A quantitative trait GWAS on lens thickness identifies novel risk loci on PTPRM in the narrow angle individuals susceptible to PACG

Abstract

Purpose PACG is one of the leading causes of blindness where lens thickness is a major risk factor for narrow-angle individuals. To our knowledge, no literature has been reported on candidate gene for lens thickness as a quantitative trait (QT). Here, we performed a genome-wide association analysis on lens thickness in the narrow-angle individuals. Materials and Methods We conducted a genome-wide association study (GWAS) in the narrow angle individuals to investigate comprehensive genetic insights on lens thickness. Results In QT-GWAS, we identified 145 genome-wide suggestive significant loci in the discovery cohort. Subsequently, we observed 13 SNPs that showed statistical significance around the region of PTRRM. Regional association analysis for top significant genotyped variants identified PTPRM as the most likely candidate for increased LT. Integrative bioinformatic analyses confirmed that the associated genomic region has potential regulatory roles for modulating transcription as enhancers. In the replication cohort, the sentinel genotype SNP was further associated significantly (P-value =0.000448) with high LT individuals. In both cohorts, the T allele of rs1941137 in the PTPRM gene indicates as a risk allele for the increased LT. Conclusion In this study, we discovered evidence of a genomic association between chromosomal areas around the PTPRM and increased lens thickness, resulting in a narrow angle. The regulatory components corresponding to PTPRM variations might have a role in the thicker lens. We report that the genomic region near PTPRM, a gene of potential interest, is associated with increased lens thickness.

Post-GWAS functional analyses ofCNTNAP5suggests its role in glaucomatous neurodegeneration

“…We specifically queried genomic coordinates chr2:125,083,095-125,084,384 spanning the CNTNAP5 locus for reported CREs characterized by empirical DNaseI, CTCF, H3K4me3, and H3K27ac signals. Data on genomic location, biochemical epigenetic readouts, normal cell/tissue source identifiers and other annotation metadata were systematically compiled for downstream analysis in R software (R, version 4.1.2) environment as described in Chakraborty et al, 2023 14 . The regulatory potential of CNTNAP5 intronic and 3’ UTR SNPs was assessed using the DeepSEA web server and RegulomeDB.…”