rs11217878 - ARHGEF12

Magnitude 2.2 · 4 studies on file

Reported associations

• Genome-wide association analyses identify new loci influencing intraocular pressure. - Human molecular genetics (2019) · Gao XR, Huang H, Nannini DR, Fan F, Kim H · PubMed 29617998

  Elevated intraocular pressure (IOP) is a significant risk factor for glaucoma, the leading cause of irreversible blindness worldwide. While previous studies have identified numerous genetic variants associated with IOP, these loci only explain a fraction of IOP heritability. Recently established of biobank repositories have resulted in large amounts of data, enabling the identification of the remaining heritability for complex traits. Here, we describe the largest genome-wide association study of IOP to date using participants of European ancestry from the UK Biobank. We identified 671 directly genotyped variants that are significantly associated with IOP (P < 5 × 10-8). In addition to 103 novel loci, the top ranked novel IOP genes are LMX1B, NR1H3, MADD and SEPT9. We replicated t

• Genome-wide association study of intraocular pressure uncovers new pathways to glaucoma. - Nature genetics (2019) · MacGregor S, Ong JS, An J, Han X, Zhou T, Siggs OM, Law MH, Souzeau E, Sharma S, Lynn DJ, Beesley J, Sheldrick B, Mills RA, Landers J, Ruddle JB, Graham SL, Healey PR, White AJR, Casson RJ, Best S, Grigg JR, Goldberg I, Powell JE, Whiteman DC, Radford-Smith GL, Martin NG, Montgomery GW, Burdon KP, Mackey DA, Gharahkhani P, Craig JE, Hewitt AW · PubMed 30054594

  Intraocular pressure (IOP) is currently the sole modifiable risk factor for primary open-angle glaucoma (POAG), one of the leading causes of blindness worldwide . Both IOP and POAG are highly heritable . We report a combined analysis of participants from the UK Biobank (n = 103,914) and previously published data from the International Glaucoma Genetic Consortium (n = 29,578) that identified 101 statistically independent genome-wide-significant SNPs for IOP, 85 of which have not been previously reported . We examined these SNPs in 11,018 glaucoma cases and 126,069 controls, and 53 SNPs showed evidence of association. Gene-based tests implicated an additional 22 independent genes associated with IOP. We derived an allele score based on the IOP loci and loci influencing optic nerve he

• ARHGEF12 influences the risk of glaucoma by increasing intraocular pressure. - Human molecular genetics (2015) · Springelkamp H, Iglesias AI, Cuellar-Partida G, Amin N, Burdon KP, van Leeuwen EM, Gharahkhani P, Mishra A, van der Lee SJ, Hewitt AW, Rivadeneira F, Viswanathan AC, Wolfs RC, Martin NG, Ramdas WD, van Koolwijk LM, Pennell CE, Vingerling JR, Mountain JE, Uitterlinden AG, Hofman A, Mitchell P, Lemij HG, Wang JJ, Klaver CC, Mackey DA, Craig JE, van Duijn CM, MacGregor S · PubMed 25637523

  Primary open-angle glaucoma (POAG) is a blinding disease. Two important risk factors for this disease are a positive family history and elevated intraocular pressure (IOP), which is also highly heritable. Genes found to date associated with IOP and POAG are ABCA1, CAV1/CAV2, GAS7 and TMCO1. However, these genes explain only a small part of the heritability of IOP and POAG. We performed a genome-wide association study of IOP in the population-based Rotterdam Study I and Rotterdam Study II using single nucleotide polymorphisms (SNPs) imputed to 1000 Genomes. In this discovery cohort (n = 8105), we identified a new locus associated with IOP. The most significantly associated SNP was rs58073046 (β = 0.44, P-value = 1.87 × 10(-8), minor allele frequency = 0.12), within the gene ARHGEF12. Inde

• Principled distillation of UK Biobank phenotype data reveals underlying structure in human variation - Unknown journal (n.d.) · Unknown authors · PubMed 38965376

  ABSTRACT: Data within biobanks capture broad yet detailed indices of human variation, but biobank-wide insights can be difficult to extract due to complexity and scale. Here, using large-scale factor analysis, we distill hundreds of variables (diagnoses, assessments and survey items) into 35 latent constructs, using data from unrelated individuals with predominantly estimated European genetic ancestry in UK Biobank. These factors recapitulate known disease classifications, disentangle elements of socioeconomic status, highlight the relevance of psychiatric constructs to health and improve measurement of pro-health behaviours. We go on to demonstrate the power of this approach to clarify genetic signal, enhance discovery and identify associations between underlying phenotypic structure and

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