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| 001 | 295908 | ||
| 005 | 20241227135010.0 | ||
| 024 | 7 | _ | |a 10.1016/j.ebiom.2024.105510 |2 doi |
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| 037 | _ | _ | |a DKFZ-2024-02721 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Peruchet-Noray, Laia |b 0 |
| 245 | _ | _ | |a Nature or nurture: genetic and environmental predictors of adiposity gain in adults. |
| 260 | _ | _ | |a Amsterdam [u.a.] |c 2025 |b Elsevier |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1735303787_21519 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
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| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 500 | _ | _ | |a Volume 111, January 2025, 105510 |
| 520 | _ | _ | |a 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.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 fitted 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.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: ∼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).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.French National Cancer Institute (INCA_N°2019-176) 1220, German Research Foundation (BA 5459/2-1), Instituto de Salud Carlos III (Miguel Servet Program CP21/00058). |
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| 650 | _ | 7 | |a Adiposity gain |2 Other |
| 650 | _ | 7 | |a Environmental factors |2 Other |
| 650 | _ | 7 | |a Polygenic risk scores |2 Other |
| 650 | _ | 7 | |a Prediction |2 Other |
| 700 | 1 | _ | |a Dimou, Niki |b 1 |
| 700 | 1 | _ | |a Cordova, Reynalda |b 2 |
| 700 | 1 | _ | |a Fontvieille, Emma |b 3 |
| 700 | 1 | _ | |a Jansana, Anna |b 4 |
| 700 | 1 | _ | |a Gan, Quan |b 5 |
| 700 | 1 | _ | |a Breeur, Marie |b 6 |
| 700 | 1 | _ | |a Baurecht, Hansjörg |b 7 |
| 700 | 1 | _ | |a Bohmann, Patricia |b 8 |
| 700 | 1 | _ | |a Konzok, Julian |b 9 |
| 700 | 1 | _ | |a Stein, Michael J |b 10 |
| 700 | 1 | _ | |a Dahm, Christina C |b 11 |
| 700 | 1 | _ | |a Zilhão, Nuno R |b 12 |
| 700 | 1 | _ | |a Mellemkjær, Lene |b 13 |
| 700 | 1 | _ | |a Tjønneland, Anne |b 14 |
| 700 | 1 | _ | |a Kaaks, Rudolf |0 P:(DE-He78)4b2dc91c9d1ac33a1c0e0777d0c1697a |b 15 |u dkfz |
| 700 | 1 | _ | |a Katzke, Verena |0 P:(DE-He78)fb68a9386399d72d84f7f34cfc6048b4 |b 16 |u dkfz |
| 700 | 1 | _ | |a Inan-Eroglu, Elif |b 17 |
| 700 | 1 | _ | |a Schulze, Matthias B |b 18 |
| 700 | 1 | _ | |a Masala, Giovanna |b 19 |
| 700 | 1 | _ | |a Sieri, Sabina |b 20 |
| 700 | 1 | _ | |a Simeon, Vittorio |b 21 |
| 700 | 1 | _ | |a Matullo, Giuseppe |b 22 |
| 700 | 1 | _ | |a Molina-Montes, Esther |b 23 |
| 700 | 1 | _ | |a Amiano, Pilar |b 24 |
| 700 | 1 | _ | |a Chirlaque, María-Dolores |b 25 |
| 700 | 1 | _ | |a Gasque, Alba |b 26 |
| 700 | 1 | _ | |a Atkins, Joshua |b 27 |
| 700 | 1 | _ | |a Smith-Byrne, Karl |b 28 |
| 700 | 1 | _ | |a Ferrari, Pietro |b 29 |
| 700 | 1 | _ | |a Viallon, Vivian |b 30 |
| 700 | 1 | _ | |a Agudo, Antonio |b 31 |
| 700 | 1 | _ | |a Gunter, Marc J |b 32 |
| 700 | 1 | _ | |a Bonet, Catalina |b 33 |
| 700 | 1 | _ | |a Freisling, Heinz |b 34 |
| 700 | 1 | _ | |a Carreras-Torres, Robert |b 35 |
| 773 | _ | _ | |a 10.1016/j.ebiom.2024.105510 |g Vol. 111, p. 105510 - |0 PERI:(DE-600)2799017-5 |p 105510 |t EBioMedicine |v 111 |y 2025 |x 2352-3964 |
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