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

Janina S. Ried, So Youn Shin, Jan Krumsiek, Thomas Illig, Fabian J. Theis, Tim D. Spector, Jerzy Adamski, H. Erich Wichmann, K. Konstantin Strauch, Nicole Soranzo, Karsten Suhre, Christian Gieger

Research output: Contribution to journalArticle

15 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)5847-5857
Number of pages11
JournalHuman Molecular Genetics
Volume23
Issue number21
DOIs
Publication statusPublished - 1 Nov 2014
Externally publishedYes

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Phenotype
Serum
Genes
Genome
Genetic Loci
Genome-Wide Association Study
Single Nucleotide Polymorphism
Cohort Studies
Population

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics
  • Genetics(clinical)

Cite this

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

Novel genetic associations with serum level metabolites identified by phenotype set enrichment analyses. / Ried, Janina S.; Shin, So Youn; Krumsiek, Jan; Illig, Thomas; Theis, Fabian J.; Spector, Tim D.; Adamski, Jerzy; Wichmann, H. Erich; Strauch, K. Konstantin; Soranzo, Nicole; Suhre, Karsten; Gieger, Christian.

In: Human Molecular Genetics, Vol. 23, No. 21, 01.11.2014, p. 5847-5857.

Research output: Contribution to journalArticle

Ried, JS, Shin, SY, Krumsiek, J, Illig, T, Theis, FJ, Spector, TD, Adamski, J, Wichmann, HE, Strauch, KK, Soranzo, N, Suhre, K & Gieger, C 2014, 'Novel genetic associations with serum level metabolites identified by phenotype set enrichment analyses', Human Molecular Genetics, vol. 23, no. 21, pp. 5847-5857. https://doi.org/10.1093/hmg/ddu301
Ried, Janina S. ; Shin, So Youn ; Krumsiek, Jan ; Illig, Thomas ; Theis, Fabian J. ; Spector, Tim D. ; Adamski, Jerzy ; Wichmann, H. Erich ; Strauch, K. Konstantin ; Soranzo, Nicole ; Suhre, Karsten ; Gieger, Christian. / Novel genetic associations with serum level metabolites identified by phenotype set enrichment analyses. In: Human Molecular Genetics. 2014 ; Vol. 23, No. 21. pp. 5847-5857.
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