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Olshansky B, Ricci F, Fedorowski A. Importance of resting heart rate. Trends Cardiovasc Med 2023; 33:502-515. [PMID: 35623552 DOI: 10.1016/j.tcm.2022.05.006] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 05/20/2022] [Accepted: 05/20/2022] [Indexed: 11/30/2022]
Abstract
Resting heart rate is a determinant of cardiac output and physiological homeostasis. Although a simple, but critical, parameter, this vital sign predicts adverse outcomes, including mortality, and development of diseases in otherwise normal and healthy individuals. Temporal changes in heart rate can have valuable predictive capabilities. Heart rate can reflect disease severity in patients with various medical conditions. While heart rate represents a compilation of physiological inputs, including sympathetic and parasympathetic tone, aside from the underlying intrinsic sinus rate, how resting heart rate affects outcomes is uncertain. Mechanisms relating resting heart rate to outcomes may be disease-dependent but why resting heart rate in otherwise healthy, normal individuals affects outcomes remains obscure. For specific conditions, physiologically appropriate heart rate reductions may improve outcomes. However, to date, in the normal population, evidence that interventions aimed at reducing heart rate improves outcomes remains undefined. Emerging data suggest that reduction in heart rate via vagal activation and/or sympathetic inhibition is propitious.
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Affiliation(s)
- Brian Olshansky
- Division of Cardiology, Department of Internal Medicine, University of Iowa, Iowa City, IA 52242, USA.
| | - Fabrizio Ricci
- Department of Neuroscience, Imaging and Clinical Sciences, "G.d'Annunzio" University of Chieti-Pescara, Via dei Vestini, 33, Chieti 66100, Italy; Department of Clinical Sciences, Lund University, 214 28 Malmö, Sweden
| | - Artur Fedorowski
- Department of Clinical Sciences, Lund University, 214 28 Malmö, Sweden; Department of Cardiology, Karolinska University Hospital, and Department of Medicine, Karolinska Institute, 171 76 Stockholm, Sweden
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2
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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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Ma Y, Qi M, Li K, Wang Y, Ren F, Gao D. Conventional and genetic associations between resting heart rate, cardiac morphology and function as assessed by magnetic resonance imaging: Insights from the UK biobank population study. Front Cardiovasc Med 2023; 10:1110231. [PMID: 37008308 PMCID: PMC10063878 DOI: 10.3389/fcvm.2023.1110231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 02/28/2023] [Indexed: 03/19/2023] Open
Abstract
AimTo examine the direction, strength and causality of the associations of resting heart rate (RHR) with cardiac morphology and function in 20,062 UK Biobank participants.Methods and resultsParticipants underwent cardiac magnetic resonance (CMR) and we extracted CMR biventricular structural and functional metrics using automated pipelines. Multivariate linear regression adjusted for the main cardiovascular risk factors and Two-sample Mendelian Randomization analyses were performed to assess the potential relationship, grouped by heart rate and stratified by sex. Each 10 beats per minute increase in RHR was linked with smaller ventricular structure (lower biventricular end-diastolic volume and end-systolic volume), poorer left ventricular (LV) function (lower LV ejection fraction, global longitude strain and global function index) and unhealthy pattern of LV remodeling (higher values of myocardial contraction fraction), but there is no statistical difference in LV wall thickness. These trends are more pronounced among males and consistent with the causal effect direction of genetic variants interpretation. These observations reflect that RHR has an independent and broad impact on LV remodeling, however, genetically-predicted RHR is not statistically related to heart failure.ConclusionWe demonstrate higher RHR cause smaller ventricular chamber volume, poorer systolic function and unhealthy cardiac remodeling pattern. Our findings provide effective evidence for the potential mechanism of cardiac remodeling and help to explore the potential scope or benefit of intervention.
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Affiliation(s)
- Yao Ma
- Cardiology Diseases Department, Xi’an Jiaotong University Second Affiliated Hospital, Xi’an, China
| | - Mengyao Qi
- Cardiology Diseases Department, Xi’an Jiaotong University Second Affiliated Hospital, Xi’an, China
| | - Kexin Li
- Cardiology Diseases Department, Xi’an Jiaotong University Second Affiliated Hospital, Xi’an, China
| | - Yuan Wang
- Cardiology Diseases Department, Xi’an Jiaotong University Second Affiliated Hospital, Xi’an, China
| | - Fuxian Ren
- Department of Cardiology, Meishan Brach of the Third Affiliated Hospital, Yanan University School of Medical, Meishan, China
- Correspondence: Dengfeng Gao Fuxian Ren
| | - Dengfeng Gao
- Cardiology Diseases Department, Xi’an Jiaotong University Second Affiliated Hospital, Xi’an, China
- Correspondence: Dengfeng Gao Fuxian Ren
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Liu LY, Gu Q, Hu X, Fan J, Liu XZ. Potential Mediators of Causal Associations of Circulating Triglycerides With Blood Pressure: Evidence From Genetic and Observational Data. Hypertension 2022; 79:2439-2447. [DOI: 10.1161/hypertensionaha.122.19510] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Background:
Existing evidence indicates that elevated triglycerides may affect blood pressure, but the underlying mechanisms are not fully understood. Herein, we aim to identify the intermediaries of associations of triglyceride with systolic blood pressure and diastolic blood pressure using the Mendelian randomization (MR) framework.
