遗传倾向与环境因素之间的相互作用是复杂疾病发病机理的关键。
用来了解这种关系的一个很有希望的方法，将全基因组关联研究(GWAS)与对作为功能性中间体表现型的血液代谢物的分析综合在了一起。
这种方法的潜力由一个大型合作研究项目得到了展示，该项目综合了来自德国KORA F4和英国TwinsUK两个人群的研究数据。利用GWAS数据，再加上覆盖2 820人的60个生物化学通道的非定向“代谢组学”数据，研究人员识别出了37个与血液代谢物浓度相关的基因位点，其中25个对于一项GWAS来说有异常高的效应规模（effect size）。
这些关联让人们对很多以前所报告的关联（包括与心血管病和肾病、2-型糖尿病、癌症、痛风、静脉血栓和克罗恩病相关的关联）在功能方面有了新认识。
生物探索推荐英文摘要
Human metabolic individuality in biomedical and pharmaceutical research
Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10–60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn’s disease. The study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.
