Author:
Jiang Xinyi,Boutin Thibaud,Vitart Veronique
Abstract
Background: Genome-wide association studies (GWAS) for corneal resistance factor (CRF) have identified 100s of loci and proved useful to uncover genetic determinants for keratoconus, a corneal ectasia of early-adulthood onset and common indication of corneal transplantation. In the current absence of studies to probe the impact of candidate causal variants in the cornea, we aimed to fill some of this knowledge gap by leveraging tissue-shared genetic effects.Methods: 181 CRF signals were examined for evidence of colocalization with genetic signals affecting steady-state gene transcription and splicing in adult, non-eye, tissues of the Genotype-Tissue Expression (GTEx) project. Expression of candidate causal genes thus nominated was evaluated in single cell transcriptomes from adult cornea, limbus and conjunctiva. Fine-mapping and colocalization of CRF and keratoconus GWAS signals was also deployed to support their sharing causal variants.Results and discussion: 26.5% of CRF causal signals colocalized with GTEx v8 signals and nominated genes enriched in genes with high and specific expression in corneal stromal cells amongst tissues examined. Enrichment analyses carried out with nearest genes to all 181 CRF GWAS signals indicated that stromal cells of the limbus could be susceptible to signals that did not colocalize with GTEx’s. These cells might not be well represented in GTEx and/or the genetic associations might have context specific effects. The causal signals shared with GTEx provide new insights into mediation of CRF genetic effects, including modulation of splicing events. Functionally relevant roles for several implicated genes’ products in providing tensile strength, mechano-sensing and signaling make the corresponding genes and regulatory variants prime candidates to be validated and their roles and effects across tissues elucidated. Colocalization of CRF and keratoconus GWAS signals strengthened support for shared causal variants but also highlighted many ways into which likely true shared signals could be missed when using readily available GWAS summary statistics.
Subject
Genetics (clinical),Genetics,Molecular Medicine