A comprehensive meta-analysis and prioritization study to identify vitiligo associated coding and non-coding SNV candidates using web-based bioinformatics tools

Abstract

AbstractVitiligo is a prevalent depigmentation disorder affecting around 1% of the general population. So far, various Genome Wide Association Studies (GWAS) and Candidate Gene Association Studies (CGAS) have identified several single nucleotide variants (SNVs) as a risk factor for vitiligo. Nonetheless, little has been discerned regarding their direct functional significance to the disease pathogenesis. In this study, we did extensive data mining and downstream analysis using several experimentally validated datasets like GTEx Portal and web tools like rSNPBase, RegulomeDB, HaploReg and STRING to prioritize 13 SNVs from a set of 291SNVs that have been previously reported to be associated with vitiligo. We also prioritized their underlying/target genes and tried annotating their functional contribution to vitiligo pathogenesis. Our analysis revealed genes like FGFR10P, SUOX, CDK5RAP1 and RERE that have never been implicated in vitiligo previously to have strong potentials to contribute to the disease pathogenesis. The study is the first of its kind to prioritize and functionally annotate vitiligo-associated GWAS and CGAS SNVs and their underlying/target genes, based on functional data available in the public domain database.