新陈代谢情况的不同会导致一些人更易患上糖尿病之类的疾病，这也解释了饮食、锻炼、药物对不同病人产生的结果各不相同的原因。
 
研究人员共扫描了284个人的基因，发现FADS1、LIPC、SCAD和MCAD这4个基因能决定人体的新陈代谢速度。
 
德国慕尼黑的黑尔姆霍尔茨中心研究人员卡斯滕·祖雷说：“这些基因似乎与新陈代谢有关，或者能对新陈代谢起重要作用。”
 
祖雷说，这方面的可能为更个性化的护理开辟了道路，医生可以根据病人的基因构成来研究他们的新陈代谢情况，再根据这些情况决定如何进行治疗。这对于治疗与新陈代谢有关的疾病，如冠状动脉疾病和肥胖可能尤其有效。
 
祖雷和同事在《公共科学图书馆·遗传学》（PLoS Genetics）月刊上撰文说：“这些发现使我们可以根据基因和新陈代谢两方面的特点来作出判断，从而带领我们向个性化护理和营养供给迈进。”

PLoS Genet 4(11): e1000282. doi:10.1371/journal.pgen.1000282

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

Christian Gieger1,2, Ludwig Geistlinger1, Elisabeth Altmaier3,4, Martin Hrabé de Angelis5,6, Florian Kronenberg7, Thomas Meitinger8,9, Hans-Werner Mewes3,10, H.-Erich Wichmann1,2, Klaus M. Weinberger11, Jerzy Adamski5,6, Thomas Illig1, Karsten Suhre3,4*

1 Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany,
2 Institute of Medical Informatics, Biometry, and Epidemiology, Ludwig-Maximilians-Universit?t, Munich, Germany,
3 Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany,
4 Faculty of Biology, Ludwig-Maximilians-Universit?t, Planegg-Martinsried, Germany,
5 Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany,
6 Institute of Experimental Genetics, Life and Food Science Center Weihenstephan, Technische Universit?t München, Freising-Weihenstephan, Germany,
7 Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, Innsbruck, Austria,
8 Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany,
9 Institute of Human Genetics, Klinikum rechts der Isar, Technische Universit?t München, Munich, Germany,
10 Department of Genome-Oriented Bioinformatics, Life and Food Science Center Weihenstephan, Technische Universit?t München, Freising-Weihenstephan, Germany,
11 Biocrates Life Sciences AG, Innsbruck, Austria

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.