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Ramírez J, van Duijvenboden S, Young WJ, Chen Y, Usman T, Orini M, Lambiase PD, Tinker A, Bell CG, Morris AP, Munroe PB. Fine mapping of candidate effector genes for heart rate. Hum Genet 2024:10.1007/s00439-024-02684-z. [PMID: 38969939 DOI: 10.1007/s00439-024-02684-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 06/19/2024] [Indexed: 07/07/2024]
Abstract
An elevated resting heart rate (RHR) is associated with increased cardiovascular mortality. Genome-wide association studies (GWAS) have identified > 350 loci. Uniquely, in this study we applied genetic fine-mapping leveraging tissue specific chromatin segmentation and colocalization analyses to identify causal variants and candidate effector genes for RHR. We used RHR GWAS summary statistics from 388,237 individuals of European ancestry from UK Biobank and performed fine mapping using publicly available genomic annotation datasets. High-confidence causal variants (accounting for > 75% posterior probability) were identified, and we collated candidate effector genes using a multi-omics approach that combined evidence from colocalisation with molecular quantitative trait loci (QTLs), and long-range chromatin interaction analyses. Finally, we performed druggability analyses to investigate drug repurposing opportunities. The fine mapping pipeline indicated 442 distinct RHR signals. For 90 signals, a single variant was identified as a high-confidence causal variant, of which 22 were annotated as missense. In trait-relevant tissues, 39 signals colocalised with cis-expression QTLs (eQTLs), 3 with cis-protein QTLs (pQTLs), and 75 had promoter interactions via Hi-C. In total, 262 candidate genes were highlighted (79% had promoter interactions, 15% had a colocalised eQTL, 8% had a missense variant and 1% had a colocalised pQTL), and, for the first time, enrichment in nervous system pathways. Druggability analyses highlighted ACHE, CALCRL, MYT1 and TDP1 as potential targets. Our genetic fine-mapping pipeline prioritised 262 candidate genes for RHR that warrant further investigation in functional studies, and we provide potential therapeutic targets to reduce RHR and cardiovascular mortality.
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Affiliation(s)
- Julia Ramírez
- Aragon Institute of Engineering Research, University of Zaragoza, Zaragoza, Spain.
- Centro de Investigación Biomédica en Red - Bioingeniería, Biomateriales y Nanomedicina, Zaragoza, Spain.
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.
| | - Stefan van Duijvenboden
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.
- Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK.
- Institute of Cardiovascular Science, University College London, London, UK.
| | - William J Young
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew's Hospital, London, EC1A 7BE, UK
| | - Yutang Chen
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland
| | | | - Michele Orini
- Institute of Cardiovascular Science, University College London, London, UK
| | - Pier D Lambiase
- Institute of Cardiovascular Science, University College London, London, UK
- Barts Heart Centre, St Bartholomew's Hospital, London, EC1A 7BE, UK
| | - Andrew Tinker
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Barts Cardiovascular Biomedical Research Centre, National Institute of Health and Care Research, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Christopher G Bell
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Andrew P Morris
- Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK
- National Institute of Health and Care Research, Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Patricia B Munroe
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.
- Khalifa University, Abu Dhabi, United Arab Emirates.
- Barts Cardiovascular Biomedical Research Centre, National Institute of Health and Care Research, Queen Mary University of London, London, EC1M 6BQ, UK.
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2
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Gelernter J, Levey DF, Galimberti M, Harrington K, Zhou H, Adhikari K, Gupta P, Gaziano JM, Eliott D, Stein MB. Genome-wide association study of the common retinal disorder epiretinal membrane: Significant risk loci in each of three American populations. CELL GENOMICS 2024; 4:100582. [PMID: 38870908 PMCID: PMC11228954 DOI: 10.1016/j.xgen.2024.100582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 02/20/2024] [Accepted: 05/10/2024] [Indexed: 06/15/2024]
Abstract
Epiretinal membrane (ERM) is a common retinal condition characterized by the presence of fibrocellular tissue on the retinal surface, often with visual distortion and loss of visual acuity. We studied European American (EUR), African American (AFR), and Latino (admixed American, AMR) ERM participants in the Million Veteran Program (MVP) for genome-wide association analysis-a total of 38,232 case individuals and 557,988 control individuals. We completed a genome-wide association study (GWAS) in each population separately, and then results were meta-analyzed. Genome-wide significant (GWS) associations were observed in all three populations studied: 31 risk loci in EUR subjects, 3 in AFR, and 2 in AMR, with 48 in trans-ancestry meta-analysis. Many results replicated in the FinnGen sample. Several GWS variants associate to alterations in gene expression in the macula. ERM showed significant genetic correlation to multiple traits. Pathway enrichment analyses implicated collagen and collagen-adjacent mechanisms, among others. This well-powered ERM GWAS identified novel genetic associations that point to biological mechanisms for ERM.
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Affiliation(s)
- Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA; Departments of Genetics and Neuroscience, Yale School of Medicine, New Haven, CT, USA.
| | - Daniel F Levey
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Marco Galimberti
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Kelly Harrington
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA; Department of Psychiatry, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Hang Zhou
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Keyrun Adhikari
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Priya Gupta
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - J Michael Gaziano
- Department of Medicine, Harvard Medical School, Boston, MA, USA; Department of Medicine, Divisions of Aging and Preventative Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Dean Eliott
- Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Murray B Stein
- University of California, San Diego, La Jolla, CA, USA; VA San Diego Healthcare System, San Diego, CA, USA
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3
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Luo P, Guo R, Gao D, Zhang Q. Causal relationship between sex hormones and cutaneous melanoma: a two-sample Mendelian randomized study. Melanoma Res 2024:00008390-990000000-00153. [PMID: 38842104 DOI: 10.1097/cmr.0000000000000983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2024]
Abstract
OBJECTIVE This study aimed to elucidate the genetic aspects of the relationship between sex hormones and cutaneous melanoma risk, providing valuable insights into this complex association. METHODS In this study, we used estradiol, bioavailable testosterone, sex hormone-binding globulin, and total testosterone as the exposure and melanoma as the outcome for two-sample Mendelian randomization analysis. In this study, a random-effects inverse-variance weighting (IVW) model was used as the main analysis model, and the corresponding weighted median, simple mode, weighted mode, and Mendelian randomization‒Egger methods were used as supplementary methods. We assessed both heterogeneity and horizontal pleiotropy in our study, scrutinizing whether the analysis results were affected by any individual single nucleotide polymorphism. RESULTS The random-effects IVW method indicated that estradiol [odds ratio (OR), 1.000; 95% confidence interval (CI), 0.998-1.003; P = 0.658], bioavailable testosterone (OR = 1.001, 95% CI, 0.999-1.003; P = 0.294), sex hormone-binding globulin (IVW: OR, 1.000; 95% CI, 0.998-1.003; P = 0.658), and total testosterone (IVW: OR, 1.002; 95% CI, 0.999-1.005; P = 0.135) were not genetically linked to cutaneous melanoma. No analyses exhibited heterogeneity, horizontal pleiotropy, or deviations. CONCLUSION We were unable to find genetic evidence for a causal relationship between sex hormones and the occurrence of cutaneous melanoma in this study. These results are limited by sample size and population, so the causal relationship between sex hormones and cutaneous melanoma needs to be further studied.
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Affiliation(s)
- Pan Luo
- Department of Auricular Reconstruction, Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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4
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Luo P, Gao D, Zhang Q. Genetic causal relationship between gut microbiota and basal cell carcinoma: A two-sample mendelian randomization study. Skin Res Technol 2024; 30:e13804. [PMID: 38895789 PMCID: PMC11187847 DOI: 10.1111/srt.13804] [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: 05/14/2024] [Accepted: 05/27/2024] [Indexed: 06/21/2024]
Abstract
OBJECTIVE Research has previously established connections between the intestinal microbiome and the progression of some cancers. However, there is a noticeable gap in the literature in regard to using Mendelian randomisation (MR) to delve into potential causal relationships between the gut microbiota (GM) and basal cell carcinoma (BCC). Therefore, the purpose of our study was to use MR to explore the causal relationship between four kinds of GM (Bacteroides, Streptococcus, Proteobacteria and Lachnospiraceae) and BCC. METHODS We used genome-wide association study (GWAS) data and MR to explore the causal relationship between four kinds of GM and BCC. This study primarily employed the random effect inverse variance weighted (IVW) model for analysis, as complemented by additional methods including the simple mode, weighted median, weighted mode and MR‒Egger methods. We used heterogeneity and horizontal multiplicity to judge the reliability of each analysis. MR-PRESSO was mainly used to detect and correct outliers. RESULTS The random-effects IVW results showed that Bacteroides (OR = 0.936, 95% CI = 0.787-1.113, p = 0.455), Streptococcus (OR = 0.974, 95% CI = 0.875-1.083, p = 0.629), Proteobacteria (OR = 1.113, 95% CI = 0.977-1.267, p = 0.106) and Lachnospiraceae (OR = 1.027, 95% CI = 0.899-1.173, p = 0.688) had no genetic causal relationship with BCC. All analyses revealed no horizontal pleiotropy, heterogeneity or outliers. CONCLUSION We found that Bacteroides, Streptococcus, Proteobacteria and Lachnospiraceae do not increase the incidence of BCC at the genetic level, which provides new insight for the study of GM and BCC.
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Affiliation(s)
- Pan Luo
- Department of Comprehensive Plastic SurgeryPlastic Surgery HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Dejin Gao
- Department of Comprehensive Plastic SurgeryPlastic Surgery HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Qingguo Zhang
- Department of Comprehensive Plastic SurgeryPlastic Surgery HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
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5
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Wang Q, Tang TM, Youlton N, Weldy CS, Kenney AM, Ronen O, Weston Hughes J, Chin ET, Sutton SC, Agarwal A, Li X, Behr M, Kumbier K, Moravec CS, Wilson Tang WH, Margulies KB, Cappola TP, Butte AJ, Arnaout R, Brown JB, Priest JR, Parikh VN, Yu B, Ashley EA. Epistasis regulates genetic control of cardiac hypertrophy. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.11.06.23297858. [PMID: 37987017 PMCID: PMC10659487 DOI: 10.1101/2023.11.06.23297858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
The combinatorial effect of genetic variants is often assumed to be additive. Although genetic variation can clearly interact non-additively, methods to uncover epistatic relationships remain in their infancy. We develop low-signal signed iterative random forests to elucidate the complex genetic architecture of cardiac hypertrophy. We derive deep learning-based estimates of left ventricular mass from the cardiac MRI scans of 29,661 individuals enrolled in the UK Biobank. We report epistatic genetic variation including variants close to CCDC141 , IGF1R , TTN , and TNKS. Several loci where variants were deemed insignificant in univariate genome-wide association analyses are identified. Functional genomic and integrative enrichment analyses reveal a complex gene regulatory network in which genes mapped from these loci share biological processes and myogenic regulatory factors. Through a network analysis of transcriptomic data from 313 explanted human hearts, we found strong gene co-expression correlations between these statistical epistasis contributors in healthy hearts and a significant connectivity decrease in failing hearts. We assess causality of epistatic effects via RNA silencing of gene-gene interactions in human induced pluripotent stem cell-derived cardiomyocytes. Finally, single-cell morphology analysis using a novel high-throughput microfluidic system shows that cardiomyocyte hypertrophy is non-additively modifiable by specific pairwise interactions between CCDC141 and both TTN and IGF1R . Our results expand the scope of genetic regulation of cardiac structure to epistasis.
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6
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Reimann MJ, Cremer S, Christiansen L, Ibragimov E, Gao F, Cirera S, Fredholm M, Olsen LH, Karlskov-Mortensen P. Mitral valve transcriptome analysis in thirty-four age-matched Cavalier King Charles Spaniels with or without congestive heart failure caused by myxomatous mitral valve disease. Mamm Genome 2024; 35:77-89. [PMID: 37938355 PMCID: PMC10884180 DOI: 10.1007/s00335-023-10024-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 10/08/2023] [Indexed: 11/09/2023]
Abstract
We here report the results of a mitral valve transcriptome study designed to identify genes and molecular pathways involved in development of congestive heart failure (CHF) following myxomatous mitral valve disease (MMVD) in dogs. The study is focused on a cohort of elderly age-matched dogs (n = 34, age ~ 10 years) from a single breed-Cavalier King Charles Spaniels (CKCS)-with a high incidence of MMVD. The cohort comprises 19 dogs (10♀, 9♂) without MMVD-associated CHF, and 15 dogs (6♀, 9♂) with CHF caused by MMVD; i.e., we compare gene expression in breed and age-matched groups of dogs, which only differ with respect to CHF status. We identify 56 genes, which are differentially expressed between the two groups. In this list of genes, we confirm an enrichment of genes related to the TNFβ-signaling pathway, extracellular matrix organization, vascular development, and endothelium damage, which also have been identified in previous studies. However, the genes with the greatest difference in expression between the two groups are CNTN3 and MYH1. Both genes encode proteins, which are predicted to have an effect on the contractile activity of myocardial cells, which in turn may have an effect on valvular performance and hemodynamics across the mitral valve. This may result in shear forces with impact on MMVD progression.
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Affiliation(s)
- Maria J Reimann
- Preclinical Disease Biology, Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark
| | - Signe Cremer
- Preclinical Disease Biology, Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark
| | - Liselotte Christiansen
- Preclinical Disease Biology, Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark
| | - Emil Ibragimov
- Animal Genetics and Breeding, Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark
| | - Fei Gao
- Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Comparative Pediatrics and Nutrition, Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark
| | - Susanna Cirera
- Animal Genetics and Breeding, Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark
| | - Merete Fredholm
- Animal Genetics and Breeding, Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark
| | - Lisbeth H Olsen
- Preclinical Disease Biology, Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark
| | - Peter Karlskov-Mortensen
- Animal Genetics and Breeding, Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark.
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7
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Gomes B, Singh A, O'Sullivan JW, Schnurr TM, Goddard PC, Loong S, Amar D, Hughes JW, Kostur M, Haddad F, Salerno M, Foo R, Montgomery SB, Parikh VN, Meder B, Ashley EA. Genetic architecture of cardiac dynamic flow volumes. Nat Genet 2024; 56:245-257. [PMID: 38082205 DOI: 10.1038/s41588-023-01587-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 10/23/2023] [Indexed: 02/04/2024]
Abstract
Cardiac blood flow is a critical determinant of human health. However, the definition of its genetic architecture is limited by the technical challenge of capturing dynamic flow volumes from cardiac imaging at scale. We present DeepFlow, a deep-learning system to extract cardiac flow and volumes from phase-contrast cardiac magnetic resonance imaging. A mixed-linear model applied to 37,653 individuals from the UK Biobank reveals genome-wide significant associations across cardiac dynamic flow volumes spanning from aortic forward velocity to aortic regurgitation fraction. Mendelian randomization reveals a causal role for aortic root size in aortic valve regurgitation. Among the most significant contributing variants, localizing genes (near ELN, PRDM6 and ADAMTS7) are implicated in connective tissue and blood pressure pathways. Here we show that DeepFlow cardiac flow phenotyping at scale, combined with genotyping data, reinforces the contribution of connective tissue genes, blood pressure and root size to aortic valve function.
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Affiliation(s)
- Bruna Gomes
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
- Department of Cardiology, Pneumology and Angiology, Heidelberg University Hospital, Heidelberg, Germany
- Informatics for Life, Heidelberg, Germany
| | - Aditya Singh
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Jack W O'Sullivan
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Theresia M Schnurr
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Pagé C Goddard
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Shaun Loong
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - David Amar
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - J Weston Hughes
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Mykhailo Kostur
- Department of Cardiology, Pneumology and Angiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Francois Haddad
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Michael Salerno
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Roger Foo
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Stephen B Montgomery
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Victoria N Parikh
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Benjamin Meder
- Department of Cardiology, Pneumology and Angiology, Heidelberg University Hospital, Heidelberg, Germany
- Informatics for Life, Heidelberg, Germany
| | - Euan A Ashley
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA.
