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- Padmanabhan, Sandosh, et al.
(author)
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Hypertension and genome-wide association studies: combining high fidelity phenotyping and hypercontrols.
- 2008
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In: Journal of Hypertension. - 1473-5598. ; 26:7, s. 1275-1281
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Journal article (peer-reviewed)abstract
- Among the common complex diseases, hypertension has been particularly unlucky in the recent surge of positive results from genome-wide association studies. We summarize the evidence that would support continuing the effort in the hunt for a genetic basis for hypertension. The problems facing the genetic studies for hypertension are not unique, but phenotypic characterization, heterogeneity and high prevalence make it a special case requiring a more individualized approach. We argue that, even in the presence of a strong environmental component to hypertension risk, the common disease/common variant model is relevant for hypertension and discuss the issues involved in designing a genome-wide association study for hypertension. It is likely that the individual odds ratios for disease variants will be less than 1.3 and, although individually these effect sizes are minor, the combination of even a few such common polymorphisms can have substantial population attributable risks. The identification of hypertension gene variants should provide new insight into the disease susceptibility, progression and severity. This will lead to the identification of potential targets for lifestyle and pharmacological interventions, with the ultimate goal of improving prevention, diagnosis and treatment.
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| 2. |
- Talmud, Philippa J., et al.
(author)
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Gene-centric Association Signals for Lipids and Apolipoproteins Identified via the HumanCVD BeadChip
- 2009
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In: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297. ; 85:5, s. 628-642
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Journal article (peer-reviewed)abstract
- Blood lipids are important cardiovascular disease (CVD) risk factors with both genetic and environmental determinants. The Whitehall II study (n = 5592) was genotyped with the gene-centric HumanCVD BeadChip (Illumina). We identified 195 SNPs in 16 genes/regions associated with 3 major lipid fractions and 2 apolipoprotein components at p < 10(-5), with the associations being broadly concordant with prior genome-wide analysis. SNPs associated with LDL cholesterol and apolipoprotein B were located in LDLR, PCSK9, APOB, CELSR2, HWGCR, CETP, the TOMM40-APOE-C1-C2-C4 cluster, and the APOA5-A4-C3-A1 cluster; SNPs associated with HDL cholesterol and apolipoprotein AI were in CETP, LPL, LIPC, APOA5-A4-C3-A1, and ABCA1; and SNPs associated with triglycerides in GCKR, BAZIB, MLXIPL, LPL, and APOA5-A4-C3-A1. For 48 SNPs in previously unreported loci that were significant at p < 10(-4) in Whitehall II, in silico analysis including the British Women's Heart and Health Study, BRIGHT, ASCOT, and NORDIL studies (total n > 12,500) revealed previously unreported associations of SH2B3 (p < 2.2 x 10(-6)), BMPR2 (p < 2.3 x 10(-7)), BCL3/PVRL2 (flanking APOE; p < 4.4 x 10(-8)), and SMARCA4 (flanking LDLR; p < 2.5 x 10(-7)) with LDL cholesterol. Common alleles in these genes explained 6.1%-14.7% of the variance in the five lipid-related traits, and individuals at opposite tails of the additive allele score exhibited substantial differences in trait levels (e.g., > 1 mmol/L in LDL cholesterol [similar to 1 SD of the trait distribution]). These data suggest that multiple common alleles of small effect can make important contributions to individual differences in blood lipids potentially relevant to the assessment of CVD risk. These genes provide further insights into lipid metabolism and the likely effects of modifying the encoded targets therapeutically.
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