Apr 13, 2016

Network-based metabolite ratios for an improved functional characterization of genome-wide association study results

BioRxiv : the Preprint Server for Biology
Jan KrumsiekFabian J Theis

Abstract

Genome-wide association studies (GWAS) with metabolite ratios as quantitative traits have successfully deepened our understanding of the complex relationship between genetic variants and metabolic phenotypes. Usually all ratio combinations are selected for association tests. However, with more metabolites being detectable, the quadratic increase of the ratio number becomes challenging from a statistical, computational and interpretational point-of-view. Therefore methods which select biologically meaningful ratios are required. We here present a network-based approach by selecting only closely connected metabolites in a given metabolic network. The feasibility of this approach was tested on in silico data derived from simulated reaction networks. Especially for small effect sizes, network-based metabolite ratios (NBRs) improved the metabolite-based prediction accuracy of genetically-influenced reactions compared to the 'all ratios' approach. Evaluating the NBR approach on published GWAS association results, we compared reported 'all ratio'-SNP hits with results obtained by selecting only NBRs as candidates for association tests. Input networks for NBR selection were derived from public pathway databases or reconstructed from me...Continue Reading

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Mentioned in this Paper

Metabolic Process, Cellular
Genome-Wide Association Study
Study
Biochemical Pathway
Metabolic Networks
NBR-A isoenzyme
Simulation
Analysis
Metabolite
Gene Mutant

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