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Jonker T, Barnett P, Boink GJJ, Christoffels VM. Role of Genetic Variation in Transcriptional Regulatory Elements in Heart Rhythm. Cells 2023; 13:4. [PMID: 38201209 PMCID: PMC10777909 DOI: 10.3390/cells13010004] [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: 09/27/2023] [Revised: 12/08/2023] [Accepted: 12/11/2023] [Indexed: 01/12/2024] Open
Abstract
Genetic predisposition to cardiac arrhythmias has been a field of intense investigation. Research initially focused on rare hereditary arrhythmias, but over the last two decades, the role of genetic variation (single nucleotide polymorphisms) in heart rate, rhythm, and arrhythmias has been taken into consideration as well. In particular, genome-wide association studies have identified hundreds of genomic loci associated with quantitative electrocardiographic traits, atrial fibrillation, and less common arrhythmias such as Brugada syndrome. A significant number of associated variants have been found to systematically localize in non-coding regulatory elements that control the tissue-specific and temporal transcription of genes encoding transcription factors, ion channels, and other proteins. However, the identification of causal variants and the mechanism underlying their impact on phenotype has proven difficult due to the complex tissue-specific, time-resolved, condition-dependent, and combinatorial function of regulatory elements, as well as their modest conservation across different model species. In this review, we discuss research efforts aimed at identifying and characterizing-trait-associated variant regulatory elements and the molecular mechanisms underlying their impact on heart rate or rhythm.
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Affiliation(s)
- Timo Jonker
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, 1105 AZ Amsterdam, The Netherlands; (T.J.); (P.B.); (G.J.J.B.)
| | - Phil Barnett
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, 1105 AZ Amsterdam, The Netherlands; (T.J.); (P.B.); (G.J.J.B.)
| | - Gerard J. J. Boink
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, 1105 AZ Amsterdam, The Netherlands; (T.J.); (P.B.); (G.J.J.B.)
- Department of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, 1105 AZ Amsterdam, The Netherlands
| | - Vincent M. Christoffels
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, 1105 AZ Amsterdam, The Netherlands; (T.J.); (P.B.); (G.J.J.B.)
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9
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Xiang Y, Song J, Liang Y, Sun J, Zheng Z. Causal relationship between psychiatric traits and temporomandibular disorders: a bidirectional two-sample Mendelian randomization study. Clin Oral Investig 2023; 27:7513-7521. [PMID: 37907704 PMCID: PMC10713754 DOI: 10.1007/s00784-023-05339-x] [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: 04/03/2023] [Accepted: 10/11/2023] [Indexed: 11/02/2023]
Abstract
OBJECTIVES This study was to investigate the causal relationship between temporomandibular disorders (TMD) and psychiatric disorders by Mendelian randomization (MR) analysis. MATERIALS AND METHODS A two-sample bidirectional MR analysis was adopted to systematically explore the causal relationship between TMD and eight psychiatric traits, including anxiety disorder (AD), panic disorder (PD), major depressive disorder (MDD), neuroticism, attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BIP), and schizophrenia (SCZ). Inverse variance weighted (IVW), weighted median, and MR-Egger regression were used in my study. Furthermore, we also performed three sensitivity analyses to illustrate the reliability of the analysis. RESULTS Two psychiatric traits have risk effects on TMD: PD (OR = 1.118, 95% CI: 1.047-1.194, P = 8.161 × 10-4, MDD (OR = 1.961, 95% CI: 1.450-2.653, P = 1.230 × 10-5). Despite not surpassing the strict Bonferroni correction applied (P > 0.00625), we could think that there was a suggestive causal effect of neuroticism and SCZ increasing the risk of TMD. On the reverse MR analysis, we found no significant evidence of causal effects of TMD on these psychiatric traits. Except for heterogeneity in the causal analysis for SCZ on TMD, no heterogeneity and horizontal pleiotropy were detected in the other analyses. CONCLUSIONS Our two-sample MR study has provided further evidence of PD and MDD being related to a higher risk of TMD. CLINICAL RELEVANCE These findings highlight the importance of closely monitoring mental traits during future TMD treatments to prevent an increased risk of TMD.
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Affiliation(s)
- Yulin Xiang
- School of Stomatology, Zunyi Medical University, Zunyi, China
- Department of Endodontics, Guiyang Stomatological Hospital, 253 Jiefang Road, Nanming District, Guiyang, 550005, Guizhou, China
| | - Jukun Song
- Department of Oral and Maxillofacial Surgery, The Affiliated Stomatological Hospital of Guizhou Medical University, Guiyang, China
| | - Ying Liang
- School of Stomatology, Zunyi Medical University, Zunyi, China
- Department of Endodontics, Guiyang Stomatological Hospital, 253 Jiefang Road, Nanming District, Guiyang, 550005, Guizhou, China
| | - Jiaxin Sun
- School of Stomatology, Zunyi Medical University, Zunyi, China
- Department of Endodontics, Guiyang Stomatological Hospital, 253 Jiefang Road, Nanming District, Guiyang, 550005, Guizhou, China
| | - Zhijun Zheng
- School of Stomatology, Zunyi Medical University, Zunyi, China.
- Department of Endodontics, Guiyang Stomatological Hospital, 253 Jiefang Road, Nanming District, Guiyang, 550005, Guizhou, China.
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10
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James A, Bruce D, Tetlow N, Patel AB, Black E, Whitehead N, Ratcliff A, Jamie Humphreys A, MacDonald N, McDonnell G, Raobaikady R, Thirugnanasambanthar J, Ravindran JI, Whitehead N, Minto G, Abbott TE, Jhanji S, Milliken D, Ackland GL. Heart rate recovery after orthostatic challenge and cardiopulmonary exercise testing in older individuals: prospective multicentre observational cohort study. BJA OPEN 2023; 8:100238. [PMID: 38026081 PMCID: PMC10654531 DOI: 10.1016/j.bjao.2023.100238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 09/12/2023] [Accepted: 10/06/2023] [Indexed: 12/01/2023]
Abstract
Background Impaired vagal function in older individuals, quantified by the 'gold standard' delayed heart rate recovery after maximal exercise (HRRexercise), is an independent predictor of cardiorespiratory capacity and mortality (particularly when HRR ≤12 beats min-1). Heart rate also often declines after orthostatic challenge (HRRorthostatic), but the mechanism remains unclear. We tested whether HRRorthostatic reflects similar vagal autonomic characteristics as HRRexercise. Methods Prospective multicentre cohort study of subjects scheduled for cardiopulmonary exercise testing (CPET) as part of routine care. Before undergoing CPET, heart rate was measured with participants seated for 3 min, before standing for 3 min (HRRorthostatic). HRRexercise 1 min after the end of CPET was recorded. The primary outcome was the correlation between mean heart rate change every 10 s for 1 min after peak heart rate was attained on standing and after exercise for each participant. Secondary outcomes were HRRorthostatic and peak VO2 compared between individuals with HRRexercise <12 beats min-1. Results A total of 87 participants (mean age: 64 yr [95%CI: 61-66]; 48 (55%) females) completed both tests. Mean heart rate change every 10 s for 1 min after peak heart rate after standing and exercise was significantly correlated (R2=0.81; P<0.0001). HRRorthostatic was unchanged in individuals with HRRexercise ≤12 beats min-1 (n=27), but was lower when HRRexercise >12 beats min-1 (n=60; mean difference: 3 beats min-1 [95% confidence interval 1-5 beats min-1]; P<0.0001). Slower HRRorthostatic was associated with lower peak VO2 (mean difference: 3.7 ml kg-1 min-1 [95% confidence interval 0.7-6.8 ml kg-1 min-1]; P=0.039). Conclusion Prognostically significant heart rate recovery after exhaustive exercise is characterised by quantitative differences in heart rate recovery after orthostatic challenge. These data suggest that orthostatic challenge is a valid, simple test indicating vagal impairment. Clinical trial registration researchregistry6550.
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Affiliation(s)
- Aaron James
- Department of Anaesthesia, University Hospitals Plymouth NHS Trust, Plymouth, UK
| | - David Bruce
- Department of Anaesthesia, Perioperative Medicine and Critical Care, Royal Marsden Hospital, London, UK
| | - Nicholas Tetlow
- Department of Anaesthesia, Perioperative Medicine and Critical Care, Royal Marsden Hospital, London, UK
| | - Amour B.U. Patel
- Translational Medicine and Therapeutics, William Harvey Research Institute, Queen Mary, University of London, UK
| | - Ethel Black
- Department of Anaesthesia, Perioperative Medicine and Critical Care, Royal Marsden Hospital, London, UK
| | - Nicole Whitehead
- Department of Anaesthesia, Perioperative Medicine and Critical Care, Royal Marsden Hospital, London, UK
| | - Anna Ratcliff
- Department of Anaesthesia, University Hospitals Plymouth NHS Trust, Plymouth, UK
| | | | - Neil MacDonald
- Department of Anaesthesia and Perioperative Medicine, Royal London Hospital, London, UK
| | - Gayle McDonnell
- Department of Anaesthesia and Perioperative Medicine, Royal London Hospital, London, UK
| | - Ravishankar Raobaikady
- Translational Medicine and Therapeutics, William Harvey Research Institute, Queen Mary, University of London, UK
| | | | - Jeuela I. Ravindran
- Translational Medicine and Therapeutics, William Harvey Research Institute, Queen Mary, University of London, UK
| | - Nicole Whitehead
- Department of Anaesthesia, Perioperative Medicine and Critical Care, Royal Marsden Hospital, London, UK
| | - Gary Minto
- Department of Anaesthesia, University Hospitals Plymouth NHS Trust, Plymouth, UK
| | - Tom E.F. Abbott
- Translational Medicine and Therapeutics, William Harvey Research Institute, Queen Mary, University of London, UK
- Department of Anaesthesia and Perioperative Medicine, Royal London Hospital, London, UK
| | - Shaman Jhanji
- Department of Anaesthesia, Perioperative Medicine and Critical Care, Royal Marsden Hospital, London, UK
| | - Don Milliken
- Department of Anaesthesia, Perioperative Medicine and Critical Care, Royal Marsden Hospital, London, UK
| | - Gareth L. Ackland
- Translational Medicine and Therapeutics, William Harvey Research Institute, Queen Mary, University of London, UK
- Department of Anaesthesia and Perioperative Medicine, Royal London Hospital, London, UK
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11
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Lyu F, Wang L, Jia Y, Wang Y, Qi H, Dai Z, Zhou X, Zhu H, Li B, Xu Y, Liu J. Analysis of Zinc and Stromal Immunity in Disuse Osteoporosis: Mendelian Randomization and Transcriptomic Analysis. Orthop Surg 2023; 15:2947-2959. [PMID: 37752822 PMCID: PMC10622276 DOI: 10.1111/os.13840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 06/22/2023] [Accepted: 06/30/2023] [Indexed: 09/28/2023] Open
Abstract
OBJECTIVE Disuse osteoporosis is known to be primarily caused by a lack of exercise. However, the causal relationships between zinc and immunity and disuse osteoporosis remain unknown. This study investigated these relationships and their potential mechanisms. METHODS This study was an integrative study combining genome-wide association studies and transcriptomics. Two-sample Mendelian randomization analysis (MR) was used to analyze the causal relationships between exposures (zinc, immunity, physical activity) and the outcome (osteoporosis) with the aid of single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs). Four models, MR-Egger, inverse variance weighted, weighted median and MR-Pleiotrophy RESidual Sum and Outlier (MRPRESSO), were used to calculate odds ratio values. Sensitivity and heterogeneity analyses were also performed using MRPRESSO and MR-Egger methods. The mRNA transcriptomic analysis was subsequently conducted. Zinc metabolism scores were acquired through single-sample Gene Set Enrichment Analysis algorithms. Stromal scores were obtained using the R Package "estimate" algorithms. Important Kyoto Encyclopedia of Genes and Genomes and Gene Ontology pathways were also derived through gene set variation analysis. Cytoscape software helped construct the transcription factor (TF)-mRNA-microRNA (miRNA) network. Virtual screening and molecular docking were performed. Polymerase chain reaction validation was also carried out in vivo. RESULTS Causal relationships were demonstrated between zinc and exercise (95% confidence interval [CI] = 1.30-2.95, p = 0.001), exercise and immunity (95% CI = 0.36-0.80, p = 0.002), exercise and osteoporosis (95% CI = 0.97-0.99, p = 0.0007), and immunity disorder and osteoporosis (95% CI = 1.30-2.03, p = 0.00002). One hundred and seventy-nine mRNAs in important modules were screened. Combining the differential expressional genes (DEGs) and the Boruta selection, six DEGs were screened (AHNAK, CSF2, ADAMTS12, SRA1, RUNX2, and SLC39A14). TF HOXC10 and miRNA hsa-miR-204 were predicted. Then, the TF-mRNA-miRNA network was successfully constructed. RUNX2 and SLC39A14 were identified as hub mRNAs in the TF-mRNA-miRNA network. Eventually, the novel small drug C6O4NH5 was designed according to the pharmacophore structure of SLC39A14. The docking energy for the novel drug was -5.83 kcal/mol. SLC39A14 and RUNX2 were downregulated (of statistical significance p-value < 0.05) in our animal experiment. CONCLUSION This study revealed that zinc had a protective causal relationship with disuse osteoporosis by promoting exercise and immunity. SLC39A14 and RUNX2 mRNA participated in this zinc-related mechanism.
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Affiliation(s)
- Fei Lyu
- College of OrthopedicsTianjin Medical UniversityTianjinChina
- Department of Joint SurgeryTianjin HospitalTianjinChina
- Orthopedic Center (Sports Medicine Center)Inner Mongolia People's HospitalHohhotChina
| | - Li Wang
- College of OrthopedicsTianjin Medical UniversityTianjinChina
- Department of Joint SurgeryTianjin HospitalTianjinChina
| | - Yiming Jia
- College of OrthopedicsTianjin Medical UniversityTianjinChina
- Department of Joint SurgeryTianjin HospitalTianjinChina
- Department of OrthopedicsChifeng Municipal HospitalChifengChina
| | - Yuanlin Wang
- Department of Joint SurgeryTianjin HospitalTianjinChina
- Tianjin Institute of AnesthesiologyTianjin Medical UniversityTianjinChina
| | - Haolan Qi
- School of MedicineNankai UniversityTianjinChina
| | - Zhengxu Dai
- College of OrthopedicsTianjin Medical UniversityTianjinChina
- Department of Joint SurgeryTianjin HospitalTianjinChina
| | - Xuyang Zhou
- College of OrthopedicsTianjin Medical UniversityTianjinChina
- Department of Joint SurgeryTianjin HospitalTianjinChina
| | - Haoran Zhu
- School of MedicineXi'an Jiaotong UniversityXianChina
| | - Bing Li
- College of OrthopedicsTianjin Medical UniversityTianjinChina
- Department of Joint SurgeryTianjin HospitalTianjinChina
| | - Yujing Xu
- Tianjin Key Laboratory on Technologies Enabling Development of Clinical Therapeutics and Diagnostics, School of PharmacyTianjin Medical UniversityTianjinChina
| | - Jun Liu
- College of OrthopedicsTianjin Medical UniversityTianjinChina
- Department of Joint SurgeryTianjin HospitalTianjinChina
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12
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Tegegne BS, Said MA, Ani A, van Roon AM, Shah S, de Geus EJC, van der Harst P, Riese H, Nolte IM, Snieder H. Phenotypic but not genetically predicted heart rate variability associated with all-cause mortality. Commun Biol 2023; 6:1013. [PMID: 37803156 PMCID: PMC10558565 DOI: 10.1038/s42003-023-05376-y] [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: 07/19/2022] [Accepted: 09/19/2023] [Indexed: 10/08/2023] Open
Abstract
Low heart rate variability (HRV) has been widely reported as a predictor for increased mortality. However, the molecular mechanisms are poorly understood. Therefore, this study aimed to identify novel genetic loci associated with HRV and assess the association of phenotypic HRV and genetically predicted HRV with mortality. In a GWAS of 46,075 European ancestry individuals from UK biobank, we identified 17 independent genome-wide significant genetic variants in 16 loci associated with HRV traits. Notably, eight of these loci (RNF220, GNB4, LINCR-002, KLHL3/HNRNPA0, CHRM2, KCNJ5, MED13L, and C160rf72) have not been reported previously. In a prospective phenotypic relationship between HRV and mortality during a median follow-up of seven years, individuals with lower HRV had higher risk of dying from any cause. Genetically predicted HRV, as determined by the genetic risk scores, was not associated with mortality. To the best of our knowledge, the findings provide novel biological insights into the mechanisms underlying HRV. These results also underline the role of the cardiac autonomic nervous system, as indexed by HRV, in predicting mortality.
