Tachmazidou, I;
Suveges, D;
Min, JL;
Ritchie, GRS;
Steinberg, J;
Walter, K;
Iotchkova, V;
... Zeggini, E; + view all
(2017)
Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits.
The American Journal of Human Genetics
, 100
(6)
pp. 865-884.
10.1016/j.ajhg.2017.04.014.
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Abstract
Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and polygenic anthropometric traits and find signal enrichment in cis expression QTLs in relevant tissues. Our results highlight the potential of WGS strategies to enhance biologically relevant discoveries across the frequency spectrum
| Type: | Article |
|---|---|
| Title: | Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.ajhg.2017.04.014 |
| Publisher version: | http://doi.org/10.1016/j.ajhg.2017.04.014 |
| Language: | English |
| Additional information: | �Copyright © 2017 The Authors. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
| UCL classification: | UCL 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 Population Health Sciences > Institute of Cardiovascular Science UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Population Science and Experimental Medicine |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10043586 |
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