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. 2017 Mar;49(3):403-415.
doi: 10.1038/ng.3768. Epub 2017 Jan 30.

Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk

Helen R Warren  1   2 Evangelos Evangelou  3   4 Claudia P Cabrera  1   2 He Gao  3   5 Meixia Ren  1   2 Borbala Mifsud  1 Ioanna Ntalla  1 Praveen Surendran  6 Chunyu Liu  7   8   9 James P Cook  10 Aldi T Kraja  11 Fotios Drenos  12   13 Marie Loh  3   14 Niek Verweij  15   16   17   18 Jonathan Marten  19 Ibrahim Karaman  3 Marcelo P Segura Lepe  3   20 Paul F O'Reilly  21 Joanne Knight  22 Harold Snieder  23 Norihiro Kato  24 Jiang He  25 E Shyong Tai  26   27 M Abdullah Said  15 David Porteous  28 Maris Alver  29 Neil Poulter  30 Martin Farrall  31 Ron T Gansevoort  32 Sandosh Padmanabhan  33 Reedik Mägi  29 Alice Stanton  34 John Connell  35 Stephan J L Bakker  36 Andres Metspalu  29 Denis C Shields  37 Simon Thom  38 Morris Brown  1   2 Peter Sever  38 Tõnu Esko  16   29 Caroline Hayward  19 Pim van der Harst  15 Danish Saleheen  39   40   41 Rajiv Chowdhury  6 John C Chambers  3   42   43   44 Daniel I Chasman  45   46 Aravinda Chakravarti  47 Christopher Newton-Cheh  16   17   18 Cecilia M Lindgren  16   48   49 Daniel Levy  7   9 Jaspal S Kooner  43   50   51 Bernard Keavney  52   53 Maciej Tomaszewski  52   53 Nilesh J Samani  54   55 Joanna M M Howson  6 Martin D Tobin  56 Patricia B Munroe  1   2 Georg B Ehret  47   57 Louise V Wain  56 International Consortium of Blood Pressure (ICBP) 1000G AnalysesBIOS ConsortiumLifelines Cohort StudyUnderstanding Society Scientific groupCHD Exome+ ConsortiumExomeBP ConsortiumT2D-GENES ConsortiumGoT2DGenes ConsortiumCohorts for Heart and Ageing Research in Genome Epidemiology (CHARGE) BP Exome ConsortiumInternational Genomics of Blood Pressure (iGEN-BP) ConsortiumUK Biobank CardioMetabolic Consortium BP working group
Collaborators, Affiliations

Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk

Helen R Warren et al. Nat Genet. 2017 Mar.

Erratum in

  • Corrigendum: Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk.
    Warren HR, Evangelou E, Cabrera CP, Gao H, Ren M, Mifsud B, Ntalla I, Surendran P, Liu C, Cook JP, Kraja AT, Drenos F, Loh M, Verweij N, Marten J, Karaman I, Segura Lepe MP, O'Reilly PF, Knight J, Snieder H, Kato N, He J, Tai ES, Said MA, Porteous D, Alver M, Poulter N, Farrall M, Gansevoort RT, Padmanabhan S, Mägi R, Stanton A, Connell J, Bakker SJL, Metspalu A, Shields DC, Thom S, Brown M, Sever P, Esko T, Hayward C, van der Harst P, Saleheen D, Chowdhury R, Chambers JC, Chasman DI, Chakravarti A, Newton-Cheh C, Lindgren CM, Levy D, Kooner JS, Keavney B, Tomaszewski M, Samani NJ, Howson JMM, Tobin MD, Munroe PB, Ehret GB, Wain LV; International Consortium of Blood Pressure (ICBP) 1000G Analyses, The CHD Exome+ Consortium, The ExomeBP Consortium, The T2D-GENES Consortium, The GoT2DGenes Consortium, The Cohorts for Heart and Ageing Research in Genome Epidemiology (CHARGE) BP Exome Consortium, The International Genomics of Blood Pressure (iGEN-BP) Consortium; Barnes MR, Tzoulaki I, Caulfield MJ, Elliott P; UK Biobank CardioMetabolic Consortium BP working group. Warren HR, et al. Nat Genet. 2017 Sep 27;49(10):1558. doi: 10.1038/ng1017-1558a. Nat Genet. 2017. PMID: 28951623 No abstract available.

