Integrated systems analysis of salivary gland transcriptomics reveals key molecular networks in Sjogren's syndrome.

ABSTRACT:

Background

Treatment of patients with Sjögren's syndrome (SjS) is a clinical challenge with high unmet needs. Gene expression profiling and integrative network-based approaches to complex disease can offer an insight on molecular characteristics in the context of clinical setting.

Methods

An integrated dataset was created from salivary gland samples of 30 SjS patients. Pathway-driven enrichment profiles made by gene set enrichment analysis were categorized using hierarchical clustering. Differentially expressed genes (DEGs) were subjected to functional network analysis, where the elements of the core subnetwork were used for key driver analysis.

Results

We identified 310 upregulated DEGs, including nine known genetic risk factors and two potential biomarkers. The core

SUBMITTER: Min HK 

PROVIDER: S-EPMC6921432 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature