A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context
A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context
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DOI：
10.1038/s41467-019-12703-7
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发表时间：
2019-10-21
影响因子：
16.6
通讯作者：
Aschard, Hugues
中科院分区：
文献类型：
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作者：
Gallois, Apolline;Mefford, Joel;Aschard, Hugues
代谢物的遗传研究已经确定了数千种变异，其中许多与下游代谢和致肥性疾病有关。然而，这些研究依赖于单变量分析，降低了能力并限制了对特定情境的理解。在这里，我们的目标是通过利用芬兰男性代谢综合征（METSIM）队列提供代谢物遗传基础的综合视角，这是一个独特的遗传资源，包含代谢测量，主要是脂质，跨越不同的时间点以及他汀类药物使用的信息。通过应用多表型研究（CMS）方法的协变量，我们将有效样本量平均增加了两倍，确定了588个显著的snp代谢物关联，其中包括228个新的关联。我们的分析确定了少数主要的代谢调节基因，平衡了几十种代谢物水平的相对比例。我们进一步确定了代谢水平随时间变化的相关性，以及在主代谢调节因子和全基因组水平上与他汀类药物的遗传相互作用。
Genetic studies of metabolites have identified thousands of variants, many of which are associated with downstream metabolic and obesogenic disorders. However, these studies have relied on univariate analyses, reducing power and limiting context-specific understanding. Here we aim to provide an integrated perspective of the genetic basis of metabolites by leveraging the Finnish Metabolic Syndrome In Men (METSIM) cohort, a unique genetic resource which contains metabolic measurements, mostly lipids, across distinct time points as well as information on statin usage. We increase effective sample size by an average of two-fold by applying the Covariates for Multi-phenotype Studies (CMS) approach, identifying 588 significant SNP-metabolite associations, including 228 new associations. Our analysis pinpoints a small number of master metabolic regulator genes, balancing the relative proportion of dozens of metabolite levels. We further identify associations to changes in metabolic levels across time as well as genetic interactions with statin at both the master metabolic regulator and genome-wide level.