These authors contributed equally to this work.
A Genome-Wide Assessment of Variability in Human Serum Metabolism
Article first published online: 18 FEB 2013
© 2012 Wiley Periodicals, Inc.
Volume 34, Issue 3, pages 515–524, March 2013
How to Cite
Hong, M.-G., Karlsson, R., Magnusson, P. K. E., Lewis, M. R., Isaacs, W., Zheng, L. S., Xu, J., Grönberg, H., Ingelsson, E., Pawitan, Y., Broeckling, C., Prenni, J. E., Wiklund, F. and Prince, J. A. (2013), A Genome-Wide Assessment of Variability in Human Serum Metabolism. Hum. Mutat., 34: 515–524. doi: 10.1002/humu.22267
Communicated by Stephen J. Chanock
Contract grant sponsors: U.S. Army (W81XWH-10–1-0323); the Swedish Medical Research Council (2007/2722).
- Issue published online: 18 FEB 2013
- Article first published online: 18 FEB 2013
- Accepted manuscript online: 24 DEC 2012 12:05AM EST
- Manuscript Accepted: 6 DEC 2012
- Manuscript Received: 9 MAR 2012
- U.S. Army. Grant Number: W81XWH-10–1-0323
- Swedish Medical Research Council. Grant Number: 2007/2722
The study of the genetic regulation of metabolism in human serum samples can contribute to a better understanding of the intermediate biological steps that lead from polymorphism to disease. Here, we conducted a genome-wide association study (GWAS) to discover metabolic quantitative trait loci (mQTLs) utilizing samples from a study of prostate cancer in Swedish men, consisting of 402 individuals (214 cases and 188 controls) in a discovery set and 489 case-only samples in a replication set. A global nontargeted metabolite profiling approach was utilized resulting in the detection of 6,138 molecular features followed by targeted identification of associated metabolites. Seven replicating loci were identified (PYROXD2, FADS1, PON1, CYP4F2, UGT1A8, ACADL, and LIPC) with associated sequence variants contributing significantly to trait variance for one or more metabolites (P = 10−13–10−91). Regional mQTL enrichment analyses implicated two loci that included FADS1 and a novel locus near PDGFC. Biological pathway analysis implicated ACADM, ACADS, ACAD8, ACAD10, ACAD11, and ACOXL, reflecting significant enrichment of genes with acyl-CoA dehydrogenase activity. mQTL SNPs and mQTL-harboring genes were over-represented across GWASs conducted to date, suggesting that these data may have utility in tracing the molecular basis of some complex disease associations.