Associations between body mass index-related genetic variants and adult body composition: The Fenland cohort study.
Associations between body mass index-related genetic variants and adult body composition: The Fenland cohort study.
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DOI：
10.1038/ijo.2017.11
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发表时间：
2017-04
期刊：
影响因子：
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通讯作者：
Ong KK
中科院分区：
文献类型：
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作者：
Clifton EA;Day FR;De Lucia Rolfe E;Forouhi NG;Brage S;Griffin SJ;Wareham NJ;Ong KK
身体质量指数（BMI）是肥胖的替代指标，但不能区分脂肪和瘦肉或骨量。BMI的遗传决定因素被认为主要影响肥胖，但这尚未得到证实。在这里，我们研究了BMI相关的遗传变异与成人身体组成之间的关联。在来自Fenland研究的9667名年龄在29-64岁之间的成年人中，计算每个人的BMI遗传风险评分（BMI-GRS），作为96个报告的BMI相关变异体中BMI增加等位基因的加权和。通过DXA扫描估计的BMI-GRS和身体成分之间的关联，分别按性别使用年龄调整的线性回归模型进行检查。BMI-GRS与所有脂肪、瘦肉和骨骼变量呈正相关。在整个身体区域，观察到肥胖变量的最大程度的关联，例如，对于BMI-GRS预测BMI的每个标准差（SD）增加，我们观察到0.90 SD（95% CI：0.71，1.09）男性总脂肪量增加（P=3.75×10−21），女性增加0.96 SD（95% CI：0.77，1.16）（P=6.12×10−22）。观察到中等程度的关联与瘦变量，例如总瘦体重：男性：0.68 SD（95% CI：0.49，0.86）（P=1.91×10−12）;女性：0.85 SD（95% CI：0.65，1.04）（P=2.66×10−17），骨变量（如总骨量）的幅度较低：男性：0.39 SD（95% CI：0.20，0.58）（P=5.69×10−5）;女性：0.45 SD（95% CI：0.26，0.65）（P=3.96×10−6）。观察到28个SNP与BMI名义上显著相关。所有28个与脂肪量呈正相关，13个显示出脂肪特异性效应。在成年人中，遗传易感性升高的BMI影响肥胖超过瘦或骨量。这反映了BMI和身体成分之间的联系。BMI-GRS可用于模拟测量的BMI和肥胖对健康和其他结果的影响。
Body mass index (BMI) is a surrogate measure of adiposity but does not distinguish fat from lean or bone mass. The genetic determinants of BMI are thought to predominantly influence adiposity but this has not been confirmed. Here we characterise the association between BMI-related genetic variants and body composition in adults. Among 9667 adults aged 29-64 years from the Fenland study, a genetic risk score for BMI (BMI-GRS) was calculated for each individual as the weighted sum of BMI-increasing alleles across 96 reported BMI-related variants. Associations between the BMI-GRS and body composition, estimated by DXA scans, were examined using age-adjusted linear regression models, separately by sex. The BMI-GRS was positively associated with all fat, lean and bone variables. Across body regions, associations of the greatest magnitude were observed for adiposity variables e.g. for each standard deviation (SD) increase in BMI-GRS predicted BMI, we observed a 0.90 SD (95% CI: 0.71, 1.09) increase in total fat mass for men (P=3.75×10−21) and a 0.96 SD (95% CI: 0.77, 1.16) increase for women (P=6.12×10−22). Associations of intermediate magnitude were observed with lean variables e.g. total lean mass: men: 0.68 SD (95% CI: 0.49, 0.86) (P=1.91×10−12); women: 0.85 SD (95% CI: 0.65, 1.04) (P=2.66×10−17) and of a lower magnitude with bone variables e.g. total bone mass: men: 0.39 SD (95% CI: 0.20, 0.58) (P=5.69×10−5); women: 0.45 SD (95% CI: 0.26, 0.65) (P=3.96×10−6). Nominally significant associations with BMI were observed for 28 SNPs. All 28 were positively associated with fat mass and 13 showed adipose-specific effects. In adults, genetic susceptibility to elevated BMI influences adiposity more than lean or bone mass. This mirrors the association between BMI and body composition. The BMI-GRS can be used to model the effects of measured BMI and adiposity on health and other outcomes.