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Pozarickij A, Gan W, Lin K, Clarke R, Fairhurst-Hunter Z, Koido M, Kanai M, Okada Y, Kamatani Y, Bennett D, Du H, Chen Y, Yang L, Avery D, Guo Y, Yu M, Yu C, Schmidt Valle D, Lv J, Chen J, Peto R, Collins R, Li L, Chen Z, Millwood IY, Walters RG. Causal relevance of different blood pressure traits on risk of cardiovascular diseases: GWAS and Mendelian randomisation in 100,000 Chinese adults. Nat Commun 2024; 15:6265. [PMID: 39048560 PMCID: PMC11269703 DOI: 10.1038/s41467-024-50297-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 07/04/2024] [Indexed: 07/27/2024] Open
Abstract
Elevated blood pressure (BP) is major risk factor for cardiovascular diseases (CVD). Genome-wide association studies (GWAS) conducted predominantly in populations of European ancestry have identified >2,000 BP-associated loci, but other ancestries have been less well-studied. We conducted GWAS of systolic, diastolic, pulse, and mean arterial BP in 100,453 Chinese adults. We identified 128 non-overlapping loci associated with one or more BP traits, including 74 newly-reported associations. Despite strong genetic correlations between populations, we identified appreciably higher heritability and larger variant effect sizes in Chinese compared with European or Japanese ancestry populations. Using instruments derived from these GWAS, multivariable Mendelian randomisation demonstrated that BP traits contribute differently to the causal associations of BP with CVD. In particular, only pulse pressure was independently causally associated with carotid plaque. These findings reinforce the need for studies in diverse populations to understand the genetic determinants of BP traits and their roles in disease risk.
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Affiliation(s)
- Alfred Pozarickij
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Wei Gan
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Human Genetics Centre of Excellence, Novo Nordisk Research Centre Oxford, Innovation Building, Old Road Campus, Oxford, UK
| | - Kuang Lin
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Robert Clarke
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Zammy Fairhurst-Hunter
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Masaru Koido
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan
- Department of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, 113-0033, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, 230- 0045, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, 565-0871, Japan
| | - Yoichiro Kamatani
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Derrick Bennett
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Huaidong Du
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ling Yang
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Daniel Avery
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yu Guo
- National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, 100037, Beijing, China
| | - Min Yu
- Zhejiang CDC, Zhejiang, China
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Xueyuan Road, Haidian District, 100191, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, 100191, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, 100191, Beijing, China
| | - Dan Schmidt Valle
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Xueyuan Road, Haidian District, 100191, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, 100191, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, 100191, Beijing, China
| | - Junshi Chen
- China National Center For Food Safety Risk Assessment, Beijing, China
| | - Richard Peto
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Rory Collins
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Xueyuan Road, Haidian District, 100191, Beijing, China.
- Peking University Center for Public Health and Epidemic Preparedness and Response, 100191, Beijing, China.
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, 100191, Beijing, China.
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iona Y Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Robin G Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
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2
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Zhang Y, Ding Y, Yu C, Sun D, Pei P, Du H, Yang L, Chen Y, Schmidt D, Avery D, Chen J, Chen J, Chen Z, Li L, Lv J. Predictive value of 8-year blood pressure measures in intracerebral hemorrhage risk over 5 years. Eur J Prev Cardiol 2024:zwae147. [PMID: 38629743 DOI: 10.1093/eurjpc/zwae147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 03/21/2024] [Accepted: 04/16/2024] [Indexed: 05/07/2024]
Abstract
AIMS The relationships between long-term blood pressure (BP) measures and intracerebral hemorrhage (ICH), as well as their predictive ability on ICH, were unclear. We aimed to investigate the independent associations of multiple BP measures with subsequent 5-year ICH risk, as well as the incremental value of these measures over a single-point BP measurement in ICH risk prediction. METHODS We included 12,398 participants from the China Kadoorie Biobank (CKB) who completed three surveys every four to five years. The following long-term BP measures were calculated: mean, minimum, maximum, standard deviation, coefficient of variation, average real variability, and cumulative BP exposure (cumBP). Cox proportional hazard models were used to examine the associations between these measures and ICH. The potential incremental value of these measures in ICH risk prediction was assessed using Harrell's C statistics, continuous net reclassification improvement (cNRI), and relative integrated discrimination improvement (rIDI). RESULTS The hazard ratios (95% confidence intervals) of incident ICH associated with per SD increase in cumSBP and cumDBP were 1.62 (1.25, 2.10) and 1.59 (1.23, 2.07), respectively. When cumBP was added to the conventional 5-year ICH risk prediction model, the C-statistic change was 0.009 (-0.001, 0.019), the cNRI was 0.267 (0.070, 0.464), and the rIDI was 18.2% (5.8%, 30.7%). Further subgroup analyses revealed a consistent increase in cNRI and rIDI in men, rural residents, and participants without diabetes. Other long-term BP measures showed no statistically significant associations with incident ICH and generally did not improve model performance. CONCLUSION The nearly 10-year cumBP was positively associated with an increased 5-year risk of ICH and could significantly improve risk reclassification for the ICH risk prediction model that included single-point BP measurement.