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Affiliation(s)
- Balewgizie S Tegegne
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - M Abdullah Said
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Alireza Ani
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Arie M van Roon
- Department of Vascular Medicine, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Sonia Shah
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
- Institute of Cardiovascular Science, University College London, London, UK
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Pim van der Harst
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
| | - Harriëtte Riese
- Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation, 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
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
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13
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van de Vegte YJ, Eppinga RN, van der Ende MY, Hagemeijer YP, Mahendran Y, Salfati E, Smith AV, Tan VY, Arking DE, Ntalla I, Appel EV, Schurmann C, Brody JA, Rueedi R, Polasek O, Sveinbjornsson G, Lecoeur C, Ladenvall C, Zhao JH, Isaacs A, Wang L, Luan J, Hwang SJ, Mononen N, Auro K, Jackson AU, Bielak LF, Zeng L, Shah N, Nethander M, Campbell A, Rankinen T, Pechlivanis S, Qi L, Zhao W, Rizzi F, Tanaka T, Robino A, Cocca M, Lange L, Müller-Nurasyid M, Roselli C, Zhang W, Kleber ME, Guo X, Lin HJ, Pavani F, Galesloot TE, Noordam R, Milaneschi Y, Schraut KE, den Hoed M, Degenhardt F, Trompet S, van den Berg ME, Pistis G, Tham YC, Weiss S, Sim XS, Li HL, van der Most PJ, Nolte IM, Lyytikäinen LP, Said MA, Witte DR, Iribarren C, Launer L, Ring SM, de Vries PS, Sever P, Linneberg A, Bottinger EP, Padmanabhan S, Psaty BM, Sotoodehnia N, Kolcic I, Arnar DO, Gudbjartsson DF, Holm H, Balkau B, Silva CT, Newton-Cheh CH, Nikus K, Salo P, Mohlke KL, Peyser PA, Schunkert H, Lorentzon M, Lahti J, Rao DC, Cornelis MC, Faul JD, Smith JA, Stolarz-Skrzypek K, Bandinelli S, Concas MP, Sinagra G, Meitinger T, Waldenberger M, Sinner MF, Strauch K, Delgado GE, Taylor KD, Yao J, Foco L, Melander O, de Graaf J, de Mutsert R, de Geus EJC, Johansson Å, Joshi PK, Lind L, Franke A, Macfarlane PW, Tarasov KV, Tan N, Felix SB, Tai ES, Quek DQ, Snieder H, Ormel J, Ingelsson M, Lindgren C, Morris AP, Raitakari OT, Hansen T, Assimes T, Gudnason V, Timpson NJ, Morrison AC, Munroe PB, Strachan DP, Grarup N, Loos RJF, Heckbert SR, Vollenweider P, Hayward C, Stefansson K, Froguel P, Groop L, Wareham NJ, van Duijn CM, Feitosa MF, O'Donnell CJ, Kähönen M, Perola M, Boehnke M, Kardia SLR, Erdmann J, Palmer CNA, Ohlsson C, Porteous DJ, Eriksson JG, Bouchard C, Moebus S, Kraft P, Weir DR, Cusi D, Ferrucci L, Ulivi S, Girotto G, Correa A, Kääb S, Peters A, Chambers JC, Kooner JS, März W, Rotter JI, Hicks AA, Smith JG, Kiemeney LALM, Mook-Kanamori DO, Penninx BWJH, Gyllensten U, Wilson JF, Burgess S, Sundström J, Lieb W, Jukema JW, Eijgelsheim M, Lakatta ELM, Cheng CY, Dörr M, Wong TY, Sabanayagam C, Oldehinkel AJ, Riese H, Lehtimäki T, Verweij N, van der Harst P. Genetic insights into resting heart rate and its role in cardiovascular disease. Nat Commun 2023; 14:4646. [PMID: 37532724 PMCID: PMC10397318 DOI: 10.1038/s41467-023-39521-2] [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: 06/06/2022] [Accepted: 06/16/2023] [Indexed: 08/04/2023] Open
Abstract
Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.
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Affiliation(s)
- Yordi J van de Vegte
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, 9700RB, the Netherlands
| | - Ruben N Eppinga
- Department of Cardiology, Isala Zwolle ziekenhuis, Zwolle, 8025 AB, the Netherlands
| | - M Yldau van der Ende
- Department of Cardiology, University medical Center Utrecht, Utrecht, 3584 Cx, the Netherlands
| | - Yanick P Hagemeijer
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, 9700RB, the Netherlands
- Analytical Biochemistry, University of Groningen, Groningen, 9713 AV, the Netherlands
| | - Yuvaraj Mahendran
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medicine Science, University of Copenhagen, Copenhagen Ø, 2100, Denmark
| | - Elias Salfati
- Department of Medicine, Stanford University School of Medicine, Stanford, 94305, USA
- Faculty of Medicine, University of Iceland, Reykjavik, 101, Iceland
| | - Albert V Smith
- Department of Biostatistics, University of Michigan, Ann Arbor, MI48109, USA
| | - Vanessa Y Tan
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, BS82BN, UK
- MRC Integrative Epidemiology, University of Bristol, Bristol, BS82BN, UK
| | - Dan E Arking
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, 21215, USA
| | - Ioanna Ntalla
- Clinical Pharmacology and Precision Medicine, William Harvey Research Institute, Barts and The London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Emil V Appel
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medicine Science, University of Copenhagen, Copenhagen Ø, 2100, Denmark
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, 10029, USA
| | | | - Rico Rueedi
- Department of Computational Biology, University of Lausanne, Lausanne, 1015, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland
| | - Ozren Polasek
- Department of Public Health, University of Split School of Medicine, Split, 21000, Croatia
- Algebra LAB, Algebra University College, Zagreb, 10000, Croatia
| | | | - Cecile Lecoeur
- UMR 8199, University of Lille Nord de France, Lille, 59000, France
| | - Claes Ladenvall
- Clinial Genomics Uppsala, Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, 75185, Sweden
- Lund University Diabetes Center, Department of Clinical Sciences, Lund University, Malmö, 20502, Sweden
| | - Jing Hua Zhao
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, Victor Phillip Dahdaleh Heart & Lung Research Institute, University of Cambridge, Cambridge, CB2 0BB, UK
| | - Aaron Isaacs
- CARIM School for Cardiovascular Diseases, Maastricht Centre for Systems Biology (MaCSBio), Department of Physiology, Maastricht University, Maastricht, 6229ER, Netherlands
| | - Lihua Wang
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, 63108-2212, Campus Box 8506, USA
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Shih-Jen Hwang
- Division of Intramural Research, National Heart Lung and Blood Institute, NIH, USA, Framingham, 1702, USA
| | - Nina Mononen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, FI-33014, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, FI-33014, Finland
| | - Kirsi Auro
- Department of Health, unit of genetics and biomarkers, , National Institute for Health and Welfare, Finland, Helsinki, FI-00290, Finland
- Department of molecular medicine, University of Helsinki, Helsinki, FI-00290, Finland
| | - Anne U Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Lawrence F Bielak
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Linyao Zeng
- Department of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Munich, 80636, Germany
| | - Nabi Shah
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, DD1 9SY, UK
- Pharmacogenetics Research Lab, Department of Pharmacy, COMSATS University Islamabad, Abbottabad, 22060, Pakistan
| | - Maria Nethander
- Sahlgrenska Osteoporosis Centre, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, 41345, Sweden
- Bioinformatics Core Facility, Sahlgrenska Academy, University of Gothenburg, Gothenburg, 40530, Sweden
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Usher Institute for Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, EH16 4UX, UK
| | - Tuomo Rankinen
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA
| | - Sonali Pechlivanis
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, 45122, Germany
| | - Lu Qi
- Department of Epidemiology, Tulane University, New Orleans, LA, 70112, USA
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Federica Rizzi
- Unit of Biomedicine, Bio4Dreams-Business Nursery for Life Sciences, Milano, 20121, Italy
| | - Toshiko Tanaka
- Longitudinal Study Section, National Institute on Aging, Baltimore, 21224, USA
| | - Antonietta Robino
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, 34137, Italy
| | - Massimiliano Cocca
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, 34137, Italy
| | - Leslie Lange
- Medicine, University of Colorado Anschutz Medical Campus, Aurora, 80045, USA
| | - Martina Müller-Nurasyid
- IBE, Ludwig-Maximilians-University Munich, LMU Munich, Munich, 81377, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, 55101, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Carolina Roselli
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, 02142, USA
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UB1 3HW, UK
| | - Marcus E Kleber
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Mannheim, 68167, Germany
- SYNLAB MVZ Humangenetik Mannheim, Mannheim, 68163, Germany
| | - Xiuqing Guo
- Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA, Torrance, 90502, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, 90502, USA
| | - Henry J Lin
- Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA, Torrance, 90502, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, 90502, USA
| | - Francesca Pavani
- Institute for Biomedicine, Eurac Research, Bolzano, 39100, Italy
| | | | - Raymond Noordam
- Department of Internal Medicine, section Gerontology and Geriatrics, Leiden University Medical Center, Leiden, 2300 RC, the Netherlands
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam Public Health, Amsterdam UMC, Amsterdam UMC, Vrije Universiteit, Amsterdam, Amsterdam, 1081 HL, the Netherlands
| | - Katharina E Schraut
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, EH16 4TJ, Scotland, UK
| | - Marcel den Hoed
- The Beijer laboratory and Department of Immunology, Genetics and Pathology, Uppsala University and Science for Life Laboratory, Uppsala, 75237, Sweden
| | - Frauke Degenhardt
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, 24105, Germany
| | - Stella Trompet
- Department of Internal Medicine, section Gerontology and Geriatrics, Leiden University Medical Center, Leiden, 2300 RC, the Netherlands
- Department of Cardiology, Leiden University Medical Center, Leiden, ZA, 2333, the Netherlands
| | - Marten E van den Berg
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3015GD, the Netherlands
| | - Giorgio Pistis
- Institute of Genetics and Biomedic Research (IRGB), Italian National Research Council (CNR), Monserrato, (CA), 9042, Italy
- Center for Statistical Genetics, University of Michigan, Ann Arbor, 48109, USA
| | - Yih-Chung Tham
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 169856, Singapore
| | - Stefan Weiss
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, 17475, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, 17475, Germany
| | - Xueling S Sim
- Saw Swee Hock School of Public Health, National University Health System and National University of Singapore, Singapore, 117549, Singapore
| | - Hengtong L Li
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 169856, Singapore
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, FI-33014, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, FI-33014, Finland
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB2 0SL, UK
| | - M Abdullah Said
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, 9700RB, the Netherlands
| | - Daniel R Witte
- Department of Public Health, Aarhus University, Aarhus C, 8000, Denmark
| | - Carlos Iribarren
- Division of Research, Kaiser Permenente of Northern California, Oakland, 94612, USA
- The Scripps Research Institute, La Jolla, 10550, USA
| | | | - Susan M Ring
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, BS82BN, UK
- MRC Integrative Epidemiology, University of Bristol, Bristol, BS82BN, UK
| | - Paul S de Vries
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, School of Public Health, Houston, 77030, USA
| | - Peter Sever
- National Heart and Lung Institute, Imperial College London, London, W12 0NN, UK
| | - Allan Linneberg
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, 2400, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, 2200, Denmark
| | - Erwin P Bottinger
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, 10029, USA
- Department of Preventive Medicine, The Icahn School of Medicine at Mount Sinai, New York, 10029, USA
| | - Sandosh Padmanabhan
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, G12 8TA, UK
| | - Bruce M Psaty
- Departments of Medicine, Epidemiology and Health Systems and Population Health, University of Washington, Seattle, 98195, USA
| | - Nona Sotoodehnia
- Medicine and Epidemiology, University of Washington, Seattle, 98195, USA
| | - Ivana Kolcic
- Department of Public Health, University of Split School of Medicine, Split, 21000, Croatia
- Algebra LAB, Algebra University College, Zagreb, 10000, Croatia
| | - David O Arnar
- deCODE genetics / Amgen Inc., Reykjavik, 102, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, 101, Iceland
- Department of Medicine, Landspitali-The National University Hospital of Iceland, Reykjavik, 101, Iceland
| | - Daniel F Gudbjartsson
- deCODE genetics / Amgen Inc., Reykjavik, 102, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, 101, Iceland
| | - Hilma Holm
- deCODE genetics / Amgen Inc., Reykjavik, 102, Iceland
| | - Beverley Balkau
- Centre for Research in Epidemiology and Population Health, Institut national de la santé et de la recherche médicale, Villejuif, 94800, France
- UMRS 1018, University Versailles Saint-Quentin-en-Yvelines, Versailles, 78035, France
- UMRS 1018, University Paris Sud, Villejuif, 94807, France
| | - Claudia T Silva
- Genetic Epidemiology Unit, Dept. of Epidemiology, Erasmus University Medical Center, Rotterdam, 3000CA, Netherlands
| | | | - Kjell Nikus
- Department of Cardiology, Heart Center, Tampere University Hospital, Tampere, FI-33521, Finland
- Department of Cardiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, FI-33014, Finland
| | - Perttu Salo
- Department of Health, unit of genetics and biomarkers, , National Institute for Health and Welfare, Finland, Helsinki, FI-00290, Finland
- Department of molecular medicine, University of Helsinki, Helsinki, FI-00290, Finland
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Patricia A Peyser
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Heribert Schunkert
- Department of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Munich, 80636, Germany
- Deutsches Zentrum für Herz- und Kreislauferkrankungen (DZHK), Partner Site Munich Heart Alliance, Munich, 80636, Germany
| | - Mattias Lorentzon
- Sahlgrenska Osteoporosis Centre, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, 41345, Sweden
- Region Västra Götaland, Geriatric Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Mölndal, 43180, Sweden
- Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, 3000, Australia
| | - Jari Lahti
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, 00014, Finland
| | - Dabeeru C Rao
- Division of Biostatistics, Washington University, St. Louis, MO, 63110, USA
| | | | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Katarzyna Stolarz-Skrzypek
- Department of Cardiology, Interventional Electrocardiology and Hypertension, Jagiellonian University Medical College, Kraków, 31-008, Poland
| | - Stefania Bandinelli
- Geriatric Unit, Unità sanitaria locale Toscana Centro, Florence, 50142, Italy
| | - Maria Pina Concas
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, 34137, Italy
| | - Gianfranco Sinagra
- Cardiovascular Department, "Ospedali Riuniti and University of Trieste", Trieste, 34149, Italy
| | - Thomas Meitinger
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, München, 81675, Germany
- Institute of Human Genetics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
- German Centre for Cardiovascular Research (DZHK), partner site: Munich Heart Alliance, Munich, 80802, Germany
| | - Moritz F Sinner
- German Centre for Cardiovascular Research (DZHK), partner site: Munich Heart Alliance, Munich, 80802, Germany
- Department of Cardiology, University Hospital, LMU Munich, Munich, 81377, Germany
| | - Konstantin Strauch
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, 55101, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
- Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, 81377, Germany
| | - Graciela E Delgado
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Mannheim, 68167, Germany
| | - Kent D Taylor
- Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA, Torrance, 90502, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, 90502, USA
| | - Jie Yao
- Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA, Torrance, 90502, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, 90502, USA
| | - Luisa Foco
- Institute for Biomedicine, Eurac Research, Bolzano, 39100, Italy
| | - Olle Melander
- Department of Internal Medicine, Clinical Sciences, Lund University and Skåne University Hospital, Malmo, 221 85, Sweden
- Lund University Diabetes Center, Lund University, Malmö, 221 85, Sweden
| | | | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, 2300 RC, the Netherlands
| | - Eco J C de Geus
- Biological Psychology, EMGO+ Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University, Amsterdam, 1081 BT, the Netherlands
| | - Åsa Johansson
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, 75108, Sweden
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, EH8 9AG, Scotland, UK
| | - Lars Lind
- Department of Medical Sciences, Cardiovascular Epidemiology, Uppsala University Hospital, Uppsala, 75237, Sweden
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, 24105, Germany
| | - Peter W Macfarlane
- Institute of Health and Wellbeing, Faculty of Medicine, University of Glasgow, Glasgow, G12 0XH, UK
| | - Kirill V Tarasov
- Laboratory of Cardiovascular Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD, 21224, USA
| | - Nicholas Tan
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 169856, Singapore
| | - Stephan B Felix
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, 17475, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, 17475, Germany
| | - E-Shyong Tai
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 169856, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
| | - Debra Q Quek
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 169856, Singapore
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Johan Ormel
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Martin Ingelsson
- Department of Public Health and Caring Sciences, Molecular Geriatrics, Uppsala University, Uppsala, 75237, Sweden
| | - Cecilia Lindgren
- Genetic and Genomic Epidemiology Unit, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Andrew P Morris
- Genetic and Genomic Epidemiology Unit, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Olli T Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, FI-20521, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, FI-20521, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, FI-20521, Finland
| | - Torben Hansen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medicine Science, University of Copenhagen, Copenhagen Ø, 2100, Denmark
| | - Themistocles Assimes
- Department of Medicine, Stanford University School of Medicine, Stanford, 94305, USA
| | - Vilmundur Gudnason
- Faculty of Medicine, University of Iceland, Reykjavik, 101, Iceland
- Icelandic Heart Association, Kopavogur, 201, Iceland
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School,, University of Bristol, Bristol, BS8 2BN, UK
| | - Alanna C Morrison
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, School of Public Health, Houston, 77030, USA
| | - Patricia B Munroe
- Clinical Pharmacology and Precision Medicine, William Harvey Research Institute, Barts and The London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- NIHR Barts Biomedical Research Centre, Barts and The London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - David P Strachan
- Population Health Research Institute, St George's, University of London, London, SW17 0RE, UK
| | - Niels Grarup
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medicine Science, University of Copenhagen, Copenhagen Ø, 2100, Denmark
| | - Ruth J F Loos
