Integrative analysis of transcriptome and proteome in primary Sjögren syndrome

Primary Sjögren's syndrome (pSS) is a intricate autoimmune disease mainly characterized of immune-mediated destruction of exocrine tissues, such as salivary and lacrimal glands, occurring dry mouth and eyes. Although some breakthroughs in understanding pSS have been uncovered, many questions remain about its pathogenesis, especially the internal relations between exocrine glands and secretions.

Transcriptomic and proteomic analyses were conducted on salivary tissues and saliva in experimental Sjögren syndrome (ESS). The ESS model was established by immunization with salivary gland protein. The expression of mRNAs and proteins in salivary tissues and saliva were determined by high-throughput sequencing transcriptomic analysis and LC-MS/MS-based proteome, respectively. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to recognize dysregulated genes and proteins. The association between RNA and protein abundance was investigated to provides a comprehensive understanding of RNA-protein correlations in the pathogenesis of pSS.

As a result, we successfully established the ESS model. We recognized 3221 differentially expressed genes (DEGs) and 253 differentially expressed proteins (DEPs). The sample analysis showed that 61 proteins overlapped through the integrative analysis of transcriptomics and proteomics data. The enrichment pathway analysis of DEGs and DEPs in samples showed alterations in renin-angiotensin-system (RAS), lysosome, and apoptosis. Notably, we found that some genes, such as AGT, FN1, Klk1b26, Klk1, Klk1b5, Klk1b3 had a consistent trend in the regulation at the RNA and protein levels and might be potential diagnostic biomarkers of pSS.

Herein, we found critical processes and potential biomakers that may contribute to pSS pathogenesis by analyzing dysregulated genes and pathways. Additionally, the integrative multi-omics datasets provided additional insight into understanding complicated disease mechanisms.