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Affiliation(s)
- Yiqian Zhang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Yinqi Ding
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
| | - Dianjianyi Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Dan Schmidt
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Daniel Avery
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Jianwei Chen
- Liuyang Centers for Disease Control and Prevention, Liuyang, Changsha, Hunan, China
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University
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3
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Feng L, Ye Z, Mo C, Wang J, Liu S, Gao S, Ke H, Canida TA, Pan Y, van Greevenbroek MM, Houben AJ, Wang K, Hatch KS, Ma Y, Lei DK, Chen C, Mitchell BD, Hong LE, Kochunov P, Chen S, Ma T. Elevated blood pressure accelerates white matter brain aging among late middle-aged women: a Mendelian Randomization study in the UK Biobank. J Hypertens 2023; 41:1811-1820. [PMID: 37682053 PMCID: PMC11083214 DOI: 10.1097/hjh.0000000000003553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/09/2023]
Abstract
BACKGROUND Elevated blood pressure (BP) is a modifiable risk factor associated with cognitive impairment and cerebrovascular diseases. However, the causal effect of BP on white matter brain aging remains unclear. METHODS In this study, we focused on N = 228 473 individuals of European ancestry who had genotype data and clinical BP measurements available (103 929 men and 124 544 women, mean age = 56.49, including 16 901 participants with neuroimaging data available) collected from UK Biobank (UKB). We first established a machine learning model to compute the outcome variable brain age gap (BAG) based on white matter microstructure integrity measured by fractional anisotropy derived from diffusion tensor imaging data. We then performed a two-sample Mendelian randomization analysis to estimate the causal effect of BP on white matter BAG in the whole population and subgroups stratified by sex and age brackets using two nonoverlapping data sets. RESULTS The hypertension group is on average 0.31 years (95% CI = 0.13-0.49; P < 0.0001) older in white matter brain age than the nonhypertension group. Women are on average 0.81 years (95% CI = 0.68-0.95; P < 0.0001) younger in white matter brain age than men. The Mendelian randomization analyses showed an overall significant positive causal effect of DBP on white matter BAG (0.37 years/10 mmHg, 95% CI 0.034-0.71, P = 0.0311). In stratified analysis, the causal effect was found most prominent among women aged 50-59 and aged 60-69. CONCLUSION High BP can accelerate white matter brain aging among late middle-aged women, providing insights on planning effective control of BP for women in this age group.