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medicine Science, University of Copenhagen, Copenhagen Ø, 2100, Denmark
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, 10029, USA
- The Mindich Child Health and Development Institute, The Icahn School of Medicine at Mount Sinai, New York, 10029, USA
| | - Susan R Heckbert
- Department of Epidemiology, University of Washington, Seattle, 98195, USA
| | - Peter Vollenweider
- Department of Medicine, Internal Medicine, Lausanne University hospital, Lausanne, 1015, Switzerland
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, Scotland, UK
| | - Kari Stefansson
- deCODE genetics / Amgen Inc., Reykjavik, 102, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, 101, Iceland
| | - Philippe Froguel
- Department of Metabolism, Imperial College London, London, W12 0HS, UK
- Inserm/CNRS UMR 1283/8199, Pasteur Institute of Lille, Lille University Hospital, EGID, Lille, 59000, France
- University of Lille, Lille, 59000, France
| | - Leif Groop
- Lund University Diabetes Center, Department of Clinical Sciences, Lund University, Malmö, 20502, Sweden
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, 00290, Finland
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Cornelia M van Duijn
- Genetic Epidemiology Unit, Dept. of Epidemiology, Erasmus University Medical Center, Rotterdam, 3000CA, Netherlands
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, 63108-2212, Campus Box 8506, USA
| | - Christopher J O'Donnell
- Cardiology Section, VA Boston Healthcare System, Harvard Medical School, Boston, MA, 02132, USA
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, FI-33521, Finland
- Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, FI-33521, Finland
| | - Markus Perola
- Department of Health, unit of genetics and biomarkers, , National Institute for Health and Welfare, Finland, Helsinki, FI-00290, Finland
- Department of molecular medicine, University of Helsinki, Helsinki, FI-00290, Finland
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Sharon L R Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Jeanette Erdmann
- Institute for Cardiogenetics, University of Lübeck, Lübeck, 23562, Germany
| | - Colin N A Palmer
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, DD1 9SY, UK
| | - Claes Ohlsson
- Sahlgrenska Osteoporosis Centre, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, 41345, Sweden
- Department of Drug Treatment, Sahlgrenska University Hospital, Gothenburg, 41345, Sweden
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Johan G Eriksson
- Department of General practice and primary care, University of Helsinki, Helsinki, 00014, Finland
- Department of Obstetrics and Gynecology, National University of Singapore, Singapore, 119228, Singapore
- Public health Research Program, Folkhalsan Research Center, Helsinki, 000250, Finland
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA
| | - Susanne Moebus
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, 45122, Germany
- Centre for Urban Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, 45122, Germany
| | - Peter Kraft
- Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02112, USA
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Daniele Cusi
- Unit of Biomedicine, Bio4Dreams-Business Nursery for Life Sciences, Milano, 20121, Italy
- Institute of Biomedical Technologies, National Research Council of Italy, Segrate, (MI), 20090, Italy
| | - Luigi Ferrucci
- Longitudinal Study Section, National Institute on Aging, Baltimore, 21224, USA
| | - Sheila Ulivi
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, 34137, Italy
| | - Giorgia Girotto
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, 34137, Italy
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, 34149, Italy
| | - Adolfo Correa
- Jackson Heart Study, University of Mississippi Medical Center, Jackson, 39216, USA
| | - Stefan Kääb
- German Centre for Cardiovascular Research (DZHK), partner site: Munich Heart Alliance, Munich, 80802, Germany
- Department of Cardiology, University Hospital, LMU Munich, Munich, 81377, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, 85764, Germany
- German Centre for Cardiovascular Research (DZHK), partner site: Munich Heart Alliance, Munich, 80802, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, 81377, Germany
| | - John C Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UB1 3HW, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UB1 3HW, UK
- National Heart and Lung Institute, Imperial College London, London, W12 0NN, UK
- Imperial College Healthcare NHS Trust, Imperial College London, London, W12 0HS, UK
| | - Winfried März
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Mannheim, 68167, Germany
- Synlab Academy, Synlab Holding Deutschland GmbH, Mannheim, 68161, Germany
| | - Jerome I Rotter
- Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA, Torrance, 90502, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, 90502, USA
| | - Andrew A Hicks
- Institute for Biomedicine, Eurac Research, Bolzano, 39100, Italy
| | - J Gustav Smith
- Department of Cardiology, Clinical Sciences, Lund University and Skåne University Hospital, Lund, 221 85, Sweden
- Wallenberg Center for Molecular Medicine and Lund University Diabetes Center, Lund University, Lund, 221 84, Sweden
- The Wallenberg Laboratory/Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg University and the Department of Cardiology, Sahlgrenska University Hospital, Gothenburg, 413 45, Sweden
| | | | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, 2300 RC, the Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, 2300 RC, the Netherlands
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam Public Health, Amsterdam UMC, Amsterdam UMC, Vrije Universiteit, Amsterdam, Amsterdam, 1081 HL, the Netherlands
| | - Ulf Gyllensten
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, 75108, Sweden
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, EH8 9AG, Scotland, UK
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, Scotland, UK
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, CB2 0SR, UK
| | - Johan Sundström
- Department of Medical Sciences, Cardiovascular Epidemiology, Uppsala University Hospital, Uppsala, 75237, Sweden
| | - Wolfgang Lieb
- Institute of Epidemiology and Biobank PopGen, Kiel University, Kiel, 24105, Germany
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, ZA, 2333, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, ZA, 2333, the Netherlands
- Netherlands Heart Institute, Utrecht, 3511 EP, the Netherlands
| | - Mark Eijgelsheim
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3015GD, the Netherlands
- Department of Nephrology, University Medical Center Groningen, Groningen, 9700RB, the Netherlands
| | - Edward L M Lakatta
- Laboratory of Cardiovascular Sciences, Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD, 21224, USA
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 169856, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, 169857, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
| | - Marcus Dörr
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, 17475, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, 17475, Germany
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 169856, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, 169857, Singapore
- Tsinghua Medicine, Tsinghua University, Beijing, 100084, China
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 169856, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, 169857, Singapore
| | - Albertine J Oldehinkel
- Interdisciplinary Center Psychopathology and Emotion Regulation, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Harriette Riese
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, FI-33014, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, FI-33014, Finland
| | - Niek Verweij
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, 9700RB, the Netherlands
| | - Pim van der Harst
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, 9700RB, the Netherlands.
- Department of Cardiology, University medical Center Utrecht, Utrecht, 3584 Cx, the Netherlands.
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, 9700RB, the Netherlands.
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14
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Yin M, Xu W, Pang J, Xie S, Xiang M, Shi B, Fan H, Yu G. Causal relationship between osteoarthritis with atrial fibrillation and coronary atherosclerosis: a bidirectional Mendelian randomization study of European ancestry. Front Cardiovasc Med 2023; 10:1213672. [PMID: 37583579 PMCID: PMC10424699 DOI: 10.3389/fcvm.2023.1213672] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 07/20/2023] [Indexed: 08/17/2023] Open
Abstract
Background Osteoarthritis (OA) is a degenerative disease with high prevalence. Some observational studies have shown that patients with osteoarthritis often have co-existing cardiovascular diseases (CVD) such as atrial fibrillation (AF) and coronary atherosclerosis (CA). However, there is still a lack of stronger evidence confirming the association between osteoarthritis and cardiovascular disease. In this study, we used a bidirectional two-sample Mendelian randomization study to investigate the relationship between OA with AF and CA. Methods OA data from the UK Biobank and arcOGEN (Arthritis Research UK Osteoarthritis Genetics, a study that aimed to find genetic determinants of osteoarthritis and elucidate the genetic architecture of the disease) integration were selected for the study (n = 417,596), AF data were obtained from six studies (n = 1,030,836), and coronary atherosclerosis data were derived from the FinnGen (n = 218,792). MR analysis was performed primarily using the Inverse variance weighted (IVW) method, with MR Egger, weighted median, simple mode, weighted mode as supplements, sensitivity analysis was performed using Cochran Q statistic, and leave-one-out analysis. Results We found that OA and AF were positively associated [IVW: OR (95% CI): 1.11 (1.04, 1.19), P = 0.002], while OA and CA were negatively associated [IVW: OR (95% CI): 0.88 (0.79, 0.98), P = 0.02]. In the reverse MR analysis, no effect of AF on OA was found [IVW: OR (95% CI): 1.00 (0.97, 1.03), P = 0.84], meanwhile, CA and OA were found to be associated negatively [IVW: OR (95% CI): 0.95 (0.92, 0.99), P = 0.01]. No violations of MR assumptions were found in the sensitivity analysis. Conclusion This research confirms that OA is a risk factor for AF, and there is a mutual protective factor between OA and CA. However, further studies are still necessary to elucidate the underlying mechanisms.
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Affiliation(s)
- Meng Yin
- Shandong Academy of Occupational Health and Occupational Medicine, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Wenchang Xu
- School of Acupuncture and Tuina, Shandong University of Traditional Chinese Medicine, Jinan, China
- Neck-Shoulder and Lumbocrural Pain Hospital of Shandong First Medical University, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Jixiang Pang
- Department of Development Planning and Discipline Construction, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Siwen Xie
- Shandong Academy of Occupational Health and Occupational Medicine, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Mengting Xiang
- Shandong Academy of Occupational Health and Occupational Medicine, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Bin Shi
- Neck-Shoulder and Lumbocrural Pain Hospital of Shandong First Medical University, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Hua Fan
- Department of Development Planning and Discipline Construction, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
| | - Gongchang Yu
- Neck-Shoulder and Lumbocrural Pain Hospital of Shandong First Medical University, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
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15
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Kanemaru K, Cranley J, Muraro D, Miranda AMA, Ho SY, Wilbrey-Clark A, Patrick Pett J, Polanski K, Richardson L, Litvinukova M, Kumasaka N, Qin Y, Jablonska Z, Semprich CI, Mach L, Dabrowska M, Richoz N, Bolt L, Mamanova L, Kapuge R, Barnett SN, Perera S, Talavera-López C, Mulas I, Mahbubani KT, Tuck L, Wang L, Huang MM, Prete M, Pritchard S, Dark J, Saeb-Parsy K, Patel M, Clatworthy MR, Hübner N, Chowdhury RA, Noseda M, Teichmann SA. Spatially resolved multiomics of human cardiac niches. Nature 2023; 619:801-810. [PMID: 37438528 PMCID: PMC10371870 DOI: 10.1038/s41586-023-06311-1] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 06/12/2023] [Indexed: 07/14/2023]
Abstract
The function of a cell is defined by its intrinsic characteristics and its niche: the tissue microenvironment in which it dwells. Here we combine single-cell and spatial transcriptomics data to discover cellular niches within eight regions of the human heart. We map cells to microanatomical locations and integrate knowledge-based and unsupervised structural annotations. We also profile the cells of the human cardiac conduction system1. The results revealed their distinctive repertoire of ion channels, G-protein-coupled receptors (GPCRs) and regulatory networks, and implicated FOXP2 in the pacemaker phenotype. We show that the sinoatrial node is compartmentalized, with a core of pacemaker cells, fibroblasts and glial cells supporting glutamatergic signalling. Using a custom CellPhoneDB.org module, we identify trans-synaptic pacemaker cell interactions with glia. We introduce a druggable target prediction tool, drug2cell, which leverages single-cell profiles and drug-target interactions to provide mechanistic insights into the chronotropic effects of drugs, including GLP-1 analogues. In the epicardium, we show enrichment of both IgG+ and IgA+ plasma cells forming immune niches that may contribute to infection defence. Overall, we provide new clarity to cardiac electro-anatomy and immunology, and our suite of computational approaches can be applied to other tissues and organs.
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Affiliation(s)
- Kazumasa Kanemaru
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - James Cranley
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Daniele Muraro
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | | | - Siew Yen Ho
- Cardiac Morphology Unit, Royal Brompton Hospital and Imperial College London, London, UK
| | - Anna Wilbrey-Clark
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Jan Patrick Pett
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Krzysztof Polanski
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Laura Richardson
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Monika Litvinukova
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Natsuhiko Kumasaka
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Yue Qin
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Zuzanna Jablonska
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Claudia I Semprich
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Lukas Mach
- National Heart and Lung Institute, Imperial College London, London, UK
- Royal Brompton Hospital, London, UK
| | - Monika Dabrowska
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Nathan Richoz
- Molecular Immunity Unit, Department of Medicine, University of Cambridge, MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Liam Bolt
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Lira Mamanova
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Rakeshlal Kapuge
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Sam N Barnett
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Shani Perera
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Carlos Talavera-López
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
- Würzburg Institute for Systems Immunology, Max Planck Research Group, Julius-Maximilian-Universität, Würzburg, Germany
| | - Ilaria Mulas
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Krishnaa T Mahbubani
- Department of Surgery, University of Cambridge, and Cambridge Biorepository for Translational Medicine, NIHR Cambridge Biomedical Centre, Cambridge, UK
| | - Liz Tuck
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Lu Wang
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Margaret M Huang
- Department of Surgery, University of Cambridge, and Cambridge Biorepository for Translational Medicine, NIHR Cambridge Biomedical Centre, Cambridge, UK
| | - Martin Prete
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Sophie Pritchard
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - John Dark
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Kourosh Saeb-Parsy
- Department of Surgery, University of Cambridge, and Cambridge Biorepository for Translational Medicine, NIHR Cambridge Biomedical Centre, Cambridge, UK
| | - Minal Patel
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Menna R Clatworthy
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
- Molecular Immunity Unit, Department of Medicine, University of Cambridge, MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Norbert Hübner
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
- Charité-Universitätsmedizin, Berlin, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
| | | | - Michela Noseda
- National Heart and Lung Institute, Imperial College London, London, UK.
| | - Sarah A Teichmann
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
- Department of Physics, Cavendish Laboratory, University of Cambridge, Cambridge, UK.
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16
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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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17
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Chen Z, Wang S, He Z, Tegegne BS, van Roon AM, Holtjer JCS, van der Harst P, Snieder H, Thio CHL. Observational and genetic evidence support a relationship between cardiac autonomic function and blood pressure. Front Cardiovasc Med 2023; 10:1187275. [PMID: 37404742 PMCID: PMC10315649 DOI: 10.3389/fcvm.2023.1187275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 05/31/2023] [Indexed: 07/06/2023] Open
Abstract
Background It is unclear how cardiac autonomic function, as indicated by heart rate (HR), heart rate variability (HRV), HR increase during exercise, and HR recovery after exercise, is related to blood pressure (BP). We aimed to examine the observational and genetic evidence for a potential causal effect of these HR(V) traits on BP. Methods We performed multivariable adjusted linear regression using Lifelines and UK Biobank cohorts to investigate the relationship between HR(V) traits and BP. Linkage disequilibrium score regression was conducted to examine genetic correlations. We used two-sample Mendelian randomization (2SMR) to examine potential causal relations between HR(V) traits and BP. Results Observational analyses showed negative associations of all HR(V) traits with BP, except for HR, which was positively associated. Genetic correlations were directionally consistent with the observational associations, but most significant genetic correlations between HR(V) traits and BP were limited to diastolic blood pressure (DBP). 2SMR analyses suggested a potentially causal relationship between HR(V) traits and DBP but not systolic blood pressure (SBP). No reverse effect of BP on HR(V) traits was found. One standard deviation (SD) unit increase in HR was associated with a 1.82 mmHg elevation of DBP. In contrast, one ln(ms) unit increase of the root mean square of the successive differences (RMSSD) and corrected RMSSD (RMSSDc), decreased DBP by 1.79 and 1.83 mmHg, respectively. For HR increase and HR recovery at 50 s, every additional SD increase was associated with a lower DBP by 2.05 and 1.47 mmHg, respectively. Results of secondary analyses with pulse pressure as outcome were inconsistent between observational and 2SMR analyses, as well as between HR(V) traits, and therefore inconclusive. Conclusion Both observational and genetic evidence show strong associations between indices of cardiac autonomic function and DBP, suggesting that a larger relative contribution of the sympathetic versus the parasympathetic nervous system to cardiac function may cause elevated DBP.
