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@ARTICLE{PeruchetNoray:295908,
      author       = {L. Peruchet-Noray and N. Dimou and R. Cordova and E.
                      Fontvieille and A. Jansana and Q. Gan and M. Breeur and H.
                      Baurecht and P. Bohmann and J. Konzok and M. J. Stein and C.
                      C. Dahm and N. R. Zilhão and L. Mellemkjær and A.
                      Tjønneland and R. Kaaks$^*$ and V. Katzke$^*$ and E.
                      Inan-Eroglu and M. B. Schulze and G. Masala and S. Sieri and
                      V. Simeon and G. Matullo and E. Molina-Montes and P. Amiano
                      and M.-D. Chirlaque and A. Gasque and J. Atkins and K.
                      Smith-Byrne and P. Ferrari and V. Viallon and A. Agudo and
                      M. J. Gunter and C. Bonet and H. Freisling and R.
                      Carreras-Torres},
      title        = {{N}ature or nurture: genetic and environmental predictors
                      of adiposity gain in adults.},
      journal      = {EBioMedicine},
      volume       = {111},
      issn         = {2352-3964},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier},
      reportid     = {DKFZ-2024-02721},
      pages        = {105510},
      year         = {2025},
      note         = {Volume 111, January 2025, 105510},
      abstract     = {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).},
      keywords     = {Adiposity gain (Other) / Environmental factors (Other) /
                      Polygenic risk scores (Other) / Prediction (Other)},
      cin          = {C020},
      ddc          = {610},
      cid          = {I:(DE-He78)C020-20160331},
      pnm          = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
      pid          = {G:(DE-HGF)POF4-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:39689375},
      doi          = {10.1016/j.ebiom.2024.105510},
      url          = {https://inrepo02.dkfz.de/record/295908},
}