Abstract

Elevated blood pressure is the leading heritable risk factor for cardiovascular disease worldwide. We report genetic association of blood pressure (systolic, diastolic, pulse pressure) among UK Biobank participants of European ancestry with independent replication in other cohorts, and robust validation of 107 independent loci. We also identify new independent variants at 11 previously reported blood pressure loci. In combination with results from a range of in silico functional analyses and wet bench experiments, our findings highlight new biological pathways for blood pressure regulation enriched for genes expressed in vascular tissues and identify potential therapeutic targets for hypertension. Results from genetic risk score models raise the possibility of a precision medicine approach through early lifestyle intervention to offset the impact of blood pressure-raising genetic variants on future cardiovascular disease risk.

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Conflict of interest statement

Conflicts/Disclosures

MJC is Chief Scientist for Genomics England, a wholly owned UK government company. He leads the 100,000 Genomes Project which includes syndromic forms of blood pressure.

Figures

Figure 1
Figure 1
Study design schematic for discovery and validation of loci. N: sample size; QC: Quality Control; PCA: Principal Component Analysis; BP: blood pressure; SBP: systolic BP; DBP: diastolic BP; PP: pulse pressure; SNVs: single nucleotide variants; BMI: body mass index; UKB: UK Biobank; UKBL: UK BiLEVE; GWAS: Genome-wide association study; MAF: Minor Allele Frequency; P: P-value; LD: Linkage Disequilibrium; 1000G: 1000 Genomes. UKBBvsUKBL: a binary indicator variable for UK Biobank vs UK BiLEVE to adjust for the different genotyping chips
Figure 2
Figure 2
Venn diagram of 107 validated loci from our study. This shows concordance of significant associations across the three blood pressure phenotypes for the 107 validated sentinel variants (Tables 1-3) from both the GWAS and exome analyses, according to genome-wide significance in the combined meta-analysis. The locus names labelled within the Venn Diagram correspond to Tables 1-3, and relate to the nearest annotated gene. The loci names in bold font highlight the 32 novel loci which are reported for the first time in our study.
Figure 3
Figure 3
Distribution of Genetic Risk Score (GRS) and its relationship with blood pressure, hypertension and CVD outcomes. The GRS is based on all reported loci: both previously reported loci at the time of analysis; and all validated blood pressure variants from this study. (a) Distribution of GRS in Airwave and sex-adjusted odds ratio of hypertension in age 50+ comparing each of the upper four GRS quintiles with the lowest quintile; dotted lines represent the upper 95% confidence intervals. (b) Mean blood pressures and standard deviation in bracket in Airwave age 50+ across GRS quintiles. (c) Distribution of GRS in UKB and sex-adjusted odds ratio of CVD, CAD and stroke comparing each of the upper four GRS quintiles with the lowest quintile; dotted lines represent the upper 95% confidence intervals. (d) Count of CVD, CAD and stroke (events and deaths) across GRS quintiles in UKB participants
Figure 4
Figure 4
Summary of gene cardiovascular expression from validated loci. Genes are shown on the basis of their tissue expression and supporting evidence summarised in Supplementary Table 16, based on Knockout (KO) phenotype, previously reported blood pressure biology or a strong functional rationale: eQTL (expression Quantitative Trait Loci), nsSNV (non-synonymous SNV), Hi-C. Multiple lines of evidence indicate the central importance of the vasculature in blood pressure regulation and we thus highlight existing drugged (*) and druggable (#) targets among these genes. Illustrations used elements with permission from Servier Medical Art. We note that some druggable genes may carry a safety liability, such as GJA1, which has known association with QT interval

Comment in

References

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