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- Asselbergs, Folkert W., et al.
(författare)
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Large-Scale Gene-Centric Meta-analysis across 32 Studies Identifies Multiple Lipid Loci
- 2012
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Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297. ; 91:5, s. 823-838
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom similar to 50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering similar to 2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids.
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| 2. |
- Neisius, Ulf, et al.
(författare)
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Association of central and peripheral pulse pressure with intermediate cardiovascular phenoytpes.
- 2012
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Ingår i: Journal of Hypertension. - 1473-5598. ; 30:1, s. 67-74
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: We assessed the relationship between pulse pressure and intermediate cardiovascular phenotypes in a middle-aged cohort with high prevalence of hypertension. BACKGROUND: It has been suggested that central pulse pressure (cPP) is a better predictor of cardiovascular outcome than peripheral pulse pressure (pPP), particularly in the elderly. Yet, it is unclear if cPP provides additional prognostic information to pPP in younger individuals. METHODS: In 535 individuals we assessed cPP and pPP as well as the intermediate cardiovascular phenotypes pulse wave velocity (PWV; SphygmoCor, Complior, PulsePen), carotid intima-media thickness (C-IMT; carotid ultrasound), left-ventricular mass index (LVMI; echocardiography) and urinary albumin : creatinine ratio (ACR). cPP was derived noninvasively from brachial blood pressure by pulse wave analysis (PWA; SphygmoCor) based on radial pulse wave tonometry and a validated transfer function. RESULTS: The cohort contained 331 hypertensive participants of whom 84% were treated. The average age was 46 ± 16 years. When compared to pPP, cPP had stronger associations with PWV (r = 0.471 vs. r = 0.372; P < 0.01), C-IMT (r = 0.426 vs. r = 0.235; P < 0.01) and LVMI (r = 0.385 vs. r = 0.189; P < 0.01), but equal association with ACR (r = 0.236 vs. r = 0.226; P = n.s.). In contrast, after adjustment for age, mean arterial pressure, heart rate and hypertension status there was no significant difference between cPP and pPP for prediction of PWV (adjusted R, 0.399 vs. 0.413; P = 0.066), C-IMT (adjusted R, 0.399 vs. 0.413; P = 0.487) and LVMI (adjusted R, 0.181 vs. 0.170; P = 0.094) in multivariate analysis. CONCLUSION: In our middle-aged cohort with high prevalence of hypertension cPP is more closely correlated with cardiovascular phenotypes than pPP. When adjusted for relevant cofactors, however, cPP does not provide additional information beyond pPP.
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