Logo Logo
Help
Contact
Switch Language to German

Draisma, Harmen H. M.; Pool, Rene; Kobl, Michael; Jansen, Rick; Petersen, Ann-Kristin; Vaarhorst, Anika A. M.; Yet, Idil; Haller, Toomas; Demirkan, Ayse; Esko, Tonu; Zhu, Gu; Boehringer, Stefan; Beekman, Marian; Klinken, Jan Bert van; Roemisch-Margl, Werner; Prehn, Cornelia; Adamski, Jerzy; Craen, Anton J. M. de; Leeuwen, Elisabeth M. van; Amin, Najaf; Dharuri, Harish; Westra, Harm-Jan; Franke, Lude; Geus, Eco J. C. de; Hottenga, Jouke Jan; Willemsen, Gonneke; Henders, Anjali K.; Montgomery, Grant W.; Nyholt, Dale R.; Whitfield, John B.; Penninx, Brenda W.; Spector, Tim D.; Metspalu, Andres; Slagboom, P. Eline; Dijk, Ko Willems van; Hoen, Peter A. C. 't; Strauch, Konstantin; Martin, Nicholas G.; Ommen, Gert-Jan B. van; Illig, Thomas; Bell, Jordana T.; Mangino, Massimo; Suhre, Karsten; McCarthy, Mark I.; Gieger, Christian; Isaacs, Aaron; Duijn, Cornelia M. van and Boomsma, Dorret I. (2015): Genome-wide association study identifies novel genetic variants contributing to variation in blood metabolite levels. In: Nature Communications, Vol. 6, 7208 [PDF, 1MB]

[thumbnail of 10.1038_ncomms8208.pdf]
Preview
Download (1MB)

Abstract

Metabolites are small molecules involved in cellular metabolism, which can be detected in biological samples using metabolomic techniques. Here we present the results of genome-wide association and meta-analyses for variation in the blood serum levels of 129 metabolites as measured by the Biocrates metabolomic platform. In a discovery sample of 7, 478 individuals of European descent, we find 4, 068 genome-and metabolome-wide significant (Z-test, P<1.09 x 10(-9)) associations between single-nucleotide polymorphisms (SNPs) and metabolites, involving 59 independent SNPs and 85 metabolites. Five of the fifty-nine independent SNPs are new for serum metabolite levels, and were followed-up for replication in an independent sample (N = 1, 182). The novel SNPs are located in or near genes encoding metabolite transporter proteins or enzymes (SLC22A16, ARG1, AGPS and ACSL1) that have demonstrated biomedical or pharmaceutical importance. The further characterization of genetic influences on metabolic phenotypes is important for progress in biological and medical research.

Actions (login required)

View Item View Item