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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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Tan Q, Duan H, Wang A, Zhu D, Li S. Longitudinal analysis of sibling correlation on blood pressure using mixed modeling. Ann Epidemiol 2019; 33:49-53. [PMID: 30904389 DOI: 10.1016/j.annepidem.2019.02.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Revised: 01/25/2019] [Accepted: 02/20/2019] [Indexed: 11/26/2022]
Abstract
PURPOSE Although moderate to high genetic contribution to blood pressure variation have been estimated in numerous studies, the genetic control over the longitudinal change in blood pressure has been less frequently investigated because of the requirement of longitudinal design. METHODS Based on blood pressure data from a large-scale family-based longitudinal survey, we introduced hierarchical modeling of longitudinal family data in combination with fractional polynomials for fitting nonlinear age patterns of blood pressure and the mixed-effect models for estimating sibling correlation on blood pressure to assess the genetic and shared environmental effects on blood pressure level as well as on the rate of change in blood pressure over ages. RESULTS Significant sibling correlations were estimated on the levels of systolic blood pressure (0.2, 95% CI: 0.10-0.30) and diastolic blood pressure (0.28, 95% CI: 0.18-0.38), whereas for the longitudinal change or the rate of change, significant correlation was estimated only for diastolic blood pressure (0.13, 95% CI: 0.04-0.23). In the sex-specific analysis, similar pattern is observed, but statistical significance was only reached in female siblings with correlation estimates higher than the overall sample. CONCLUSION The rate of change in blood pressure is mainly influenced by individual's unique environment; and the genetic and common family environment may play a role in regulating the longitudinal change of diastolic but not systolic blood pressure.
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Affiliation(s)
- Qihua Tan
- Department of Public Health, Epidemiology and Biostatistics, University of Southern Denmark, Odense, Denmark; Department of Clinical Research, Unit of Human Genetics, University of Southern Denmark, Odense, Denmark.
| | - Hongmei Duan
- Institute for Clinical Medicine, Copenhagen University, Denmark
| | - Ancong Wang
- Centre for Reproductive Medicine, Linyi People's Hospital, Linyi, China
| | - Dongyi Zhu
- Centre for Reproductive Medicine, Linyi People's Hospital, Linyi, China
| | - Shuxia Li
- Department of Clinical Research, Unit of Human Genetics, University of Southern Denmark, Odense, Denmark
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Li S, Kyvik KO, Duan H, Zhang D, Pang Z, Hjelmborg J, Tan Q, Kruse T, Dalgård C. Longitudinal Investigation into Genetics in the Conservation of Metabolic Phenotypes in Danish and Chinese Twins. PLoS One 2016; 11:e0162805. [PMID: 27618179 PMCID: PMC5019416 DOI: 10.1371/journal.pone.0162805] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2016] [Accepted: 08/29/2016] [Indexed: 12/02/2022] Open
Abstract
Longitudinal twin studies on long term conservation of individual metabolic phenotypes can help to explore the genetic and environmental basis in maintaining metabolic homeostasis and metabolic health. We performed a longitudinal twin study on 12 metabolic phenotypes from Danish twins followed up for 12 years and Chinese twins traced for 7 years. The study covered a relatively large sample of 502 pairs of Danish adult twins with a mean age at intake of 38 years and a total of 181 Chinese adult twin pairs with a mean baseline age of 39.5 years. Bivariate twin models were fitted to the longitudinal measurements taken at two time points (at baseline and follow-up) to estimate the genetic and environmental contributions to phenotype variation and correlation at and between the two time points. High genetic components in the regulation of intra-individual phenotype correlation or stability over time were estimated in both Danish (h2>0.75 except fasting blood glucose) and Chinese (h2>0.72 except blood pressure) twins; moderate to high genetic contribution to phenotype variation at the two time points were also estimated except for the low genetic regulation on glucose in Danish and on blood pressure in Chinese twins. Meanwhile the bivariate twin models estimated shared environmental contributions to the variance and covariance in fasting blood glucose in Danish twins, and in systolic and diastolic blood pressure, low and high density lipoprotein cholesterol in Chinese twins. Overall, our longitudinal twin study on long-term stability of metabolic phenotypes in Danish and Chinese twins identified a common pattern of high genetic control over phenotype conservation, and at the same time revealed population-specific patterns of genetic and common environmental regulation on the variance as well as covariance of glucose and blood pressure.
