We conducted the first GWAS of macular thickness, which was measured by spectral-domain optical coherence tomography using 68,423 participants from the UK Biobank cohort. We identified 139 genetic loci associated with macular thickness at genome-wide significance (P < 5 ? 10-8). The most significant loci were LINC00461 (P = 5.1x10-120), TSPAN10 (P = 1.2x10-118), RDH5 (P = 9.2x10-105), and SLC6A20 (P = 1.4x10-71). Results from gene expression demonstrated that these genes are highly expressed in the retina. Other hits included many previously reported AMD genes, such as NPLOC4 (P = 1.7x10-103), RAD51B (P = 9.1x10-14) and SLC16A8 (P = 1.7x10-8), further providing functional significance of the identified loci. Through cross-phenotype analysis, these genetic loci also exhibited pleiotropic effects with myopia, neurodegenerative diseases (e.g. Parkinson s disease, schizophrenia, and Alzheimer s disease), cancer (e.g. breast, ovarian, and lung cancers), and metabolic traits (e.g. body mass index, waist circumference, and type 2 diabetes). Our findings provide the first insight into the genetic architecture of macular thickness.
Ocular Genetics in the UK Biobank
Genome-wide association studies (GWAS) have led to the identification of genetic variants that are associated with a variety of human diseases and traits. While their use in the field of ophthalmology has revealed biological insight into the pathogenesis of many ocular diseases, we believe additional variants remain to be identified. The primary aim of this research is to identify novel single nucleotide polymorphisms (SNPs) and pathways associated with ocular phenotypes such as glaucoma, cataract, macular degeneration, intraocular pressure, and corneal hysteresis. And secondly, we aim to replicate previously identified loci for these ocular phenotypes. Visual impairment and eye disorders are significant public health issues around the world, resulting in decreased quality of life for these affected individuals. With an aging global population, the number of individuals affected by these conditions is expected to increase. Therefore, identifying genetic variants that influence such conditions will allow for better prediction of ocular traits, leading to the identification of at risk individuals in which targeted prevention strategies and early detection methods can be made available. Furthermore, identification of biological pathways may enable the development of effective therapeutic treatments for these blinding disorders. After receiving the data, both the genotype and phenotype data will undergo stringent quality control parameters to retain high quality information. Identification of novel SNPs will then be conducted via single variant association testing for each phenotype utilizing statistical models, adjusting for covariates. Enrichment of biological pathways will be performed by analyzing gene sets, generated from SNP data, with known pathways from multiple databases. Replication of previously reported loci will be conducted by examining the results generated from the current study with those from previous studies. The number of participants to be included in our study is a subset of the full cohort. Our study will include the 117,649 individuals who underwent the eye and vision component of the UK Biobank, individuals with available eyesight medical history, and individuals who have available genotype data.
|Lead investigator:||Dr Xiaoyi Gao|
|Lead institution:||Ohio State University Physicians, Inc.|
1 related Return
|Return ID||App ID||Description||Archive Date|
|2144||23424||Polygenic Risk Score Is Associated With Intraocular Pressure and Improves Glaucoma Prediction in the UK Biobank Cohort||16 Mar 2020|
|3088||Genome-wide association analyses identify 139 loci associated with macular thickness in the UK Biobank cohort||Gao et al||2019||Human Molecular Genetics (2019)|