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• W3103342445 abstract "HomeCirculation: Genomic and Precision MedicineVol. 13, No. 6Blood Pressure Modification and Life Expectancy in a General Population Free AccessLetterPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyRedditDiggEmail Jump toFree AccessLetterPDF/EPUBBlood Pressure Modification and Life Expectancy in a General PopulationMendelian Randomization Analysis Iyas Daghlas, BS and Dipender Gill, BMBCh, PhD Iyas DaghlasIyas Daghlas Correspondence to: Iyas Daghlas, Harvard Medical School, 25 Shattuck St, Boston, MA 02115. Email E-mail Address: [email protected] https://orcid.org/0000-0001-8735-284X Harvard Medical School, Boston, MA (I.D.). Search for more papers by this author and Dipender GillDipender Gill https://orcid.org/0000-0001-7312-7078 Department of Epidemiology & Biostatistics, School of Public Health (D.G.), Imperial College London. Centre for Pharmacology & Therapeutics, Department of Medicine (D.G.), Imperial College London. Novo Nordisk Research Centre Oxford (D.G.). Clinical Pharmacology and Therapeutics Section, Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George’s, University of London (D.G.). Clinical Pharmacology Group, Pharmacy and Medicines Directorate, St George’s University Hospitals NHS Foundation Trust, London, United Kingdom (D.G.). Search for more papers by this author Originally published14 Nov 2020https://doi.org/10.1161/CIRCGEN.120.003143Circulation: Genomic and Precision Medicine. 2020;13:e003143Other version(s) of this articleYou are viewing the most recent version of this article. Previous versions: November 15, 2020: Ahead of Print Elevated blood pressure (BP) is a leading cause of cardiovascular disease and reduced life expectancy.1 It is, therefore, important to quantify the potential benefit of public health interventions that systematically lower BP across a population. Such estimates from observational research can be biased by confounding. In contrast, sufficient follow-up for mortality outcomes in clinical trials is often limited by resource constraints. The Mendelian randomization (MR) approach leverages genetic variants as proxies for investigating the effect of modifying an exposure on an outcome.2 As genetic variants are randomly allocated, they are relatively robust to the confounding that can limit causal inference in observational research. The aim of this study was to employ the MR paradigm to estimate the effect of BP modification on life expectancy in a general population.We identified genetic proxies for BP modification as variants associated (P<5x10-8) with systolic (SBP) and diastolic BP (DBP), respectively (measured at a single time point; N=757 601).3 We obtained associations of these variants with lifespan from a meta-analysis of genetic associations with reported parental lifespan (N=1 012 240).4 The substantially larger sample sizes available for parental, rather than individual, lifespan may be leveraged in such analyses because parents share half of their genetic sequence with their offspring.4 To assess the association of genetically proxied BP modification with longevity (ie, lifespan beyond a cutoff), we obtained genetic associations from a meta-analysis of individual survival to a sex and birth cohort-specific age percentile of 90 versus 60 (11 262 cases and 25 483 controls).5 All genetic associations were harmonized by aligning effect alleles, with no exclusion made for palindromic variants. The variants were clumped to pair-wise linkage disequilibrium r2<0.0012. The variants proxying SBP and DBP collectively explained 4.49% and 4.74% of the variance, respectively, with a mean F statistic (reflecting instrument strength) of 74.6 and 79.1, respectively.We estimated MR effects using the random-effects inverse-variance weighted method2 and performed the MR-Egger and weighted median methods as sensitivity analyses that can be more robust to the presence of pleiotropic variants.2 We further performed multivariable MR analyses adjusting for potential pleiotropic effects of the variants on body mass index (N=806 834), waist-hip ratio (N=212 244), alcohol consumption (measured as log drinks per week; N=537 349), and smoking initiation (N=632 802). Data sources for these association estimates are provided in the links below. Estimates were scaled to represent the effect of a 10 mm Hg increase in the respective BP trait. All genetic association studies were performed in European ancestry populations, received relevant ethical approval and participant consent, and have made their summary data publicly available.3–5A 10 mm Hg increase in genetically proxied SBP reduced lifespan by 1.83 years (95% CI, −2.03 to −1.64; P=4×10-76) and had odds ratio 0.67 for the outcome of longevity (95% CI, 0.62–0.73; P=6×10-22; Figure). Consistent findings were obtained for DBP and across sensitivity analyses (Figure). The Egger intercept test did not provide evidence for bias attributable to pleiotropy (all P ≥0.22). Despite differences in the magnitude of effect on the mm Hg scale, the effects of SBP (−3.54 years [95% CI, −3.91 to −3.16]) and DBP (−3.09 years [95% CI −3.42 to −2.75]) on lifespan were similar (Pdifference=0.08) when the scale was standardized to SD units (19.3 mm Hg for SBP and 10.5 mm Hg for DBP