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Nurkkala J, Vaura F, Toivonen J, Niiranen T. Genetics of hypertension-related sex differences and hypertensive disorders of pregnancy. Blood Press 2024; 33:2408574. [PMID: 39371034 DOI: 10.1080/08037051.2024.2408574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2024] [Revised: 09/16/2024] [Accepted: 09/19/2024] [Indexed: 10/08/2024]
Abstract
Background: Hypertension and hypertensive disorders of pregnancy (HDP) cause a significant burden of disease on societies and individuals by increasing cardiovascular disease risk. Environmental risk factors alone do not explain the observed sexual dimorphism in lifetime blood pressure (BP) trajectories nor inter-individual variation in HDP risk. Methods: In this short review, we focus on the genetics of hypertension-related sex differences and HDP and discuss the importance of genetics utilization for sex-specific hypertension risk prediction. Results: Population and twin studies estimate that 28-66% of variation in BP levels and HDP is explained by genetic variation, while genomic wide association studies suggest that BP traits and HDP partly share a common genetic background. Moreover, environmental and epigenetic regulation of these genes differ by sex and oestrogen receptors in particular are shown to convey cardio- and vasculoprotective effects through epigenetic regulation of DNA. The majority of known genetic variation in hypertension and HDP is polygenic. Polygenic risk scores for BP display stronger associations with hypertension risk in women than in men and are associated with sex-specific age of hypertension onset. Monogenic forms of hypertension are rare and mostly present equally in both sexes. Conclusion: Despite recent genetic discoveries providing new insights into HDP and sex differences in BP traits, further research is needed to elucidate the underlying biology. Emphasis should be placed on demonstrating the added clinical value of these genetic discoveries, which may eventually facilitate genomics-based personalized treatments for hypertension and HDP.
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Affiliation(s)
- Jouko Nurkkala
- Division of Perioperative Services, Intensive Care and Pain Medicine, Turku University Hospital, Turku, Finland
- Department of Anesthesiology and Intensive Care, University of Turku, Turku, Finland
| | - Felix Vaura
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Jenni Toivonen
- Division of Perioperative Services, Intensive Care and Pain Medicine, Turku University Hospital, Turku, Finland
- Department of Anesthesiology and Intensive Care, University of Turku, Turku, Finland
| | - Teemu Niiranen
- Department of Internal Medicine, University of Turku, Turku, Finland
- Division of Medicine, Turku University Hospital, Turku, Finland
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Turku, Finland
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Jüres F, Kaufmann C, Riesel A, Grützmann R, Heinzel S, Elsner B, Bey K, Wagner M, Kathmann N, Klawohn J. Heart rate and heart rate variability in obsessive-compulsive disorder: Evidence from patients and unaffected first-degree relatives. Biol Psychol 2024; 189:108786. [PMID: 38531496 DOI: 10.1016/j.biopsycho.2024.108786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 03/16/2024] [Accepted: 03/22/2024] [Indexed: 03/28/2024]
Abstract
Altered heart rate (HR) and heart rate variability (HRV) are common observations in psychiatric disorders. Yet, few studies have examined these cardiac measures in obsessive-compulsive disorder (OCD). The current study aimed to investigate HR and HRV, indexed by the root mean square of successive differences (RMSSD) and further time domain indices, as putative biological characteristics of OCD. Electrocardiogram was recorded during a five-minute resting state. Group differences between patients with OCD (n = 96), healthy participants (n = 112), and unaffected first-degree relatives of patients with OCD (n = 47) were analyzed. As potential moderators of group differences, we examined the influence of age and medication, respectively. As results indicated, patients with OCD showed higher HR and lower HRV compared to healthy participants. These group differences were not moderated by age. Importantly, subgroup analyses showed that only medicated patients displayed lower HRV compared to healthy individuals, while HR alterations were evident in unmedicated patients. Regarding unaffected first-degree relatives, group differences in HRV remained at trend level. Further, an age-moderated group differentiation showed that higher HRV distinguished relatives from healthy individuals in young adulthood, whereas at higher age lower HRV was indicative of relatives. Both the role of familial risk and medication in HRV alterations need further elucidation. Pending future studies, alterations in HR and potentially HRV might serve as useful indices to characterize the pathophysiology of OCD.
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Affiliation(s)
- Franziska Jüres
- Humboldt-Universität zu Berlin, Department of Psychology, Berlin, Germany.
| | - Christian Kaufmann
- Humboldt-Universität zu Berlin, Department of Psychology, Berlin, Germany
| | - Anja Riesel
- Humboldt-Universität zu Berlin, Department of Psychology, Berlin, Germany; Universität Hamburg, Department of Psychology, Hamburg, Germany
| | - Rosa Grützmann
- Humboldt-Universität zu Berlin, Department of Psychology, Berlin, Germany; MSB Medical School Berlin, Department of Psychology, Berlin, Germany
| | - Stephan Heinzel
- Humboldt-Universität zu Berlin, Department of Psychology, Berlin, Germany; Freie Universität Berlin, Department of Education and Psychology, Berlin, Germany; TU Dortmund University, Department of Educational Sciences and Psychology, Dortmund, Germany
| | - Björn Elsner
- Humboldt-Universität zu Berlin, Department of Psychology, Berlin, Germany
| | - Katharina Bey
- University Hospital Bonn, Department of Psychiatry and Psychotherapy, Bonn, Germany
| | - Michael Wagner
- University Hospital Bonn, Department of Psychiatry and Psychotherapy, Bonn, Germany
| | - Norbert Kathmann
- Humboldt-Universität zu Berlin, Department of Psychology, Berlin, Germany
| | - Julia Klawohn
- Humboldt-Universität zu Berlin, Department of Psychology, Berlin, Germany; MSB Medical School Berlin, Department of Medicine, Berlin, Germany
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Ballin M, Neovius M, Ortega FB, Henriksson P, Nordström A, Berglind D, Nordström P, Ahlqvist VH. Genetic and Environmental Factors and Cardiovascular Disease Risk in Adolescents. JAMA Netw Open 2023; 6:e2343947. [PMID: 37976057 PMCID: PMC10656641 DOI: 10.1001/jamanetworkopen.2023.43947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 10/09/2023] [Indexed: 11/19/2023] Open
Abstract
Importance Cardiovascular risk factors in youth have been associated with future cardiovascular disease (CVD), but conventional observational studies are vulnerable to genetic and environmental confounding. Objective To examine the role of genetic and environmental factors shared by full siblings in the association of adolescent cardiovascular risk factors with future CVD. Design, Setting, and Participants This is a nationwide cohort study with full sibling comparisons. All men who underwent mandatory military conscription examinations in Sweden between 1972 and 1995 were followed up until December 31, 2016. Data analysis was performed from May 1 to November 10, 2022. Exposures Body mass index (BMI), cardiorespiratory fitness, blood pressure, handgrip strength, and a combined risk z score in late adolescence. Main Outcomes and Measures The primary outcome was fatal or nonfatal CVD, as recorded in the National Inpatient Register or the Cause of Death Register before 2017. Results A total of 1 138 833 men (mean [SD] age, 18.3 [0.8] years), of whom 463 995 were full brothers, were followed up for a median (IQR) of 32.1 (26.7-37.7) years, during which 48 606 experienced a CVD outcome (18 598 among full brothers). All risk factors were associated with CVD, but the effect of controlling for unobserved genetic and environmental factors shared by full siblings varied. In the sibling analysis, hazard ratios for CVD (top vs bottom decile) were 2.10 (95% CI, 1.90-2.32) for BMI, 0.77 (95% CI, 0.68-0.88) for cardiorespiratory fitness, 1.45 (95% CI, 1.32-1.60) for systolic blood pressure, 0.90 (95% CI, 0.82-0.99) for handgrip strength, and 2.19 (95% CI, 1.96-2.46) for the combined z score. The percentage attenuation in these hazard ratios in the sibling vs total cohort analysis ranged from 1.1% for handgrip strength to 40.0% for cardiorespiratory fitness. Consequently, in the sibling analysis, the difference in cumulative CVD incidence at age 60 years (top vs bottom decile) was 7.2% (95% CI, 5.9%-8.6%) for BMI and 1.8% (95% CI, 1.0%-2.5%) for cardiorespiratory fitness. Similarly, in the sibling analysis, hypothetically shifting everyone in the worst deciles of BMI to the middle decile would prevent 14.9% of CVD at age 60 years, whereas the corresponding number for cardiorespiratory fitness was 5.3%. Conclusions and Relevance In this Swedish national cohort study, cardiovascular risk factors in late adolescence, especially a high BMI, were important targets for CVD prevention, independently of unobserved genetic and environmental factors shared by full siblings. However, the role of adolescent cardiorespiratory fitness in CVD may have been overstated by conventional observational studies.
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Affiliation(s)
- Marcel Ballin
- Centre for Epidemiology and Community Medicine, Region Stockholm, Stockholm, Sweden
- Department of Public Health and Caring Sciences, Clinical Geriatrics, Uppsala University, Uppsala, Sweden
| | - Martin Neovius
- Department of Medicine, Clinical Epidemiology Division, Karolinska Institutet, Stockholm, Sweden
| | - Francisco B. Ortega
- Department of Physical Education and Sports, Faculty of Sport Sciences, Sport and Health University Research Institute, University of Granada, Granada, Spain
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Granada, Spain
| | - Pontus Henriksson
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Anna Nordström
- Rehabilitation and Pain Centre, Uppsala University Hospital, Uppsala, Sweden
- School of Sport Sciences, UiT the Arctic University of Norway, Tromsø, Norway
- Department of Health Sciences, The Swedish Winter Sport Research Centre, Mid Sweden University, Östersund, Sweden
| | - Daniel Berglind
- Centre for Epidemiology and Community Medicine, Region Stockholm, Stockholm, Sweden
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
| | - Peter Nordström
- Department of Public Health and Caring Sciences, Clinical Geriatrics, Uppsala University, Uppsala, Sweden
| | - Viktor H. Ahlqvist
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
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Ropponen A, Narusyte J, Wang M, Silventoinen K, Böckerman P, Svedberg P. Genetic and environmental contributions to individual differences in sustainable working life-A Swedish twin cohort study. PLoS One 2023; 18:e0289074. [PMID: 37498854 PMCID: PMC10374081 DOI: 10.1371/journal.pone.0289074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 07/10/2023] [Indexed: 07/29/2023] Open
Abstract
Although genetics is known to have a role in sickness absences (SA), disability pensions (DP) and in their mutual associations, the empirical knowledge is scarce on not having these interruptions, i.e., sustainable working life. Hence, we aimed to investigate how genetic and environmental factors affect individual variation in sustainable working life in short-term (two consecutive years) and in long-term (22 years of follow-up) using the classical twin modeling based on different genetic relatedness of mono- and dizygotic twins. The final sample (n = 51 071) included Swedish same-sex twins with known zygosity born between 1930 and 1990 (53% women) with complete national register data of employment, SA, DP, unemployment, old-age pension, emigration, and death. For the short-term sustainable working life, genetic factors explained 36% (95% confidence intervals (CI) 31-41%), environmental factors shared by co-twins such as family background 8% (95% CI 5-14%) and environmental factors unique to each twin individual 56% (95% CI 56-56%) on the individual differences. For the long-term sustainable working life, the largest proportions on individual differences were explained by environmental factors shared by co-twins (46%, 95% CI 44-48%) and unique to each twin individual (37% 95% CI 36-38%) whereas a small proportion was explained by genetic factors (18%, 95%CI 14-22%). To conclude, short-term sustainable working life was explained to a large extent by unique environment and to lesser extent by genetic factors whereas long-term (22 years) sustainable working life had both moderate unique and common environmental effect, and to lower extent genetic effects contributing to individual differences. These findings suggest that sustainable working life have different short- and long-term predictors.
