Expression Quantitative Trait Locus Analysis in Systemic Sclerosis Identifies New Candidate Genes Associated With Multiple Aspects of Disease Pathology

Abstract

Objective: To identify the genetic variants that affect gene expression (expression quantitative trait loci [eQTLs]) in systemic sclerosis (SSc) and to investigate their role in the pathogenesis of the disease.

Methods: We performed an eQTL analysis using whole-blood sequencing data from 333 SSc patients and 524 controls and integrated them with SSc genome-wide association study (GWAS) data. We integrated our findings from expression modeling, differential expression analysis, and transcription factor binding site enrichment with key clinical features of SSc.

Results: We detected 49,123 validated cis-eQTLs from 4,539 SSc-associated single-nucleotide polymorphisms (SNPs) (PGWAS < 10-5 ). A total of 1,436 genes were within 1 Mb of the 4,539 SSc-associated SNPs. Of those 1,436 genes, 565 were detected as having ≥1 eQTL with an SSc-associated SNP. We developed a strategy to prioritize disease-associated genes based on their expression variance explained by SSc eQTLs (r2 > 0.05). As a result, 233 candidates were identified, 134 (58%) of them associated with hallmarks of SSc and 105 (45%) of them differentially expressed in the blood cells, skin, or lung tissue of SSc patients. Transcription factor binding site analysis revealed enriched motifs of 24 transcription factors (5%) among SSc eQTLs, 5 of which were found to be differentially regulated in the blood cells (ELF1 and MGA), skin (KLF4 and ID4), and lungs (TBX4) of SSc patients. Ten candidate genes (4%) can be targeted by approved medications for immune-mediated diseases, of which only 3 have been tested in clinical trials in patients with SSc.

Conclusion: The findings of the present study indicate a new layer to the molecular complexity of SSc, contributing to a better understanding of the pathogenesis of the disease.