Ried Janina S, Shin So-Youn, Krumsiek Jan, Illig Thomas, Theis Fabian J, Spector Tim D, Adamski Jerzy, Wichmann H-Erich, Strauch Konstantin, Soranzo Nicole, Suhre Karsten, Gieger Christian
Institute of Genetic Epidemiology,
Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, CB10 1HH Hinxton, UK, MRC Integrative Epidemiology Unit, University of Bristol, BS8 2BN Bristol, UK.
Hum Mol Genet. 2014 Nov 1;23(21):5847-57. doi: 10.1093/hmg/ddu301. Epub 2014 Jun 13.
Availability of standardized metabolite panels and genome-wide single-nucleotide polymorphism data endorse the comprehensive analysis of gene-metabolite association. Currently, many studies use genome-wide association analysis to investigate the genetic effects on single metabolites (mGWAS) separately. Such studies have identified several loci that are associated not only with one but with multiple metabolites, facilitated by the fact that metabolite panels often include metabolites of the same or related pathways. Strategies that analyse several phenotypes in a combined way were shown to be able to detect additional genetic loci. One of those methods is the phenotype set enrichment analysis (PSEA) that tests sets of metabolites for enrichment at genes. Here we applied PSEA on two different panels of serum metabolites together with genome-wide data. All analyses were performed as a two-step identification-validation approach, using data from the population-based KORA cohort and the TwinsUK study. In addition to confirming genes that were already known from mGWAS, we were able to identify and validate 12 new genes. Knowledge about gene function was supported by the enriched metabolite sets. For loci with unknown gene functions, the results suggest a function that is interrelated with the metabolites, and hint at the underlying pathways.
标准化代谢物面板和全基因组单核苷酸多态性数据的可得性支持了基因-代谢物关联的综合分析。目前，许多研究分别使用全基因组关联分析来研究对单个代谢物的遗传效应（代谢物全基因组关联研究，mGWAS）。这类研究已经确定了几个不仅与一种代谢物而且与多种代谢物相关的基因座，代谢物面板通常包含相同或相关途径的代谢物这一事实促进了此类研究。以组合方式分析几种表型的策略已被证明能够检测到更多的遗传基因座。其中一种方法是表型集富集分析（PSEA），它测试代谢物集在基因处的富集情况。在这里，我们将PSEA应用于两个不同的血清代谢物面板以及全基因组数据。所有分析均采用两步鉴定-验证方法，使用基于人群的KORA队列和双胞胎英国研究的数据。除了确认mGWAS中已有的基因外，我们还能够鉴定并验证12个新基因。关于基因功能的知识得到了富集代谢物集的支持。对于基因功能未知的基因座，结果表明其功能与代谢物相关，并暗示了潜在的途径。