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Affiliation(s)
- Annina Ropponen
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Finnish Institute of Occupational Health, Helsinki, Finland
| | - Jurgita Narusyte
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Mo Wang
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Karri Silventoinen
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - Petri Böckerman
- School of Business and Economics, University of Jyväskylä, Jyväskylä, Finland
- Labour Institute for Economic Research LABORE, Helsinki, Finland
- IZA Institute of Labor Economics, Bonn, Germany
| | - Pia Svedberg
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
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Zheng H, Ye Y, Huang H, Huang C, Gao W, Wang M, Li W, Zhou R, Jiang J, Wang S, Yu C, Lv J, Wu X, Huang X, Cao W, Yan Y, Zheng K, Wu T, Li L. A pedigree-based cohort to study the genetic risk factors for cardiometabolic diseases: study design, baseline characteristics and preliminary results. Front Public Health 2023; 11:1189993. [PMID: 37521988 PMCID: PMC10374840 DOI: 10.3389/fpubh.2023.1189993] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 06/26/2023] [Indexed: 08/01/2023] Open
Abstract
Background We initiated the Fujian Tulou Pedigree-based Cohort (FTPC) as the integration of extended pedigrees and prospective cohort to clarify the genetic and environmental risk factors of cardiometabolic diseases. Methods FTPC was carried out in Nanjing County, Fujian Province, China from August 2015 to December 2017 to recruit probands with the same surnames and then enroll their first-degree and more distant relatives. The participants were asked to complete questionnaire interview, physical examination, and blood collection. According to the local genealogical booklets and family registry, we reconstructed extended pedigrees to estimate the heritability of cardiometabolic traits. The follow-up of FTPC is scheduled every 5 years in the future. Results The baseline survey interviewed 2,727 individuals in two clans. A total of 1,563 adult subjects who completed all baseline examinations were used to reconstruct pedigrees and 452 extended pedigrees were finally identified, including one seven-generation pedigree, two five-generation pedigrees, 23 four-generation pedigrees, 186 three-generation pedigrees, and 240 two-generation pedigrees. The average age of the participants was 57.4 years, with 43.6% being males. The prevalence of hypertension, diabetes and dyslipidemia in FTPC were 49.2, 10.0, and 45.2%, respectively. Based on the pedigree structure, the heritability of systolic blood pressure, diastolic blood pressure, fast blood glucose, total cholesterol, triglyceride, high-density lipoprotein, and low-density lipoprotein was estimated at 0.379, 0.306, 0.386, 0.452, 0.568, 0.852, and 0.387, respectively. Conclusion As an extended pedigree cohort in China, FTPC will provide an important source to study both genetic and environmental risk factors prospectively.
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Affiliation(s)
- Hongchen Zheng
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Laboratory of Genetics, Peking University Cancer Hospital and Institute, Beijing, China
| | - Ying Ye
- Department of Local Diseases Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Hui Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Chunlan Huang
- Department of Hygiene, Nanjing Country Center for Disease Control and Prevention, Nanjing, China
| | - Wenjing Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Mengying Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Wenyong Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Ren Zhou
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Jin Jiang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Siyue Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, China
| | - Xiaoling Wu
- Department of Hygiene, Nanjing Country Center for Disease Control and Prevention, Nanjing, China
| | - Xiaoming Huang
- Department of Hygiene, Nanjing Country Center for Disease Control and Prevention, Nanjing, China
| | - Weihua Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Yansheng Yan
- Department of Local Diseases Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Kuicheng Zheng
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Tao Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
- Key Laboratory of Reproductive Health, Ministry of Health, Beijing, China
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, China
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Ciochetti NP, Lugli-Moraes B, da Silva BS, Rovaris DL. Genome-wide association studies: utility and limitations for research in physiology. J Physiol 2023; 601:2771-2799. [PMID: 37208942 PMCID: PMC10527550 DOI: 10.1113/jp284241] [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: 01/31/2023] [Accepted: 05/10/2023] [Indexed: 05/21/2023] Open
Abstract
Physiological systems are subject to interindividual variation encoded by genetics. Genome-wide association studies (GWAS) operate by surveying thousands of genetic variants from a substantial number of individuals and assessing their association to a trait of interest, be it a physiological variable, a molecular phenotype (e.g. gene expression), or even a disease or condition. Through a myriad of methods, GWAS downstream analyses then explore the functional consequences of each variant and attempt to ascertain a causal relationship to the phenotype of interest, as well as to delve into its links to other traits. This type of investigation allows mechanistic insights into physiological functions, pathological disturbances and shared biological processes between traits (i.e. pleiotropy). An exciting example is the discovery of a new thyroid hormone transporter (SLC17A4) and hormone metabolising enzyme (AADAT) from a GWAS on free thyroxine levels. Therefore, GWAS have substantially contributed with insights into physiology and have been shown to be useful in unveiling the genetic control underlying complex traits and pathological conditions; they will continue to do so with global collaborations and advances in genotyping technology. Finally, the increasing number of trans-ancestry GWAS and initiatives to include ancestry diversity in genomics will boost the power for discoveries, making them also applicable to non-European populations.
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Affiliation(s)
- Nicolas Pereira Ciochetti
- Laboratory of Physiological Genomics of Mental Health (PhysioGen Lab), Instituto de Ciencias Biomedicas Universidade de Sao Paulo, São Paulo, Brazil
| | - Beatriz Lugli-Moraes
- Laboratory of Physiological Genomics of Mental Health (PhysioGen Lab), Instituto de Ciencias Biomedicas Universidade de Sao Paulo, São Paulo, Brazil
| | - Bruna Santos da Silva
- Laboratory of Physiological Genomics of Mental Health (PhysioGen Lab), Instituto de Ciencias Biomedicas Universidade de Sao Paulo, São Paulo, Brazil
- Laboratory of Developmental Psychiatry, Center of Experimental Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil
| | - Diego Luiz Rovaris
- Laboratory of Physiological Genomics of Mental Health (PhysioGen Lab), Instituto de Ciencias Biomedicas Universidade de Sao Paulo, São Paulo, Brazil
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Hellwege JN, Stallings SC, Piekos JA, Jasper EA, Aronoff DM, Edwards TL, Velez Edwards DR. Association of genetically-predicted placental gene expression with adult blood pressure traits. J Hypertens 2023; 41:1024-1032. [PMID: 37016918 PMCID: PMC10287061 DOI: 10.1097/hjh.0000000000003427] [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: 04/06/2023]
Abstract
OBJECTIVE Blood pressure is a complex, polygenic trait, and the need to identify prehypertensive risks and new gene targets for blood pressure control therapies or prevention continues. We hypothesize a developmental origins model of blood pressure traits through the life course where the placenta is a conduit mediating genomic and nongenomic transmission of disease risk. Genetic control of placental gene expression has recently been described through expression quantitative trait loci (eQTL) studies which have identified associations with childhood phenotypes. METHODS We conducted a transcriptome-wide gene expression analysis estimating the predicted gene expression of placental tissue in adult individuals with genome-wide association study (GWAS) blood pressure summary statistics. We constructed predicted expression models of 15 154 genes from reference placenta eQTL data and investigated whether genetically-predicted gene expression in placental tissue is associated with blood pressure traits using published GWAS summary statistics. Functional annotation of significant genes was generated using FUMA. RESULTS We identified 18, 9, and 21 genes where predicted expression in placenta was significantly associated with systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP), respectively. There were 14 gene-tissue associations (13 unique genes) significant only in placenta. CONCLUSIONS In this meta-analysis using S-PrediXcan and GWAS summary statistics, the predicted expression in placenta of 48 genes was statistically significantly associated with blood pressure traits. Notable findings included the association of FGFR1 expression with increased SBP and PP. This evidence of gene expression variation in placenta preceding the onset of adult blood pressure phenotypes is an example of extreme preclinical biological changes which may benefit from intervention.
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Affiliation(s)
- Jacklyn N Hellwege
- Department of Medicine, Division of Genetic Medicine
- Vanderbilt Genetics Institute
| | - Sarah C Stallings
- Department of Medicine, Division of Genetic Medicine
- Vanderbilt Genetics Institute
| | - Jacqueline A Piekos
- Vanderbilt Genetics Institute
- Department of Obstetrics and Gynecology, Division of Quantitative Sciences
| | - Elizabeth A Jasper
- Department of Obstetrics and Gynecology, Division of Quantitative Sciences
| | - David M Aronoff
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Todd L Edwards
- Vanderbilt Genetics Institute
- Department of Medicine, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Digna R Velez Edwards
- Vanderbilt Genetics Institute
- Department of Obstetrics and Gynecology, Division of Quantitative Sciences
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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8
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Xiao Z, Xu C, Liu Q, Yan Q, Liang J, Weng Z, Zhang X, Xu J, Hang D, Gu A. Night Shift Work, Genetic Risk, and Hypertension. Mayo Clin Proc 2022; 97:2016-2027. [PMID: 35995626 DOI: 10.1016/j.mayocp.2022.04.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 04/04/2022] [Accepted: 04/05/2022] [Indexed: 12/15/2022]
Abstract
OBJECTIVE To perform a prospective cohort study to investigate whether night shift work is associated with incident hypertension and whether this association is modified by genetic susceptibility to hypertension because evidence on the association between night shift work and hypertension is insufficient. METHODS A total of 232,665 participants of UK Biobank who were recruited from 2006 to 2010 and observed to January 31, 2018, were included in this study. A Cox proportional hazards model with covariate adjustment was performed to assess the association between night shift work exposure and hypertension risk. We constructed a polygenic risk score (PRS) for genetic susceptibility to hypertension, which was used to explore whether genetic susceptibility to hypertension modified the effect of night shift work. The robustness of the results was assessed by sensitivity analysis. RESULTS Night shift workers had a higher hypertension risk than day shift workers, which increased with increasing frequency of night shift work (Ptrend<.001). The association was attenuated but still remained statistically significant in the fully adjusted model. We explored the joint effect of night shift work and genetic susceptibility on hypertension. Permanent night shift workers with higher hypertension PRSs had higher risk of hypertension than day workers with low PRSs. CONCLUSION Night shift work exposure was associated with increased hypertension risk, which was modified by the genetic risk for hypertension, indicating that there is a joint effect of night shift work and genetic risk on hypertension.
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Affiliation(s)
- Zhihao Xiao
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Cheng Xu
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China.
| | - Qian Liu
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China; Gusu School, Nanjing Medical University, Nanjing, China
| | - Qing Yan
- Department of Neurosurgery, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Jingjia Liang
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Zhenkun Weng
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Xin Zhang
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Jin Xu
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China; Department of Maternal, Child, and Adolescent Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Dong Hang
- Department of Epidemiology and Biostatistics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Aihua Gu
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China.
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Xia K, Zhang L, Tang L, Huang T, Fan D. Assessing the role of blood pressure in amyotrophic lateral sclerosis: a Mendelian randomization study. Orphanet J Rare Dis 2022; 17:56. [PMID: 35172853 PMCID: PMC8848798 DOI: 10.1186/s13023-022-02212-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 02/06/2022] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Observational studies have suggested a close but controversial relationship between blood pressure (BP) and amyotrophic lateral sclerosis (ALS). It remains unclear whether this association is causal. The authors employed a bidirectional two-sample Mendelian randomization (MR) approach to evaluate the causal relationship between BP and ALS. Genetic proxies for systolic blood pressure (SBP), diastolic blood pressure (DBP), antihypertensive drugs (AHDs), ALS, and their corresponding genome-wide association study (GWAS) summary datasets were obtained from the most recent studies with the largest sample sizes. The inverse variance weighted (IVW) method was adopted as the main approach to examine the effect of BP on ALS and four other MR methods were used for sensitivity analyses. To exclude the interference between SBP and DBP, a multivariable MR approach was used. RESULTS We found that genetically determined increased DBP was a protective factor for ALS (OR = 0.978, 95% CI 0.960-0.996, P = 0.017) and that increased SBP was an independent risk factor for ALS (OR = 1.014, 95% CI 1.003-1.025, P = 0.015), which is supported by sensitivity analyses. The use of calcium channel blocker (CCB) showed a causal relationship with ALS (OR = 0.985, 95% CI 0.971-1.000, P = 0.049). No evidence was revealed that ALS caused changes in BP. CONCLUSIONS This study provides genetic support for a causal effect of BP and ALS that increased DBP has a protective effect on ALS, and increased SBP is a risk factor for ALS, which may be related to sympathetic excitability. Blood pressure management is essential in ALS, and CCB may be a promising candidate.
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Affiliation(s)
- Kailin Xia
- Department of Neurology, Peking University Third Hospital, Garden North Road No. 49, Beijing, 100191, China.,Beijing Municipal Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases, Beijing, China
| | - Linjing Zhang
- Department of Neurology, Peking University Third Hospital, Garden North Road No. 49, Beijing, 100191, China.,Beijing Municipal Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases, Beijing, China
| | - Lu Tang
- Department of Neurology, Peking University Third Hospital, Garden North Road No. 49, Beijing, 100191, China.,Beijing Municipal Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases, Beijing, China
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China. .,Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing, China.
| | - Dongsheng Fan
- Department of Neurology, Peking University Third Hospital, Garden North Road No. 49, Beijing, 100191, China. .,Beijing Municipal Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases, Beijing, China. .,Key Laboratory for Neuroscience, National Health Commission/Ministry of Education, Peking University, Beijing, China.
