Haplotypes and SNPs in 13 lipid-relevant genes explain most of the genetic variance in high-density lipoprotein and low-density lipoprotein cholesterol

Medical Faculty of the Charité, Franz Volhard Clinic, Helios Klinikum, Berlin, Germany.
Human Molecular Genetics (Impact Factor: 6.39). 06/2004; 13(10):993-1004. DOI: 10.1093/hmg/ddh119
Source: PubMed


Single nucleotide polymorphisms (SNPs) and derived haplotypes within multiple genes may explain genetic variance in complex traits; however, this hypothesis has not been rigorously tested. In an earlier study we analyzed six genes and have now expanded this investigation to include 13. We studied 250 families including 1054 individuals and measured lipid phenotypes. We focused on low-density cholesterol (LDL), high-density cholesterol (HDL) and their ratio (LDL/HDL). A component analysis of the phenotypic variance relying on a standard genetic model' showed that the genetic variance on LDL explained 26%, on HDL explained 38% and on LDL/HDL explained 28% of the total variance, respectively. Genotyping of 93 SNPs in 13 lipid-relevant genes generated 230 haplotypes. The association of haplotypes in all the genes tested explained a major fraction of the genetic phenotypic variance component. For LDL, the association with haplotypes explained 67% and for HDL 58% of the genetic variance relative to the polygenic background. We conclude that these haplotypes explain most of the genetic variance in LDL, HDL and LDL/HDL in these representative German families. An analysis of the contribution to the genetic variance at each locus showed that APOE (50%), CETP (28%), LIPC (9%), APOB (8%) and LDLR (5%) influenced variation in LDL. LIPC (53%), CETP (25%), ABCA1 (10%), LPL (6%) and LDLR (6%) influenced the HDL variance. The LDL/HDL ratio was primarily influenced by APOE (36%), CETP (27%) and LIPC (31%). This expanded analysis substantially increases the explanation of genetic variance on these complex traits.

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    Nutrition 10/2014; 31(3). DOI:10.1016/j.nut.2014.09.007 · 2.93 Impact Factor
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    • "Increasingly, it is being realised that it is important to take an overall biological pathway approach to identify SNPs that show an association with a disease/disorder (e.g. [23], [24]). The present study used a two-phase genotyping approach to assess the influence of interaction of Se status and SNPs in genes across the selenium biological pathway on prostate cancer risk. "
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    PLoS ONE 11/2012; 7(11):e48709. DOI:10.1371/journal.pone.0048709 · 3.23 Impact Factor
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