Methods:
Triglyceride-associated single nucleotide polymorphisms were extracted and used to match phenotypes in PhenoScanner. From the broad spectrum of possible triglyceride-associated traits, potential mediators linking triglyceride to blood pressure were screened out by MR and MR-based mediation analysis. Moreover, cross-sectional observational data of 206 341 adults were used to validate the mediators identified at the genetic level.
Results:
Among the nearly 100 raw phenotypes matched by 313 triglyceride-associated single nucleotide polymorphisms, 39 traits were filtered and integrated into subsequent analysis. By further filtering using MR analysis, only pulse rate and lymphocyte count (LC) were identified as independent mediators. MR-based mediation analysis showed that genetically predicted LC could mediate 9.2% of the association of triglyceride with systolic blood pressure; genetically predicted pulse rate and LC could mediate 18.3% and 17.6% of the association of triglyceride with DBP, respectively. Observational data also support the mediating role of pulse rate and LC.
Conclusions:
The current findings highlighted the mediating role of pulse rate and LC on the causal pathway from triglyceride to blood pressure and may contribute to a better understanding of the pathogenic mechanism by which high triglyceride affects other cardiometabolic factors.
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Affiliation(s)
- Lian Yong Liu
- Department of Endocriology, Punan Hospital of Pudong New District, Shanghai, China (L.Y.L.)
| | - Qing Gu
- Department of Endocrinology, Shidong Hospital, University of Shanghai for Science and Technology, China (Q.G., X.H.)
| | - Xue Hu
- Department of Endocrinology, Shidong Hospital, University of Shanghai for Science and Technology, China (Q.G., X.H.)
| | - Jie Fan
- Zhejiang Police College, Hangzhou, China (J.F.)
| | - Xing Zhen Liu
- Hangzhou Aeronautical Sanatorium for Special Service of China Air Force, China (X.Z.L.)
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Huang T, Wang W, Wang J, Lv J, Yu C, Guo Y, Pei P, Huang N, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Su J, Chen J, Chen Z, Tang Y, Li L. Conventional and Bidirectional Genetic Evidence on Resting Heart Rate and Cardiometabolic Traits. J Clin Endocrinol Metab 2022; 107:e1518-e1527. [PMID: 34850013 DOI: 10.1210/clinem/dgab847] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Indexed: 11/19/2022]
Abstract
CONTEXT Observational studies have suggested that higher resting heart rate (RHR) may be associated with increased cardiometabolic risk. However, causal associations are not fully understood. OBJECTIVE We aimed to examine the direction, strength, and causality of the associations of RHR with cardiometabolic traits. METHODS We assessed the strength of associations between measured RHR and cardiometabolic traits in 506 211 and 372 452 participants from China Kadoorie Biobank (CKB) and UK Biobank (UKB). Mendelian randomization (MR) analyses were used to make causal inferences in 99 228 and 371 508 participants from CKB and UKB, respectively. RESULTS We identified significant directionally concordant observational associations between RHR and higher total cholesterol, triglycerides (TG), low-density lipoprotein, C-reactive protein (CRP), glucose, body mass index, waist-hip ratio (WHR), systolic blood pressure (SBP), and diastolic blood pressure (DBP) after the Bonferroni correction. MR analyses showed that 10 beat/min higher genetically predicted RHR was trans-ethnically associated with a higher DBP (beta 2.059 [95% CI 1.544, 2.574] mmHg in CKB; 2.037 [1.845, 2.229] mmHg in UKB), higher CRP (0.180 [0.057, 0.303] log mg/L in CKB; 0.154 [0.134, 0.174] log mg/L in UKB), higher TG (0.052 [-0.009, 0.113] log mmol/L in CKB; 0.020 [0.010, 0.030] log mmol/L in UKB) and higher WHR (0.218 [-0.033, 0.469] % in CKB; 0.225 [0.111, 0.339] % in UKB). In the opposite direction, higher genetically predicted SBP, TG, glucose, and WHR, and lower high-density lipoprotein, were associated with elevated RHR. CONCLUSION Our large-scale analyses provide causal evidence for associations between RHR and cardiometabolic traits, highlighting the importance of monitoring heat rate as a means of alleviating the adverse effects of metabolic disorders.
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Affiliation(s)
- Tao Huang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China
| | - Wenxiu Wang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Jingjia Wang
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 102308, China
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, 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
| | - Yu Guo
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Pei Pei
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Ninghao Huang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Iona Y Millwood
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Robin G Walters
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Jian Su
- Jiangsu CDC, Nanjing, Jiangsu 210009, China
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Yida Tang
- Department of Cardiology, Peking University Third Hospital, Beijing 100191, China
| | - 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
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