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Affiliation(s)
- Zekai Chen
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Siqi Wang
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Zhen He
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Balewgizie S. Tegegne
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
- Department of Neurology, Center for Statistical Genetics, Gertrude H. Sergievsky Center, Columbia University Medical Center, Columbia University, New York, NY, United States
| | - Arie M. van Roon
- Department of Vascular Medicine, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Judith C. S. Holtjer
- Department of Environmental Epidemiology, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, Netherlands
| | - Pim van der Harst
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
- Division of Heart & Lungs, Department of Cardiology, Utrecht University Medical Center, Utrecht University, Utrecht, Netherlands
| | - Harold Snieder
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Chris H. L. Thio
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
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18
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Scarpa JR, Elemento O. Multi-omic molecular profiling and network biology for precision anaesthesiology: a narrative review. Br J Anaesth 2023:S0007-0912(23)00125-3. [PMID: 37055274 DOI: 10.1016/j.bja.2023.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 02/21/2023] [Accepted: 03/04/2023] [Indexed: 04/15/2023] Open
Abstract
Technological advancement, data democratisation, and decreasing costs have led to a revolution in molecular biology in which the entire set of DNA, RNA, proteins, and various other molecules - the 'multi-omic' profile - can be measured in humans. Sequencing 1 million bases of human DNA now costs US$0.01, and emerging technologies soon promise to reduce the cost of sequencing the whole genome to US$100. These trends have made it feasible to sample the multi-omic profile of millions of people, much of which is publicly available for medical research. Can anaesthesiologists use these data to improve patient care? This narrative review brings together a rapidly growing literature in multi-omic profiling across numerous fields that points to the future of precision anaesthesiology. Here, we discuss how DNA, RNA, proteins, and other molecules interact in molecular networks that can be used for preoperative risk stratification, intraoperative optimisation, and postoperative monitoring. This literature provides evidence for four fundamental insights: (1) Clinically similar patients have different molecular profiles and, as a consequence, different outcomes. (2) Vast, publicly available, and rapidly growing molecular datasets have been generated in chronic disease patients and can be repurposed to estimate perioperative risk. (3) Multi-omic networks are altered in the perioperative period and influence postoperative outcomes. (4) Multi-omic networks can serve as empirical, molecular measurements of a successful postoperative course. With this burgeoning universe of molecular data, the anaesthesiologist-of-the-future will tailor their clinical management to an individual's multi-omic profile to optimise postoperative outcomes and long-term health.
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Affiliation(s)
- Joseph R Scarpa
- Department of Anesthesiology, Weill Cornell Medicine, New York, NY, USA.
| | - Olivier Elemento
- Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
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19
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Aegisdottir HM, Thorolfsdottir RB, Sveinbjornsson G, Stefansson OA, Gunnarsson B, Tragante V, Thorleifsson G, Stefansdottir L, Thorgeirsson TE, Ferkingstad E, Sulem P, Norddahl G, Rutsdottir G, Banasik K, Christensen AH, Mikkelsen C, Pedersen OB, Brunak S, Bruun MT, Erikstrup C, Jacobsen RL, Nielsen KR, Sørensen E, Frigge ML, Hjorleifsson KE, Ivarsdottir EV, Helgadottir A, Gretarsdottir S, Steinthorsdottir V, Oddsson A, Eggertsson HP, Halldorsson GH, Jones DA, Anderson JL, Knowlton KU, Nadauld LD, Haraldsson M, Thorgeirsson G, Bundgaard H, Arnar DO, Thorsteinsdottir U, Gudbjartsson DF, Ostrowski SR, Holm H, Stefansson K. Genetic variants associated with syncope implicate neural and autonomic processes. Eur Heart J 2023; 44:1070-1080. [PMID: 36747475 DOI: 10.1093/eurheartj/ehad016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 11/22/2022] [Accepted: 01/05/2023] [Indexed: 02/08/2023] Open
Abstract
AIMS Syncope is a common and clinically challenging condition. In this study, the genetics of syncope were investigated to seek knowledge about its pathophysiology and prognostic implications. METHODS AND RESULTS This genome-wide association meta-analysis included 56 071 syncope cases and 890 790 controls from deCODE genetics (Iceland), UK Biobank (United Kingdom), and Copenhagen Hospital Biobank Cardiovascular Study/Danish Blood Donor Study (Denmark), with a follow-up assessment of variants in 22 412 cases and 286 003 controls from Intermountain (Utah, USA) and FinnGen (Finland). The study yielded 18 independent syncope variants, 17 of which were novel. One of the variants, p.Ser140Thr in PTPRN2, affected syncope only when maternally inherited. Another variant associated with a vasovagal reaction during blood donation and five others with heart rate and/or blood pressure regulation, with variable directions of effects. None of the 18 associations could be attributed to cardiovascular or other disorders. Annotation with regard to regulatory elements indicated that the syncope variants were preferentially located in neural-specific regulatory regions. Mendelian randomization analysis supported a causal effect of coronary artery disease on syncope. A polygenic score (PGS) for syncope captured genetic correlation with cardiovascular disorders, diabetes, depression, and shortened lifespan. However, a score based solely on the 18 syncope variants performed similarly to the PGS in detecting syncope risk but did not associate with other disorders. CONCLUSION The results demonstrate that syncope has a distinct genetic architecture that implicates neural regulatory processes and a complex relationship with heart rate and blood pressure regulation. A shared genetic background with poor cardiovascular health was observed, supporting the importance of a thorough assessment of individuals presenting with syncope.
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Affiliation(s)
- Hildur M Aegisdottir
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
- Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, Reykjavik 101, Iceland
| | | | | | | | | | | | | | | | | | - Egil Ferkingstad
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
| | - Patrick Sulem
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
| | | | | | - Karina Banasik
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3A, Copenhagen 2200, Denmark
| | - Alex Hoerby Christensen
- The Unit for Inherited Cardiac Diseases, Department of Cardiology, The Heart Centre, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen 2100, Denmark
- Department of Cardiology, Herlev-Gentofte Hospital, Copenhagen University Hospital, Borgmester Ib Juuls Vej 1, Herlev 2730, Denmark
- Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3B, Copenhagen 2200, Denmark
| | - Christina Mikkelsen
- Department of Clinical Immunology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen 2100, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Blegdamsvej 3A, Copenhagen 2200, Denmark
| | - Ole Birger Pedersen
- Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3B, Copenhagen 2200, Denmark
- Department of Clinical Immunology, Zealand University Hospital - Køge, Lykkebækvej 1, Køge 4600, Denmark
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3A, Copenhagen 2200, Denmark
| | - Mie Topholm Bruun
- Department of Clinical Immunology, Odense University Hospital, J. B. Winsløws Vej 4, Odense 5000, Denmark
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, Aarhus 8200, Denmark
- Department of Clinical Medicine, Aarhus University, Nordre Ringgade 1, Aarhus 8000, Denmark
| | - Rikke Louise Jacobsen
- Department of Clinical Immunology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen 2100, Denmark
| | - Kaspar Rene Nielsen
- Department of Clinical Immunology, Aalborg University Hospital, Urbansgade 32, Aalborg 9000, Denmark
| | - Erik Sørensen
- Department of Clinical Immunology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen 2100, Denmark
| | - Michael L Frigge
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
| | | | | | - Anna Helgadottir
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
| | | | | | - Asmundur Oddsson
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
| | | | | | - David A Jones
- Precision Genomics, Intermountain Healthcare, 600 S. Medical Center Drive, Saint George, UT 84790, USA
| | - Jeffrey L Anderson
- Intermountain Medical Center, Intermountain Heart Institute, 5171 S. Cottonwood Street Building 1, Salt Lake City, UT 84107, USA
- Department of Internal Medicine, University of Utah, 30 N 1900 E, Salt Lake City, UT 84132, USA
| | - Kirk U Knowlton
- Intermountain Medical Center, Intermountain Heart Institute, 5171 S. Cottonwood Street Building 1, Salt Lake City, UT 84107, USA
- School of Medicine, University of Utah, 30 N 1900 E, Salt Lake City, UT 84132, USA
| | - Lincoln D Nadauld
- Precision Genomics, Intermountain Healthcare, 600 S. Medical Center Drive, Saint George, UT 84790, USA
- School of Medicine, Stanford University, 291 Campus Drive, Stanford, CA 94305, USA
| | | | - Magnus Haraldsson
- Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, Reykjavik 101, Iceland
- Department of Psychiatry, Landspitali, The National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Gudmundur Thorgeirsson
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
- Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, Reykjavik 101, Iceland
- Department of Medicine, Landspitali, The National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Henning Bundgaard
- Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3B, Copenhagen 2200, Denmark
- The Capital Regions Unit for Inherited Cardiac Diseases, Department of Cardiology, The Heart Centre, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen 2100, Denmark
| | - David O Arnar
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
- Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, Reykjavik 101, Iceland
- Department of Medicine, Landspitali, The National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
- Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, Reykjavik 101, Iceland
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Hjardarhagi 4, Reykjavik 107, Iceland
| | - Sisse R Ostrowski
- Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3B, Copenhagen 2200, Denmark
- Department of Clinical Immunology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen 2100, Denmark
| | - Hilma Holm
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
| | - Kari Stefansson
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
- Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, Reykjavik 101, Iceland
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20
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The genetic basis of exercise and cardiorespiratory fitness – Relation to cardiovascular disease. CURRENT OPINION IN PHYSIOLOGY 2023. [DOI: 10.1016/j.cophys.2023.100649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
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21
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Sun X, Chen L, Zheng L. A Mendelian randomization study to assess the genetic liability of gastroesophageal reflux disease for cardiovascular diseases and risk factors. Hum Mol Genet 2022; 31:4275-4285. [PMID: 35861629 DOI: 10.1093/hmg/ddac162] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 06/25/2022] [Accepted: 07/11/2022] [Indexed: 01/21/2023] Open
Abstract
Observational studies have reported that gastroesophageal reflux disease (GERD) is a risk factor for cardiovascular diseases (CVD); however, the causal inferences between them remain unknown. We conducted a Mendelian randomization (MR) study to estimate the causal associations between GERD and 10 CVD outcomes, as well as 14 cardiovascular risk factors. We used summary statistics from genome-wide association studies for GERD and the FinnGen consortium for CVD. We further investigated whether GERD correlated with cardiovascular risk factors and performed multivariable MR and mediation analyses to estimate the mediating effects of these risk factors on GERD-CVD progression. Sensitivity analyses and replication analyses were also performed. Our results indicated that GERD was positively associated with seven CVD outcomes with odds ratios of 1.26 [95% confidence interval (CI), 1.15, 1.37] for coronary artery disease, 1.41 (95% CI, 1.28, 1.57) for myocardial infarction, 1.34 (95% CI, 1.19, 1.51) for atrial fibrillation, 1.34 (95% CI, 1.21, 1.50) for heart failure, 1.30 (95% CI, 1.18, 1.43) for any stroke, 1.19 (95% CI, 1.06, 1.34) for ischemic stroke and 1.29 (95% CI, 1.16, 1.44) for venous thromboembolism. Furthermore, GERD was associated with nine cardiovascular risk factors and major depressive disorder demonstrated significant mediation effects on the causal pathway linking GERD and any stroke. This study demonstrates that GERD is associated with seven CVD outcomes and nine cardiovascular risk factors. Importantly, GERD treatment may help prevent common CVD events.
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Affiliation(s)
- Xingang Sun
- Department of Cardiology and Atrial fibrillation Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, Zhejiang Province, China
| | - Lu Chen
- Department of Cardiology and Atrial fibrillation Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, Zhejiang Province, China
| | - Liangrong Zheng
- Department of Cardiology and Atrial fibrillation Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, Zhejiang Province, China
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22
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Mompeo O, Freidin MB, Gibson R, Hysi PG, Christofidou P, Segal E, Valdes AM, Spector TD, Menni C, Mangino M. Genome-Wide Association Analysis of Over 170,000 Individuals from the UK Biobank Identifies Seven Loci Associated with Dietary Approaches to Stop Hypertension (DASH) Diet. Nutrients 2022; 14:4431. [PMID: 36297114 PMCID: PMC9611599 DOI: 10.3390/nu14204431] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 10/17/2022] [Accepted: 10/17/2022] [Indexed: 01/24/2023] Open
Abstract
Diet is a modifiable risk factor for common chronic diseases and mental health disorders, and its effects are under partial genetic control. To estimate the impact of diet on individual health, most epidemiological and genetic studies have focused on individual aspects of dietary intake. However, analysing individual food groups in isolation does not capture the complexity of the whole diet pattern. Dietary indices enable a holistic estimation of diet and account for the intercorrelations between food and nutrients. In this study we performed the first ever genome-wide association study (GWA) including 173,701 individuals from the UK Biobank to identify genetic variants associated with the Dietary Approaches to Stop Hypertension (DASH) diet. DASH was calculated using the 24 h-recall questionnaire collected by UK Biobank. The GWA was performed using a linear mixed model implemented in BOLT-LMM. We identified seven independent single-nucleotide polymorphisms (SNPs) associated with DASH. Significant genetic correlations were observed between DASH and several educational traits with a significant enrichment for genes involved in the AMP-dependent protein kinase (AMPK) activation that controls the appetite by regulating the signalling in the hypothalamus. The colocalization analysis implicates genes involved in body mass index (BMI)/obesity and neuroticism (ARPP21, RP11-62H7.2, MFHAS1, RHEBL1). The Mendelian randomisation analysis suggested that increased DASH score, which reflect a healthy diet style, is causal of lower glucose, and insulin levels. These findings further our knowledge of the pathways underlying the relationship between diet and health outcomes. They may have significant implications for global public health and provide future dietary recommendations for the prevention of common chronic diseases.
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Affiliation(s)
- Olatz Mompeo
- Department of Twin Research and Genetic Epidemiology, King’s College London, London SE1 7EH, UK
| | - Maxim B. Freidin
- Department of Twin Research and Genetic Epidemiology, King’s College London, London SE1 7EH, UK
| | - Rachel Gibson
- Department of Nutritional Sciences, King’s College London, London SE1 9NH, UK
| | - Pirro G. Hysi
- Department of Twin Research and Genetic Epidemiology, King’s College London, London SE1 7EH, UK
| | - Paraskevi Christofidou
- Department of Twin Research and Genetic Epidemiology, King’s College London, London SE1 7EH, UK
| | - Eran Segal
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Ana M. Valdes
- Department of Twin Research and Genetic Epidemiology, King’s College London, London SE1 7EH, UK
- Academic Rheumatology Clinical Sciences Building, Nottingham City Hospital, University of Nottingham, Nottingham NG5 1PB, UK
| | - Tim D. Spector
- Department of Twin Research and Genetic Epidemiology, King’s College London, London SE1 7EH, UK
| | - Cristina Menni
- Department of Twin Research and Genetic Epidemiology, King’s College London, London SE1 7EH, UK
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King’s College London, London SE1 7EH, UK
- NIHR Biomedical Research Centre at Guy’s and St Thomas’ Foundation Trust, London SE1 9RT, UK
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23
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Integrated Analysis of the microRNA–mRNA Network Predicts Potential Regulators of Atrial Fibrillation in Humans. Cells 2022; 11:cells11172629. [PMID: 36078037 PMCID: PMC9454849 DOI: 10.3390/cells11172629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 08/15/2022] [Accepted: 08/15/2022] [Indexed: 11/17/2022] Open
Abstract
Atrial fibrillation (AF) is a form of sustained cardiac arrhythmia and microRNAs (miRs) play crucial roles in the pathophysiology of AF. To identify novel miR–mRNA pairs, we performed RNA-seq from atrial biopsies of persistent AF patients and non-AF patients with normal sinus rhythm (SR). Differentially expressed miRs (11 down and 9 up) and mRNAs (95 up and 82 down) were identified and hierarchically clustered in a heat map. Subsequently, GO, KEGG, and GSEA analyses were run to identify deregulated pathways. Then, miR targets were predicted in the miRDB database, and a regulatory network of negatively correlated miR–mRNA pairs was constructed using Cytoscape. To select potential candidate genes from GSEA analysis, the top-50 enriched genes in GSEA were overlaid with predicted targets of differentially deregulated miRs. Further, the protein–protein interaction (PPI) network of enriched genes in GSEA was constructed, and subsequently, GO and canonical pathway analyses were run for genes in the PPI network. Our analyses showed that TNF-α, p53, EMT, and SYDECAN1 signaling were among the highly affected pathways in AF samples. SDC-1 (SYNDECAN-1) was the top-enriched gene in p53, EMT, and SYDECAN1 signaling. Consistently, SDC-1 mRNA and protein levels were significantly higher in atrial samples of AF patients. Among negatively correlated miRs, miR-302b-3p was experimentally validated to suppress SDC-1 transcript levels. Overall, our results suggested that the miR-302b-3p/SDC-1 axis may be involved in the pathogenesis of AF.
