Large scale phenotype imputation and in vivo functional validation implicate ADAMTS14 as an adiposity gene

Kentistou, KA, Luan, J, Wittemans, LBL, Hambly, C, Klaric, L, Kutalik, Z, Speakman, JR, Wareham, NJ, Kendall, TJ, Langenberg, C, Wilson, JF, Joshi, PK and Morton, NM ORCID: https://orcid.org/0000-0001-8218-8462, 2023. Large scale phenotype imputation and in vivo functional validation implicate ADAMTS14 as an adiposity gene. Nature Communications, 14: 307. ISSN 2041-1723

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Abstract

Obesity remains an unmet global health burden. Detrimental anatomical distribution of body fat is a major driver of obesity-mediated mortality risk and is demonstrably heritable. However, our understanding of the full genetic contribution to human adiposity is incomplete, as few studies measure adiposity directly. To address this, we impute whole-body imaging adiposity phenotypes in UK Biobank from the 4,366 directly measured participants onto the rest of the cohort, greatly increasing our discovery power. Using these imputed phenotypes in 392,535 participants yielded hundreds of genome-wide significant associations, six of which replicate in independent cohorts. The leading causal gene candidate, ADAMTS14, is further investigated in a mouse knockout model. Concordant with the human association data, the Adamts14−/− mice exhibit reduced adiposity and weight-gain under obesogenic conditions, alongside an improved metabolic rate and health. Thus, we show that phenotypic imputation at scale offers deeper biological insights into the genetics of human adiposity that could lead to therapeutic targets.

Item Type:	Journal article
Publication Title:	Nature Communications
Creators:	Kentistou, K.A., Luan, J., Wittemans, L.B.L., Hambly, C., Klaric, L., Kutalik, Z., Speakman, J.R., Wareham, N.J., Kendall, T.J., Langenberg, C., Wilson, J.F., Joshi, P.K. and Morton, N.M.
Publisher:	Nature Research
Date:	2023
Volume:	14
ISSN:	2041-1723
Identifiers:	Number Type 10.1038/s41467-022-35563-0 DOI 2465520 Other
Rights:	© the author(s) 2022. 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 Creative Commons license and your intended use is not permitted 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/.
Divisions:	Schools > School of Science and Technology
Record created by:	Jonathan Gallacher
Date Added:	09 Jul 2025 10:54
Last Modified:	09 Jul 2025 10:54
URI:	https://irep.ntu.ac.uk/id/eprint/53920

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