Genome-Wide Analysis in Over 1 Million Individuals of European Ancestry Yields Improved Polygenic Risk Scores for Blood Pressure Traits

Hypertension affects more than one billion people worldwide. Here we identify 113 novel loci, reporting a total of 2,103 independent genetic signals (P \u3c 5 × 10-8) from the largest single-stage blood pressure (BP) genome-wide association study to date (n = 1,028,980 European individuals). These associations explain more than 60% of single nucleotide polymorphism-based BP heritability. Comparing top versus bottom deciles of polygenic risk scores (PRSs) reveals clinically meaningful differences in BP (16.9 mmHg systolic BP, 95% CI, 15.5-18.2 mmHg, P = 2.22 × 10-126) and more than a sevenfold higher odds of hypertension risk (odds ratio, 7.33; 95% CI, 5.54-9.70; P = 4.13 × 10-44) in an independent dataset. Adding PRS into hypertension-prediction models increased the area under the receiver operating characteristic curve (AUROC) from 0.791 (95% CI, 0.781-0.801) to 0.826 (95% CI, 0.817-0.836, ∆AUROC, 0.035, P = 1.98 × 10-34). We compare the 2,103 loci results in non-European ancestries and show significant PRS associations in a large African-American sample. Secondary analyses implicate 500 genes previously unreported for BP. Our study highlights the role of increasingly large genomic studies for precision health research

Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney.

Elevated blood pressure is a major risk factor for cardiovascular disease and has a substantial genetic contribution. Genetic variation influencing blood pressure has the potential to identify new pharmacological targets for the treatment of hypertension. To discover additional novel blood pressure loci, we used 1000 Genomes Project-based imputation in 150 134 European ancestry individuals and sought significant evidence for independent replication in a further 228 245 individuals. We report 6 new signals of association in or near HSPB7, TNXB, LRP12, LOC283335, SEPT9, and AKT2, and provide new replication evidence for a further 2 signals in EBF2 and NFKBIA Combining large whole-blood gene expression resources totaling 12 607 individuals, we investigated all novel and previously reported signals and identified 48 genes with evidence for involvement in blood pressure regulation that are significant in multiple resources. Three novel kidney-specific signals were also detected. These robustly implicated genes may provide new leads for therapeutic innovation

Genome-wide analysis in over 1 million individuals of European ancestry yields improved polygenic risk scores for blood pressure traits

Hypertension affects more than one billion people worldwide. Here we identify 113 novel loci, reporting a total of 2,103 independent genetic signals (P < 5 × 10−8) from the largest single-stage blood pressure (BP) genome-wide association study to date (n = 1,028,980 European individuals). These associations explain more than 60% of single nucleotide polymorphism-based BP heritability. Comparing top versus bottom deciles of polygenic risk scores (PRSs) reveals clinically meaningful differences in BP (16.9 mmHg systolic BP, 95% CI, 15.5–18.2 mmHg, P = 2.22 × 10−126) and more than a sevenfold higher odds of hypertension risk (odds ratio, 7.33; 95% CI, 5.54–9.70; P = 4.13 × 10−44) in an independent dataset. Adding PRS into hypertension-prediction models increased the area under the receiver operating characteristic curve (AUROC) from 0.791 (95% CI, 0.781–0.801) to 0.826 (95% CI, 0.817–0.836, ∆AUROC, 0.035, P = 1.98 × 10−34). We compare the 2,103 loci results in non-European ancestries and show significant PRS associations in a large African-American sample. Secondary analyses implicate 500 genes previously unreported for BP. Our study highlights the role of increasingly large genomic studies for precision health research

Penalized-regression-based multimarker genotype analysis of Genetic Analysis Workshop 17 data

Testing for association between multiple markers and a phenotype can not only capture untyped causal variants in weak linkage disequilibrium with nearby typed markers but also identify the effect of a combination of markers. We propose a sliding window approach that uses multimarker genotypes as variables in a penalized regression. We investigate a penalty with three separate components: (1) a group least absolute shrinkage and selection operator (LASSO) that selects multimarker genotypes in a gene to be included in or excluded from the model, (2) an allele-sharing penalty that encourages multimarker genotypes with similar alleles to have similar coefficients, and (3) a penalty that shrinks the size of coefficients while performing model selection. The penalized likelihood is minimized with a cyclic coordinate descent algorithm, allowing quick coefficient estimation for a large number of markers. We compare our method to single-marker analysis and a gene-based sparse group LASSO on the Genetic Analysis Workshop 17 data for quantitative trait Q2. We found that all of the methods were underpowered to detect the simulated rare causal variants at the low false-positive rates desired in association studies. However, the sparse group LASSO on multi-marker genotypes seems to provide some advantage over the sparse group LASSO applied to single SNPs within genes, giving further evidence that there may be an advantage to modeling combinations of rare variant alleles over modeling them individually