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Diamant N, Di Achille P, Weng LC, Lau ES, Khurshid S, Friedman S, Reeder C, Singh P, Wang X, Sarma G, Ghadessi M, Mielke J, Elci E, Kryukov I, Eilken HM, Derix A, Ellinor PT, Anderson CD, Philippakis AA, Batra P, Lubitz SA, Ho JE. Deep learning on resting electrocardiogram to identify impaired heart rate recovery. CARDIOVASCULAR DIGITAL HEALTH JOURNAL 2022; 3:161-170. [PMID: 36046430 PMCID: PMC9422063 DOI: 10.1016/j.cvdhj.2022.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Background and Objective Postexercise heart rate recovery (HRR) is an important indicator of cardiac autonomic function and abnormal HRR is associated with adverse outcomes. We hypothesized that deep learning on resting electrocardiogram (ECG) tracings may identify individuals with impaired HRR. Methods We trained a deep learning model (convolutional neural network) to infer HRR based on resting ECG waveforms (HRRpred) among UK Biobank participants who had undergone exercise testing. We examined the association of HRRpred with incident cardiovascular disease using Cox models, and investigated the genetic architecture of HRRpred in genome-wide association analysis. Results Among 56,793 individuals (mean age 57 years, 51% women), the HRRpred model was moderately correlated with actual HRR (r = 0.48, 95% confidence interval [CI] 0.47-0.48). Over a median follow-up of 10 years, we observed 2060 incident diabetes mellitus (DM) events, 862 heart failure events, and 2065 deaths. Higher HRRpred was associated with lower risk of DM (hazard ratio [HR] 0.79 per 1 standard deviation change, 95% CI 0.76-0.83), heart failure (HR 0.89, 95% CI 0.83-0.95), and death (HR 0.83, 95% CI 0.79-0.86). After accounting for resting heart rate, the association of HRRpred with incident DM and all-cause mortality were similar. Genetic determinants of HRRpred included known heart rate, cardiac conduction system, cardiomyopathy, and metabolic trait loci. Conclusion Deep learning-derived estimates of HRR using resting ECG independently associated with future clinical outcomes, including new-onset DM and all-cause mortality. Inferring postexercise heart rate response from a resting ECG may have potential clinical implications and impact on preventive strategies warrants future study.
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Affiliation(s)
- Nathaniel Diamant
- Data Sciences Platform, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Paolo Di Achille
- Data Sciences Platform, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Lu-Chen Weng
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts.,Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Emily S Lau
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts.,Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts.,Division of Cardiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Shaan Khurshid
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts.,Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts.,Division of Cardiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Samuel Friedman
- Data Sciences Platform, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Christopher Reeder
- Data Sciences Platform, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Pulkit Singh
- Data Sciences Platform, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Xin Wang
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts.,Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Gopal Sarma
- Data Sciences Platform, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Mercedeh Ghadessi
- Bayer, AG, Research and Development, Pharmaceuticals, Leverkusen, Germany
| | - Johanna Mielke
- Bayer, AG, Research and Development, Pharmaceuticals, Wuppertal, Germany
| | - Eren Elci
- Bayer, AG, Research and Development, Pharmaceuticals, Wuppertal, Germany
| | - Ivan Kryukov
- Bayer, AG, Research and Development, Pharmaceuticals, Wuppertal, Germany
| | - Hanna M Eilken
- Bayer, AG, Research and Development, Pharmaceuticals, Leverkusen, Germany
| | - Andrea Derix
- Bayer, AG, Research and Development, Pharmaceuticals, Leverkusen, Germany
| | - Patrick T Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts.,Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts.,Division of Cardiology, Massachusetts General Hospital, Boston, Massachusetts.,Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, Massachusetts
| | - Christopher D Anderson
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts.,Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts.,Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, Massachusetts
| | - Anthony A Philippakis
- Data Sciences Platform, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts.,Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts.,Eric and Wendy Schmidt Center, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Puneet Batra
- Data Sciences Platform, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts.,Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Steven A Lubitz
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts.,Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts.,Division of Cardiology, Massachusetts General Hospital, Boston, Massachusetts.,Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, Massachusetts
| | - Jennifer E Ho
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts.,Cardiovascular Institute and Division of Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
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Forstenpointner J, Elman I, Freeman R, Borsook D. The Omnipresence of Autonomic Modulation in Health and Disease. Prog Neurobiol 2022; 210:102218. [PMID: 35033599 DOI: 10.1016/j.pneurobio.2022.102218] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 12/13/2021] [Accepted: 01/10/2022] [Indexed: 10/19/2022]
Abstract
The Autonomic Nervous System (ANS) is a critical part of the homeostatic machinery with both central and peripheral components. However, little is known about the integration of these components and their joint role in the maintenance of health and in allostatic derailments leading to somatic and/or neuropsychiatric (co)morbidity. Based on a comprehensive literature search on the ANS neuroanatomy we dissect the complex integration of the ANS: (1) First we summarize Stress and Homeostatic Equilibrium - elucidating the responsivity of the ANS to stressors; (2) Second we describe the overall process of how the ANS is involved in Adaptation and Maladaptation to Stress; (3) In the third section the ANS is hierarchically partitioned into the peripheral/spinal, brainstem, subcortical and cortical components of the nervous system. We utilize this anatomical basis to define a model of autonomic integration. (4) Finally, we deploy the model to describe human ANS involvement in (a) Hypofunctional and (b) Hyperfunctional states providing examples in the healthy state and in clinical conditions.
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Affiliation(s)
- Julia Forstenpointner
- Center for Pain and the Brain, Boston Children's Hospital, Department of Anesthesia, Critical Care and Pain Medicine, Harvard Medical School, Boston, MA, USA; Division of Neurological Pain Research and Therapy, Department of Neurology, University Hospital Schleswig-Holstein, Campus Kiel, SH, Germany.
| | - Igor Elman
- Center for Pain and the Brain, Boston Children's Hospital, Department of Anesthesia, Critical Care and Pain Medicine, Harvard Medical School, Boston, MA, USA; Cambridge Health Alliance, Harvard Medical School, Cambridge, MA, USA
| | - Roy Freeman
- Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - David Borsook
- Center for Pain and the Brain, Boston Children's Hospital, Department of Anesthesia, Critical Care and Pain Medicine, Harvard Medical School, Boston, MA, USA; Departments of Psychiatry and Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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26
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Lin L, Luo P, Yang M, Wang J, Hou W, Xu P. Causal relationship between osteoporosis and osteoarthritis: A two-sample Mendelian randomized study. Front Endocrinol (Lausanne) 2022; 13:1011246. [PMID: 36339427 PMCID: PMC9633945 DOI: 10.3389/fendo.2022.1011246] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 10/11/2022] [Indexed: 11/30/2022] Open
Abstract
INTRODUCTION At present, clinical studies have confirmed that osteoporosis (OP) has an inverse relationship with osteoarthritis (OA), but it has not been proven from the point of view of genetics, so our study hopes to clarify the potential effect of OP on OA at the level of gene prediction through two-sample Mendelian randomization (MR) analysis. METHODS A two-sample MR was adopted to research the causal relationship of OP with OA (including total OA, knee OA and hip OA). All data come from a public shared database. Such traditional methods as simple and weighted models, inverse variance weighted, weighted median, and Mendelian Randomization (MR-Egger) regression were employed to assess the causal effect of OP on OA. We used the Pleiotrophy RESidual Sum and Outlier (MR-PRESSO) method and MR-Egger method to study sensitivity. The leave-one-out test is used to determine the influence of outliers. The heterogeneity was calculated by using Cochran Q statistics and MR-Egger regression in the inverse variance-weighted (IVW) method. P > 0.05 indicates that there is a large heterogeneity. MR-Robust Adjustment Profile Score (RAPS) is stable to both systematic and specific multiplicity, so we used MR-RAPS as a supplementary method to verify the results of IVW. RESULTS According to the results of IVW, we found that there was a causal relationship between OP and total OA, and OP reduced the incidence of total OA (beta=-0.285, OR=0.751, P value< 0.016). The MR estimation of the causal effect of OP on knee OA suggested that the genetic prediction of OP was negatively correlated with knee osteoarthritis (KOA) (IVW: beta=-6.11, OR=0.002, P value< 0.016). The IVW results suggested that OP was causally related to hip OA, and OP had a protective effect on hip OA (beta=-5.48, OR=4.15e-3, P value= 3.99e-3). Except for heterogeneity in the analysis of OP and knee OA, there was no horizontal pleiotropy or heterogeneity in the other analyses. CONCLUSION We explored the causal relationship between OP and OA through a two-sample MR analysis and found that OP can reduce the incidence of OA (including knee OA and hip OA).
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Hanscombe KB, Persyn E, Traylor M, Glanville KP, Hamer M, Coleman JRI, Lewis CM. The genetic case for cardiorespiratory fitness as a clinical vital sign and the routine prescription of physical activity in healthcare. Genome Med 2021; 13:180. [PMID: 34753499 PMCID: PMC8579601 DOI: 10.1186/s13073-021-00994-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 10/19/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Cardiorespiratory fitness (CRF) and physical activity (PA) are well-established predictors of morbidity and all-cause mortality. However, CRF is not routinely measured and PA not routinely prescribed as part of standard healthcare. The American Heart Association (AHA) recently presented a scientific case for the inclusion of CRF as a clinical vital sign based on epidemiological and clinical observation. Here, we leverage genetic data in the UK Biobank (UKB) to strengthen the case for CRF as a vital sign and make a case for the prescription of PA. METHODS We derived two CRF measures from the heart rate data collected during a submaximal cycle ramp test: CRF-vo2max, an estimate of the participants' maximum volume of oxygen uptake, per kilogram of body weight, per minute; and CRF-slope, an estimate of the rate of increase of heart rate during exercise. Average PA over a 7-day period was derived from a wrist-worn activity tracker. After quality control, 70,783 participants had data on the two derived CRF measures, and 89,683 had PA data. We performed genome-wide association study (GWAS) analyses by sex, and post-GWAS techniques to understand genetic architecture of the traits and prioritise functional genes for follow-up. RESULTS We found strong evidence that genetic variants associated with CRF and PA influenced genetic expression in a relatively small set of genes in the heart, artery, lung, skeletal muscle and adipose tissue. These functionally relevant genes were enriched among genes known to be associated with coronary artery disease (CAD), type 2 diabetes (T2D) and Alzheimer's disease (three of the top 10 causes of death in high-income countries) as well as Parkinson's disease, pulmonary fibrosis, and blood pressure, heart rate, and respiratory phenotypes. Genetic variation associated with lower CRF and PA was also correlated with several disease risk factors (including greater body mass index, body fat and multiple obesity phenotypes); a typical T2D profile (including higher insulin resistance, higher fasting glucose, impaired beta-cell function, hyperglycaemia, hypertriglyceridemia); increased risk for CAD and T2D; and a shorter lifespan. CONCLUSIONS Genetics supports three decades of evidence for the inclusion of CRF as a clinical vital sign. Given the genetic, clinical and epidemiological evidence linking CRF and PA to increased morbidity and mortality, regular measurement of CRF as a marker of health and routine prescription of PA could be a prudent strategy to support public health.
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Affiliation(s)
- Ken B Hanscombe
- Department of Medical & Molecular Genetics, King's College London, London, UK. .,Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK.
| | - Elodie Persyn
- Department of Medical & Molecular Genetics, King's College London, London, UK
| | | | - Kylie P Glanville
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
| | - Mark Hamer
- Institute of Sport Exercise & Health, Division of Surgery and Interventional Science, University College London, London, UK
| | - Jonathan R I Coleman
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
| | - Cathryn M Lewis
- Department of Medical & Molecular Genetics, King's College London, London, UK.,Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
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28
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Ma P, Mao B. The many faces of the E3 ubiquitin ligase, RNF220, in neural development and beyond. Dev Growth Differ 2021; 64:98-105. [PMID: 34716995 DOI: 10.1111/dgd.12756] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 09/30/2021] [Accepted: 10/02/2021] [Indexed: 11/28/2022]
Abstract
Ubiquitin modification plays important roles in many cellular processes that are fundamental for vertebrate embryo development, such as cell division, differentiation, and migration. Aberrant function or deregulation of ubiquitination enzymes can cause developmental disorders, cancer progression, and neurodegenerative diseases in humans. RING finger protein 220 (RNF220) is an evolutionarily conserved RING-type ubiquitin E3 ligase. Recent studies have revealed the roles and mechanisms of RNF220 and its partner protein, zinc finger C4H2-type containing protein (ZC4H2), in embryonic development and human diseases. Using mouse and zebrafish models, it has been shown that RNF220 regulates sonic hedgehog (Shh) signaling via Gli and embryonic ectoderm development (EED), a polycomb repressive complex 2 (PRC2) component, during ventral neural patterning and cerebellum development. In addition, RNF220 also regulates the development and functions of central noradrenergic and motor neurons in mice. By stabilizing β-catenin and signal transducer and activator of transcription 1 (STAT1), RNF220 is also involved in Wnt and interferon (IFN)-STAT1 signaling and thus the regulation of tumorigenesis and immune response, respectively. In humans, both RNF220 and ZC4H2 mutations have been reported to be associated with diseases accompanied by complicated neural defects. In this review, we summarize the current knowledge of RNF220 with special emphasis on its roles and mechanisms of action in signal transduction, vertebrate neural development, and related human disorders.
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Affiliation(s)
- Pengcheng Ma
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Bingyu Mao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
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29
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Abstract
Human physiology is likely to have been selected for endurance physical activity. However, modern humans have become largely sedentary, with physical activity becoming a leisure-time pursuit for most. Whereas inactivity is a strong risk factor for disease, regular physical activity reduces the risk of chronic disease and mortality. Although substantial epidemiological evidence supports the beneficial effects of exercise, comparatively little is known about the molecular mechanisms through which these effects operate. Genetic and genomic analyses have identified genetic variation associated with human performance and, together with recent proteomic, metabolomic and multi-omic analyses, are beginning to elucidate the molecular genetic mechanisms underlying the beneficial effects of physical activity on human health.
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Affiliation(s)
- Daniel Seung Kim
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Matthew T Wheeler
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.,Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
| | - Euan A Ashley
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA. .,Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA. .,Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA. .,Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
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30
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Liu X, Li C, Sun X, Yu Y, Si S, Hou L, Yan R, Yu Y, Li M, Li H, Xue F. Genetically Predicted Insomnia in Relation to 14 Cardiovascular Conditions and 17 Cardiometabolic Risk Factors: A Mendelian Randomization Study. J Am Heart Assoc 2021; 10:e020187. [PMID: 34315237 PMCID: PMC8475657 DOI: 10.1161/jaha.120.020187] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Background This Mendelian randomization study aims to investigate causal associations between genetically predicted insomnia and 14 cardiovascular diseases (CVDs) as well as the potential mediator role of 17 cardiometabolic risk factors. Methods and Results Using genetic association estimates from large genome‐wide association studies and UK Biobank, we performed a 2‐sample Mendelian randomization analysis to estimate the associations of insomnia with 14 CVD conditions in the primary analysis. Then mediation analysis was conducted to explore the potential mediator role of 17 cardiometabolic risk factors using a network Mendelian randomization design. After correcting for multiple testing, genetically predicted insomnia was consistent significantly positively associated with 9 of 14 CVDs, those odds ratios ranged from 1.13 (95% CI, 1.08–1.18) for atrial fibrillation to 1.24 (95% CI, 1.16–1.32) for heart failure. Moreover, genetically predicted insomnia was consistently associated with higher body mass index, triglycerides, and lower high‐density lipoprotein cholesterol, each of which may act as a mediator in the causal pathway from insomnia to several CVD outcomes. Additionally, we found very little evidence to support a causal link between insomnia with abdominal aortic aneurysm, thoracic aortic aneurysm, total cholesterol, low‐density lipoprotein cholesterol, glycemic traits, renal function, and heart rate increase during exercise. Finally, we found no evidence of causal associations of genetically predicted body mass index, high‐density lipoprotein cholesterol, or triglycerides on insomnia. Conclusions This study provides evidence that insomnia is associated with 9 of 14 CVD outcomes, some of which may be partially mediated by 1 or more of higher body mass index, triglycerides, and lower high‐density lipoprotein cholesterol.