in UK Biobank3).Download figureDownload PowerPointFigure. Forest plot depicting Mendelian randomization (MR) results for the association of genetically proxied blood pressure (BP) with lifespan (N=1 012 240) and longevity (11 262 cases/25 483 controls). Point estimates are expressed as the association of a 10 mm Hg increase in each genetically proxied BP trait with (A) years of lifespan or (B) survival to the 90th vs 60th percentile age. Multivariable MR estimates are adjusted for genetic associations with body mass index, waist-hip ratio, alcohol consumption (drinks per week), and smoking initiation. DBP indicates diastolic BP; IVW, inverse-variance weighted; MVMR, multivariable MR; OR, odds ratio; SBP, systolic BP; and WM, weighted median.Our results quantify the effect of BP-lowering on life expectancy in a general European population and support the notion that population-based strategies to reduce BP can have a significant impact on life expectancy. Even small incremental reductions in BP, when aggregated across the population, will yield large dividends in total life-years saved. Strategies for achieving population-wide BP reduction include promotion of physical activity, weight loss, and dietary modification.Our study has strengths. The MR approach is less likely to be affected by confounding, and the use of parental lifespan as an outcome reduces risk of survival bias. Our study also has limitations. Although our MR estimates were consistent in sensitivity analyses, we cannot exclude the possibility of bias due to pleiotropy. Our approach tests the linear associations of small changes in genetically proxied BP near the population mean, and should not be extrapolated to BP extremes. Similarly, these results cannot be extrapolated to predict the effect of a BP-lowering intervention. The genetic association estimates for BP were also taken from measures at a single time point and may not reflect BP over the life course. Finally, participant overlap in the BP and life expectancy genetic association studies (up to 65% overlap with the lifespan dataset and up to 2.2% overlap with the longevity dataset) may bias results away from the null.In summary, findings from this MR analysis support the notion that public health interventions that persistently lower blood pressure, even by a small amount, are likely to have tremendous cumulative benefit in terms of life expectancy.Nonstandard Abbreviations and AcronymsBPblood pressureDBPdiastolic BPMRMendelian randomizationSBPsystolic BPSources of FundingThis work was supported by the British Heart Foundation Centre of Research Excellence (RE/18/4/34215) at Imperial College London (Dr Gill). The funding source had no role in the design, acquisition of data, analysis, interpretation, or write up of this study.AcknowledgmentsBody mass index: https://zenodo.org/record/1251813#.Xz44nOhKiUl; Waist-hip-ratio: https://portals.broadinstitute.org/collaboration/giant/images/f/fd/GIANT_2015_WHR_MALES_EUR.txt.gz; Alcohol consumption and smoking initiation: https://conservancy.umn.edu/handle/11299/201564.DisclosuresDr Gill is employed part-time by Novo Nordisk. The other author reports no conflicts.FootnotesFor Sources of Funding and Disclosures, see page 711.Correspondence to: Iyas Daghlas, Harvard Medical School, 25 Shattuck St, Boston, MA 02115. Email [email protected]harvard.eduReferences1. Forouzanfar MH, Liu P, Roth GA, Ng M, Biryukov S, Marczak L, Alexander L, Estep K, Hassen Abate K, Akinyemiju TF, et al.. Global burden of hypertension and systolic blood pressure of at least 110 to 115 mm Hg, 1990-2015.JAMA. 2017; 317:165–182. doi: 10.1001/jama.2016.19043CrossrefMedlineGoogle Scholar2. Hemani G, Zheng J, Elsworth B, Wade KH, Haberland V, Baird D, Laurin C, Burgess S, Bowden J, Langdon R, et al.. The MR-Base platform supports systematic causal inference across the human phenome.Elife. 2018; 7:e34408.CrossrefMedlineGoogle Scholar3. Evangelou E, Warren HR, Mosen-Ansorena D, Mifsud B, Pazoki R, Gao H, Ntritsos G, Dimou N, Cabrera CP, Karaman I, et al.; Million Veteran Program. Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits.Nat Genet. 2018; 50:1412–1425. doi: 10.1038/s41588-018-0205-xCrossrefMedlineGoogle Scholar4. Timmers PR, Mounier N, Lall K, Fischer K, Ning Z, Feng X, Bretherick AD, Clark DW, Agbessi M, Ahsan H, et al.. Genomics of 1 million parent lifespans implicates novel pathways and common diseases and distinguishes survival chances.Elife. 2019; 8:1–40.CrossrefGoogle Scholar5. Deelen J, Evans DS, Arking DE, Tesi N, Nygaard M, Liu X, Wojczynski MK, Biggs ML, van der Spek A, Atzmon G, et al.. A meta-analysis of genome-wide association studies identifies multiple longevity genes.Nat Commun. 2019; 10:3669. doi: 10.1038/s41467-019-11558-2CrossrefMedlineGoogle Scholar Previous Back to top Next FiguresReferencesRelatedDetails December 2020Vol 13, Issue 6Article InformationMetrics Download: 349 © 2020 American Heart Association, Inc.https://doi.org/10.1161/CIRCGEN.120.003143PMID: 33191764 Originally publishedNovember 14, 2020 Keywordslife expectancyblood pressurehypertensioncardiovascular diseaseallelesPDF download Advertisement SubjectsEpidemiologyGenetic, Association StudiesHigh Blood PressureHypertensionRisk Factors" @default.
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