptomic sequences from a subset of this cohort. ]]>
dbGAP Study Cohort TableSS GWAS Cohort SchematicInclusion Criteria:All Sjögren's cases fulfilled internationally accepted American-European Consensus Group (AECG) classification criteria or the American College of Rheumatology/European League Against Rheumatism classification criteria for primary Sjögren's disease according to clinical evaluations performed within the respective SGENE cohortsEuropean ancestry Must be 18 years of age or older Signed an IRB consent form agreeing to the terms of the study Exclusion Criteria:Less than 18 years of age Belongs to a vulnerable population defined by the National Institutes of Health (NIH)Non-European-derived ancestry ]]>
The International Sjögren's Genetics Network (SGENE) is a continually growing collaboration of 26 research groups from across the globe that are working together to uncover the genetic architecture of Sjögren's. In 2013, SGENE collaborators published the first large-scale genomic study of Sjögren's of European ancestry using ImmunoChip 1.0 array (Lessard, et al. Nature Genetics 2013. PMID: 24097067). This study identified six novel genome-wide significant regions of association, replicated several previously established associations, and identified several regions of suggestive association. In 2022, SGENE collaborators published the largest-to-date genome-wide association study (GWAS) of Sjögren's of European ancestry, identifying 10 novel risk loci with functional implications in immune cells and the salivary gland (Khatri, et al. Nat Commun 2022. PMID 35896530). In 2022, Lessard and colleagues also published a study that used bulk RNA-sequencing of whole blood to identify differentially expressed lncRNAs in Sjögren's. LINC01871 was identified and functionally characterized using CRISPR technologies (Joachims, et al. RMD Open 2022. PMID 36456101). In 2025, Lessard and colleagues leveraged this GWAS data in a trans disease meta-analysis, fine-mapping, and bioinformatic interrogation of the DDX6-CXCR5 risk locus associated with Sjögren's and systemic lupus erythematosus (SLE). The study prioritized and functionally characterized five common SNPs spanning the two risk loci and identified shared genetic susceptibility that likely alters common mechanisms of autoimmunity including interferon signaling, autophagy, and lymphocytic infiltration of disease-target tissues (Wiley, et al. Ann Rheum Dis 2025. PMID 40447495). ]]>