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

Relationships between the Planetary Health Diet Index, its food groups, and polygenic risk of obesity in the CARTaGENE cohort.

作者信息

Masip Guiomar, Nielsen Daiva E

机构信息

School of Human Nutrition, McGill University, 21111 Lakeshore Road, Sainte-Anne-de-Bellevue, QC, H9X 3V9, Canada.

GENUD (Growth, Exercise, Nutrition and Development) Research Group, Facultad de Ciencias de la Salud, Universidad de Zaragoza, Instituto Agroalimentario de Aragón (IA2), Instituto de Investigación Sanitaria de Aragón (IISA), Zaragoza, Spain.

出版信息

Nutr Metab (Lond). 2024 Dec 31;21(1):116. doi: 10.1186/s12986-024-00890-0.

DOI:10.1186/s12986-024-00890-0
PMID:39741271
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11689624/
Abstract

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.

摘要

背景

由EAT-柳叶刀委员会提出的“行星健康饮食”旨在促进对人类和环境均可持续且健康的饮食。然而,很少有研究调查“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循“行星健康饮食指数”(PHDI)是否介导或调节了肥胖的遗传易感性。

方法

研究参与者为来自魁北克CARTaGENE生物库的7037名成年人(57%为女性,年龄55.6±7.7岁)。我们构建了一个由约200万个单核苷酸多态性(SNP)组成的体重指数(BMI)原发性多基因风险评分(PRS-Khera),并使用一个包含97个SNP的继发性多基因风险评分(PRS-Locke)进行敏感性分析。PHDI基于16个食物组。采用一般线性模型评估PRS、“行星健康饮食指数”(PHDI)以及构成PHDI的各个食物组与肥胖结局之间的主要效应关联。采用因果中介分析(CMA)评估中介效应和交互效应。所有模型均对年龄、性别、遗传血统、社会人口统计学和生活方式变量进行了调整,包括与饮食习惯相关的变量。

结果

总体PHDI与所有参与者的BMI(β=-0.11,95%置信区间(CI):-0.13,-0.09)、腰围(WC)(β=-0.12,95%CI:-0.14,-0.10)和体脂百分比(β=-0.10,95%CI:-0.12,-0.08)呈负相关,但并未介导或调节肥胖多基因风险。所有参与者中,PRS-Khera与肥胖结局之间的关联部分由红肉摄入量介导(中介效应BMI:1.72%,p=0.01;WC:2.22%,p=0.01;体脂百分比:2.14%,p=0.01)。此外,在男性中,全谷物摄入量部分介导了PRS-Khera与横断面结局(BMI:1.28%,p=0.03;WC:1.71%,p=0.02;体脂百分比:2.19%,p=0.02)以及纵向结局(BMI:3.80%,p=0.02;WC:7.38%,p=0.04)之间的关联,但在进行多重比较校正后,一些观察结果有所减弱。

结论

遵循PHDI与较低的BMI、WC和体脂百分比相关,肥胖的遗传易感性部分由红肉和全谷物的摄入量介导。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。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/01ce/11689624/24e63d94dd51/12986_2024_890_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/01ce/11689624/ecdab568f61b/12986_2024_890_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/01ce/11689624/24e63d94dd51/12986_2024_890_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/01ce/11689624/ecdab568f61b/12986_2024_890_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/01ce/11689624/24e63d94dd51/12986_2024_890_Fig2_HTML.jpg

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