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Affiliation(s)
- Li Feng
- Department of Nutrition and Food Science, College of Agriculture & Natural Resources, University of Maryland, College Park
| | - Zhenyao Ye
- Maryland Psychiatric Research Center, Department of Psychiatry
- Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, Maryland
| | - Chen Mo
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Jingtao Wang
- Department of Hematology, Qilu Hospital of Shandong University
| | - Song Liu
- School of Computer Science and Technology, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong, China
| | - Si Gao
- Maryland Psychiatric Research Center, Department of Psychiatry
| | - Hongjie Ke
- Department of Epidemiology and Biostatistics, School of Public Health
| | - Travis A. Canida
- Department of Mathematics, The College of Computer, Mathematical, and Natural Sciences, University of Maryland, College Park, Maryland, USA
| | - Yezhi Pan
- Maryland Psychiatric Research Center, Department of Psychiatry
| | - Marleen M.J. van Greevenbroek
- Department of Internal Medicine, Maastricht University Medical Centre
- CARIM Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands
| | - Alfons J.H.M. Houben
- Department of Internal Medicine, Maastricht University Medical Centre
- CARIM Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands
| | - Kai Wang
- Department of Internal Medicine, Maastricht University Medical Centre
- CARIM Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands
| | | | - Yizhou Ma
- Maryland Psychiatric Research Center, Department of Psychiatry
| | - David K.Y. Lei
- Department of Nutrition and Food Science, College of Agriculture & Natural Resources, University of Maryland, College Park
| | - Chixiang Chen
- Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, Maryland
| | - Braxton D. Mitchell
- Department of Epidemiology and Biostatistics, University of Maryland School of Public Health, College Park, MD, USA
| | - L. Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of Psychiatry
- Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, Maryland
| | - Tianzhou Ma
- Department of Epidemiology and Biostatistics, School of Public Health
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4
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Walters RG, Millwood IY, Lin K, Schmidt Valle D, McDonnell P, Hacker A, Avery D, Edris A, Fry H, Cai N, Kretzschmar WW, Ansari MA, Lyons PA, Collins R, Donnelly P, Hill M, Peto R, Shen H, Jin X, Nie C, Xu X, Guo Y, Yu C, Lv J, Clarke RJ, Li L, Chen Z. Genotyping and population characteristics of the China Kadoorie Biobank. CELL GENOMICS 2023; 3:100361. [PMID: 37601966 PMCID: PMC10435379 DOI: 10.1016/j.xgen.2023.100361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 02/09/2023] [Accepted: 06/24/2023] [Indexed: 08/22/2023]
Abstract
The China Kadoorie Biobank (CKB) is a population-based prospective cohort of >512,000 adults recruited from 2004 to 2008 from 10 geographically diverse regions across China. Detailed data from questionnaires and physical measurements were collected at baseline, with additional measurements at three resurveys involving ∼5% of surviving participants. Analyses of genome-wide genotyping, for >100,000 participants using custom-designed Axiom arrays, reveal extensive relatedness, recent consanguinity, and signatures reflecting large-scale population movements from recent Chinese history. Systematic genome-wide association studies of incident disease, captured through electronic linkage to death and disease registries and to the national health insurance system, replicate established disease loci and identify 14 novel disease associations. Together with studies of candidate drug targets and disease risk factors and contributions to international genetics consortia, these demonstrate the breadth, depth, and quality of the CKB data. Ongoing high-throughput omics assays of collected biosamples and planned whole-genome sequencing will further enhance the scientific value of this biobank.
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Affiliation(s)
- Robin G. Walters
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- MRC Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - Iona Y. Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- MRC Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Dan Schmidt Valle
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Pandora McDonnell
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Alex Hacker
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Daniel Avery
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Ahmed Edris
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Hannah Fry
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Na Cai
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | | | - M. Azim Ansari
- Nuffield Department of Medicine, Oxford University, Oxford OX1 3SY, UK
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
| | - Paul A. Lyons
- Cambridge Institute for Therapeutic Immunology and Infectious Disease, University of Cambridge, Cambridge CB2 0AW, UK
- Department of Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Rory Collins
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Peter Donnelly
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Michael Hill
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- MRC Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - Richard Peto
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Hongbing Shen
- Department of Epidemiology, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing 211116, China
| | - Xin Jin
- BGI-Shenzhen, Shenzhen 518083, China
| | - Chao Nie
- BGI-Shenzhen, Shenzhen 518083, China
| | - Xun Xu
- BGI-Shenzhen, Shenzhen 518083, China
| | - Yu Guo
- Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing 100191, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing 100191, China
| | - Robert J. Clarke
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing 100191, China
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- MRC Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - China Kadoorie Biobank Collaborative Group
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- MRC Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
- Nuffield Department of Medicine, Oxford University, Oxford OX1 3SY, UK
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
- Cambridge Institute for Therapeutic Immunology and Infectious Disease, University of Cambridge, Cambridge CB2 0AW, UK
- Department of Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
- Department of Epidemiology, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing 211116, China
- BGI-Shenzhen, Shenzhen 518083, China
- Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing 100191, China
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5
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McCarthy CP, Natarajan P. Systolic Blood Pressure and Cardiovascular Risk: Straightening the Evidence. Hypertension 2023; 80:577-579. [PMID: 36791225 PMCID: PMC9942105 DOI: 10.1161/hypertensionaha.123.20788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Affiliation(s)
- Cian P McCarthy
- Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Boston (C.P.M., P.N.)
| | - Pradeep Natarajan
- Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Boston (C.P.M., P.N.)
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston (P.N.)
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