GWAS summary statistics for corneal resistance factor in 72,301 unrelated UK Biobank white-British participants

<p>The dataset contains summary statistics of the genome-wide association study (GWAS) for corneal resistance factor (CRF) of 72,301 unrelated UK-biobank white-British individuals, originally generated by Jiang X, et al (2020<a href="https://doi.org/10.1038/s42003-020-01497-w">)</a> (doi: <a href="https://doi.org/10.1038%2Fs42003-020-01497-w">10.1038/s42003-020-01497-w</a>).</p> <p><strong>Generation of the dataset:&nbsp;</strong></p> <ul> <li><strong>Phynotypic filtering:</strong></li> </ul> <p>The CRF analysis was performed on the average of the left and right eye measurements. Any outliers (i.e. CRF greater than the population mean difference + 3 standard deviations) were removed. Further phenotypic filtering was applied by removing samples linked to, or self-reporting, ocular conditions that could affect the measurements accuracy such as eye surgery, refractive laser surgery, cataract surgery, glaucoma high pressure surgery or laser treatment, corneal graft surgery, eye injury, keratoconus or cornea disorders.</p> <ul> <li><strong>Population selection:</strong></li> </ul> <p>Using the genetic quality control of the UK Biobank, white British participants with imputed data failing heterozygosity or/and missingness, or having a mismatch between self-reported and genotype-derived gender or showing putative sex chromosome aneuploidy as well as individuals who have withdrawn from the study at the time of analysis were removed. <em>This GWAS is restricted to individuals who were <strong>not closely related</strong> (pairwise kinship coefficient greater than 0.025 calculated by KING).</em> Finally, a total of 72,301 individuals were included in the GWAS.</p> <ul> <li><strong>GWAS:</strong></li> </ul> <p>The GWAS was performed using the generalized linear model&nbsp; (--glm) in PLINK2, common and low-frequency (MAF &gt; 0.5%) well-imputed (INFO &gt; 0.6) variants. Covariates fitted in the model were: age, sex, genotyping array, assessment center, genotyping batch, and the 20 first principal components of ancestry provided by the UK Biobank.</p> <ul> <li>UK Biobank application number: 19655</li> </ul> <p>&nbsp;</p> <p>Methods:</p> <p>Please see Jiang X, et al (2020<a href="https://doi.org/10.1038/s42003-020-01497-w">)</a> (doi: <a href="https://doi.org/10.1038%2Fs42003-020-01497-w">10.1038/s42003-020-01497-w</a>) for more details:</p> <p>&nbsp;</p> <p><strong>Header Description:</strong></p> <ul> <li>CHROM: chromosome,</li> <li>POS: hg19/GRCh37 position</li> <li>ID: variant Rsid</li> <li>A1: effective allele, minor allele</li> <li>A2: alternative allele, major allele</li> <li>BETA: effect size</li> <li>SE: standard error</li> <li>P: P value</li> <li>INFO: imputation quality</li> <li>MAF: Minor allele frequency</li> </ul> <p>&nbsp;</p> <p><strong>Some related analysis using this dataset:&nbsp;</strong></p> <p>Jiang X, et al (2020<a href="https://doi.org/10.1038/s42003-020-01497-w">)</a> (doi: <a href="https://doi.org/10.1038%2Fs42003-020-01497-w">10.1038/s42003-020-01497-w</a>):&nbsp; Fine-mapped CRF GWAS loci using FINEMAP and in-sample linkage disequilibrium data&nbsp;</p> <p>Jiang X, et al (2023) (doi: <a href="https://doi.org/10.3389%2Ffgene.2023.1171217">10.3389/fgene.2023.1171217</a>): Two colocalisation analysis using fine-mapped data: 1) CRF - cis-e/sQTL (GTEx v8); (2) CRF-keratoconus</p>