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10
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Xhaard C, Dandine-Roulland C, Villemereuil PD, Floch EL, Bacq-Daian D, Machu JL, Ferreira JP, Deleuze JF, Zannad F, Rossignol P, Girerd N. Heritability of a resting heart rate in a 20-year follow-up family cohort with GWAS data: Insights from the STANISLAS cohort. Eur J Prev Cardiol 2021; 28:1334-1341. [PMID: 34647585 DOI: 10.1177/2047487319890763] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Accepted: 11/05/2019] [Indexed: 11/17/2022]
Abstract
BACKGROUND The association between resting heart rate (HR) and cardiovascular outcomes, especially heart failure, is now well established. However, whether HR is mainly an integrated marker of risk associated with other features, or rather a genetic origin risk marker, is still a matter for debate. Previous studies reported a heritability ranging from 14% to 65%. DESIGN We assessed HR heritability in the STANISLAS family-study, based on the data of four visits performed over a 20-year period, and adjusted for most known confounding effects. METHODS These analyses were conducted using a linear mixed model, adjusted on age, sex, tea or coffee consumption, beta-blocker use, physical activity, tobacco use, and alcohol consumption to estimate the variance captured by additive genetic effects, via average information restricted maximum likelihood analysis, with both self-reported pedigree and genetic relatedness matrix (GRM) calculated from genome-wide association study data. RESULTS Based on the data of all visits, the HR heritability (h2) estimate was 23.2% with GRM and 24.5% with pedigree. However, we found a large heterogeneity of HR heritability estimations when restricting the analysis to each of the four visits (h2 from 19% to 39% using pedigree, and from 14% to 32% using GRM). Moreover, only a little part of variance was explained by the common household effect (<5%), and half of the variance remained unexplained. CONCLUSION Using a comprehensive analysis based on a family cohort, including the data of multiple visits and GRM, we found that HR variability is about 25% from genetic origin, 25% from repeated measures and 50% remains unexplained.
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Affiliation(s)
- Constance Xhaard
- INSERM Centre d'Investigation Clinique CIC-P 1433, CHRU Nancy, INSERM U1116, FCRIN INI-CRCT, Lorraine Université, Nancy, France
| | - Claire Dandine-Roulland
- Centre National de Recherche en Génomique Humaine (CNRGH), Institut de Biologie François Jacob, CEA, Université Paris-Saclay, Evry, France
| | - Pierre de Villemereuil
- CEFE, CNRS, Université de Montpellier, Université Paul Valéry Montpellier 3, EPHE, IRD, Montpellier, France
| | - Edith Le Floch
- Centre National de Recherche en Génomique Humaine (CNRGH), Institut de Biologie François Jacob, CEA, Université Paris-Saclay, Evry, France
| | - Delphine Bacq-Daian
- Centre National de Recherche en Génomique Humaine (CNRGH), Institut de Biologie François Jacob, CEA, Université Paris-Saclay, Evry, France
| | - Jean-Loup Machu
- INSERM Centre d'Investigation Clinique CIC-P 1433, CHRU Nancy, INSERM U1116, FCRIN INI-CRCT, Lorraine Université, Nancy, France
| | - Joao Pedro Ferreira
- INSERM Centre d'Investigation Clinique CIC-P 1433, CHRU Nancy, INSERM U1116, FCRIN INI-CRCT, Lorraine Université, Nancy, France
| | - Jean-François Deleuze
- Centre National de Recherche en Génomique Humaine (CNRGH), Institut de Biologie François Jacob, CEA, Université Paris-Saclay, Evry, France
| | - Faiez Zannad
- INSERM Centre d'Investigation Clinique CIC-P 1433, CHRU Nancy, INSERM U1116, FCRIN INI-CRCT, Lorraine Université, Nancy, France
| | - Patrick Rossignol
- INSERM Centre d'Investigation Clinique CIC-P 1433, CHRU Nancy, INSERM U1116, FCRIN INI-CRCT, Lorraine Université, Nancy, France
| | - Nicolas Girerd
- INSERM Centre d'Investigation Clinique CIC-P 1433, CHRU Nancy, INSERM U1116, FCRIN INI-CRCT, Lorraine Université, Nancy, France
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11
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Ropponen A, Wang M, Narusyte J, Kärkkäinen S, Blom V, Svedberg P. The role of sickness absence diagnosis for the risk of future inpatient- or specialized outpatient care in a Swedish population-based twin sample. BMC Public Health 2021; 21:957. [PMID: 34016075 PMCID: PMC8136267 DOI: 10.1186/s12889-021-10942-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2021] [Accepted: 04/27/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Studies of consequences of sickness absence such as health and well-being have been rare whereas risk factors for sickness absence have been studied extensively. This study assumed the consequences of sickness absence would differ by diagnostic group or by patient care type. The aim was to investigate sickness absence due to various diagnosis groups as a predictor for subsequent inpatient- and specialized outpatient care while controlling for familial confounding. METHODS We utilized the register data of 69,552 twin individuals between 16 and 80 years of age (48% women). The first incident sickness absence spell, from baseline year 2005, including diagnosis of sickness absence was our primary exposure of interest and we followed them until the first incident inpatient- and specialized outpatient care episode with main diagnosis code or until 31.12.2013. RESULTS A total of 7464 incident sickness absence spells took place (11%), 42% had inpatient care and 83% specialized outpatient care (mean follow-up time 3.2 years, SD 3.1 years). All the main sickness absence diagnosis groups were associated with increased risk of future care in comparison to no sickness absence. Controlling for confounders attenuated the associations in magnitude but with retaining direction, and we could not confirm an effect of familial factors. CONCLUSIONS Sickness absence predicts both inpatient- and specialized outpatient care and the association is universal across diagnosis groups. The lower survival time and incidence rates of inpatient than specialized outpatient care point towards severity of diseases assumption. This finding was also universal across sickness absence diagnosis groups.
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Affiliation(s)
- Annina Ropponen
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, SE-171 77, Stockholm, Sweden.
- Finnish Institute of Occupational Health, Helsinki, Finland.
| | - Mo Wang
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, SE-171 77, Stockholm, Sweden
| | - Jurgita Narusyte
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, SE-171 77, Stockholm, Sweden
- Center of Epidemiology and Community Medicine, Stockholm County Council, Stockholm, Sweden
| | - Sanna Kärkkäinen
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, SE-171 77, Stockholm, Sweden
| | - Victoria Blom
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, SE-171 77, Stockholm, Sweden
- The Swedish School of Sport and Health Sciences, Stockholm, Sweden
| | - Pia Svedberg
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, SE-171 77, Stockholm, Sweden
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12
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Azevêdo LM, Santos LS, Pardono E, Almeida JA, Menezes AS. Physical Activity Level, Anthropometric and Cardiovascular Profile Among Students in Sergipe State Attending Public Schools. INTERNATIONAL JOURNAL OF CARDIOVASCULAR SCIENCES 2020. [DOI: 10.36660/ijcs.20200050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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13
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Tegegne BS, Man T, van Roon AM, Asefa NG, Riese H, Nolte I, Snieder H. Heritability and the Genetic Correlation of Heart Rate Variability and Blood Pressure in >29 000 Families: The Lifelines Cohort Study. Hypertension 2020; 76:1256-1262. [PMID: 32829661 PMCID: PMC7480943 DOI: 10.1161/hypertensionaha.120.15227] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 05/05/2020] [Accepted: 07/23/2020] [Indexed: 12/21/2022]
Abstract
Dysregulation of the cardiac autonomic nervous system, as indexed by reduced heart rate variability (HRV), has been associated with the development of high blood pressure (BP). However, the underlying pathological mechanisms are not yet fully understood. This study aimed to estimate heritability of HRV and BP and to determine their genetic overlap. We used baseline data of the 3-generation Lifelines population-based cohort study (n=149 067; mean age, 44.5). In-house software was used to calculate root mean square of successive differences and SD of normal-to-normal intervals as indices of HRV based on 10-second resting ECGs. BP was recorded with an automatic BP monitor. We estimated heritabilities and genetic correlations with variance components methods in ASReml software. We additionally estimated genetic correlations with bivariate linkage disequilibrium score regression using publicly available genome-wide association study data. The heritability (SE) estimates were 15.6% (0.90%) for SD of normal-to-normal intervals and 17.9% (0.90%) for root mean square of successive differences. For BP measures, they ranged from 24.4% (0.90%) for pulse pressure to 30.3% (0.90%) for diastolic BP. Significant negative genetic correlations (all P<0.0001) of root mean square of successive differences/SD of normal-to-normal intervals with systolic BP (-0.20/-0.16) and with diastolic BP (-0.15/-0.13) were observed. LD score regression showed largely consistent genetic correlation estimates of root mean square of successive differences/SD of normal-to-normal intervals with systolic BP (range, -0.08 to -0.23) and diastolic BP (range, -0.20 to -0.27). Our study shows a substantial contribution of genetic factors in explaining the variance of HRV and BP measures in the general population. The significant negative genetic correlations between HRV and BP indicate that genetic pathways for HRV and BP partially overlap.
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Affiliation(s)
- Balewgizie S. Tegegne
- From the Department of Epidemiology (B.S.T., T.M., N.G.A., I.N., H.S.), University Medical Center Groningen, University of Groningen, the Netherlands
| | - Tengfei Man
- From the Department of Epidemiology (B.S.T., T.M., N.G.A., I.N., H.S.), University Medical Center Groningen, University of Groningen, the Netherlands
| | - Arie M. van Roon
- Department of Vascular Medicine (A.M.v.R.), University Medical Center Groningen, University of Groningen, the Netherlands
| | - Nigus G. Asefa
- From the Department of Epidemiology (B.S.T., T.M., N.G.A., I.N., H.S.), University Medical Center Groningen, University of Groningen, the Netherlands
| | - Harriëtte Riese
- Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation (H.R.), University Medical Center Groningen, University of Groningen, the Netherlands
| | - Ilja Nolte
- From the Department of Epidemiology (B.S.T., T.M., N.G.A., I.N., H.S.), University Medical Center Groningen, University of Groningen, the Netherlands
| | - Harold Snieder
- From the Department of Epidemiology (B.S.T., T.M., N.G.A., I.N., H.S.), University Medical Center Groningen, University of Groningen, the Netherlands
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14
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Wang B, Wu T, Neale MC, Verweij R, Liu G, Su S, Snieder H. Genetic and Environmental Influences on Blood Pressure and Body Mass Index in the National Academy of Sciences-National Research Council World War II Veteran Twin Registry. Hypertension 2020; 76:1428-1434. [PMID: 32981367 PMCID: PMC7535104 DOI: 10.1161/hypertensionaha.120.15232] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Supplemental Digital Content is available in the text. Blood pressure (BP) and obesity phenotypes may covary due to shared genetic or environmental factors or both. Furthermore, it is possible that the heritability of BP differs according to obesity status—a form of G×E interaction. This hypothesis has never been tested in White twins. The present study included 15 924 White male twin pairs aged between 15 and 33 years from the National Academy of Sciences–National Research Council World War II Veteran Twin Registry. Systolic and diastolic BPs, as well as height and weight, were measured at the induction physical examination. Body mass index (BMI) was used as the index of general obesity. Quantitative genetic modeling was performed using Mx software. Univariate analysis showed that narrow sense heritabilities (95% CI) for systolic BP, diastolic BP, height, and BMI were 0.401 (0.381–0.420), 0.297 (0.280–0.320), 0.866 (0.836–0.897), and 0.639 (0.614–0.664), respectively. Positive phenotypic correlations of BMI with systolic BP (r=0.13) and diastolic BP (r=0.08) were largely due to genetic factors (70% and 86%, respectively). The gene-BMI interaction analysis did not show any support for a modifying effect of BMI on genetic and environmental influences of systolic BP and diastolic BP. Our results suggest that correlations between BP and BMI are mainly explained by common genes influencing both. Higher BMI levels have no influence on the penetrance of genetic vulnerability to elevated BP. These conclusions may prove valuable for gene-finding studies.
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Affiliation(s)
- Bin Wang
- From the Department of Epidemiology, University of Groningen, University Medical Center Groningen, the Netherlands (B.W., T.W., R.V., G.L., H.S.)
| | - Ting Wu
- From the Department of Epidemiology, University of Groningen, University Medical Center Groningen, the Netherlands (B.W., T.W., R.V., G.L., H.S.)
| | - Michael C Neale
- Department of Human and Molecular Genetics (M.C.N.), Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond.,Department of Psychiatry (M.C.N.), Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond
| | - Renske Verweij
- From the Department of Epidemiology, University of Groningen, University Medical Center Groningen, the Netherlands (B.W., T.W., R.V., G.L., H.S.)
| | - Gaifen Liu
- From the Department of Epidemiology, University of Groningen, University Medical Center Groningen, the Netherlands (B.W., T.W., R.V., G.L., H.S.).,Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, China (G.L.)
| | - Shaoyong Su
- Georgia Prevention Institute, Medical College of Georgia, Augusta University (S.S., H.S.)
| | - Harold Snieder
- From the Department of Epidemiology, University of Groningen, University Medical Center Groningen, the Netherlands (B.W., T.W., R.V., G.L., H.S.).,Georgia Prevention Institute, Medical College of Georgia, Augusta University (S.S., H.S.)
