Integrative pathway analysis of a genome-wide association study of VO 2max response to exercise training

Sujoy Ghosh, Juan C. Vivar, Mark A. Sarzynski, Yun Ju Sung, James A. Timmons, Claude Bouchard, Tuomo Rankinen

Research output: Contribution to journalArticle

30 Scopus citations

Abstract

We previously reported the findings from a genome-wide association study of the response of maximal oxygen uptake (VO2max) to an exercise program. Here we follow up on these results to generate hypotheses on genes, pathways, and systems involved in the ability to respond to exercise training. A systems biology approach can help us better establish a comprehensive physiological description of what underlies V O2maxtrainability. The primary material for this exploration was the individual singlenucleotide polymorphism (SNP), SNP-gene mapping, and statistical significance levels. We aimed to generate novel hypotheses through analyses that go beyond statistical association of single-locus markers. This was accomplished through three complementary approaches: 1) building de novo evidence of gene candidacy through informaticsdriven literature mining; 2) aggregating evidence from statistical associations to link variant enrichment in biological pathways to VO 2max trainability; and 3) predicting possible consequences of variants residing in the pathways of interest. We started with candidate gene prioritization followed by pathway analysis focused on overrepresentation analysis and gene set enrichment analysis. Subsequently, leads were followed using in silico analysis of predicted SNP functions. Pathways related to cellular energetics (pantothenate and CoA biosynthesis; PPAR signaling) and immune functions (complement and coagulation cascades) had the highest levels of SNP burden. In particular, long-chain fatty acid transport and fatty acid oxidation genes and sequence variants were found to influence differences in VO2max trainability. Together, these methods allow for the hypothesisdriven ranking and prioritization of genes and pathways for future experimental testing and validation.

Original languageEnglish
Pages (from-to)1343-1359
Number of pages17
JournalJournal of Applied Physiology
Volume115
Issue number9
DOIs
StatePublished - Nov 1 2013

Keywords

  • Bioinformatics
  • Endurance training
  • Genotypes
  • Pathway analysis
  • Single-nucleotide polymorphisms

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