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Genetics Meets Metabolomics: A Genome-Wide Association Study of Metabolite Profiles in Human Serum

机译:遗传学与代谢组学的结合:人血清中代谢物谱的全基因组关联研究

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摘要

The rapidly evolving field of metabolomics aims at a comprehensive measurement of ideally all endogenous metabolites in a cell or body fluid. It thereby provides a functional readout of the physiological state of the human body. Genetic variants that associate with changes in the homeostasis of key lipids, carbohydrates, or amino acids are not only expected to display much larger effect sizes due to their direct involvement in metabolite conversion modification, but should also provide access to the biochemical context of such variations, in particular when enzyme coding genes are concerned. To test this hypothesis, we conducted what is, to the best of our knowledge, the first GWA study with metabolomics based on the quantitative measurement of 363 metabolites in serum of 284 male participants of the KORA study. We found associations of frequent single nucleotide polymorphisms (SNPs) with considerable differences in the metabolic homeostasis of the human body, explaining up to 12% of the observed variance. Using ratios of certain metabolite concentrations as a proxy for enzymatic activity, up to 28% of the variance can be explained (p-values 10−16 to 10−21). We identified four genetic variants in genes coding for enzymes (FADS1, LIPC, SCAD, MCAD) where the corresponding metabolic phenotype (metabotype) clearly matches the biochemical pathways in which these enzymes are active. Our results suggest that common genetic polymorphisms induce major differentiations in the metabolic make-up of the human population. This may lead to a novel approach to personalized health care based on a combination of genotyping and metabolic characterization. These genetically determined metabotypes may subscribe the risk for a certain medical phenotype, the response to a given drug treatment, or the reaction to a nutritional intervention or environmental challenge.
机译:代谢组学领域的快速发展旨在全面测量细胞或体液中理想的所有内源性代谢产物。因此,它提供了人体生理状态的功能读数。与关键脂质,碳水化合物或氨基酸的体内稳态变化相关的遗传变异不仅因其直接参与代谢物转化修饰而预期显示更大的效应,而且还应提供此类变异的生化背景,尤其是在涉及酶编码基因时。为了检验这一假设,我们以我们所知,进行了首次代谢组学GWA研究,该研究基于KORA研究的284名男性参与者血清中363种代谢物的定量测量。我们发现频繁的单核苷酸多态性(SNP)与人体代谢稳态中的显着差异之间的关联,解释了高达12%的观察到的差异。使用某些代谢物浓度的比率作为酶活性的代表,可以解释高达28%的方差(p值10-16至10-21)。我们在编码酶的基因(FADS1,LIPC,SCAD,MCAD)中鉴定了四种遗传变异,其中相应的代谢表型(代谢型)与这些酶活跃的生化途径明显匹配。我们的结果表明,常见的遗传多态性会导致人类代谢组成的主要差异。这可能导致基于基因分型和代谢特征结合的个性化医疗保健的新方法。这些遗传确定的代谢型可能会引起某些医学表型的风险,对给定药物治疗的反应或对营养干预或环境挑战的反应。

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