Association between C677T polymorphism of methylene tetrahydrofolate reductase and congenital heart disease: meta-analysis of 7697 cases and 13,125 controls

BACKGROUND: Association between the C677T polymorphism of the methylene tetrahydrofolate reductase (MTHFR) gene and congenital heart disease (CHD) is contentious. METHODS AND RESULTS: We compared genotypes between CHD cases and controls and between mothers of CHD cases and controls. We placed our results in context by conducting meta-analyses of previously published studies. Among 5814 cases with primary genotype data and 10 056 controls, there was no evidence of association between MTHFR C677T genotype and CHD risk (odds ratio [OR], 0.96 [95% confidence interval, 0.87-1.07]). A random-effects meta-analysis of all studies (involving 7697 cases and 13 125 controls) suggested the presence of association (OR, 1.25 [95% confidence interval, 1.03-1.51]; P=0.022) but with substantial heterogeneity among contributing studies (I(2)=64.4%) and evidence of publication bias. Meta-analysis of large studies only (defined by a variance of the log OR <0.05), which together contributed 83% of all cases, yielded no evidence of association (OR, 0.97 [95% confidence interval, 0.91-1.03]) without significant heterogeneity (I(2)=0). Moreover, meta-analysis of 1781 mothers of CHD cases (829 of whom were genotyped in this study) and 19 861 controls revealed no evidence of association between maternal C677T genotype and risk of CHD in offspring (OR, 1.13 [95% confidence interval, 0.87-1.47]). There was no significant association between MTHFR genotype and CHD risk in large studies from regions with different levels of dietary folate. CONCLUSIONS: The MTHFR C677T polymorphism, which directly influences plasma folate levels, is not associated with CHD risk. Publication biases appear to substantially contaminate the literature with regard to this genetic association

Genome-wide analysis in over 1 million individuals of European ancestry yields improved polygenic risk scores for blood pressure traits.

Acknowledgements: J.N.H. is supported by the National Institutes of Health (grant no. K12HD04348; principal investigator K. E. Hartmann). T.E. and A.M. were supported by the Council of Europe (grant no. 2014-2020.4.01.15-0012) and Estonian Research Council (grant no. PRG1291). Z.K. is supported by Isfahan University of Medical Sciences (3400581) and Iran’s National Elites Foundation (grant no. ISF140100108). J.N.D. holds a British Heart Foundation Professorship and a National Institute for Health Research Senior Investigator Award. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. Cohort support was provided by the Million Veteran Program (MVP) VA Award BX004821 (to P.W.F.W. and K.C.). Individual cohort acknowledgements are provided in the Supplementary Notes. We dedicate this paper to the memory of Evangelos Evangelou (the first author of our previous BP-GWAS paper5), who sadly passed away in July 2023.Hypertension affects more than one billion people worldwide. Here we identify 113 novel loci, reporting a total of 2,103 independent genetic signals (P < 5 × 10-8) from the largest single-stage blood pressure (BP) genome-wide association study to date (n = 1,028,980 European individuals). These associations explain more than 60% of single nucleotide polymorphism-based BP heritability. Comparing top versus bottom deciles of polygenic risk scores (PRSs) reveals clinically meaningful differences in BP (16.9 mmHg systolic BP, 95% CI, 15.5-18.2 mmHg, P = 2.22 × 10-126) and more than a sevenfold higher odds of hypertension risk (odds ratio, 7.33; 95% CI, 5.54-9.70; P = 4.13 × 10-44) in an independent dataset. Adding PRS into hypertension-prediction models increased the area under the receiver operating characteristic curve (AUROC) from 0.791 (95% CI, 0.781-0.801) to 0.826 (95% CI, 0.817-0.836, ∆AUROC, 0.035, P = 1.98 × 10-34). We compare the 2,103 loci results in non-European ancestries and show significant PRS associations in a large African-American sample. Secondary analyses implicate 500 genes previously unreported for BP. Our study highlights the role of increasingly large genomic studies for precision health research

Erratum to: Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits

In the version of this article originally published, the name of author Martin H. de Borst was coded incorrectly in the XML. The error has now been corrected in the HTML version of the paper