Centre for Genetic Origins of Health and Disease, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, Australia.
Faculty of Health Sciences, Curtin University, Perth, Australia.
Hum Genet. 2018 Jan;137(1):45-53. doi: 10.1007/s00439-017-1856-x. Epub 2017 Nov 27.
Over two billion adults are overweight or obese and therefore at an increased risk of cardiometabolic syndrome (CMS). Obesity-related anthropometric traits genetically correlated with CMS may provide insight into CMS aetiology. The aim of this study was to utilise an empirically derived genetic relatedness matrix to calculate heritabilities and genetic correlations between CMS and anthropometric traits to determine whether they share genetic risk factors (pleiotropy). We used genome-wide single nucleotide polymorphism (SNP) data on 4671 Busselton Health Study participants. Exploiting both known and unknown relatedness, empirical kinship probabilities were estimated using these SNP data. General linear mixed models implemented in SOLAR were used to estimate narrow-sense heritabilities (h ) and genetic correlations (r ) between 15 anthropometric and 9 CMS traits. Anthropometric traits were adjusted by body mass index (BMI) to determine whether the observed genetic correlation was independent of obesity. After adjustment for multiple testing, all CMS and anthropometric traits were significantly heritable (h range 0.18-0.57). We identified 50 significant genetic correlations (r range: - 0.37 to 0.75) between CMS and anthropometric traits. Five genetic correlations remained significant after adjustment for BMI [high density lipoprotein cholesterol (HDL-C) and waist-hip ratio; triglycerides and waist-hip ratio; triglycerides and waist-height ratio; non-HDL-C and waist-height ratio; insulin and iliac skinfold thickness]. This study provides evidence for the presence of potentially pleiotropic genes that affect both anthropometric and CMS traits, independently of obesity.
超过 20 亿成年人超重或肥胖,因此患心血管代谢综合征 (CMS) 的风险增加。与 CMS 遗传相关的肥胖相关人体测量特征可能有助于深入了解 CMS 的发病机制。本研究旨在利用经验衍生的遗传相关性矩阵来计算 CMS 与人体测量特征之间的遗传率和遗传相关性,以确定它们是否具有共同的遗传风险因素(多效性)。我们使用了 4671 名 Busselton 健康研究参与者的全基因组单核苷酸多态性 (SNP) 数据。利用这些 SNP 数据,利用已知和未知的相关性来估计经验亲缘关系概率。使用 SOLAR 中实现的广义线性混合模型来估计 15 个人体测量和 9 个 CMS 特征之间的狭义遗传率 (h) 和遗传相关性 (r)。对人体测量特征进行体重指数 (BMI) 调整,以确定观察到的遗传相关性是否独立于肥胖。经过多次测试调整后,所有 CMS 和人体测量特征均具有显著的遗传性 (h 范围为 0.18-0.57)。我们确定了 50 个 CMS 和人体测量特征之间具有显著遗传相关性 (r 范围:-0.37 至 0.75)。调整 BMI 后,仍有 5 个遗传相关性具有统计学意义 [高密度脂蛋白胆固醇 (HDL-C) 和腰臀比;甘油三酯和腰臀比;甘油三酯和腰高比;非高密度脂蛋白胆固醇和腰高比;胰岛素和髂皮褶厚度]。本研究为存在影响人体测量和 CMS 特征的潜在多效性基因提供了证据,这些基因独立于肥胖。