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Affiliation(s)
- Shuxia Li
- Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
- * E-mail:
| | - Kirsten Ohm Kyvik
- Department of Clinical Research, University of Southern Denmark, and Odense Patient data Explorative Network (OPEN), Odense University Hospital, Odense, Denmark
| | - Haiping Duan
- Qingdao Center for Disease Control and Prevention, Qingdao, China
| | - Dongfeng Zhang
- Department of Public Health, Qingdao University Medical College, Qingdao, China
| | - Zengchang Pang
- Qingdao Center for Disease Control and Prevention, Qingdao, China
| | - Jacob Hjelmborg
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Qihua Tan
- Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Torben Kruse
- Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Christine Dalgård
- Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark
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Li S, Kyvik KO, Pang Z, Zhang D, Duan H, Tan Q, Hjelmborg J, Kruse T, Dalgård C. Genetic and Environmental Regulation on Longitudinal Change of Metabolic Phenotypes in Danish and Chinese Adult Twins. PLoS One 2016; 11:e0148396. [PMID: 26862898 PMCID: PMC4749287 DOI: 10.1371/journal.pone.0148396] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2015] [Accepted: 01/18/2016] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVE The rate of change in metabolic phenotypes can be highly indicative of metabolic disorders and disorder-related modifications. We analyzed data from longitudinal twin studies on multiple metabolic phenotypes in Danish and Chinese twins representing two populations of distinct ethnic, cultural, social-economic backgrounds and geographical environments. MATERIALS AND METHODS The study covered a relatively large sample of 502 pairs of Danish adult twins followed up for a long period of 12 years with a mean age at intake of 38 years (range: 18-65) and a total of 181 Chinese adult twin pairs traced for about 7 years with a mean baseline age of 39.5 years (range: 23-64). The classical twin models were fitted to the longitudinal change in each phenotype (Δphenotype) to estimate the genetic and environmental contributions to the variation in Δphenotype. RESULTS Moderate to high contributions by the unique environment were estimated for all phenotypes in both Danish (from 0.51 for low density lipoprotein cholesterol up to 0.72 for triglycerides) and Chinese (from 0.41 for triglycerides up to 0.73 for diastolic blood pressure) twins; low to moderate genetic components were estimated for long-term change in most of the phenotypes in Danish twins except for triglycerides and hip circumference. Compared with Danish twins, the Chinese twins tended to have higher genetic control over the longitudinal changes in lipids (except high density lipoprotein cholesterol) and glucose, higher unique environmental contribution to blood pressure but no genetic contribution to longitudinal change in body mass traits. CONCLUSION Our results emphasize the major contribution of unique environment to the observed intra-individual variation in all metabolic phenotypes in both samples, and meanwhile reveal differential patterns of genetic and common environmental regulation on changes over time in metabolic phenotypes across the two samples.
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Affiliation(s)
- Shuxia Li
- Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
- * E-mail:
| | - Kirsten Ohm Kyvik
- Department of Clinical Research, University of Southern Denmark, and Odense Patient data Explorative Network (OPEN), Odense University Hospital, Odense, Denmark
| | - Zengchang Pang
- Qingdao Center for Disease Control and Prevention, Qingdao, China
| | - Dongfeng Zhang
- Department of Public Health, Qingdao University Medical College, Qingdao, China
| | - Haiping Duan
- Qingdao Center for Disease Control and Prevention, Qingdao, China
| | - Qihua Tan
- Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Jacob Hjelmborg
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Torben Kruse
- Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Christine Dalgård
- Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark
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