Nature or nurture: genetic and environmental predictors of adiposity gain in adults.

IF 9.7 1区 医学 Q1 MEDICINE, RESEARCH & EXPERIMENTAL EBioMedicine Pub Date : 2024-12-16 DOI:10.1016/j.ebiom.2024.105510
Laia Peruchet-Noray, Niki Dimou, Reynalda Cordova, Emma Fontvieille, Anna Jansana, Quan Gan, Marie Breeur, Hansjörg Baurecht, Patricia Bohmann, Julian Konzok, Michael J Stein, Christina C Dahm, Nuno R Zilhão, Lene Mellemkjær, Anne Tjønneland, Rudolf Kaaks, Verena Katzke, Elif Inan-Eroglu, Matthias B Schulze, Giovanna Masala, Sabina Sieri, Vittorio Simeon, Giuseppe Matullo, Esther Molina-Montes, Pilar Amiano, María-Dolores Chirlaque, Alba Gasque, Joshua Atkins, Karl Smith-Byrne, Pietro Ferrari, Vivian Viallon, Antonio Agudo, Marc J Gunter, Catalina Bonet, Heinz Freisling, Robert Carreras-Torres
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引用次数: 0

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 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.

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: ∼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.

Funding: 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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背景:以往的脂肪增长预测模型还没有达到足够的预测能力,无法应用于临床。我们研究了传统因素和遗传因素是否能准确预测脂肪增长:方法:我们预测了中晚期成年人(基线年龄中位数为 55 岁)5 年体重指数(BMI)和腰臀比(WHR)比基线增长≥5% 的情况。对欧洲癌症与营养前瞻性调查(EPIC)队列中的 245,699 名参与者进行了比例危险模型拟合,以确定可靠的环境预测因素。利用来自独立队列(英国生物库)的基因权重,计算出了 5 种脂肪代用指标(体重指数、WHR 和三种体形表型 (PC))的多基因风险评分 (PRS)。环境和遗传模型在 29 953 名 EPIC 参与者中得到了验证:环境模型具有显著的预测能力(AUCBMI:0.69,95% CI:0.68-0.70;AUCWHR:0.75,95% CI:0.74-0.77)。WHR和PC1(总体肥胖)的遗传地理分布显示,北欧的易感性高于南欧。PRSs的预测能力为零(AUC:∼0.52),与环境模型结合后也没有改善。然而,BMI 和 PC1 的 PRSs 对从 20 岁自报 BMI 到基线观察(成年早期)的 BMI 增长有一定的预测能力(AUC:0.60-0.62):我们的研究表明,可将用于判别欧洲人脂肪增长风险较高的环境模型纳入标准预防方案中。PRSs在预测成年早期而非成年中后期的脂肪增加方面可能会发挥强有力的作用,这表明遗传因素在这一时期发挥着更重要的作用:法国国家癌症研究所(INCA_N°2019-176)1220、德国研究基金会(BA 5459/2-1)、卡洛斯三世健康研究所(Miguel Servet Program CP21/00058)。
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来源期刊
EBioMedicine
EBioMedicine Biochemistry, Genetics and Molecular Biology-General Biochemistry,Genetics and Molecular Biology
CiteScore
17.70
自引率
0.90%
发文量
579
审稿时长
5 weeks
期刊介绍: eBioMedicine is a comprehensive biomedical research journal that covers a wide range of studies that are relevant to human health. Our focus is on original research that explores the fundamental factors influencing human health and disease, including the discovery of new therapeutic targets and treatments, the identification of biomarkers and diagnostic tools, and the investigation and modification of disease pathways and mechanisms. We welcome studies from any biomedical discipline that contribute to our understanding of disease and aim to improve human health.
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