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Genome-wide analysis of health-related biomarkers in the UK Household Longitudinal Study reveals novel associations

Prins, BP; Kuchenbaecker, KB; Bao, Y; Smart, M; Zabaneh, D; Fatemifar, G; Luan, J; ... Zeggini, E; + view all (2017) Genome-wide analysis of health-related biomarkers in the UK Household Longitudinal Study reveals novel associations. Scientific Reports , 7 , Article 11008. 10.1038/s41598-017-10812-1. Green open access

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Abstract

Serum biomarker levels are associated with the risk of complex diseases. Here, we aimed to gain insights into the genetic architecture of biomarker traits which can reflect health status. We performed genome-wide association analyses for twenty serum biomarkers involved in organ function and reproductive health. 9,961 individuals from the UK Household Longitudinal Study were genotyped using the Illumina HumanCoreExome array and variants imputed to the 1000 Genomes Project and UK10K haplotypes. We establish a polygenic heritability for all biomarkers, confirm associations of fifty-four established loci, and identify five novel, replicating associations at genome-wide significance. A low-frequency variant, rs28929474, (beta = 0.04, P = 2 × 10(-10)) was associated with levels of alanine transaminase, an indicator of liver damage. The variant is located in the gene encoding serine protease inhibitor, low levels of which are associated with alpha-1 antitrypsin deficiency which leads to liver disease. We identified novel associations (rs78900934, beta = 0.05, P = 6 × 10(-12); rs2911280, beta = 0.09, P = 6 × 10(-10)) for dihydroepiandrosterone sulphate, a precursor to major sex-hormones, and for glycated haemoglobin (rs12819124, beta = -0.03, P = 4 × 10(-9); rs761772, beta = 0.05, P = 5 × 10(-9)). rs12819124 is nominally associated with risk of type 2 diabetes. Our study offers insights into the genetic architecture of well-known and less well-studied biomarkers.

Type: Article
Title: Genome-wide analysis of health-related biomarkers in the UK Household Longitudinal Study reveals novel associations
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1038/s41598-017-10812-1
Publisher version: http://doi.org/10.1038/s41598-017-10812-1
Language: English
Additional information: © The Author(s) 2017. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Keywords: Genome-wide association studies, Heritable quantitative trait
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Division of Psychiatry
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Pop Health Sciences > Institute of Epidemiology and Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Pop Health Sciences > Institute of Epidemiology and Health > Epidemiology and Public Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Pop Health Sciences > Institute of Health Informatics
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Pop Health Sciences > Institute of Health Informatics > Clinical Epidemiology
URI: https://discovery.ucl.ac.uk/id/eprint/1574474
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