Data associated with "Metabolic reaction fluxes as amplifiers and buffers of risk alleles for coronary artery disease"

Abstract

Genome-wide association studies have identified thousands of variants associated with disease risk but the mechanism by which such variants contribute to disease remains largely unknown. Indeed, a major challenge is that variants do not act in isolation but rather in the framework of highly complex biological networks, such as the human metabolic network, which can amplify or buffer the effect of specific risk alleles on disease susceptibility. Here we use genetically predicted reaction fluxes to perform a systematic search for metabolic fluxes acting as buffers or amplifiers of coronary artery disease (CAD) risk alleles. Our analysis identifies 30 risk locus - reaction flux pairs with significant interaction on CAD susceptibility involving 18 individual reaction fluxes and 8 independent risk loci. Notably, many of these reactions are linked to processes with putative roles in the disease such as the metabolism of inflammatory mediators. In summary, this work establishes proof of concept that biochemical reaction fluxes can have non-additive effects with risk alleles and provides novel insights into the interplay between metabolism and genetic variation on disease susceptibility.

Description

This dataset provides summary statistics for the interaction effects between risk allele dosage and reaction fluxes on CAD and myocardial infarction (MI) risk in UK Biobank participants of European genetic ancestries. We use two complementary methods to evaluate buffering/amplification effects. First, we test for a significant interaction effect size between risk allele dosage and reaction flux value using a Cox proportional-hazards model for disease risk. Second, for each pair of reaction flux values and risk alleles, we estimate the effect of reaction flux value on disease risk within each dosage of the risk allele (0, 1, or 2), and Welch's ANOVA is then used to evaluate the significance of the differences between effect sizes across risk allele dosages. We consider that there is a buffering/amplification of disease susceptibility between a variant and a reaction flux when it is statistically significant with both approaches.

To facilitate the exploration of these results, we provide two interactive HTML files that allow users to visualize and query all interactions with P < 0.001 for CAD and MI risk.  

Additional files with reaction and variant annotation are also provided.