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Affiliation(s)
- Xinhui Liu
- Department of Biostatistics School of Public Health Cheeloo College of MedicineShandong University Jinan Shandong China.,Institute for Medical Dataology Cheeloo College of MedicineShandong University Jinan Shandong China
| | - Chuanbao Li
- Department of Emergency and Chest Pain Center Qilu HospitalCheeloo College of MedicineShandong University Jinan Shandong China
| | - Xiaoru Sun
- Department of Biostatistics School of Public Health Cheeloo College of MedicineShandong University Jinan Shandong China.,Institute for Medical Dataology Cheeloo College of MedicineShandong University Jinan Shandong China
| | - Yuanyuan Yu
- Department of Biostatistics School of Public Health Cheeloo College of MedicineShandong University Jinan Shandong China.,Institute for Medical Dataology Cheeloo College of MedicineShandong University Jinan Shandong China
| | - Shucheng Si
- Department of Biostatistics School of Public Health Cheeloo College of MedicineShandong University Jinan Shandong China.,Institute for Medical Dataology Cheeloo College of MedicineShandong University Jinan Shandong China
| | - Lei Hou
- Department of Biostatistics School of Public Health Cheeloo College of MedicineShandong University Jinan Shandong China.,Institute for Medical Dataology Cheeloo College of MedicineShandong University Jinan Shandong China
| | - Ran Yan
- Department of Biostatistics School of Public Health Cheeloo College of MedicineShandong University Jinan Shandong China.,Institute for Medical Dataology Cheeloo College of MedicineShandong University Jinan Shandong China
| | - Yifan Yu
- Department of Biostatistics School of Public Health Cheeloo College of MedicineShandong University Jinan Shandong China.,Institute for Medical Dataology Cheeloo College of MedicineShandong University Jinan Shandong China
| | - Mingzhuo Li
- Center for Big Data Research in Health and Medicine Shandong Qianfoshan HospitalCheeloo College of MedicineShandong University Jinan Shandong China
| | - Hongkai Li
- Department of Biostatistics School of Public Health Cheeloo College of MedicineShandong University Jinan Shandong China.,Institute for Medical Dataology Cheeloo College of MedicineShandong University Jinan Shandong China
| | - Fuzhong Xue
- Department of Biostatistics School of Public Health Cheeloo College of MedicineShandong University Jinan Shandong China.,Institute for Medical Dataology Cheeloo College of MedicineShandong University Jinan Shandong China
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Ramírez J, van Duijvenboden S, Young WJ, Orini M, Jones AR, Lambiase PD, Munroe PB, Tinker A. Analysing electrocardiographic traits and predicting cardiac risk in UK biobank. JRSM Cardiovasc Dis 2021; 10:20480040211023664. [PMID: 34211707 PMCID: PMC8202245 DOI: 10.1177/20480040211023664] [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: 02/04/2021] [Revised: 05/04/2021] [Accepted: 05/19/2021] [Indexed: 11/16/2022] Open
Abstract
The electrocardiogram (ECG) is a commonly used clinical tool that reflects cardiac excitability and disease. Many parameters are can be measured and with the improvement of methodology can now be quantified in an automated fashion, with accuracy and at scale. Furthermore, these measurements can be heritable and thus genome wide association studies inform the underpinning biological mechanisms. In this review we describe how we have used the resources in UK Biobank to undertake such work. In particular, we focus on a substudy uniquely describing the response to exercise performed at scale with accompanying genetic information.
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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, UK.,Institute of Cardiovascular Science, University College London, London, 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, UK.,Institute of Cardiovascular Science, University College London, London, UK
| | - William J Young
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.,Barts Heart Centre, St Bartholomew's Hospital, London, UK
| | - Michele Orini
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.,Institute of Cardiovascular Science, University College London, London, UK.,Barts Heart Centre, St Bartholomew's Hospital, London, UK
| | - Aled R Jones
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Pier D Lambiase
- Institute of Cardiovascular Science, University College London, London, UK.,Barts Heart Centre, St Bartholomew's Hospital, London, 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, UK.,NIHR Barts Cardiovascular Biomedical Research Unit, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Andrew Tinker
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.,NIHR Barts Cardiovascular Biomedical Research Unit, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
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32
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Thorolfsdottir RB, Sveinbjornsson G, Aegisdottir HM, Benonisdottir S, Stefansdottir L, Ivarsdottir EV, Halldorsson GH, Sigurdsson JK, Torp-Pedersen C, Weeke PE, Brunak S, Westergaard D, Pedersen OB, Sorensen E, Nielsen KR, Burgdorf KS, Banasik K, Brumpton B, Zhou W, Oddsson A, Tragante V, Hjorleifsson KE, Davidsson OB, Rajamani S, Jonsson S, Torfason B, Valgardsson AS, Thorgeirsson G, Frigge ML, Thorleifsson G, Norddahl GL, Helgadottir A, Gretarsdottir S, Sulem P, Jonsdottir I, Willer CJ, Hveem K, Bundgaard H, Ullum H, Arnar DO, Thorsteinsdottir U, Gudbjartsson DF, Holm H, Stefansson K. Genetic insight into sick sinus syndrome. Eur Heart J 2021; 42:1959-1971. [PMID: 36282123 PMCID: PMC8140484 DOI: 10.1093/eurheartj/ehaa1108] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 08/24/2020] [Accepted: 01/05/2021] [Indexed: 12/19/2022] Open
Abstract
Aims The aim of this study was to use human genetics to investigate the pathogenesis of sick sinus syndrome (SSS) and the role of risk factors in its development. Methods and results We performed a genome-wide association study of 6469 SSS cases and 1 000 187 controls from deCODE genetics, the Copenhagen Hospital Biobank, UK Biobank, and the HUNT study. Variants at six loci associated with SSS, a reported missense variant in MYH6, known atrial fibrillation (AF)/electrocardiogram variants at PITX2, ZFHX3, TTN/CCDC141, and SCN10A and a low-frequency (MAF = 1.1–1.8%) missense variant, p.Gly62Cys in KRT8 encoding the intermediate filament protein keratin 8. A full genotypic model best described the p.Gly62Cys association (P = 1.6 × 10−20), with an odds ratio (OR) of 1.44 for heterozygotes and a disproportionally large OR of 13.99 for homozygotes. All the SSS variants increased the risk of pacemaker implantation. Their association with AF varied and p.Gly62Cys was the only variant not associating with any other arrhythmia or cardiovascular disease. We tested 17 exposure phenotypes in polygenic score (PGS) and Mendelian randomization analyses. Only two associated with the risk of SSS in Mendelian randomization, AF, and lower heart rate, suggesting causality. Powerful PGS analyses provided convincing evidence against causal associations for body mass index, cholesterol, triglycerides, and type 2 diabetes (P > 0.05). Conclusion We report the associations of variants at six loci with SSS, including a missense variant in KRT8 that confers high risk in homozygotes and points to a mechanism specific to SSS development. Mendelian randomization supports a causal role for AF in the development of SSS.
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Affiliation(s)
| | | | | | | | | | | | | | - Jon K Sigurdsson
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
| | - Christian Torp-Pedersen
- Department of Clinical Research and Cardiology, Nordsjaelland Hospital, Dyrehavevej 29, Hillerød 3400, Denmark
| | - Peter E Weeke
- Department of Cardiology, Copenhagen University Hospital, Blegdamsvej 9, Copenhagen 2100, Denmark
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3A, Copenhagen 2200, Denmark
| | - David Westergaard
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3A, Copenhagen 2200, Denmark
| | - Ole B Pedersen
- Department of Clinical Immunology, Naestved Hospital, Ringstedgade 77B, Naestved 4700, Denmark
| | - Erik Sorensen
- Department of Clinical Immunology, Copenhagen University Hospital, Blegdamsvej 9, Copenhagen 2100, Denmark
| | - Kaspar R Nielsen
- Department of Clinical Immunology, Aalborg University Hospital North, Urbansgade 36, Aalborg 9000, Denmark
| | - Kristoffer S Burgdorf
- Department of Clinical Immunology, Copenhagen University Hospital, Blegdamsvej 9, Copenhagen 2100, Denmark
| | - Karina Banasik
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3A, Copenhagen 2200, Denmark
| | - Ben Brumpton
- Department of Thoracic and Occupational Medicine, St. Olavs Hospital, Trondheim University Hospital, Prinsesse Kristinas gate 3, Trondheim 7030, Norway
| | - Wei Zhou
- Department of Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Avenue, Ann Arbor, MI 48109-2218, USA
| | - Asmundur Oddsson
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
| | | | - Kristjan E Hjorleifsson
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland.,Department of Computing and Mathematical Sciences, California Institute of Technology, 1200 E California Blvd. MC 305-16, Pasadena, CA 91125, USA
| | | | | | - Stefan Jonsson
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
| | - Bjarni Torfason
- Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, Reykjavik 101, Iceland.,Department of Cardiothoracic Surgery, Landspitali-The National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Atli S Valgardsson
- Department of Cardiothoracic Surgery, Landspitali-The National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Gudmundur Thorgeirsson
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland.,Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, Reykjavik 101, Iceland.,Department of Medicine, Landspitali-The National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Michael L Frigge
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
| | | | | | - Anna Helgadottir
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
| | | | - Patrick Sulem
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
| | - Ingileif Jonsdottir
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland.,Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, Reykjavik 101, Iceland.,Department of Immunology, Landspitali-The National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Cristen J Willer
- Department of Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Avenue, Ann Arbor, MI 48109-2218, USA.,Department of Internal Medicine: Cardiology, University of Michigan, 1500 East Medical Center Drive, Ann Arbor, MI 48109 -5368, USA.,Department of Human Genetics, University of Michigan, 4909 Buhl Building, 1241 E. Catherine St., Ann Arbor, MI 48109 -5618, USA
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Erling Skjalgssons gt. 1, Trondheim 7491, Norway.,Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Postboks 8905, Trondheim 7491, Norway.,HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Forskningsveien 2, Levanger 7600, Norway
| | - Henning Bundgaard
- Department of Cardiology, Copenhagen University Hospital, Blegdamsvej 9, Copenhagen 2100, Denmark
| | - Henrik Ullum
- Department of Clinical Immunology, Copenhagen University Hospital, Blegdamsvej 9, Copenhagen 2100, Denmark.,Statens Serum Institut, Artillerivej 5, Copenhagen 2300, Denmark
| | - David O Arnar
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland.,Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, Reykjavik 101, Iceland.,Department of Medicine, Landspitali-The National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland.,Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, Reykjavik 101, Iceland
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland.,School of Engineering and Natural Sciences, University of Iceland, Hjardarhagi 4, Reykjavik 107, Iceland
| | - Hilma Holm
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland
| | - Kari Stefansson
- deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 101, Iceland.,Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, Reykjavik 101, Iceland
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Mensah-Kane J, Schmidt AF, Hingorani AD, Finan C, Chen Y, van Duijvenboden S, Orini M, Lambiase PD, Tinker A, Marouli E, Munroe PB, Ramírez J. No Clinically Relevant Effect of Heart Rate Increase and Heart Rate Recovery During Exercise on Cardiovascular Disease: A Mendelian Randomization Analysis. Front Genet 2021; 12:569323. [PMID: 33679875 PMCID: PMC7931909 DOI: 10.3389/fgene.2021.569323] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Accepted: 01/08/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Reduced heart rate (HR) increase (HRI), recovery (HRR), and higher resting HR are associated with cardiovascular (CV) disease, but causal inferences have not been deduced. We investigated causal effects of HRI, HRR, and resting HR on CV risk, all-cause mortality (ACM), atrial fibrillation (AF), coronary artery disease (CAD), and ischemic stroke (IS) using Mendelian Randomization. METHODS 11 variants for HRI, 11 for HRR, and two sets of 46 and 414 variants for resting HR were obtained from four genome-wide association studies (GWASs) on UK Biobank. We performed a lookup on GWASs for CV risk and ACM in UK Biobank (N = 375,367, 5.4% cases and N = 393,165, 4.4% cases, respectively). For CAD, AF, and IS, we used publicly available summary statistics. We used a random-effects inverse-variance weighted (IVW) method and sensitivity analyses to estimate causality. RESULTS IVW showed a nominally significant effect of HRI on CV events (odds ratio [OR] = 1.0012, P = 4.11 × 10-2) and on CAD and AF. Regarding HRR, IVW was not significant for any outcome. The IVW method indicated statistically significant associations of resting HR with AF (OR = 0.9825, P = 9.8 × 10-6), supported by all sensitivity analyses, and a nominally significant association with IS (OR = 0.9926, P = 9.82 × 10-3). CONCLUSION Our findings suggest no strong evidence of an association between HRI and HRR and any outcome and confirm prior work reporting a highly significant effect of resting HR on AF. Future research is required to explore HRI and HRR associations further using more powerful predictors, when available.
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Affiliation(s)
- Josephine Mensah-Kane
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Amand F. Schmidt
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, United Kingdom
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, Netherlands
| | - Aroon D. Hingorani
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, United Kingdom
| | - Chris Finan
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, United Kingdom
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, Netherlands
| | - Yutang Chen
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Stefan van Duijvenboden
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, United Kingdom
| | - Michele Orini
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, United Kingdom
| | - Pier D. Lambiase
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, United Kingdom
| | - Andrew Tinker
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Eirini Marouli
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Patricia B. Munroe
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Julia Ramírez
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
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34
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Gao L, Gaba A, Cui L, Yang HW, Saxena R, Scheer FAJL, Akeju O, Rutter MK, Lo MT, Hu K, Li P. Resting Heartbeat Complexity Predicts All-Cause and Cardiorespiratory Mortality in Middle- to Older-Aged Adults From the UK Biobank. J Am Heart Assoc 2021; 10:e018483. [PMID: 33461311 PMCID: PMC7955428 DOI: 10.1161/jaha.120.018483] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Background Spontaneous heart rate fluctuations contain rich information related to health and illness in terms of physiological complexity, an accepted indicator of plasticity and adaptability. However, it is challenging to make inferences on complexity from shorter, more practical epochs of data. Distribution entropy (DistEn) is a recently introduced complexity measure that is designed specifically for shorter duration heartbeat recordings. We hypothesized that reduced DistEn predicted increased mortality in a large population cohort. Method and Results The prognostic value of DistEn was examined in 7631 middle‐older–aged UK Biobank participants who had 2‐minute resting ECGs conducted (mean age, 59.5 years; 60.4% women). During a median follow‐up period of 7.8 years, 451 (5.9%) participants died. In Cox proportional hazards models with adjustment for demographics, lifestyle factors, physical activity, cardiovascular risks, and comorbidities, for each 1‐SD decrease in DistEn, the risk increased by 36%, 56%, and 73% for all‐cause, cardiovascular, and respiratory disease–related mortality, respectively. These effect sizes were equivalent to the risk of death from being >5 years older, having been a former smoker, or having diabetes mellitus. Lower DistEn was most predictive of death in those <55 years with a prior myocardial infarction, representing an additional 56% risk for mortality compared with older participants without prior myocardial infarction. These observations remained after controlling for traditional mortality predictors, resting heart rate, and heart rate variability. Conclusions Resting heartbeat complexity from short, resting ECGs was independently associated with mortality in middle‐ to older‐aged adults. These risks appear most pronounced in middle‐aged participants with prior MI, and may uniquely contribute to mortality risk screening.
