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Gene-Centric Meta-Analysis of Lipid Traits in African, East Asian and Hispanic Populations
Gene-Centric Meta-Analysis of Lipid Traits in African, East Asian and Hispanic Populations
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Gene-Centric Meta-Analysis of Lipid Traits in African, East Asian and Hispanic Populations
Gene-Centric Meta-Analysis of Lipid Traits in African, East Asian and Hispanic Populations

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Gene-Centric Meta-Analysis of Lipid Traits in African, East Asian and Hispanic Populations
Gene-Centric Meta-Analysis of Lipid Traits in African, East Asian and Hispanic Populations
Journal Article

Gene-Centric Meta-Analysis of Lipid Traits in African, East Asian and Hispanic Populations

Eva
2012
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Overview
Meta-analyses of European populations has successfully identified genetic variants in over 100 loci associated with lipid levels, but our knowledge in other ethnicities remains limited. To address this, we performed dense genotyping of ∼2,000 candidate genes in 7,657 African Americans, 1,315 Hispanics and 841 East Asians, using the IBC array, a custom ∼50,000 SNP genotyping array. Meta-analyses confirmed 16 lipid loci previously established in European populations at genome-wide significance level, and found multiple independent association signals within these lipid loci. Initial discovery and in silico follow-up in 7,000 additional African American samples, confirmed two novel loci: rs5030359 within ICAM1 is associated with total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) (p = 8.8×10 −7 and p = 1.5×10 −6 respectively) and a nonsense mutation rs3211938 within CD36 is associated with high-density lipoprotein cholesterol (HDL-C) levels (p = 13.5×10 −12). The rs3211938-G allele, which is nearly absent in European and Asian populations, has been previously found to be associated with CD36 deficiency and shows a signature of selection in Africans and African Americans. Finally, we have evaluated the effect of SNPs established in European populations on lipid levels in multi-ethnic populations and show that most known lipid association signals span across ethnicities. However, differences between populations, especially differences in allele frequency, can be leveraged to identify novel signals, as shown by the discovery of ICAM1 and CD36 in the current report.