Nature Communications (Jul 2024)

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,
  • Million Veteran Program,
  • Estonian Biobank Research Team,
  • Laura B. L. Wittemans,
  • Christoffer Nellåker,
  • Uku Vainik,
  • Yan V. Sun,
  • Chris Holmes,
  • Cecilia M. Lindgren,
  • George Nicholson

DOI
https://doi.org/10.1038/s41467-024-49998-0
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 19

Abstract

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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.