Novel genetic associations with serum level metabolites identified by phenotype set enrichment analyses

Ried JS, Shin SY, Krumsiek J, Illig T, Theis FJ, Spector TD, Adamski J, Wichmann HE, Strauch K, Soranzo N, Suhre K, Gieger C (2014)

Publication Type: Journal article

Publication year: 2014

Journal

Human Molecular Genetics Oxford University Press (OUP): Policy B - Oxford Open Option B

Book Volume: 23

Pages Range: 5847-5857

Journal Issue: 21

DOI: 10.1093/hmg/ddu301

Abstract

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 metabolitesof thesameor related pathways. Strategies that analyse several phenotypes in a combined waywere shown to be able to detect additional genetic loci. One of thosemethods 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.

Involved external institutions

Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (HMGU) / Helmholtz Munich DE Germany (DE) Wellcome Trust Sanger Institute - Genome Research Limited GB United Kingdom (GB) King’s College London GB United Kingdom (GB)

How to cite

APA:

Ried, J.S., Shin, S.-Y., Krumsiek, J., Illig, T., Theis, F.J., Spector, T.D.,... Gieger, C. (2014). Novel genetic associations with serum level metabolites identified by phenotype set enrichment analyses. Human Molecular Genetics, 23(21), 5847-5857. https://doi.org/10.1093/hmg/ddu301

MLA:

Ried, Janina S., et al. "Novel genetic associations with serum level metabolites identified by phenotype set enrichment analyses." Human Molecular Genetics 23.21 (2014): 5847-5857.

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