BACKGROUND: Weight trajectories might reflect individual health status. In this study, we aimed to examine the clinical and genetic associations of adult weight trajectories using electronic health records (EHRs) in the BioMe Biobank. METHODS: ) of weight trajectories using GCTA-GREML, and we did a hypothesis-driven analysis of anorexia nervosa and depression polygenic risk scores (PRS) on these weight trajectories, given both diseases are associated with weight changes. We extended our analyses to the UK Biobank to replicate findings from a patient population to a generally healthy population. FINDINGS: 1·16, 95% CI 1·07-1·26, per 1 SD higher PRS, p=0·011), and the association was not attenuated by obesity PRS. No association was found between depression PRS and weight trajectories after permutation tests. All main findings were replicated in the UK Biobank (p<0·05). INTERPRETATION: Our findings suggest the importance of considering weight from a longitudinal aspect for its association with health and highlight a crucial role of weight management during disease development and progression. FUNDING: Klarman Family Foundation, US National Institute of Mental Health (NIMH).
| Authors | Xu, Jiayi; Johnson, Jessica S; Signer, Rebecca; , ; Birgegård, Andreas; Jordan, Jennifer; Kennedy, Martin A; Landén, Mikael; Maguire, Sarah L; Martin, Nicholas G; Mortensen, Preben Bo; Petersen, Liselotte V; Thornton, Laura M; Bulik, Cynthia M; Huckins, Laura M |
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| Journal | The Lancet. Digital health |
| Pages | e604-e614 |
| Volume | 4 |
| Date | 1/01/2022 |
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| URL | http://www.ncbi.nlm.nih.gov/pubmed/?term=10.1016/S2589-7500(22)00099-1 |