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
Human metabolite levels differ between individuals due to environmental and genetic factors. In the present work, we analyzed whole blood levels of amino acids and acylcarnitines, reflecting disease relevant metabolic pathways, in a cohort of 2,107 individuals. We then performed a genome wide association analysis to discover genetic variants influencing metabolism. Thereby, we discovered six novel regions in the genome and confirmed ten regions previously found to be associated with metabolites in plasma, serum or urine. Subsequently, we analyzed whether these variants regulate gene-expression in peripheral mononuclear cells and at several loci we identified novel causal relations between SNPs, gene-expression and metabolite levels. These findings help explaining the functional mechanisms by which associated genetic variants regulate metabolism. Finally, several SNPs associated with blood metabolites in our study overlap with previously identified loci for human diseases (e.g. kidney disease), suggesting a shared genetic basis or pathomechanisms involving metabolic alterations. The identified loci are strong candidates for future functional studies directed to understand human metabolism and pathogenesis of related diseases.
Vyšlo v časopise:
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. PLoS Genet 11(9): e32767. doi:10.1371/journal.pgen.1005510
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pgen.1005510
Souhrn
Human metabolite levels differ between individuals due to environmental and genetic factors. In the present work, we analyzed whole blood levels of amino acids and acylcarnitines, reflecting disease relevant metabolic pathways, in a cohort of 2,107 individuals. We then performed a genome wide association analysis to discover genetic variants influencing metabolism. Thereby, we discovered six novel regions in the genome and confirmed ten regions previously found to be associated with metabolites in plasma, serum or urine. Subsequently, we analyzed whether these variants regulate gene-expression in peripheral mononuclear cells and at several loci we identified novel causal relations between SNPs, gene-expression and metabolite levels. These findings help explaining the functional mechanisms by which associated genetic variants regulate metabolism. Finally, several SNPs associated with blood metabolites in our study overlap with previously identified loci for human diseases (e.g. kidney disease), suggesting a shared genetic basis or pathomechanisms involving metabolic alterations. The identified loci are strong candidates for future functional studies directed to understand human metabolism and pathogenesis of related diseases.
Zdroje
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