Colocalization of corneal resistance factor GWAS loci with GTEx e/sQTLs highlights plausible candidate causal genes for keratoconus postnatal corneal stroma weakening - Jiang, Xinyi; Boutin, Thibaud; Vitart, Veronique (Frontiers in Genetics, 2023)
Genome-wide association studies (GWAS) for corneal resistance factor (CRF) have identified 100s of loci and proved useful in uncovering genetic determinants for keratoconus, a corneal ectasia of early-adulthood onset and common indication of corneal transplantation. In the current absence of studies allowing to directly probe the impact of candidate causal variants on gene expression in the cornea, we aimed to fill some of this knowledge gap by leveraging tissue-shared genetic regulatory effects. We established that 26.5% of 181 CRF causal signals colocalize with those affecting steady-2 state gene transcription and splicing in adult, non-corneal, tissues of the Genotype-Tissue Expression (GTEx) project. Based on single cell transcriptomes of adult cornea, limbus and conjunctiva, the genes thus linked to CRF associations were enriched in genes with high and specific expression in stromal cells of the cornea. Enrichment analyses carried out with nearest genes to CRF GWAS signals indicated that stromal cells of the limbus could be susceptible to the genetic signals that did not colocalize with GTEx's. These cells might not be well represented in GTEx tissues and/or the genetic associations might have context specific effects. The shared causal signals with GTEx provide many new insights into mediation of CRF genetic effects, including modulation of splicing events. Reported roles of several implicated gene-products in providing tensile strength, mechanosensing and signaling make the corresponding genes and regulatory variants prime functionally relevant candidates to be validated and their roles and effects across tissues elucidated. Finally, by additionally performing fine-mapping and colocalization of CRF and keratoconus GWAS signals, we strengthened support for their sharing causal variants but also highlighted many ways into which likely true shared signals could be missed when using readily available GWAS summary statistics.