Identification of Sjögren’s syndrome patient subgroups by clustering of labial salivary gland DNA methylation profiles

Abstract

Heterogeneity in Sjögren’s syndrome (SS), increasingly called Sjögren’s disease, suggests the presence of disease subtypes, which poses a major challenge for the diagnosis, management, and treatment of this autoimmune disorder. Previous work distinguished patient subgroups based on clinical symptoms, but it is not clear to what extent symptoms reflect underlying pathobiology. The purpose of this study was to discover clinical meaningful subtypes of SS based on genome-wide DNA methylation data. We performed a cluster analysis of genome-wide DNA methylation data from labial salivary gland (LSG) tissue collected from 64 SS cases and 67 non-cases. Specifically, hierarchical clustering was performed on low dimensional embeddings of DNA methylation data extracted from a variational autoencoder to uncover unknown heterogeneity. Clustering revealed clinically severe and mild subgroups of SS. Differential methylation analysis revealed that hypomethylation at the MHC and hypermethylation at other genome regions characterize the epigenetic differences between these SS subgroups. Epigenetic profiling of LSGs in SS yields new insights into mechanisms underlying disease heterogeneity. The methylation patterns at differentially methylated CpGs are different in SS subgroups and support the role of epigenetic contributions to the heterogeneity in SS. Biomarker data derived from epigenetic profiling could be explored in future iterations of the classification criteria for defining SS subgroups.