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- Asselbergs, Folkert W., et al.
(author)
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Large-Scale Gene-Centric Meta-analysis across 32 Studies Identifies Multiple Lipid Loci
- 2012
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In: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297. ; 91:5, s. 823-838
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Journal article (peer-reviewed)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. |
- Ganesh, Santhi K., et al.
(author)
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Loci influencing blood pressure identified using a cardiovascular gene-centric array
- 2013
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In: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 22:8, s. 1663-1678
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Journal article (peer-reviewed)abstract
- Blood pressure (BP) is a heritable determinant of risk for cardiovascular disease (CVD). To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP) and pulse pressure (PP), we genotyped 50 000 single-nucleotide polymorphisms (SNPs) that capture variation in 2100 candidate genes for cardiovascular phenotypes in 61 619 individuals of European ancestry from cohort studies in the USA and Europe. We identified novel associations between rs347591 and SBP (chromosome 3p25.3, in an intron of HRH1) and between rs2169137 and DBP (chromosome1q32.1 in an intron of MDM4) and between rs2014408 and SBP (chromosome 11p15 in an intron of SOX6), previously reported to be associated with MAP. We also confirmed 10 previously known loci associated with SBP, DBP, MAP or PP (ADRB1, ATP2B1, SH2B3/ATXN2, CSK, CYP17A1, FURIN, HFE, LSP1, MTHFR, SOX6) at array-wide significance (P 2.4 10(6)). We then replicated these associations in an independent set of 65 886 individuals of European ancestry. The findings from expression QTL (eQTL) analysis showed associations of SNPs in the MDM4 region with MDM4 expression. We did not find any evidence of association of the two novel SNPs in MDM4 and HRH1 with sequelae of high BP including coronary artery disease (CAD), left ventricular hypertrophy (LVH) or stroke. In summary, we identified two novel loci associated with BP and confirmed multiple previously reported associations. Our findings extend our understanding of genes involved in BP regulation, some of which may eventually provide new targets for therapeutic intervention.
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| 3. |
- Tragante, Vinicius, et al.
(author)
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Gene-centric Meta-analysis in 87,736 Individuals of European Ancestry Identifies Multiple Blood-Pressure-Related Loci.
- 2014
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In: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297. ; 94:3, s. 349-360
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Journal article (peer-reviewed)abstract
- Blood pressure (BP) is a heritable risk factor for cardiovascular disease. To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP), we genotyped ∼50,000 SNPs in up to 87,736 individuals of European ancestry and combined these in a meta-analysis. We replicated findings in an independent set of 68,368 individuals of European ancestry. Our analyses identified 11 previously undescribed associations in independent loci containing 31 genes including PDE1A, HLA-DQB1, CDK6, PRKAG2, VCL, H19, NUCB2, RELA, HOXC@ complex, FBN1, and NFAT5 at the Bonferroni-corrected array-wide significance threshold (p < 6 × 10(-7)) and confirmed 27 previously reported associations. Bioinformatic analysis of the 11 loci provided support for a putative role in hypertension of several genes, such as CDK6 and NUCB2. Analysis of potential pharmacological targets in databases of small molecules showed that ten of the genes are predicted to be a target for small molecules. In summary, we identified previously unknown loci associated with BP. Our findings extend our understanding of genes involved in BP regulation, which may provide new targets for therapeutic intervention or drug response stratification.
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| 4. |
- Di Angelantonio, Emanuele, et al.
(author)
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Association of Cardiometabolic Multimorbidity With Mortality : The Emerging Risk Factors Collaboration
- 2015
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In: Journal of the American Medical Association (JAMA). - : American Medical Association (AMA). - 0098-7484 .- 1538-3598. ; 314:1, s. 52-60
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Journal article (peer-reviewed)abstract
- IMPORTANCE The prevalence of cardiometabolic multimorbidity is increasing.OBJECTIVE To estimate reductions in life expectancy associated with cardiometabolic multimorbidity.DESIGN, SETTING, AND PARTICIPANTS Age-and sex-adjusted mortality rates and hazard ratios (HRs) were calculated using individual participant data from the Emerging Risk Factors Collaboration (689 300 participants; 91 cohorts; years of baseline surveys: 1960-2007; latest mortality follow-up: April 2013; 128 843 deaths). The HRs from the Emerging Risk Factors Collaboration were compared with those from the UK Biobank (499 808 participants; years of baseline surveys: 2006-2010; latest mortality follow-up: November 2013; 7995 deaths). Cumulative survival was estimated by applying calculated age-specific HRs for mortality to contemporary US age-specific death rates. EXPOSURES A history of 2 or more of the following: diabetes mellitus, stroke, myocardial infarction (MI).MAIN OUTCOMES AND MEASURES All-cause mortality and estimated reductions in life expectancy.RESULTS In participants in the Emerging Risk Factors Collaboration without a history of diabetes, stroke, or MI at baseline (reference group), the all-cause mortality rate adjusted to the age of 60 years was 6.8 per 1000 person-years. Mortality rates per 1000 person-years were 15.6 in participants with a history of diabetes, 16.1 in those with stroke, 16.8 in those with MI, 32.0 in those with both diabetes and MI, 32.5 in those with both diabetes and stroke, 32.8 in those with both stroke and MI, and 59.5 in those with diabetes, stroke, and MI. Compared with the reference group, the HRs for all-cause mortality were 1.9 (95% CI, 1.8-2.0) in participants with a history of diabetes, 2.1 (95% CI, 2.0-2.2) in those with stroke, 2.0 (95% CI, 1.9-2.2) in those with MI, 3.7 (95% CI, 3.3-4.1) in those with both diabetes and MI, 3.8 (95% CI, 3.5-4.2) in those with both diabetes and stroke, 3.5 (95% CI, 3.1-4.0) in those with both stroke and MI, and 6.9 (95% CI, 5.7-8.3) in those with diabetes, stroke, and MI. The HRs from the Emerging Risk Factors Collaboration were similar to those from the more recently recruited UK Biobank. The HRs were little changed after further adjustment for markers of established intermediate pathways (eg, levels of lipids and blood pressure) and lifestyle factors (eg, smoking, diet). At the age of 60 years, a history of any 2 of these conditions was associated with 12 years of reduced life expectancy and a history of all 3 of these conditions was associated with 15 years of reduced life expectancy.CONCLUSIONS AND RELEVANCE Mortality associated with a history of diabetes, stroke, or MI was similar for each condition. Because any combination of these conditions was associated with multiplicative mortality risk, life expectancy was substantially lower in people with multimorbidity.
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| 5. |
- Pennells, Lisa, et al.
(author)
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Equalization of four cardiovascular risk algorithms after systematic recalibration : individual-participant meta-analysis of 86 prospective studies
- 2019
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In: European Heart Journal. - : Oxford University Press (OUP). - 0195-668X .- 1522-9645. ; 40:7, s. 621-
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Journal article (peer-reviewed)abstract
- Aims: There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after ‘recalibration’, a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied.Methods and results: Using individual-participant data on 360 737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at ‘high’ 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE over-predicted CVD risk on average by 10%, 52%, and 41%, respectively, whereas RRS under-predicted by 10%. Original versions of algorithms classified 29–39% of individuals aged ≥40 years as high risk. By contrast, recalibration reduced this proportion to 22–24% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44–51 such individuals using original algorithms, in contrast to 37–39 individuals with recalibrated algorithms.Conclusion: Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need.
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