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000295908 1001_ $$aPeruchet-Noray, Laia$$b0
000295908 245__ $$aNature or nurture: genetic and environmental predictors of adiposity gain in adults.
000295908 260__ $$aAmsterdam [u.a.]$$bElsevier$$c2025
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000295908 500__ $$aVolume 111, January 2025, 105510
000295908 520__ $$aPrevious 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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000295908 650_7 $$2Other$$aAdiposity gain
000295908 650_7 $$2Other$$aEnvironmental factors
000295908 650_7 $$2Other$$aPolygenic risk scores
000295908 650_7 $$2Other$$aPrediction
000295908 7001_ $$aDimou, Niki$$b1
000295908 7001_ $$aCordova, Reynalda$$b2
000295908 7001_ $$aFontvieille, Emma$$b3
000295908 7001_ $$aJansana, Anna$$b4
000295908 7001_ $$aGan, Quan$$b5
000295908 7001_ $$aBreeur, Marie$$b6
000295908 7001_ $$aBaurecht, Hansjörg$$b7
000295908 7001_ $$aBohmann, Patricia$$b8
000295908 7001_ $$aKonzok, Julian$$b9
000295908 7001_ $$aStein, Michael J$$b10
000295908 7001_ $$aDahm, Christina C$$b11
000295908 7001_ $$aZilhão, Nuno R$$b12
000295908 7001_ $$aMellemkjær, Lene$$b13
000295908 7001_ $$aTjønneland, Anne$$b14
000295908 7001_ $$0P:(DE-He78)4b2dc91c9d1ac33a1c0e0777d0c1697a$$aKaaks, Rudolf$$b15$$udkfz
000295908 7001_ $$0P:(DE-He78)fb68a9386399d72d84f7f34cfc6048b4$$aKatzke, Verena$$b16$$udkfz
000295908 7001_ $$aInan-Eroglu, Elif$$b17
000295908 7001_ $$aSchulze, Matthias B$$b18
000295908 7001_ $$aMasala, Giovanna$$b19
000295908 7001_ $$aSieri, Sabina$$b20
000295908 7001_ $$aSimeon, Vittorio$$b21
000295908 7001_ $$aMatullo, Giuseppe$$b22
000295908 7001_ $$aMolina-Montes, Esther$$b23
000295908 7001_ $$aAmiano, Pilar$$b24
000295908 7001_ $$aChirlaque, María-Dolores$$b25
000295908 7001_ $$aGasque, Alba$$b26
000295908 7001_ $$aAtkins, Joshua$$b27
000295908 7001_ $$aSmith-Byrne, Karl$$b28
000295908 7001_ $$aFerrari, Pietro$$b29
000295908 7001_ $$aViallon, Vivian$$b30
000295908 7001_ $$aAgudo, Antonio$$b31
000295908 7001_ $$aGunter, Marc J$$b32
000295908 7001_ $$aBonet, Catalina$$b33
000295908 7001_ $$aFreisling, Heinz$$b34
000295908 7001_ $$aCarreras-Torres, Robert$$b35
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