Genomic studies of Sjgrens syndrome

National Human Genome Research Institute

Investigators

Abstract

Sjogrens Syndrome (SS) is a heterogenous disease which poses challenges in the diagnosis, management and treatment of the disease. In order to characterize disease subtypes, we performed a cluster analysis of genome-wide methylation data. The genome-wide methylation data was profiled on DNA extracted from gland tissue using the Illumina 450k Infinium Methylation BeadChip in 28 patients and the Infinium MethylationEPIC (EPIC) platform for 103 patients. All 131 patients exhibited at least one symptom related to Sjogrens. The 131 patients include 64 patients who were classified as SS cases based on the ACR-EULAR 2016 classification criteria and 67 symptomatic non-cases. For the analysis, the intersection of CpG sites from the 450K chip and the EPIC ship resulted in an initial set of 452,832 CpG sites. After quality control processing, 336,040 CpG sites remained. Hierarchical clustering analysis identified four clusters which distinguished clinically severe and mild subgroups of SS. Clusters 1 and 2 were showed the largest distance from clusters 3 and 4. Clusters 1 and 2 consisted of 93% of the SS cases while clusters 3 and 4 consisted of 73% of the non-cases. An analysis of clinical variables show that patients in clusters 1 and 2 had more severe clinical features compared to clusters 3 and 4. Differential methylation analysis showed that hypomethylation at the MHC and hypermethylation at other genome regions characterize the epigenetic differences between these SS subgroups. Differences of allele frequencies at established SS risk loci showed that severe SS cases had higher risk allele frequencies at SNPs which tag HLA-DRB1, HLA-DQA1, HLA-DQB1 and HLA-DQA2 within the MHC region. These results show that epigenetic profiling provides additional information about the biological subtypes of SS that could contribute to improving SS classification. A manuscript describing these results is being prepared for submission.