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