Characterising the genetic architecture of changes in adiposity during adulthood using electronic health records

Samvida S. Venkatesh (), Habib Ganjgahi, Duncan S. Palmer, Kayesha Coley, Gregorio V. Linchangco, Qin Hui, Peter Wilson, Yuk-Lam Ho, Kelly Cho, Kadri Arumäe, Laura B. L. Wittemans, Christoffer Nellåker, Uku Vainik, Yan V. Sun, Chris Holmes, Cecilia M. Lindgren () and George Nicholson ()
Additional contact information
Samvida S. Venkatesh: University of Oxford
Habib Ganjgahi: University of Oxford
Duncan S. Palmer: University of Oxford
Kayesha Coley: University of Leicester
Gregorio V. Linchangco: Emory University Rollins School of Public Health
Qin Hui: Emory University Rollins School of Public Health
Peter Wilson: Atlanta VA Health Care System
Yuk-Lam Ho: Veterans Affairs Boston Healthcare System
Kelly Cho: Veterans Affairs Boston Healthcare System
Kadri Arumäe: University of Tartu
Laura B. L. Wittemans: Novo Nordisk Research Centre Oxford
Christoffer Nellåker: University of Oxford
Uku Vainik: University of Tartu
Yan V. Sun: Emory University Rollins School of Public Health
Chris Holmes: University of Oxford
Cecilia M. Lindgren: University of Oxford
George Nicholson: University of Oxford

Nature Communications, 2024, vol. 15, issue 1, 1-19

Abstract: Abstract Obesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 24.5 million primary-care health records in over 740,000 individuals in the UK Biobank, Million Veteran Program USA, and Estonian Biobank, to discover and validate the genetic architecture of adiposity trajectories. Using multiple BMI measurements over time increases power to identify genetic factors affecting baseline BMI by 14%. In the largest reported genome-wide study of adiposity-change in adulthood, we identify novel associations with BMI-change at six independent loci, including rs429358 (APOE missense variant). The SNP-based heritability of BMI-change (1.98%) is 9-fold lower than that of BMI. The modest genetic correlation between BMI-change and BMI (45.2%) indicates that genetic studies of longitudinal trajectories could uncover novel biology of quantitative traits in adulthood.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-024-49998-0 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-49998-0

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-024-49998-0

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().