CARTaGENE队列中行星健康饮食指数及其食物组与肥胖多基因风险之间的关系

IF 3.9 2区 医学 Q2 NUTRITION & DIETETICS Nutrition & Metabolism Pub Date : 2024-12-31 DOI:10.1186/s12986-024-00890-0
Guiomar Masip, Daiva E Nielsen
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引用次数: 0

摘要

背景:全球健康饮食由EAT-Lancet委员会提出,旨在促进人类和环境的可持续健康饮食。然而,很少有研究调查了行星健康饮食与肥胖遗传途径之间的关系。本研究的目的是评估遵守行星健康饮食指数(PHDI)是否介导或减缓了肥胖的遗传易感性。方法:研究对象为来自魁北克CARTaGENE生物库的7037名成年人(57%为女性,年龄55.6±7.7岁)。我们构建了由约200万个snp组成的身体质量指数(BMI)的一级多基因风险评分(PRS-Khera),并利用次级97个snp多基因风险评分(PRS-Locke)进行敏感性分析。PHDI是基于16种食物类别。采用一般线性模型来评估prs、行星健康饮食指数(PHDI)和构成PHDI的单个食物组之间对肥胖结局的主要影响关联。采用因果中介分析(CMA)评价中介效应和交互效应。所有模型都根据年龄、性别、遗传血统、社会人口统计学和生活方式变量(包括与饮食习惯相关的变量)进行了调整。结果:所有参与者的总体PHDI与BMI (β = - 0.11, 95%可信区间(CI): - 0.13, - 0.09)、腰围(WC) (β = - 0.12, 95% CI: - 0.14, - 0.10)和体脂% (β = - 0.10, 95% CI: - 0.12, - 0.08)呈负相关,但不介导或中度肥胖多基因风险。所有参与者的PRS-Khera与肥胖结局之间的关联部分由红肉摄入介导(中介效应BMI: 1.72%, p = 0.01;WC: 2.22%, p = 0.01;体脂%:2.14%,p = 0.01)。此外,在男性中,全谷物摄入在一定程度上介导了PRS-Khera与横断面结局之间的关联(BMI: 1.28%, p = 0.03;WC: 1.71%, p = 0.02;体脂%:2.19%,p = 0.02),纵向(BMI: 3.80%, p = 0.02;WC: 7.38%, p = 0.04),但在多次比较校正后,一些观察值减弱。结论:坚持PHDI与较低的BMI、WC和体脂率有关,而对肥胖的遗传易感性部分是由摄入红肉和全谷物介导的。植物性饮食的某些成分可能与肥胖遗传易感性的潜在机制有关。
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Relationships between the Planetary Health Diet Index, its food groups, and polygenic risk of obesity in the CARTaGENE cohort.

Background: The Planetary Health Diet, proposed by the EAT-Lancet Commission, seeks to promote a sustainable and healthy diet for both humans and the environment. However, few studies have investigated relationships between the Planetary Health Diet and the genetic pathway of obesity. The aim of this study was to assess whether adherence to a Planetary Health Diet Index (PHDI) mediated or moderated the genetic susceptibility to obesity.

Methods: Participants were 7,037 adults (57% females, aged 55.6 ± 7.7) from the Quebec CARTaGENE Biobank. We constructed a primary polygenic risk score (PRS-Khera) for body mass index (BMI) comprised of ~ 2 million SNPs and utilized a secondary 97 SNPs polygenic risk score (PRS-Locke) for sensitivity analyses. The PHDI was based on 16 food groups. General linear models were conducted to assess main effect associations between the PRSs, the Planetary Health Diet Index (PHDI), and the individual food groups that comprise the PHDI on obesity outcomes. Causal mediation analyses (CMA) were used to evaluate mediation and interaction effects. All models were adjusted for age, sex, genetic ancestry, socio-demographic, and lifestyle variables, including those associated with dietary habits.

Results: The overall PHDI was inversely associated with BMI (β = - 0.11, 95% confidence interval (CI): - 0.13, - 0.09), waist circumference (WC) (β = - 0.12, 95% CI: - 0.14, - 0.10), and body fat % (β = - 0.10, 95% CI: - 0.12, - 0.08) for all participants, but did not mediate or moderate obesity polygenic risk. Associations between the PRS-Khera and obesity outcomes in all participants were partly mediated by the intake of red meat (mediation effect BMI: 1.72%, p = 0.01; WC: 2.22%, p = 0.01; body fat %: 2.14%, p = 0.01). Moreover, among males, whole grains intake partly mediated the association between the PRS-Khera and outcomes cross-sectionally (BMI: 1.28%, p = 0.03; WC: 1.71%, p = 0.02; body fat %: 2.19%, p = 0.02) and longitudinally (BMI: 3.80%, p = 0.02; WC: 7.38%, p = 0.04), but some observations were attenuated upon correction for multiple comparisons.

Conclusions: PHDI adherence was associated with a lower BMI, WC, and body fat % and genetic susceptibility to obesity was partly mediated by the intake of red meat and whole grains. Some components of a plant-based diet could be implicated in mechanisms underlying genetic susceptibility to obesity.

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来源期刊
Nutrition & Metabolism
Nutrition & Metabolism 医学-营养学
CiteScore
8.40
自引率
0.00%
发文量
78
审稿时长
4-8 weeks
期刊介绍: Nutrition & Metabolism publishes studies with a clear focus on nutrition and metabolism with applications ranging from nutrition needs, exercise physiology, clinical and population studies, as well as the underlying mechanisms in these aspects. The areas of interest for Nutrition & Metabolism encompass studies in molecular nutrition in the context of obesity, diabetes, lipedemias, metabolic syndrome and exercise physiology. Manuscripts related to molecular, cellular and human metabolism, nutrient sensing and nutrient–gene interactions are also in interest, as are submissions that have employed new and innovative strategies like metabolomics/lipidomics or other omic-based biomarkers to predict nutritional status and metabolic diseases. Key areas we wish to encourage submissions from include: -how diet and specific nutrients interact with genes, proteins or metabolites to influence metabolic phenotypes and disease outcomes; -the role of epigenetic factors and the microbiome in the pathogenesis of metabolic diseases and their influence on metabolic responses to diet and food components; -how diet and other environmental factors affect epigenetics and microbiota; the extent to which genetic and nongenetic factors modify personal metabolic responses to diet and food compositions and the mechanisms involved; -how specific biologic networks and nutrient sensing mechanisms attribute to metabolic variability.
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