A1 Refereed original research article in a scientific journal

Detailed metabolic and genetic characterization reveals new associations for 30 known lipid loci




AuthorsTukiainen T, Kettunen J, Kangas AJ, Lyytikainen LP, Soininen P, Sarin AP, Tikkanen E, O'Reilly PF, Savolainen MJ, Kaski K, Pouta A, Jula A, Lehtimaki T, Kahonen M, Viikari J, Taskinen MR, Jauhiainen M, Eriksson JG, Raitakari O, Salomaa V, Jarvelin MR, Perola M, Palotie A, Ala-Korpela M, Ripatti S

PublisherOXFORD UNIV PRESS

Publication year2012

JournalHuman Molecular Genetics

Journal name in sourceHUMAN MOLECULAR GENETICS

Journal acronymHUM MOL GENET

Number in series6

Volume21

Issue6

First page 1444

Last page1455

Number of pages12

ISSN0964-6906

DOIhttps://doi.org/10.1093/hmg/ddr581


Abstract
Almost 100 genetic loci are known to affect serum cholesterol and triglyceride levels. For many of these loci, the biological function and causal variants remain unknown. We performed an association analysis of the reported 95 lipid loci against 216 metabolite measures, including 95 measurements on lipids and lipoprotein subclasses, obtained via serum nuclear magnetic resonance metabolomics and four enzymatic lipid traits in 8330 individuals from Finland. The genetic variation in the loci was investigated using a dense set of 440 807 directly genotyped and imputed variants around the previously identified lead single nucleotide polymorphisms (SNPs). For 30 of the 95 loci, we identified new metabolic or genetic associations (P 5 10(8)). In the majority of the loci, the strongest association was to a more specific metabolite measure than the enzymatic lipids. In four loci, the smallest high-density lipoprotein measures showed effects opposite to the larger ones, and 14 loci had associations beyond the individual lipoprotein measures. In 27 loci, we identified SNPs with a stronger association than the previously reported markers and 12 loci harboured multiple, statistically independent variants. Our data show considerable diversity in association patterns between the loci originally identified through associations with enzymatic lipid measures and reveal association profiles of far greater detail than from routine clinical lipid measures. Additionally, a dense marker set and a homogeneous population allow for detailed characterization of the genetic association signals to a resolution exceeding that achieved so far. Further understanding of the rich variability in genetic effects on metabolites provides insights into the biological processes modifying lipid levels.



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