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. 2012;8(8):e1002907.
doi: 10.1371/journal.pgen.1002907. Epub 2012 Aug 16.

Novel Loci for Metabolic Networks and Multi-Tissue Expression Studies Reveal Genes for Atherosclerosis

Free PMC article

Novel Loci for Metabolic Networks and Multi-Tissue Expression Studies Reveal Genes for Atherosclerosis

Michael Inouye et al. PLoS Genet. .
Free PMC article


Association testing of multiple correlated phenotypes offers better power than univariate analysis of single traits. We analyzed 6,600 individuals from two population-based cohorts with both genome-wide SNP data and serum metabolomic profiles. From the observed correlation structure of 130 metabolites measured by nuclear magnetic resonance, we identified 11 metabolic networks and performed a multivariate genome-wide association analysis. We identified 34 genomic loci at genome-wide significance, of which 7 are novel. In comparison to univariate tests, multivariate association analysis identified nearly twice as many significant associations in total. Multi-tissue gene expression studies identified variants in our top loci, SERPINA1 and AQP9, as eQTLs and showed that SERPINA1 and AQP9 expression in human blood was associated with metabolites from their corresponding metabolic networks. Finally, liver expression of AQP9 was associated with atherosclerotic lesion area in mice, and in human arterial tissue both SERPINA1 and AQP9 were shown to be upregulated (6.3-fold and 4.6-fold, respectively) in atherosclerotic plaques. Our study illustrates the power of multi-phenotype GWAS and highlights candidate genes for atherosclerosis.

Conflict of interest statement

The authors have declared that no competing interests exist.


Figure 1
Figure 1. Overview of the study design.
Figure 2
Figure 2. Serum metabolic networks.
A Pearson correlation matrix of serum metabolites across both YFS and NFBC66 cohorts was hierarchically clustered and the resulting heatmap and dendrogram are presented here with red indicating high positive correlation, blue high negative correlation, and white no correlation. Clusters of tightly correlated metabolites, metabolic networks, are labeled 1–11.
Figure 3
Figure 3. Associations detected between genomic loci and metabolic networks.
A Venn diagram showing the number of associations between all genomic loci and metabolic networks stratified by joint multivariate and univariate analysis (for univariate, at least one metabolite from a network need be associated).
Figure 4
Figure 4. Connecting genetic variation, gene expression, metabolites, and atherosclerosis for SERPINA1 and AQP9.
(a) Boxplots show SNPs associated with metabolic networks are also cis eQTLs for SERPINA1 (human blood and liver) and AQP9 (human liver). Boxplots consist of median log2-normalised expression for each genotype with first and third quartiles designated by box edges. Whiskers extend to +/−1.5 times interquartile range. (b) Human blood expression of SERPINA1 and AQP9 was associated with metabolites derived from the same metabolic networks as their corresponding genetic variants. Edge widths are proportional to the strength of association (P value). (c) Liver expression of AQP9 (but not SERPINA1) in mice on a hyperlipidemic APOE −/− background showed significant positive association with aortic lesion area. (d) Boxplots for log2-normalised expression of SERPINA1 and AQP9 in healthy human arterial tissue versus that for atherosclerotic plaques.

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