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15
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Cecelja M, Keehn L, Ye L, Spector TD, Hughes AD, Chowienczyk P. Genetic aetiology of blood pressure relates to aortic stiffness with bi-directional causality: evidence from heritability, blood pressure polymorphisms, and Mendelian randomization. Eur Heart J 2020; 41:3314-3322. [PMID: 32357239 PMCID: PMC7544538 DOI: 10.1093/eurheartj/ehaa238] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2019] [Revised: 11/08/2019] [Accepted: 03/18/2020] [Indexed: 11/13/2022] Open
Abstract
AIMS Haemodynamic determinants of blood pressure (BP) include cardiac output (CO), systemic vascular resistance (SVR), and arterial stiffness. We investigated the heritability of these phenotypes, their association with BP-related single-nucleotide polymorphisms (SNPs), and the causal association between BP and arterial stiffness. METHODS AND RESULTS We assessed BP, central BP components, and haemodynamic properties (during a single visit) including CO, SVR, and pulse wave velocity (PWV, measure of arterial stiffness) in 3531 (1934 monozygotic, 1586 dizygotic) female TwinsUK participants. Heritability was estimated using structural equation modelling. Association with 984 BP-associated SNP was examined using least absolute shrinkage and selection operator (LASSO) and generalized estimating equation regression. One and two-sample Mendelian randomization (MR) was used to estimate the causal direction between BP and arterial stiffness including data on 436 419 UK Biobank participants. We found high heritability for systolic and pulsatile components of BP (>50%) and PWV (65%) with overlapping genes accounting for >50% of their observed correlation. Environmental factors explained most of the variability of CO and SVR (>80%). Regression identified SNPs (n = 5) known to be associated with BP to also be associated with PWV. One-sample MR showed evidence of bi-directional causal association between BP and PWV in TwinsUK participants. Two-sample MR, confirmed a bi-directional causal effect of PWV on BP (inverse variance weighted (IVW) beta = 0.11, P < 0.02) and BP on arterial stiffness (IVW beta = 0.004, P < 0.0001). CONCLUSION The genetic basis of BP is mediated not only by genes regulating BP but also by genes that influence arterial stiffness. Mendelian randomization indicates a bi-directional causal association between BP and arterial stiffness.
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Affiliation(s)
- Marina Cecelja
- Cardiovascular Division, Department of Clinical Pharmacology, King’s College London British Heart Foundation Centre, St Thomas’ Hospital, Westminster Bridge Road, London SE1 7EH, UK
| | - Louise Keehn
- Cardiovascular Division, Department of Clinical Pharmacology, King’s College London British Heart Foundation Centre, St Thomas’ Hospital, Westminster Bridge Road, London SE1 7EH, UK
| | - Li Ye
- Cardiovascular Division, Department of Clinical Pharmacology, King’s College London British Heart Foundation Centre, St Thomas’ Hospital, Westminster Bridge Road, London SE1 7EH, UK
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King’s College London, St Thomas’ Hospital, Westminster Bridge Road, London SE1 7EH, UK
| | - Alun D Hughes
- Department of Population Science and Experimental Medicine, Institute of Cardiovascular Sciences, University College London, 69 Chenies Mews, London W1T 7HA, UK
| | - Phil Chowienczyk
- Cardiovascular Division, Department of Clinical Pharmacology, King’s College London British Heart Foundation Centre, St Thomas’ Hospital, Westminster Bridge Road, London SE1 7EH, UK
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16
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Pineda B, Pertusa C, Panach L, Tarín JJ, Cano A, García-Pérez MÁ. Polymorphisms in genes involved in T-cell co-stimulation are associated with blood pressure in women. Gene 2020; 754:144838. [PMID: 32525043 DOI: 10.1016/j.gene.2020.144838] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Revised: 05/06/2020] [Accepted: 06/01/2020] [Indexed: 02/07/2023]
Abstract
In recent years, conclusive data have emerged on a relationship between immune system, especially the T-cell, and blood pressure (BP). The objective of the present study was to determine the association between BP and four polymorphisms in CD80, CD86, CD28 and CTLA4 genes that code for key proteins in the T-cell co-stimulation process, in a female cohort. To that end, an association study in a cohort of 934 women over 40 years old from two hospitals was done. Raw data showed a significant association between the SNP rs1129055 of CD86 gene and BP. Analyzing this association against inheritance patterns, higher SBP (p < 0.000) and DBP (p = 0.005) values were observed in AA than in GG/GA genotype subjects in the largest sample cohort (Hospital 1). In multivariate linear regression studies, with adjustment for presumed independent predictors of BP, the SNP of the CD86 gene remained a predictor of SBP (p = 0.001) and DBP (p = 0.006), as did the SNP rs867234 of the CD80 gene for DBP (p < 0.000), both resisting the Bonferroni correction for multiple comparisons. As conclusion, we report a robust association between the SNP rs1129055 of CD86 gene and BP. The SNP rs867234 of CD80 gene was also shown to be a strong predictor of DBP.
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Affiliation(s)
- Begoña Pineda
- Research Foundation, INCLIVA Institute of Health Research, 46010 Valencia, Spain
| | - Clara Pertusa
- Research Foundation, INCLIVA Institute of Health Research, 46010 Valencia, Spain
| | - Layla Panach
- Research Foundation, INCLIVA Institute of Health Research, 46010 Valencia, Spain
| | - Juan J Tarín
- Department of Cellular Biology, Functional Biology and Physical Anthropology, University of Valencia, 46100 Burjassot, Spain
| | - Antonio Cano
- Department of Pediatrics, Obstetrics and Gynecology, University of Valencia, 46010 Valencia, Spain
| | - Miguel Ángel García-Pérez
- Research Foundation, INCLIVA Institute of Health Research, 46010 Valencia, Spain; Department of Genetics, University of Valencia, 46100 Burjassot, Spain.
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17
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Huang Y, Ollikainen M, Muniandy M, Zhang T, van Dongen J, Hao G, van der Most PJ, Pan Y, Pervjakova N, Sun YV, Hui Q, Lahti J, Fraszczyk E, Lu X, Sun D, Richard MA, Willemsen G, Heikkila K, Leach IM, Mononen N, Kähönen M, Hurme MA, Raitakari OT, Drake AJ, Perola M, Nuotio ML, Huang Y, Khulan B, Räikkönen K, Wolffenbuttel BHR, Zhernakova A, Fu J, Zhu H, Dong Y, van Vliet-Ostaptchouk JV, Franke L, Eriksson JG, Fornage M, Milani L, Lehtimäki T, Vaccarino V, Boomsma DI, van der Harst P, de Geus EJC, Salomaa V, Li S, Chen W, Su S, Wilson J, Snieder H, Kaprio J, Wang X. Identification, Heritability, and Relation With Gene Expression of Novel DNA Methylation Loci for Blood Pressure. Hypertension 2020; 76:195-205. [PMID: 32520614 PMCID: PMC7295009 DOI: 10.1161/hypertensionaha.120.14973] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Accepted: 04/23/2020] [Indexed: 02/05/2023]
Abstract
We conducted an epigenome-wide association study meta-analysis on blood pressure (BP) in 4820 individuals of European and African ancestry aged 14 to 69. Genome-wide DNA methylation data from peripheral leukocytes were obtained using the Infinium Human Methylation 450k BeadChip. The epigenome-wide association study meta-analysis identified 39 BP-related CpG sites with P<1×10-5. In silico replication in the CHARGE consortium of 17 010 individuals validated 16 of these CpG sites. Out of the 16 CpG sites, 13 showed novel association with BP. Conversely, out of the 126 CpG sites identified as being associated (P<1×10-7) with BP in the CHARGE consortium, 21 were replicated in the current study. Methylation levels of all the 34 CpG sites that were cross-validated by the current study and the CHARGE consortium were heritable and 6 showed association with gene expression. Furthermore, 9 CpG sites also showed association with BP with P<0.05 and consistent direction of the effect in the meta-analysis of the Finnish Twin Cohort (199 twin pairs and 4 singletons; 61% monozygous) and the Netherlands Twin Register (266 twin pairs and 62 singletons; 84% monozygous). Bivariate quantitative genetic modeling of the twin data showed that a majority of the phenotypic correlations between methylation levels of these CpG sites and BP could be explained by shared unique environmental rather than genetic factors, with 100% of the correlations of systolic BP with cg19693031 (TXNIP) and cg00716257 (JDP2) determined by environmental effects acting on both systolic BP and methylation levels.
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Affiliation(s)
- Yisong Huang
- Georgia Prevention Institute, Medical College of Georgia, Augusta University, Augusta, GA, USA
| | - Miina Ollikainen
- Institute for Molecular Medicine FIMM, HiLIFE, University of Helsinki, PO Box 20 (Tukholmankatu 8), Helsinki, Finland
- Department of Public Health, Faculty of Medicine, University of Helsinki, PO Box 20 (Tukholmankatu 8), Helsinki, Finland
| | - Maheswary Muniandy
- Institute for Molecular Medicine FIMM, HiLIFE, University of Helsinki, PO Box 20 (Tukholmankatu 8), Helsinki, Finland
| | - Tao Zhang
- Department of Biostatistics, Shandong University School of Public Health, Jinan, China
| | - Jenny van Dongen
- Department of Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, Van der Boechorststraat 7-9, 1081BT, Amsterdam, The Netherlands
| | - Guang Hao
- Georgia Prevention Institute, Medical College of Georgia, Augusta University, Augusta, GA, USA
| | - Peter J. van der Most
- University of Groningen, University Medical Center Groningen, Groningen, Department of Epidemiology, the Netherlands
| | - Yue Pan
- Georgia Prevention Institute, Medical College of Georgia, Augusta University, Augusta, GA, USA
| | - Natalia Pervjakova
- Estonian Genome Center, Institute of Genomics, University of Tartu, 23 Riia Street, 51010, Tartu, Estonia
| | - Yan V. Sun
- Department of Epidemiology, Emory Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Qin Hui
- Department of Epidemiology, Emory Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Jari Lahti
- Turku Institute for Advanced Studies, University of Turku, Turku, Finland
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Eliza Fraszczyk
- University of Groningen, University Medical Center Groningen, Groningen, Department of Epidemiology, the Netherlands
| | - Xueling Lu
- University of Groningen, University Medical Center Groningen, Groningen, Department of Epidemiology, the Netherlands
- Laboratory of Environmental Medicine and Developmental Toxicology, Shantou University Medical College, 515041, Guangdong, China
| | - Dianjianyi Sun
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Melissa A. Richard
- Department of Pediatrics, Section of Hematology/Oncology, Baylor College of Medicine
| | - Gonneke Willemsen
- Department of Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, Van der Boechorststraat 7-9, 1081BT, Amsterdam, The Netherlands
| | - Kauko Heikkila
- Institute for Molecular Medicine FIMM, HiLIFE, University of Helsinki, PO Box 20 (Tukholmankatu 8), Helsinki, Finland
| | - Irene Mateo Leach
- University of Groningen, University Medical Center Groningen, Groningen, Department of Cardiology, the Netherlands
| | - Nina Mononen
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33014, Finland; Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Finnish Cardiovascular Research Center – Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33014, Finland; Department of Clinical Physiology, Tampere University Hospital, Tampere 33521
| | - Mikko A. Hurme
- Department of Microbiology and Immunology, Faculty of Medicine and Health Technology, Tampere University, Tampere 33014, Finland
| | - Olli T. Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku 20520, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku 20014, Finland
| | - Amanda J Drake
- University/British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Queen’s Medical Research Institute, Edinburgh, UK
| | - Markus Perola
- National Institute for Health and Welfare, P.O. Box 30, 00271 Helsinki, Finland
| | - Marja-Liisa Nuotio
- National Institute for Health and Welfare, P.O. Box 30, 00271 Helsinki, Finland
| | - Yunfeng Huang
- Department of Epidemiology, Emory Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Batbayar Khulan
- University/British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Queen’s Medical Research Institute, Edinburgh, UK
| | - Katri Räikkönen
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Bruce HR Wolffenbuttel
- University of Groningen, University Medical Center Groningen, Department of Endocrinology, the Netherlands
| | - Alexandra Zhernakova
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, The Netherlands
| | - Jingyuan Fu
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, The Netherlands
- University of Groningen and University Medical Center Groningen, Groningen, Department of Pediatrics, The Netherlands
| | - Haidong Zhu
- Georgia Prevention Institute, Medical College of Georgia, Augusta University, Augusta, GA, USA
| | - Yanbin Dong
- Georgia Prevention Institute, Medical College of Georgia, Augusta University, Augusta, GA, USA
| | - Jana V. van Vliet-Ostaptchouk
- University of Groningen, University Medical Center Groningen, Groningen, Department of Epidemiology, the Netherlands
- University of Groningen, University Medical Center Groningen, Department of Endocrinology, the Netherlands
- University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Department of Genetics, Groningen, The Netherlands
| | - Lude Franke
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, The Netherlands
| | - Johan G Eriksson
- Department of General Practice and Primary health Care, Tukholmankatu 8 B, University of Helsinki, Finland and Helsinki University Hospital, Unit of General Practice, Helsinki, Finland
- Department of Obstetrics and Gynecology, Yong Loo Lin School of Medicine, National University of Singapore
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, Mc Govern Medical School, University of Texas Health Science Center at Houston
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston
| | - Lili Milani
- Estonian Genome Center, Institute of Genomics, University of Tartu, 23 Riia Street, 51010, Tartu, Estonia
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33014, Finland; Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland
| | - Viola Vaccarino
- Department of Epidemiology, Emory Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Dorret I. Boomsma
- Department of Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, Van der Boechorststraat 7-9, 1081BT, Amsterdam, The Netherlands
| | - Pim van der Harst
