Peruchet-Noray, Laia and Dimou, Niki and Cordova, Reynalda and Fontvieille, Emma and Jansana, Anna and Gan, Quan and Breeur, Marie and Baurecht, Hansjoerg and Bohmann, Patricia and Konzok, Julian and Stein, Michael J. and Dahm, Christina C. and Zilhao, Nuno R. and Mellemkjaer, Lene and Tjonneland, Anne and Kaaks, Rudolf and Katzke, Verena and Inan-Eroglu, Elif and Schulze, Matthias B. and Masala, Giovanna and Sieri, Sabina and Simeon, Vittorio and Matullo, Giuseppe and Molina-Montes, Esther and Amiano, Pilar and Chirlaque, Maria-Dolores and Gasque, Alba and Atkins, Joshua and Smith-Byrne, Karl and Ferrari, Pietro and Viallon, Vivian and Agudo, Antonio and Gunter, Marc J. and Bonet, Catalina and Freisling, Heinz and Carreras-Torres, Robert (2025) Nature or nurture: genetic and environmental predictors of adiposity gain in adults. EBIOMEDICINE, 111: 105510. ISSN 2352-3964,
Full text not available from this repository. (Request a copy)Abstract
Background Previous prediction models for adiposity gain have not yet achieved sufficient predictive ability for clinical relevance. We investigated whether traditional and genetic factors accurately predict adiposity gain. Methods A 5-year gain of >= 5% in body mass index (BMI) and waist-to-hip ratio (WHR) from baseline were predicted in mid-late adulthood individuals (median of 55 years old at baseline). Proportional hazards models were fi tted in 245,699 participants from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort to identify robust environmental predictors. Polygenic risk scores (PRS) of 5 proxies of adiposity [BMI, WHR, and three body shape phenotypes (PCs)] were computed using genetic weights from an independent cohort (UK Biobank). Environmental and genetic models were validated in 29,953 EPIC participants. Findings Environmental models presented a remarkable predictive ability (AUCBMI: 0.69, 95% CI: 0.68-0.70; AUCWHR: 0.75, 95% CI: 0.74-0.77). The genetic geographic distribution for WHR and PC1 (overall adiposity) showed higher predisposition in North than South Europe. Predictive ability of PRSs was null (AUC: similar to 0.52) and did not improve when combined with environmental models. However, PRSs of BMI and PC1 showed some prediction ability for BMI gain from self-reported BMI at 20 years old to baseline observation (early adulthood) (AUC: 0.60-0.62). Interpretation Our study indicates that environmental models to discriminate European individuals at higher risk of adiposity gain can be integrated in standard prevention protocols. PRSs may play a robust role in predicting adiposity gain at early rather than mid-late adulthood suggesting a more important role of genetic factors in this life period.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | BODY-MASS INDEX; LIFE-COURSE; AGE; CANCER; TWIN; Adiposity gain; Prediction; Polygenic risk scores; Environmental factors |
| Subjects: | 600 Technology > 610 Medical sciences Medicine |
| Divisions: | Medicine > Institut für Epidemiologie und Präventivmedizin |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 07 Apr 2026 11:57 |
| Last Modified: | 07 Apr 2026 11:57 |
| URI: | https://pred.uni-regensburg.de/id/eprint/65662 |
Actions (login required)
 |
View Item |
