Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA
By J. Kettunen, A. Demirkan, P. Würtz, H. Draisma, T. Haller, R. Rawal, A. Vaarhorst, A. Kangas, L. Lyytikäinen, Matti Pirinen and 40 more. Nature Communications, 2016
691 citations recorded by the source corpus.
Genome-wide association studies have identified numerous loci linked with complex diseases, for which the molecular mechanisms remain largely unclear. Comprehensive molecular profiling of circulating metabolites captures highly heritable traits, which can help to uncover metabolic pathophysiology underlying established disease variants. We conduct an extended genome-wide association study of genetic influences on 123 circulating metabolic traits quantified by nuclear magnetic resonance metabolomics from up to 24,925 individuals and identify eight novel loci for amino acids, pyruvate and fatty acids. The LPA locus link with cardiovascular risk exemplifies how detailed metabolic profiling may inform underlying aetiology via extensive associations with very-low-density lipoprotein and triglyceride metabolism. Genetic fine mapping and Mendelian randomization uncover wide-spread causal effects of lipoprotein(a) on overall lipoprotein metabolism and we assess potential pleiotropic consequences of genetically elevated lipoprotein(a) on diverse morbidities via electronic health-care records. Our findings strengthen the argument for safe LPA-targeted intervention to reduce cardiovascular risk. Circulating metabolites reflect human health and disease. Here, Kettunen et al. perform a genome-wide association study on 123 circulating metabolic traits and identify novel genetic loci influencing systemic metabolism. They also link new molecular pathways with a known cardiovascular risk factor Lp(a).
Subfields: Cancer Research, Genetics, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/0c728c7740db1181b886aff382dfdbe665762f28
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Citations in the corpus
- Bayesian weighted Mendelian randomization for causal inference based on summary statistics (2018, methodology): “Besides the four global lipids in Data-A, Data-B, and Data-C, we further collected GWAS summary statistics, covering 126 metabolites (Kettunen et al., 2016) and 93 human complex traits.”
- Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: A multivariable Mendelian randomisation analysis (2020, methodology): “001 by the Global Lipids Genetics Consortium [40] (for LDL cholesterol, triglycerides and HDL cholesterol) or by Kettunen and colleagues [41] (for”
- The MR-Base platform supports systematic causal inference across the human phenome (2018, methodology): “, 2016) and metabolite (Shin et al., 2014; Kettunen et al., 2016) levels generate hundreds to thousands of independent associations for thousands of traits.”