- University of Groningen, University Medical Center Groningen, Groningen, Department of Cardiology, the Netherlands
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Eco J. C. de Geus
- Department of Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, Van der Boechorststraat 7-9, 1081BT, Amsterdam, The Netherlands
| | - Veikko Salomaa
- National Institute for Health and Welfare, P.O. Box 30, 00271 Helsinki, Finland
| | - Shengxu Li
- Children’s Minnesota Research Institute, Children’s Hospitals and Clinics of Minnesota, Minneapolis, MN, USA
| | - Wei Chen
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Shaoyong Su
- Georgia Prevention Institute, Medical College of Georgia, Augusta University, Augusta, GA, USA
| | - James Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, 2500 N. State St., Jackson, MS 39216 USA
| | - Harold Snieder
- University of Groningen, University Medical Center Groningen, Groningen, Department of Epidemiology, the Netherlands
| | - Jaakko Kaprio
- Institute for Molecular Medicine FIMM, HiLIFE, University of Helsinki, PO Box 20 (Tukholmankatu 8), Helsinki, Finland
- Department of Public Health, Faculty of Medicine, University of Helsinki, PO Box 20 (Tukholmankatu 8), Helsinki, Finland
| | - Xiaoling Wang
- Georgia Prevention Institute, Medical College of Georgia, Augusta University, Augusta, GA, USA
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郑 鸿, 薛 恩, 王 雪, 陈 曦, 王 斯, 黄 辉, 江 锦, 叶 莺, 黄 春, 周 筠, 高 文, 余 灿, 吕 筠, 吴 小, 黄 小, 曹 卫, 严 延, 吴 涛, 李 立. [Bivariate heritability estimation of resting heart rate and common chronic disease based on extended pedigrees]. BEIJING DA XUE XUE BAO. YI XUE BAN = JOURNAL OF PEKING UNIVERSITY. HEALTH SCIENCES 2020; 52:432-437. [PMID: 32541974 PMCID: PMC7433431 DOI: 10.19723/j.issn.1671-167x.2020.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 02/16/2020] [Indexed: 11/20/2022]
Abstract
OBJECTIVE To estimate the univariate heritability of resting heart rate and common chronic disease such as hypertension, diabetes, and dyslipidemia based on extended pedigrees in Fujian Tulou area and to explore bivariate heritability to test for the genetic correlation between resting heart rate and other relative phenotypes. METHODS The study was conducted in Tulou area of Nanjing County, Fujian Province from August 2015 to December 2017. The participants were residents with Zhang surname and their relatives from Taxia Village, Qujiang Village, and Nanou Village or residents with Chen surname and their relatives from Caoban Village, Tumei Village, and Beiling Village. The baseline survey recruited 1 563 family members from 452 extended pedigrees. The pedigree reconstruction was based on the family information registration and the genealogy booklet. Univariate and bivariate heritability was estimated using variance component models for continuous variables, and susceptibility-threshold model for binary variables. RESULTS The pedigree reconstruction identified 1 seven-generation pedigree, 2 five-generation pedigrees, 23 four-generation pedigrees, 186 three-generation pedigrees, and 240 two-generation pedigrees. The mean age of the participants was 57.2 years and the males accounted for 39.4%. The prevalence of hypertension, diabetes, dyslipidemia in this population was 49.2%, 10.0%, and 45.2%, respectively. The univariate heritability estimation of resting heart rate, hypertension, and dyslipidemia was 0.263 (95%CI: 0.120-0.407), 0.404 (95%CI: 0.135-0.673), and 0.799 (95%CI: 0.590-1), respectively. The heritability of systolic blood pressure, diastolic blood pressure, fasting glucose, total cholesterol, triglyceride, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol was 0.379, 0.306, 0.393, 0.452, 0.568, 0.852, and 0.387, respectively. In bivariate analysis, there were phenotypic correlations between resting heart rate with hypertension, diabetes, diastolic blood pressure, fasting glucose, and triglyceride. After taking resting heart rate into account, there were strong genetic correlations between resting heart rate with fasting glucose (genetic correlation 0.485, 95%CI: 0.120-1, P<0.05) and diabetes (genetic correlation 0.795, 95%CI: 0.181-0.788, P<0.05). CONCLUSION Resting heart rate was a heritable trait and correlated with several common chronic diseases and related traits. There was strong genetic correlation between resting heart rate with fasting glucose and diabetes, suggesting that they may share common genetic risk factors.
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Affiliation(s)
- 鸿尘 郑
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191 Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - 恩慈 薛
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191 Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - 雪珩 王
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191 Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - 曦 陈
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191 Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - 斯悦 王
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191 Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - 辉 黄
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191 Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - 锦 江
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191 Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - 莺 叶
- 福建省疾病预防控制中心地方病防治科,福州 350001 Department of Local Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou 350001, China
| | - 春兰 黄
- 福建省漳州市南靖县疾病预防控制中心卫生科,福建南靖 363600 Department of Hygiene, Nanjing County Center for Disease Control and Prevention, Nanjing 363600 Fujian, China
| | - 筠 周
- 首都医科大学附属天坛医院国家神经系统疾病临床医学研究中心,北京 100070 Beijing Tiantan Hospital, Capital Medical University, China National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - 文静 高
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191 Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - 灿清 余
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191 Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - 筠 吕
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191 Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - 小玲 吴
- 福建省漳州市南靖县疾病预防控制中心卫生科,福建南靖 363600 Department of Hygiene, Nanjing County Center for Disease Control and Prevention, Nanjing 363600 Fujian, China
| | - 小明 黄
- 福建省漳州市南靖县疾病预防控制中心卫生科,福建南靖 363600 Department of Hygiene, Nanjing County Center for Disease Control and Prevention, Nanjing 363600 Fujian, China
| | - 卫华 曹
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191 Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - 延生 严
- 福建省疾病预防控制中心地方病防治科,福州 350001 Department of Local Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou 350001, China
| | | | - 立明 李
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191 Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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Guo Y, Chung W, Zhu Z, Shan Z, Li J, Liu S, Liang L. Genome-Wide Assessment for Resting Heart Rate and Shared Genetics With Cardiometabolic Traits and Type 2 Diabetes. J Am Coll Cardiol 2020; 74:2162-2174. [PMID: 31648709 DOI: 10.1016/j.jacc.2019.08.1055] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Revised: 06/24/2019] [Accepted: 08/05/2019] [Indexed: 01/24/2023]
Abstract
BACKGROUND High resting heart rate (RHR) occurs in parallel with type 2 diabetes (T2D) and metabolic disorders, implying shared etiology between them. However, it is unknown if they are causally related, and no study has been conducted to investigate the shared mechanisms underlying these associations. OBJECTIVES The objective of this study was to understand the genetic basis of the association between resting heart rate and cardiometabolic disorders/T2D. METHODS This study examined the genetic correlation, causality, and shared genetics between RHR and T2D using LD Score regression, generalized summary data-based Mendelian randomization, and transcriptome wide association scan (TWAS) in UK Biobank data (n = 428,250) and summary-level data for T2D (74,124 cases and 824,006 control subjects) and 8 cardiometabolic traits (sample size ranges from 51,750 to 236,231). RESULTS Significant genetic correlation between RHR and T2D (rg = 0.22; 95% confidence interval: 0.18 to 0.26; p = 1.99 × 10-22), and 6 cardiometabolic traits (fasting insulin, fasting glucose, waist-hip ratio, triglycerides, high-density lipoprotein, and body mass index; rg range -0.12 to 0.24; all p < 0.05) were observed. RHR has significant estimated causal effect on T2D (odds ratio: 1.12 per 10-beats/min increment; p = 7.79 × 10-11) and weaker causal estimates from T2D to RHR (0.32 beats/min per doubling increment in T2D prevalence; p = 6.14 × 10-54). Sensitivity analysis by controlling for the included cardiometabolic traits did not modify the relationship between RHR and T2D. TWAS found locus chr2q23.3 (rs1260326) was highly pleiotropic among RHR, cardiometabolic traits, and T2D, and identified 7 genes (SMARCAD1, RP11-53O19.3, CTC-498M16.4, PDE8B, AKTIP, KDM4B, and TSHZ3) that were statistically independent and shared between RHR and T2D in tissues from the nervous and cardiovascular systems. These shared genes suggested the involvement of epigenetic regulation of energy and glucose metabolism, and AKT activation-related telomere dysfunction and vascular endothelial aging in the shared etiologies between RHR and T2D. Finally, FADS1 was found to be shared among RHR, fasting glucose, high-density lipoprotein, and triglycerides. CONCLUSIONS These findings provide evidence of significant genetic correlations and causation between RHR and T2D/cardiometabolic traits, advance our understanding of RHR, and provide insight into shared etiology for high RHR and T2D.
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Affiliation(s)
- Yanjun Guo
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Wonil Chung
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts; Department of Statistics and Actuarial Science, Soongsil University, Seoul, Korea
| | - Zhaozhong Zhu
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Zhilei Shan
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts; Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jun Li
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Simin Liu
- Departments of Epidemiology, Medicine, and Center for Global Cardiometabolic Health (CGCH), Brown University, Providence, Rhode Island
| | - Liming Liang
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
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Saarinen AIL, Keltikangas-Järvinen L, Hintsa T, Pulkki-Råback L, Ravaja N, Lehtimäki T, Raitakari O, Hintsanen M. Does Compassion Predict Blood Pressure and Hypertension? The Modifying Role of Familial Risk for Hypertension. Int J Behav Med 2020; 27:527-538. [PMID: 32347444 PMCID: PMC7497423 DOI: 10.1007/s12529-020-09886-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Background This study investigated (i) whether compassion is associated with blood pressure or hypertension in adulthood and (ii) whether familial risk for hypertension modifies these associations. Method The participants (N = 1112–1293) came from the prospective Young Finns Study. Parental hypertension was assessed in 1983–2007; participants’ blood pressure in 2001, 2007, and 2011; hypertension in 2007 and 2011 (participants were aged 30–49 years in 2007–2011); and compassion in 2001. Results High compassion predicted lower levels of diastolic and systolic blood pressure in adulthood. Additionally, high compassion was related to lower risk for hypertension in adulthood among individuals with no familial risk for hypertension (independently of age, sex, participants’ and their parents’ socioeconomic factors, and participants’ health behaviors). Compassion was not related to hypertension in adulthood among individuals with familial risk for hypertension. Conclusion High compassion predicts lower diastolic and systolic blood pressure in adulthood. Moreover, high compassion may protect against hypertension among individuals without familial risk for hypertension. As our sample consisted of comparatively young participants, our findings provide novel implications for especially early-onset hypertension. Electronic supplementary material The online version of this article (10.1007/s12529-020-09886-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Aino I L Saarinen
- Research Unit of Psychology, University of Oulu, P.O. Box 2000 (Erkki Koiso-Kanttilan katu 1), 90014, Oulu, Finland.,Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | | | - Taina Hintsa
- Department of Educational Sciences and Psychology, University of Eastern Finland, Joensuu, Finland
| | - Laura Pulkki-Råback
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Niklas Ravaja
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.,Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland.,Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Mirka Hintsanen
- Research Unit of Psychology, University of Oulu, P.O. Box 2000 (Erkki Koiso-Kanttilan katu 1), 90014, Oulu, Finland.
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21
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Man T, Riese H, Jaju D, Muñoz ML, Hassan MO, Al-Yahyaee S, Bayoumi RA, Comuzzie AG, Floras JS, van Roon AM, Nolte IM, Albarwani S, Snieder H. Heritability and genetic and environmental correlations of heart rate variability and baroreceptor reflex sensitivity with ambulatory and beat-to-beat blood pressure. Sci Rep 2019; 9:1664. [PMID: 30733514 PMCID: PMC6367510 DOI: 10.1038/s41598-018-38324-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2018] [Accepted: 12/19/2018] [Indexed: 12/23/2022] Open
Abstract
This family study from Oman (n = 1231) explored the heritability and genetic and environmental correlations of heart rate variability (HRV) and baroreceptor reflex sensitivity (BRS) with ambulatory and beat-to-beat blood pressure (BP). Ambulatory BP was measured for 24 hours to calculate mean values for daytime and sleep separately. Time and frequency domain HRV indices, BRS, office beat-to-beat BP, and heart rate (HR) were measured for 10 minutes at rest. SOLAR software was used to perform univariate and bivariate quantitative genetic analyses adjusting for age, age2, sex, their interactions and BMI. Heritability of SBP and DBP ranged from 16.8% to 40.4% for daytime, sleeping, 24-hour and office beat-to-beat measurements. HR and BRS showed a heritability of 31.9% and 20.6%, respectively, and for HRV indices heritability ranged from 11.1% to 20.5%. All HRV measurements and BRS were found to be negatively correlated with BP, but phenotypic correlation coefficients were relatively weak; HR was positively correlated with BP. None of the genetic correlations were statistically significant while environmental factors explained most of the correlations for all HRV indices with BP. Our study found consistent but weak correlations among HRV, HR, BRS and ambulatory/office beat-to-beat BP. However, environmental rather than genetic factors contributed most to those correlations.
