Integration of Genome-Wide SNP Data and Gene-Expression Profiles Reveals Six Novel Loci and Regulatory Mechanisms for Amino Acids and Acylcarnitines in Whole Blood.

• Main Authors: Ralph Burkhardt, Holger Kirsten, Frank Beutner, Lesca M Holdt, Arnd Gross, Andrej Teren, Anke Tönjes, Susen Becker, Knut Krohn, Peter Kovacs, Michael Stumvoll, Daniel Teupser, Joachim Thiery, Uta Ceglarek, Markus Scholz
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2015-09-01
• Series: PLoS Genetics
• Online Access: http://europepmc.org/articles/PMC4581711?pdf=render

Profiling amino acids and acylcarnitines in whole blood spots is a powerful tool in the laboratory diagnosis of several inborn errors of metabolism. Emerging data suggests that altered blood levels of amino acids and acylcarnitines are also associated with common metabolic diseases in adults. Thus, the identification of common genetic determinants for blood metabolites might shed light on pathways contributing to human physiology and common diseases. We applied a targeted mass-spectrometry-based method to analyze whole blood concentrations of 96 amino acids, acylcarnitines and pathway associated metabolite ratios in a Central European cohort of 2,107 adults and performed genome-wide association (GWA) to identify genetic modifiers of metabolite concentrations. We discovered and replicated six novel loci associated with blood levels of total acylcarnitine, arginine (both on chromosome 6; rs12210538, rs17657775), propionylcarnitine (chromosome 10; rs12779637), 2-hydroxyisovalerylcarnitine (chromosome 21; rs1571700), stearoylcarnitine (chromosome 1; rs3811444), and aspartic acid traits (chromosome 8; rs750472). Based on an integrative analysis of expression quantitative trait loci in blood mononuclear cells and correlations between gene expressions and metabolite levels, we provide evidence for putative causative genes: SLC22A16 for total acylcarnitines, ARG1 for arginine, HLCS for 2-hydroxyisovalerylcarnitine, JAM3 for stearoylcarnitine via a trans-effect at chromosome 1, and PPP1R16A for aspartic acid traits. Further, we report replication and provide additional functional evidence for ten loci that have previously been published for metabolites measured in plasma, serum or urine. In conclusion, our integrative analysis of SNP, gene-expression and metabolite data points to novel genetic factors that may be involved in the regulation of human metabolism. At several loci, we provide evidence for metabolite regulation via gene-expression and observed overlaps with GWAS loci for common diseases. These results form a strong rationale for subsequent functional and disease-related studies.