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Affiliation(s)
- Tengfei Man
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Harriëtte Riese
- Interdisciplinary Center Psychopathology and Emotion regulation, Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Deepali Jaju
- College of Medicine and Health Sciences, Sultan Qaboos University, Muscat, Sultanate of Oman
| | - M Loretto Muñoz
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | | | - Said Al-Yahyaee
- Department of Biochemistry, College of Medicine and Health Sciences, Sultan Qaboos University, Muscat, 123, Sultanate of Oman
| | - Riad A Bayoumi
- College of Medicine, Mohammed Bin Rashid University for Medicine and Health Science, Dubai, UAE
| | | | - John S Floras
- University Health Network and Mount Sinai Hospital Division of Cardiology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Arie M van Roon
- Department of Vascular Medicine, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Sulayma Albarwani
- College of Medicine and Health Sciences, Sultan Qaboos University, Muscat, Sultanate of Oman
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
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22
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Owen D, Bracher-Smith M, Kendall KM, Rees E, Einon M, Escott-Price V, Owen MJ, O'Donovan MC, Kirov G. Effects of pathogenic CNVs on physical traits in participants of the UK Biobank. BMC Genomics 2018; 19:867. [PMID: 30509170 PMCID: PMC6278042 DOI: 10.1186/s12864-018-5292-7] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2018] [Accepted: 11/21/2018] [Indexed: 12/26/2022] Open
Abstract
Background Copy number variants (CNVs) have been shown to increase risk for physical anomalies, developmental, psychiatric and medical disorders. Some of them have been associated with changes in weight, height, and other physical traits. As most studies have been performed on children and young people, these effects of CNVs in middle-aged and older people are not well established. The UK Biobank recruited half a million adults who provided a variety of physical measurements. We called all CNVs from the Affymetrix microarrays and selected a set of 54 CNVs implicated as pathogenic (including their reciprocal deletions/duplications) and that were found in five or more persons. Linear regression analysis was used to establish their association with 16 physical traits relevant to human health. Results 396,725 participants of white British or Irish descent (excluding first-degree relatives) passed our quality control filters. Out of the 864 CNV/trait associations, 214 were significant at a false discovery rate of 0.1, most of them novel. Many of these traits increase risk for adverse health outcomes: e.g. increases in weight, waist-to-hip ratio, pulse rate and body fat composition. Deletions at 16p11.2, 16p12.1, NRXN1 and duplications at 16p13.11 and 22q11.2 produced the highest numbers of significant associations. Five CNVs produced average changes of over one standard deviation for the 16 traits, compared to controls: deletions at 16p11.2 and 22q11.2, and duplications at 3q29, the Williams-Beuren and Potocki-Lupski regions. CNVs at 1q21.1, 2q13, 16p11.2 and 16p11.2 distal, 16p12.1, 17p12 and 17q12 demonstrated one or more mirror image effects of deletions versus duplications. Conclusions Carriers of many CNVs should be monitored for physical traits that increase morbidity and mortality. Genes within these CNVs can give insights into biological processes and therapeutic interventions. Electronic supplementary material The online version of this article (10.1186/s12864-018-5292-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- David Owen
- MRC Centre for Neuropsychiatric Genetics & Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, School of Medicine, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ, UK
| | - Mathew Bracher-Smith
- MRC Centre for Neuropsychiatric Genetics & Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, School of Medicine, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ, UK
| | - Kimberley M Kendall
- MRC Centre for Neuropsychiatric Genetics & Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, School of Medicine, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ, UK
| | - Elliott Rees
- MRC Centre for Neuropsychiatric Genetics & Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, School of Medicine, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ, UK
| | - Mark Einon
- MRC Centre for Neuropsychiatric Genetics & Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, School of Medicine, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ, UK
| | - Valentina Escott-Price
- MRC Centre for Neuropsychiatric Genetics & Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, School of Medicine, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ, UK
| | - Michael J Owen
- MRC Centre for Neuropsychiatric Genetics & Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, School of Medicine, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ, UK
| | - Michael C O'Donovan
- MRC Centre for Neuropsychiatric Genetics & Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, School of Medicine, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ, UK
| | - George Kirov
- MRC Centre for Neuropsychiatric Genetics & Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, School of Medicine, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ, UK.
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23
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Bourdon JL, Moore AA, Eastman M, Savage JE, Hazlett L, Vrana SR, Hettema JM, Roberson-Nay R. Resting Heart Rate Variability (HRV) in Adolescents and Young Adults from a Genetically-Informed Perspective. Behav Genet 2018; 48:386-396. [PMID: 29995284 DOI: 10.1007/s10519-018-9915-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Accepted: 07/04/2018] [Indexed: 02/06/2023]
Abstract
Reduced heart rate variability (HRV) is associated with cardiac morbidity, mortality, and negative psychopathology. Most research concerning genetic influences on HRV has focused on adult populations, with fewer studies investigating the developmental period of adolescence and emerging adulthood. The current study estimated the genetic and environmental contributions to resting HRV in a sample of twins using various HRV time domain metrics to assess autonomic function across two different time measurement intervals (2.5- and 10-min). Five metrics of resting HRV [mean interbeat interval (IBI), the standard deviation of normal IBIs (SDNN), root square mean of successive differences between IBIs (RMSSD), cardiac vagal index (CVI), and cardiac sympathetic index (CSI)] were assessed in 421 twin pairs aged 14-20 during a baseline electrocardiogram. This was done for four successive 2.5-min intervals as well as the overall 10-min interval. Heritability (h2) appeared consistent across intervals within each metric with the following estimates (collapsed across time intervals): mean IBI (h2 = 0.36-0.46), SDNN (h2 = 0.23-0.30), RMSSD (h2 = 0.36-0.39), CVI (h2 = 0.37-0.42), CSI (h2 = 0.33-0.46). Beyond additive genetic contributions, unique environment also was an important influence on HRV. Within each metric, a multivariate Cholesky decomposition further revealed evidence of genetic stability across the four successive 2.5-min intervals. The same models showed evidence for both genetic and environmental stability with some environmental attenuation and innovation. All measures of HRV were moderately heritable across time, with further analyses revealing consistent patterns of genetic and environmental influences over time. This study confirms that in an adolescent sample, the time interval used (2.5- vs. 10-min) to measure HRV time domain metrics does not affect the relative proportions of genetic and environmental influences.
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Affiliation(s)
- Jessica L Bourdon
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St, Biotech One, Suite 101, Richmond, VA, 23219, USA.
| | - Ashlee A Moore
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St, Biotech One, Suite 101, Richmond, VA, 23219, USA
| | - Meridith Eastman
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St, Biotech One, Suite 101, Richmond, VA, 23219, USA
| | - Jeanne E Savage
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St, Biotech One, Suite 101, Richmond, VA, 23219, USA
| | - Laura Hazlett
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St, Biotech One, Suite 101, Richmond, VA, 23219, USA
| | - Scott R Vrana
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
| | - John M Hettema
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St, Biotech One, Suite 101, Richmond, VA, 23219, USA.,Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Roxann Roberson-Nay
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St, Biotech One, Suite 101, Richmond, VA, 23219, USA.,Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
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24
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Ramírez J, Duijvenboden SV, Ntalla I, Mifsud B, Warren HR, Tzanis E, Orini M, Tinker A, Lambiase PD, Munroe PB. Thirty loci identified for heart rate response to exercise and recovery implicate autonomic nervous system. Nat Commun 2018; 9:1947. [PMID: 29769521 PMCID: PMC5955978 DOI: 10.1038/s41467-018-04148-1] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Accepted: 04/06/2018] [Indexed: 12/25/2022] Open
Abstract
Impaired capacity to increase heart rate (HR) during exercise (ΔHRex), and a reduced rate of recovery post-exercise (ΔHRrec) are associated with higher cardiovascular mortality rates. Currently, the genetic basis of both phenotypes remains to be elucidated. We conduct genome-wide association studies (GWASs) for ΔHRex and ΔHRrec in ~40,000 individuals, followed by replication in ~27,000 independent samples, all from UK Biobank. Six and seven single-nucleotide polymorphisms for ΔHRex and ΔHRrec, respectively, formally replicate. In a full data set GWAS, eight further loci for ΔHRex and nine for ΔHRrec are genome-wide significant (P ≤ 5 × 10−8). In total, 30 loci are discovered, 8 being common across traits. Processes of neural development and modulation of adrenergic activity by the autonomic nervous system are enriched in these results. Our findings reinforce current understanding of HR response to exercise and recovery and could guide future studies evaluating its contribution to cardiovascular risk prediction. Genome-wide association studies have identified multiple loci for resting heart rate (HR) but the genetic factors associated with HR increase during and HR recovery after exercise are less well studied. Here, the authors examine both traits in a two-stage GWAS design in up to 67,257 individuals from UK Biobank.
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Affiliation(s)
- Julia Ramírez
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.,Institute of Cardiovascular Science, University College London, London, WC1E 6BT, UK
| | - Stefan van Duijvenboden
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.,Institute of Cardiovascular Science, University College London, London, WC1E 6BT, UK
| | - Ioanna Ntalla
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Borbala Mifsud
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.,NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Helen R Warren
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.,NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Evan Tzanis
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.,NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Michele Orini
- Barts Heart Centre, St Bartholomews Hospital, London, EC1A 7BE, UK.,Mechanical Engineering Department, University College London, London, WC1E 6BT, UK
| | - Andrew Tinker
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.,NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Pier D Lambiase
- Institute of Cardiovascular Science, University College London, London, WC1E 6BT, UK. .,Barts Heart Centre, St Bartholomews Hospital, London, EC1A 7BE, UK.
| | - Patricia B Munroe
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK. .,NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.
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25
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van den Berg ME, Warren HR, Cabrera CP, Verweij N, Mifsud B, Haessler J, Bihlmeyer NA, Fu YP, Weiss S, Lin HJ, Grarup N, Li-Gao R, Pistis G, Shah N, Brody JA, Müller-Nurasyid M, Lin H, Mei H, Smith AV, Lyytikäinen LP, Hall LM, van Setten J, Trompet S, Prins BP, Isaacs A, Radmanesh F, Marten J, Entwistle A, Kors JA, Silva CT, Alonso A, Bis JC, de Boer R, de Haan HG, de Mutsert R, Dedoussis G, Dominiczak AF, Doney ASF, Ellinor PT, Eppinga RN, Felix SB, Guo X, Hagemeijer Y, Hansen T, Harris TB, Heckbert SR, Huang PL, Hwang SJ, Kähönen M, Kanters JK, Kolcic I, Launer LJ, Li M, Yao J, Linneberg A, Liu S, Macfarlane PW, Mangino M, Morris AD, Mulas A, Murray AD, Nelson CP, Orrú M, Padmanabhan S, Peters A, Porteous DJ, Poulter N, Psaty BM, Qi L, Raitakari OT, Rivadeneira F, Roselli C, Rudan I, Sattar N, Sever P, Sinner MF, Soliman EZ, Spector TD, Stanton AV, Stirrups KE, Taylor KD, Tobin MD, Uitterlinden A, Vaartjes I, Hoes AW, van der Meer P, Völker U, Waldenberger M, Xie Z, Zoledziewska M, Tinker A, Polasek O, Rosand J, Jamshidi Y, van Duijn CM, Zeggini E, Jukema JW, Asselbergs FW, Samani NJ, Lehtimäki T, Gudnason V, Wilson J, Lubitz SA, Kääb S, Sotoodehnia N, Caulfield MJ, Palmer CNA, Sanna S, Mook-Kanamori DO, Deloukas P, Pedersen O, Rotter JI, Dörr M, O'Donnell CJ, Hayward C, Arking DE, Kooperberg C, van der Harst P, Eijgelsheim M, Stricker BH, Munroe PB. Discovery of novel heart rate-associated loci using the Exome Chip. Hum Mol Genet 2017; 26:2346-2363. [PMID: 28379579 PMCID: PMC5458336 DOI: 10.1093/hmg/ddx113] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Accepted: 03/18/2017] [Indexed: 01/06/2023] Open
Abstract
Resting heart rate is a heritable trait, and an increase in heart rate is associated with increased mortality risk. Genome-wide association study analyses have found loci associated with resting heart rate, at the time of our study these loci explained 0.9% of the variation. This study aims to discover new genetic loci associated with heart rate from Exome Chip meta-analyses.Heart rate was measured from either elecrtrocardiograms or pulse recordings. We meta-analysed heart rate association results from 104 452 European-ancestry individuals from 30 cohorts, genotyped using the Exome Chip. Twenty-four variants were selected for follow-up in an independent dataset (UK Biobank, N = 134 251). Conditional and gene-based testing was undertaken, and variants were investigated with bioinformatics methods.We discovered five novel heart rate loci, and one new independent low-frequency non-synonymous variant in an established heart rate locus (KIAA1755). Lead variants in four of the novel loci are non-synonymous variants in the genes C10orf71, DALDR3, TESK2 and SEC31B. The variant at SEC31B is significantly associated with SEC31B expression in heart and tibial nerve tissue. Further candidate genes were detected from long-range regulatory chromatin interactions in heart tissue (SCD, SLF2 and MAPK8). We observed significant enrichment in DNase I hypersensitive sites in fetal heart and lung. Moreover, enrichment was seen for the first time in human neuronal progenitor cells (derived from embryonic stem cells) and fetal muscle samples by including our novel variants.Our findings advance the knowledge of the genetic architecture of heart rate, and indicate new candidate genes for follow-up functional studies.
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Affiliation(s)
- Marten E van den Berg
- Department of Medical Informatics Erasmus MC - University Medical Center Rotterdam, P.O. Box 2040, 3000CA, Rotterdam, the Netherlands
| | - Helen R Warren
- Clinical Pharmacology, William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK.,NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Claudia P Cabrera
- Clinical Pharmacology, William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK.,NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Niek Verweij
- University Medical Center Groningen, University of Groningen, Department of Cardiology, the Netherlands
| | - Borbala Mifsud
- Clinical Pharmacology, William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK.,NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Jeffrey Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Nathan A Bihlmeyer
- Predoctoral Training Program in Human Genetics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA, 21205
| | - Yi-Ping Fu
- Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Stefan Weiss
- Interfaculty Institute for Genetics and Functional Genomics; University Medicine and Ernst-Moritz-Arndt-University Greifswald; Greifswald, 17475, Germany.,DZHK (German Centre for Cardiovascular Research); partner site Greifswald; Greifswald, 17475, Germany
| | - Henry J Lin
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 1124 W. Carson Street, Torrance, CA 90502, USA.,Division of Medical Genetics, Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Niels Grarup
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Giorgio Pistis
- Istituto di Ricerca Genetica e Biomedica (IRGB), CNR, Monserrato, Italy.,Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Nabi Shah
- Division of Molecular and Clinical Medicine, School of Medicine, University of Dundee, DD1 9SY, UK.,Department of Pharmacy, COMSATS Institute of Information Technology, Abbottabad, 22060, Pakistan
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA 98101, USA
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany.,Department of Medicine I, University Hospital Munich, Ludwig-Maximilians-Universität, Munich, Germany
| | - Honghuang Lin
- Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA
| | - Hao Mei
- Department of Data Science, University of Mississippi Medical Center, Jackson, MI, USA
| | - Albert V Smith
- Icelandic Heart Association, 201 Kopavogur, Iceland.,Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories and University of Tampere School of Medicine, Arvo, D339, P.O. Box 100, FI-33014 Tampere, Finland
| | - Leanne M Hall
- Department of Cardiovascular Sciences, University of Leicester, Cardiovascular Research Centre, Glenfield Hospital, Leicester, LE3 9QP, UK.,NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester LE3 9QP, UK
| | - Jessica van Setten
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, 2300 RC, Leiden, the Netherlands.,Department of Gerontology and Geriatrics, Leiden university Medical Center, Leiden, the Netherlands
| | - Bram P Prins
- Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton, United Kingdom, CB10 1SA.,Cardiogenetics Lab, Genetics and Molecular Cell Sciences Research Centre, Cardiovascular and Cell Sciences Institute, St George's, University of London, Cranmer Terrace, London, SW17 0RE, UK
| | - Aaron Isaacs
- CARIM School for Cardiovascular Diseases, Maastricht Centre for Systems Biology (MaCSBio), Dept. of Biochemistry, Maastricht University, Universiteitssingel 60, 6229 ER Maastricht, NL
| | - Farid Radmanesh
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114.,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142
| | - Jonathan Marten
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road South, Edinburgh, EH4?2XU, UK
| | - Aiman Entwistle
- Clinical Pharmacology, William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK.,NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Jan A Kors
- Department of Medical Informatics Erasmus MC - University Medical Center Rotterdam, P.O. Box 2040, 3000CA, Rotterdam, the Netherlands
| | - Claudia T Silva
- Genetic Epidemiology Unit, Dept. of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA Rotterdam, NL.,Doctoral Program in Biomedical Sciences, Universidad del Rosario, Bogotá, Colombia.,GENIUROS Group, Genetics and Genomics Research Center CIGGUR, School of Medicine and Health Sciences, Universidad del Rosario, Bogotá, Colombia
| | - Alvaro Alonso
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, 30322
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA 98101, USA
| | - Rudolf de Boer
- University Medical Center Groningen, University of Groningen, Department of Cardiology, the Netherlands
| | - Hugoline G de Haan
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - George Dedoussis
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens 17671, Greece
| | - Anna F Dominiczak
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Alex S F Doney
- Division of Molecular and Clinical Medicine, School of Medicine, University of Dundee, DD1?9SY, UK
| | - Patrick T Ellinor
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142.,Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Ruben N Eppinga
- University Medical Center Groningen, University of Groningen, Department of Cardiology, the Netherlands
| | - Stephan B Felix
- Department of Internal Medicine B - Cardiology, Pneumology, Infectious Diseases, Intensive Care Medicine; University Medicine Greifswald; Greifswald, 17475, Germany & DZHK (German Centre for Cardiovascular Research); partner site Greifswald; Greifswald, 17475, Germany
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 1124 W. Carson Street, Torrance, CA 90502, USA
| | - Yanick Hagemeijer
- University Medical Center Groningen, University of Groningen, Department of Cardiology, the Netherlands
| | - Torben Hansen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tamara B Harris
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, Maryland, 20892, USA
| | - Susan R Heckbert
- Cardiovascular Health Research Unit and Department of Epidemiology, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA 98101, USA.,Group Health Research Institute, Group Health Cooperative, 1730 Minor Ave, Suite 1600, Seattle, WA, USA
| | - Paul L Huang
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Shih-Jen Hwang
- Population Sciences Branch, Division of Intramural Research, NHLBI, NIH, Bethesda MD, USA
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital and University of Tampere School of Medicine, Finn-Medi 1, 3th floor, P.O. Box 2000, FI-33521 Tampere, Finland
| | - Jørgen K Kanters
- Laboratory of Experimental Cardiology, University of Copenhagen, Copenhagen, Denmark
| | - Ivana Kolcic
- Faculty of Medicine, University of Split, Split, Croatia
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, Maryland, 20892, USA
| | - Man Li
- Division of Nephrology & Hypertension, Internal Medicine, School of Medicine, University of Utah, Salt Lake City, UT 84109, USA
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 1124 W. Carson Street, Torrance, CA 90502, USA
| | - Allan Linneberg
- Research Centre for Prevention and Health, Capital Region of Denmark, Copenhagen, Denmark.,Department of Clinical Experimental Research, Rigshospitalet, Glostrup, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Simin Liu
- Brown University School of Public Health, Providence, Rhode Island 02912, USA
| | | | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.,NIHR Biomedical Research Centre at Guy's and St Thomas' Foundation Trust, London SE1 9RT, UK
| | - Andrew D Morris
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, EH8?9AG, UK
| | - Antonella Mulas
- Istituto di Ricerca Genetica e Biomedica (IRGB), CNR, Monserrato, Italy
| | - Alison D Murray
- Aberdeen Biomedical Imaging Centre, Lilian Sutton Building, University of Aberdeen, Foresterhill, Aberdeen AB25?2ZD, UK
| | - Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester, Cardiovascular Research Centre, Glenfield Hospital, Leicester, LE3 9QP, UK.,NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester LE3 9QP, UK
| | - Marco Orrú
- Unita Operativa Complessa di Cardiologia, Presidio Ospedaliero Oncologico Armando Businco Cagliari , Azienda Ospedaliera Brotzu Cagliari, Caglliari, Italy
| | - Sandosh Padmanabhan
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.,Institute of Cardiovascular and Medical Sciences, University of Glasgow, BHF GCRC, Glasgow G12 8TA, UK
| | - Annette Peters
- DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany.,Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Diabetes Research, Neuherberg, Germany
| | - David J Porteous
- Centre for Genomic & Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road South, Edinburgh EH4?2XU, UK
| | - Neil Poulter
- School of Public Health, Imperial College London, W2?1PG, UK
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Health Services, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA 98101, USA.,Group Health Research Institute, Group Health Cooperative, Seattle, WA, USA
| | - Lihong Qi
- University of California Davis, One Shields Ave Ms1c 145, Davis, CA 95616 USA
| | - Olli T Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, and Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, P.O. Box 52, FI-20521 Turku, Finland
| | - Fernando Rivadeneira
- Human Genomics Facility Erasmus MC - University Medical Center Rotterdam, P.O. Box 2040, 3000CA, Rotterdam, the Netherlands
| | - Carolina Roselli
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Igor Rudan
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, EH8?9AG, UK
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, BHF GCRC, Glasgow G12?8TA, UK
| | - Peter Sever
- National Heart and Lung Institute, Imperial College London, W2?1PG, UK
| | - Moritz F Sinner
- DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany.,Department of Medicine I, University Hospital Munich, Ludwig-Maximilians-Universität, Munich, Germany
| | - Elsayed Z Soliman
- Epidemiological Cardiology Research Center (EPICARE), Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | - Timothy D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Alice V Stanton
- Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin 2, Ireland
| | - Kathleen E Stirrups
- Clinical Pharmacology, William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK.,Department of Haematology, University of Cambridge, Cambridge, UK
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA.,Division of Genomic Outcomes, Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA.,Departments of Pediatrics, Medicine, and Human Genetics, UCLA, Los Angeles, CA, USA
| | - Martin D Tobin
- Department of Health Sciences, University of Leicester, Leicester LE1?7RH, UK
| | - André Uitterlinden
- Human Genotyping Facility Erasmus MC - University Medical Center Rotterdam, P.O. Box 2040, 3000CA, Rotterdam, the Netherlands
| | - Ilonca Vaartjes
- Julius Center for Health Sciences and Primary Care, University Medical Center, PO Box 85500, 3508 GA Utrecht, the Netherlands
| | - Arno W Hoes
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Peter van der Meer
- University Medical Center Groningen, University of Groningen, Department of Cardiology, the Netherlands
| | - Uwe Völker
- Interfaculty Institute for Genetics and Functional Genomics; University Medicine and Ernst-Moritz-Arndt-University Greifswald; Greifswald, 17475, Germany.,DZHK (German Centre for Cardiovascular Research); partner site Greifswald; Greifswald, 17475, Germany
| | - Melanie Waldenberger
- DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany.,Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, EH8 9AG, UK.,Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Zhijun Xie
- Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA
| | | | - Andrew Tinker
- Clinical Pharmacology, William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK.,NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Ozren Polasek
- Faculty of Medicine, University of Split, Split, Croatia.,Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, EH8 9AG, UK
| | - Jonathan Rosand
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114.,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142
| | - Yalda Jamshidi
- Cardiogenetics Lab, Genetics and Molecular Cell Sciences Research Centre, Cardiovascular and Cell Sciences Institute, St George's, University of London, Cranmer Terrace, London, SW17?0RE, UK
| | - Cornelia M van Duijn
- Genetic Epidemiology Unit, Dept. of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA Rotterdam, NL
| | - Eleftheria Zeggini
- Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton, United Kingdom, CB10?1SA
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, 2300 RC, Leiden, the Netherlands
| | - Folkert W Asselbergs
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht, the Netherlands.,Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Utrecht, the Netherlands.,Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Cardiovascular Research Centre, Glenfield Hospital, Leicester, LE3 9QP, UK.,NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester LE3 9QP, UK
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and University of Tampere School of Medicine, Arvo, D338, P.O. Box 100, FI-33014 Tampere, Finland
| | - Vilmundur Gudnason
- Icelandic Heart Association, 201 Kopavogur, Iceland.,Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - James Wilson
- Physiology & Biophysics, University of Mississippi Medical Center, Jackson, MI, USA
| | - Steven A Lubitz
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142.,Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Stefan Kääb
- DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany.,Department of Medicine I, University Hospital Munich, Ludwig-Maximilians-Universität, Munich, Germany
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, Departments of Medicine and Epidemiology, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, WA 98101, USA
| | - Mark J Caulfield
- Clinical Pharmacology, William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK.,NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Colin N A Palmer
- Division of Molecular and Clinical Medicine, School of Medicine, University of Dundee, DD1?9SY, UK
| | - Serena Sanna
- Istituto di Ricerca Genetica e Biomedica (IRGB), CNR, Monserrato, Italy
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.,Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - Panos Deloukas
- Clinical Pharmacology, William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Oluf Pedersen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 1124 W. Carson Street, Torrance, CA 90502, USA
| | - Marcus Dörr
- Department of Internal Medicine B - Cardiology, Pneumology, Infectious Diseases, Intensive Care Medicine; University Medicine Greifswald; Greifswald, 17475, Germany & DZHK (German Centre for Cardiovascular Research); partner site Greifswald; Greifswald, 17475, Germany
| | | | - Caroline Hayward
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road South, Edinburgh, EH4?2XU, UK
| | - Dan E Arking
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA, 21205 and
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Pim van der Harst
- University Medical Center Groningen, University of Groningen, Department of Cardiology, the Netherlands
| | - Mark Eijgelsheim
- Department of Epidemiology Erasmus MC - University Medical Center Rotterdam, P.O. Box 2040, 3000CA, Rotterdam, the Netherlands
| | - Bruno H Stricker
- Department of Epidemiology Erasmus MC - University Medical Center Rotterdam, P.O. Box 2040, 3000CA, Rotterdam, the Netherlands
| | - Patricia B Munroe
- Clinical Pharmacology, William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK.,NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, EC1M 6BQ, UK
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26
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Ge T, Chen CY, Neale BM, Sabuncu MR, Smoller JW. Phenome-wide heritability analysis of the UK Biobank. PLoS Genet 2017; 13:e1006711. [PMID: 28388634 PMCID: PMC5400281 DOI: 10.1371/journal.pgen.1006711] [Citation(s) in RCA: 149] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2016] [Revised: 04/21/2017] [Accepted: 03/22/2017] [Indexed: 11/18/2022] Open
Abstract
Heritability estimation provides important information about the relative contribution of genetic and environmental factors to phenotypic variation, and provides an upper bound for the utility of genetic risk prediction models. Recent technological and statistical advances have enabled the estimation of additive heritability attributable to common genetic variants (SNP heritability) across a broad phenotypic spectrum. Here, we present a computationally and memory efficient heritability estimation method that can handle large sample sizes, and report the SNP heritability for 551 complex traits derived from the interim data release (152,736 subjects) of the large-scale, population-based UK Biobank, comprising both quantitative phenotypes and disease codes. We demonstrate that common genetic variation contributes to a broad array of quantitative traits and human diseases in the UK population, and identify phenotypes whose heritability is moderated by age (e.g., a majority of physical measures including height and body mass index), sex (e.g., blood pressure related traits) and socioeconomic status (education). Our study represents the first comprehensive phenome-wide heritability analysis in the UK Biobank, and underscores the importance of considering population characteristics in interpreting heritability. Heritability of a trait refers to the proportion of phenotypic variation that is due to genetic variation among individuals. It provides important information about the genetic basis of complex traits and indicates whether a phenotype is an appropriate target for more specific statistical and molecular genetic analyses. Recent studies have leveraged the increasingly ubiquitous genome-wide data and documented the heritability attributable to common genetic variation captured by genotyping microarrays for a wide range of human traits. However, heritability is not a fixed property of a phenotype and can vary with population-specific differences in the genetic background and environmental variation. Here, using a computationally and memory efficient heritability estimation method, we report the heritability for a large number of traits derived from the large-scale, population-based UK Biobank, and, for the first time, demonstrate the moderating effect of three major demographic variables (age, sex and socioeconomic status) on heritability estimates derived from genome-wide common genetic variation. Our study represents the first comprehensive heritability analysis across the phenotypic spectrum in the UK Biobank.
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Affiliation(s)
- Tian Ge
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital / Harvard Medical School, Charlestown, MA, United States of America
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States of America
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, United States of America
- * E-mail: (TG); (JWS)
| | - Chia-Yen Chen
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States of America
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, United States of America
- Analytic and Translational Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States of America
| | - Benjamin M. Neale
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States of America
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, United States of America
- Analytic and Translational Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States of America
| | - Mert R. Sabuncu
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital / Harvard Medical School, Charlestown, MA, United States of America
- School of Electrical and Computer Engineering and Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, United States of America
| | - Jordan W. Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States of America
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, United States of America
- * E-mail: (TG); (JWS)
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27
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Azevêdo LM, de Souza AC, Santos LES, Miguel Dos Santos R, de Fernandes MOM, Almeida JA, Pardono E. Fractionated Concurrent Exercise throughout the Day Does Not Promote Acute Blood Pressure Benefits in Hypertensive Middle-aged Women. Front Cardiovasc Med 2017; 4:6. [PMID: 28261583 PMCID: PMC5308062 DOI: 10.3389/fcvm.2017.00006] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2016] [Accepted: 01/25/2017] [Indexed: 01/22/2023] Open
Abstract
Hypertension is a chronic disease that affects about 30% of the world’s population, and the physical exercise plays an important role on its non-pharmacological treatment. Anywise, the dose–response of physical exercise fractionation throughout the day demands more investigation, allowing new exercise prescription possibilities. Therefore, this study aimed to analyze the acute blood pressure (BP) kinetics after 1 h of exercises and the BP reactivity after different concurrent exercise (CE) sessions and its fractioning of hypertensive middle-aged women. In this way, 11 hypertensive women voluntarily underwent three experimental sessions and one control day [control session (CS)]. In the morning session (MS) and night session (NS), the exercise was fully realized in the morning and evening, respectively. For the fractionized session (FS), 50% of the volume was applied in the morning and the remaining 50% during the evening. The MS provided the greatest moments (p ≤ 0.05) of post-exercise hypotension (PEH) for systolic BP (SBP) and highest reduction of BP reactivity for SBP (~44%) and diastolic BP (DBP) (~59%) compared to CS (p ≤ 0.05). The findings of the present study have shown that MS is effective for PEH to SBP, as well as it promotes high quality of attenuation for BP reactivity, greater than the other sessions.
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Affiliation(s)
- Luan M Azevêdo
- Programa de Pós Graduação em Educação Física (PPGEF), Universidade Federal de Sergipe , São Cristóvão , Brazil
| | - Alice C de Souza
- Programa de Pós Graduação em Educação Física (PPGEF), Universidade Federal de Sergipe , São Cristóvão , Brazil
| | - Laiza Ellen S Santos
- Programa de Pós Graduação em Educação Física (PPGEF), Universidade Federal de Sergipe , São Cristóvão , Brazil
| | - Rodrigo Miguel Dos Santos
- Programa de Pós Graduação em Educação Física (PPGEF), Universidade Federal de Sergipe , São Cristóvão , Brazil
| | - Manuella O M de Fernandes
- Programa de Pós Graduação em Educação Física (PPGEF), Universidade Federal de Sergipe , São Cristóvão , Brazil
| | - Jeeser A Almeida
- Programa de Pós Graduação em Saúde e Desenvolvimento na Região Centro-Oeste (PPGSD), Universidade Federal de Mato Grosso do Sul , Campo Grande , Brazil
| | - Emerson Pardono
- Programa de Pós Graduação em Educação Física (PPGEF), Universidade Federal de Sergipe , São Cristóvão , Brazil
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28
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Associations Between Obesity Indicators and Blood Pressure in Chinese Adult Twins. Twin Res Hum Genet 2017; 20:28-35. [DOI: 10.1017/thg.2016.95] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Obesity is associated with blood pressure (BP), but the associations between different obesity indicators and BP have not reached agreement. Besides, both obesity and BP are influenced by genetic and environmental factors. Whether they share the same genetic or environmental etiology has not been fully understood. We therefore analyzed the relationship between different obesity indicators and BP components as well as the genetic and environmental contributions to these relationships in a Chinese adult twin sample. Twins aged 18–79 years (n = 941) were included in this study. Body mass index (BMI) was used as the index of general obesity, whereas waist circumference (WC), waist-to-height ratio (WHtR), and waist-to-hip ratio (WHR) were used as the indicators of central obesity. BP components included systolic blood pressure (SBP) and diastolic blood pressure (DBP). Linear regression models and bivariate structural equation models were used to examine the relation of various obesity indicators with BP components, and genetic or environmental influences on these associations, respectively. A strong association of BP components with BMI—and a somewhat weaker association with WC, WHtR, and WHR—was found in both sexes, independent of familial factors. Of these phenotypic correlations between obesity indicators and BP components, 60–76% were attributed to genetic factors, whereas 24–40% were attributed to unique environmental factors. General obesity was most strongly associated with high BP in Chinese adult twins. There were common genetic backgrounds for obesity and BP, and unique environmental factors also played a role.
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29
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Iacono WG, Malone SM, Vrieze SI. Endophenotype best practices. Int J Psychophysiol 2017; 111:115-144. [PMID: 27473600 PMCID: PMC5219856 DOI: 10.1016/j.ijpsycho.2016.07.516] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2016] [Revised: 07/21/2016] [Accepted: 07/24/2016] [Indexed: 01/19/2023]
Abstract
This review examines the current state of electrophysiological endophenotype research and recommends best practices that are based on knowledge gleaned from the last decade of molecular genetic research with complex traits. Endophenotype research is being oversold for its potential to help discover psychopathology relevant genes using the types of small samples feasible for electrophysiological research. This is largely because the genetic architecture of endophenotypes appears to be very much like that of behavioral traits and disorders: they are complex, influenced by many variants (e.g., tens of thousands) within many genes, each contributing a very small effect. Out of over 40 electrophysiological endophenotypes covered by our review, only resting heart, a measure that has received scant advocacy as an endophenotype, emerges as an electrophysiological variable with verified associations with molecular genetic variants. To move the field forward, investigations designed to discover novel variants associated with endophenotypes will need extremely large samples best obtained by forming consortia and sharing data obtained from genome wide arrays. In addition, endophenotype research can benefit from successful molecular genetic studies of psychopathology by examining the degree to which these verified psychopathology-relevant variants are also associated with an endophenotype, and by using knowledge about the functional significance of these variants to generate new endophenotypes. Even without molecular genetic associations, endophenotypes still have value in studying the development of disorders in unaffected individuals at high genetic risk, constructing animal models, and gaining insight into neural mechanisms that are relevant to clinical disorder.
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30
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Nederend I, Schutte NM, Bartels M, Ten Harkel ADJ, de Geus EJC. Heritability of heart rate recovery and vagal rebound after exercise. Eur J Appl Physiol 2016; 116:2167-2176. [PMID: 27614881 PMCID: PMC5118411 DOI: 10.1007/s00421-016-3459-y] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2016] [Accepted: 08/24/2016] [Indexed: 12/19/2022]
Abstract
Purpose The prognostic power of heart rate recovery (HRR) after exercise has been well established but the exact origin of individual differences in HRR remains unclear. This study aims to estimate the heritability of HRR and vagal rebound after maximal exercise in adolescents. Furthermore, the role of voluntary regular exercise behavior (EB) in HRR and vagal rebound is tested. Methods 491 healthy adolescent twins and their siblings were recruited for maximal exercise testing, followed by a standardized cooldown with measurement of the electrocardiogram and respiratory frequency. Immediate and long-term HRR (HRR60 and HRR180) and vagal rebound (heart rate variability in the respiratory frequency range) were assessed 1 and 3 min after exercise. Multivariate twin modeling was used to estimate heritability of all measured variables and to compute the genetic contribution to their covariance. Results Heritability of HRR60, HRR180 and immediate and long-term vagal rebound is 60 % (95 % CI: 48–67), 65 % (95 % CI: 54–73), 23 % (95 % CI: 11–35) and 3 % (95 % CI: 0–11), respectively. We find evidence for two separate genetic factors with one factor influencing overall cardiac vagal control, including resting heart rate and respiratory sinus arrhythmia, and a specific factor for cardiac vagal exercise recovery. EB was only modestly associated with resting heart rate (r = −0.27) and HRR (rHRR60 = 0.10; rHRR180 = 0.19) with very high genetic contribution to these associations (88–91 %). Conclusions Individual differences in HRR and immediate vagal rebound can to a large extent be explained by genetic factors. These innate cardiac vagal exercise recovery factors partly reflect the effects of heritable differences in EB.
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Affiliation(s)
- Ineke Nederend
- Department of Biological Psychology, Faculty of behavioral and Movement Sciences, VU University Amsterdam, Van der Boechorststraat 1, 1081 BT, Amsterdam, The Netherlands. .,EMGO + Institute for Health and Care Research, VU University Medical Center, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands. .,Department of Pediatric Cardiology, LUMC University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands.
| | - Nienke M Schutte
- Department of Biological Psychology, Faculty of behavioral and Movement Sciences, VU University Amsterdam, Van der Boechorststraat 1, 1081 BT, Amsterdam, The Netherlands.,EMGO + Institute for Health and Care Research, VU University Medical Center, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
| | - Meike Bartels
- Department of Biological Psychology, Faculty of behavioral and Movement Sciences, VU University Amsterdam, Van der Boechorststraat 1, 1081 BT, Amsterdam, The Netherlands.,EMGO + Institute for Health and Care Research, VU University Medical Center, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
| | - Arend D J Ten Harkel
- Department of Pediatric Cardiology, LUMC University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, Faculty of behavioral and Movement Sciences, VU University Amsterdam, Van der Boechorststraat 1, 1081 BT, Amsterdam, The Netherlands.,EMGO + Institute for Health and Care Research, VU University Medical Center, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
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