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Affiliation(s)
- Lei Gao
- Department of Anesthesia Critical Care and Pain Medicine Massachusetts General HospitalHarvard Medical School Boston MA.,Medical Biodynamics Program Brigham and Women's Hospital Boston MA
| | - Arlen Gaba
- Medical Biodynamics Program Brigham and Women's Hospital Boston MA
| | - Longchang Cui
- Medical Biodynamics Program Brigham and Women's Hospital Boston MA
| | - Hui-Wen Yang
- Medical Biodynamics Program Brigham and Women's Hospital Boston MA
| | - Richa Saxena
- Department of Anesthesia Critical Care and Pain Medicine Massachusetts General HospitalHarvard Medical School Boston MA.,Broad Institute of MIT and Harvard Cambridge MA.,Center for Genomic Medicine Massachusetts General Hospital Boston MA
| | - Frank A J L Scheer
- Broad Institute of MIT and Harvard Cambridge MA.,Division of Sleep Medicine Harvard Medical School Boston MA
| | - Oluwaseun Akeju
- Department of Anesthesia Critical Care and Pain Medicine Massachusetts General HospitalHarvard Medical School Boston MA
| | - Martin K Rutter
- Division of Diabetes Endocrinology & Gastroenterology The University of Manchester Manchester UK
| | - Men-Tzung Lo
- Institute of Translational and Interdisciplinary Medicine and Department of Biomedical Sciences and Engineering National Central University Taoyuan Taiwan
| | - Kun Hu
- Medical Biodynamics Program Brigham and Women's Hospital Boston MA.,Division of Sleep Medicine Harvard Medical School Boston MA
| | - Peng Li
- Medical Biodynamics Program Brigham and Women's Hospital Boston MA.,Division of Sleep Medicine Harvard Medical School Boston MA
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35
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van Eif VW, Protze S, Bosada FM, Yuan X, Sinha T, van Duijvenboden K, Ernault AC, Mohan RA, Wakker V, de Gier-de Vries C, Hooijkaas IB, Wilson MD, Verkerk AO, Bakkers J, Boukens BJ, Black BL, Scott IC, Christoffels VM. Genome-Wide Analysis Identifies an Essential Human TBX3 Pacemaker Enhancer. Circ Res 2020; 127:1522-1535. [PMID: 33040635 PMCID: PMC8153223 DOI: 10.1161/circresaha.120.317054] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
RATIONALE The development and function of the pacemaker cardiomyocytes of the sinoatrial node (SAN), the leading pacemaker of the heart, are tightly controlled by a conserved network of transcription factors, including TBX3 (T-box transcription factor 3), ISL1 (ISL LIM homeobox 1), and SHOX2 (short stature homeobox 2). Yet, the regulatory DNA elements (REs) controlling target gene expression in the SAN pacemaker cells have remained undefined. OBJECTIVE Identification of the regulatory landscape of human SAN-like pacemaker cells and functional assessment of SAN-specific REs potentially involved in pacemaker cell gene regulation. METHODS AND RESULTS We performed Assay for Transposase-Accessible Chromatin using sequencing on human pluripotent stem cell-derived SAN-like pacemaker cells and ventricle-like cells and identified thousands of putative REs specific for either human cell type. We validated pacemaker cell-specific elements in the SHOX2 and TBX3 loci. CRISPR-mediated homozygous deletion of the mouse ortholog of a noncoding region with candidate pacemaker-specific REs in the SHOX2 locus resulted in selective loss of Shox2 expression from the developing SAN and embryonic lethality. Putative pacemaker-specific REs were identified up to 1 Mbp upstream of TBX3 in a region close to MED13L harboring variants associated with heart rate recovery after exercise. The orthologous region was deleted in mice, which resulted in selective loss of expression of Tbx3 from the SAN and (cardiac) ganglia and in neonatal lethality. Expression of Tbx3 was maintained in other tissues including the atrioventricular conduction system, lungs, and liver. Heterozygous adult mice showed increased SAN recovery times after pacing. The human REs harboring the associated variants robustly drove expression in the SAN of transgenic mouse embryos. CONCLUSIONS We provided a genome-wide collection of candidate human pacemaker-specific REs, including the loci of SHOX2, TBX3, and ISL1, and identified a link between human genetic variants influencing heart rate recovery after exercise and a variant RE with highly conserved function, driving SAN expression of TBX3.
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Affiliation(s)
- Vincent W.W. van Eif
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Stephanie Protze
- McEwen Stem Cell Institute, University Health Network and the Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Fernanda M. Bosada
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Xuefei Yuan
- The Hospital for Sick Children; and the Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Canada
| | - Tanvi Sinha
- Cardiovascular Research Institute, Department of Biochemistry and Biophysics, University of California, San Francisco, United States
| | - Karel van Duijvenboden
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Auriane C. Ernault
- Department of Experimental Cardiology, University of Amsterdam, Amsterdam University Medical Centers, Amsterdam, The Netherlands
- Aix-Marseille Université, INSERM, MMG - U1251, Marseille, France
| | - Rajiv A. Mohan
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Vincent Wakker
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Corrie de Gier-de Vries
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Ingeborg B. Hooijkaas
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Michael D. Wilson
- The Hospital for Sick Children; and the Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Canada
| | - Arie O. Verkerk
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
- Department of Experimental Cardiology, University of Amsterdam, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Jeroen Bakkers
- Hubrecht Institute and University Medical Center Utrecht, 3584 CT Utrecht, Netherlands
| | - Bastiaan J. Boukens
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
- Department of Experimental Cardiology, University of Amsterdam, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Brian L. Black
- Cardiovascular Research Institute, Department of Biochemistry and Biophysics, University of California, San Francisco, United States
| | - Ian C. Scott
- The Hospital for Sick Children; and the Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Canada
| | - Vincent M. Christoffels
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
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36
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Walsh S, Izquierdo-Serra M, Acosta S, Edo A, Lloret M, Moret R, Bosch E, Oliva B, Bertranpetit J, Fernández-Fernández JM. Adaptive selection drives TRPP3 loss-of-function in an Ethiopian population. Sci Rep 2020; 10:20999. [PMID: 33268808 PMCID: PMC7710729 DOI: 10.1038/s41598-020-78081-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 11/20/2020] [Indexed: 11/15/2022] Open
Abstract
TRPP3 (also called PKD2L1) is a nonselective, cation-permeable channel activated by multiple stimuli, including extracellular pH changes. TRPP3 had been considered a candidate for sour sensor in humans, due to its high expression in a subset of tongue receptor cells detecting sour, along with its membership to the TRP channel family known to function as sensory receptors. Here, we describe the functional consequences of two non-synonymous genetic variants (R278Q and R378W) found to be under strong positive selection in an Ethiopian population, the Gumuz. Electrophysiological studies and 3D modelling reveal TRPP3 loss-of-functions produced by both substitutions. R278Q impairs TRPP3 activation after alkalinisation by mislocation of H+ binding residues at the extracellular polycystin mucolipin domain. R378W dramatically reduces channel activity by altering conformation of the voltage sensor domain and hampering channel transition from closed to open state. Sour sensitivity tests in R278Q/R378W carriers argue against both any involvement of TRPP3 in sour detection and the role of such physiological process in the reported evolutionary positive selection past event.
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Affiliation(s)
- Sandra Walsh
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Dr. Aiguader, 88, 08003, Barcelona, Catalonia, Spain
| | - Mercè Izquierdo-Serra
- Laboratory of Molecular Physiology, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, 08003, Barcelona, Spain
| | - Sandra Acosta
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Dr. Aiguader, 88, 08003, Barcelona, Catalonia, Spain
| | - Albert Edo
- Laboratory of Molecular Physiology, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, 08003, Barcelona, Spain
| | - María Lloret
- Laboratory of Molecular Physiology, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, 08003, Barcelona, Spain
| | - Roser Moret
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Dr. Aiguader, 88, 08003, Barcelona, Catalonia, Spain
| | - Elena Bosch
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Dr. Aiguader, 88, 08003, Barcelona, Catalonia, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), 43206, Reus, Spain
| | - Baldo Oliva
- Structural Bioinformatics Lab, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, 08003, Barcelona, Spain
| | - Jaume Bertranpetit
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Dr. Aiguader, 88, 08003, Barcelona, Catalonia, Spain.
| | - José Manuel Fernández-Fernández
- Laboratory of Molecular Physiology, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, 08003, Barcelona, Spain.
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37
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Verweij N, Benjamins JW, Morley MP, van de Vegte YJ, Teumer A, Trenkwalder T, Reinhard W, Cappola TP, van der Harst P. The Genetic Makeup of the Electrocardiogram. Cell Syst 2020; 11:229-238.e5. [PMID: 32916098 DOI: 10.1016/j.cels.2020.08.005] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 05/27/2020] [Accepted: 08/06/2020] [Indexed: 12/11/2022]
Abstract
The electrocardiogram (ECG) is one of the most useful non-invasive diagnostic tests for a wide array of cardiac disorders. Traditional approaches to analyzing ECGs focus on individual segments. Here, we performed comprehensive deep phenotyping of 77,190 ECGs in the UK Biobank across the complete cycle of cardiac conduction, resulting in 500 spatial-temporal datapoints, across 10 million genetic variants. In addition to characterizing polygenic risk scores for the traditional ECG segments, we identified over 300 genetic loci that are statistically associated with the high-dimensional representation of the ECG. We established the genetic ECG signature for dilated cardiomyopathy, associated the BAG3, HSPB7/CLCNKA, PRKCA, TMEM43, and OBSCN loci with disease risk and confirmed this association in an independent cohort. In total, our work demonstrates that a high-dimensional analysis of the entire ECG provides unique opportunities for studying cardiac biology and disease and furthering drug development. A record of this paper's transparent peer review process is included in the Supplemental Information.
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Affiliation(s)
- Niek Verweij
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Groningen, the Netherlands; Genomics plc, Oxford, UK.
| | - Jan-Walter Benjamins
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Groningen, the Netherlands
| | - Michael P Morley
- Cardiovascular Institute, Perelman School of Medicine , University of Pennsylvania, Philadelphia, USA
| | - Yordi J van de Vegte
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Groningen, the Netherlands
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany; DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Teresa Trenkwalder
- Klinik für Herz- und Kreislauferkrankungen, Deutsches Herzzentrum München, Technical University Munich, Munich, Germany; DZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany
| | - Wibke Reinhard
- Klinik für Herz- und Kreislauferkrankungen, Deutsches Herzzentrum München, Technical University Munich, Munich, Germany
| | - Thomas P Cappola
- Division of Cardiovascular Medicine at the Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA
| | - Pim van der Harst
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Groningen, the Netherlands; Department of Cardiology, Heart and Lung Division, University Medical Center Utrecht, Utrecht, the Netherlands
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Kalra G, Milon B, Casella AM, Herb BR, Humphries E, Song Y, Rose KP, Hertzano R, Ament SA. Biological insights from multi-omic analysis of 31 genomic risk loci for adult hearing difficulty. PLoS Genet 2020; 16:e1009025. [PMID: 32986727 PMCID: PMC7544108 DOI: 10.1371/journal.pgen.1009025] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Revised: 10/08/2020] [Accepted: 08/04/2020] [Indexed: 12/13/2022] Open
Abstract
Age-related hearing impairment (ARHI), one of the most common medical conditions, is strongly heritable, yet its genetic causes remain largely unknown. We conducted a meta-analysis of GWAS summary statistics from multiple hearing-related traits in the UK Biobank (n = up to 330,759) and identified 31 genome-wide significant risk loci for self-reported hearing difficulty (p < 5x10-8), of which eight have not been reported previously in the peer-reviewed literature. We investigated the regulatory and cell specific expression for these loci by generating mRNA-seq, ATAC-seq, and single-cell RNA-seq from cells in the mouse cochlea. Risk-associated genes were most strongly enriched for expression in cochlear epithelial cells, as well as for genes related to sensory perception and known Mendelian deafness genes, supporting their relevance to auditory function. Regions of the human genome homologous to open chromatin in epithelial cells from the mouse were strongly enriched for heritable risk for hearing difficulty, even after adjusting for baseline effects of evolutionary conservation and cell-type non-specific regulatory regions. Epigenomic and statistical fine-mapping most strongly supported 50 putative risk genes. Of these, 39 were expressed robustly in mouse cochlea and 16 were enriched specifically in sensory hair cells. These results reveal new risk loci and risk genes for hearing difficulty and suggest an important role for altered gene regulation in the cochlear sensory epithelium.
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Affiliation(s)
- Gurmannat Kalra
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, United States of America
- Program in Molecular Medicine, University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - Beatrice Milon
- Department of Otorhinolaryngology-Head & Neck Surgery, University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - Alex M. Casella
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, United States of America
- Program in Molecular Medicine, University of Maryland School of Medicine, Baltimore, MD, United States of America
- Physician Scientist Training Program, University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - Brian R. Herb
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - Elizabeth Humphries
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, United States of America
- Program in Molecular Epidemiology, University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - Yang Song
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - Kevin P. Rose
- Program in Molecular Medicine, University of Maryland School of Medicine, Baltimore, MD, United States of America
- Department of Otorhinolaryngology-Head & Neck Surgery, University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - Ronna Hertzano
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, United States of America
- Department of Otorhinolaryngology-Head & Neck Surgery, University of Maryland School of Medicine, Baltimore, MD, United States of America
- Department of Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - Seth A. Ament
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, United States of America
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States of America
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Marouli E, Kus A, Del Greco M F, Chaker L, Peeters R, Teumer A, Deloukas P, Medici M. Thyroid Function Affects the Risk of Stroke via Atrial Fibrillation: A Mendelian Randomization Study. J Clin Endocrinol Metab 2020; 105:dgaa239. [PMID: 32374820 PMCID: PMC7316221 DOI: 10.1210/clinem/dgaa239] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 05/01/2020] [Indexed: 01/07/2023]
Abstract
CONTEXT Observational studies suggest that variations in normal range thyroid function are associated with cardiovascular diseases. However, it remains to be determined whether these associations are causal or not. OBJECTIVE To test whether genetically determined variation in normal range thyroid function is causally associated with the risk of stroke and coronary artery disease (CAD) and investigate via which pathways these relations may be mediated. DESIGN, SETTING, AND PARTICIPANTS Mendelian randomization analyses for stroke and CAD using genetic instruments associated with normal range thyrotropin (TSH) and free thyroxine levels or Hashimoto's thyroiditis and Graves' disease. The potential mediating role of known stroke and CAD risk factors was examined. Publicly available summary statistics data were used. MAIN OUTCOME MEASURES Stroke or CAD risk per genetically predicted increase in TSH or FT4 levels. RESULTS A 1 standard deviation increase in TSH was associated with a 5% decrease in the risk of stroke (odds ratio [OR], 0.95; 95% confidence interval [CI], 0.91-0.99; P = 0.008). Multivariable MR analyses indicated that this effect is mainly mediated via atrial fibrillation. MR analyses did not show a causal association between normal range thyroid function and CAD. Secondary analyses showed a causal relationship between Hashimoto's thyroiditis and a 7% increased risk of CAD (OR, 1.07; 95% CI, 1.01-1.13; P = 0.026), which was mainly mediated via body mass index. CONCLUSION These results provide important new insights into the causal relationships and mediating pathways between thyroid function, stroke, and CAD. We identify variation in normal range thyroid function and Hashimoto's thyroiditis as risk factors for stroke and CAD, respectively.
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Affiliation(s)
- Eirini Marouli
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Centre for Genomic Health, Life Sciences, Queen Mary University of London, London, UK
| | - Aleksander Kus
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine and Endocrinology, Medical University of Warsaw, Warsaw, Poland
| | - Fabiola Del Greco M
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lubeck, Bolzano, Italy
| | - Layal Chaker
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Robin Peeters
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Panos Deloukas
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Centre for Genomic Health, Life Sciences, Queen Mary University of London, London, UK
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, Saudi Arabia
| | - Marco Medici
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
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Translating GWAS-identified loci for cardiac rhythm and rate using an in vivo image- and CRISPR/Cas9-based approach. Sci Rep 2020; 10:11831. [PMID: 32678143 PMCID: PMC7367351 DOI: 10.1038/s41598-020-68567-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Accepted: 06/29/2020] [Indexed: 02/07/2023] Open
Abstract
A meta-analysis of genome-wide association studies (GWAS) identified eight loci that are associated with heart rate variability (HRV), but candidate genes in these loci remain uncharacterized. We developed an image- and CRISPR/Cas9-based pipeline to systematically characterize candidate genes for HRV in live zebrafish embryos. Nine zebrafish orthologues of six human candidate genes were targeted simultaneously in eggs from fish that transgenically express GFP on smooth muscle cells (Tg[acta2:GFP]), to visualize the beating heart. An automated analysis of repeated 30 s recordings of beating atria in 381 live, intact zebrafish embryos at 2 and 5 days post-fertilization highlighted genes that influence HRV (hcn4 and si:dkey-65j6.2 [KIAA1755]); heart rate (rgs6 and hcn4); and the risk of sinoatrial pauses and arrests (hcn4). Exposure to 10 or 25 µM ivabradine—an open channel blocker of HCNs—for 24 h resulted in a dose-dependent higher HRV and lower heart rate at 5 days post-fertilization. Hence, our screen confirmed the role of established genes for heart rate and rhythm (RGS6 and HCN4); showed that ivabradine reduces heart rate and increases HRV in zebrafish embryos, as it does in humans; and highlighted a novel gene that plays a role in HRV (KIAA1755).
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van Weerd JH, Mohan RA, van Duijvenboden K, Hooijkaas IB, Wakker V, Boukens BJ, Barnett P, Christoffels VM. Trait-associated noncoding variant regions affect TBX3 regulation and cardiac conduction. eLife 2020; 9:56697. [PMID: 32672536 PMCID: PMC7365664 DOI: 10.7554/elife.56697] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Accepted: 06/28/2020] [Indexed: 11/21/2022] Open
Abstract
Genome-wide association studies have implicated common genomic variants in the gene desert upstream of TBX3 in cardiac conduction velocity. Whether these noncoding variants affect expression of TBX3 or neighboring genes and how they affect cardiac conduction is not understood. Here, we use high-throughput STARR-seq to test the entire 1.3 Mb human and mouse TBX3 locus, including two cardiac conduction-associated variant regions, for regulatory function. We identified multiple accessible and functional regulatory DNA elements that harbor variants affecting their activity. Both variant regions drove gene expression in the cardiac conduction tissue in transgenic reporter mice. Genomic deletion from the mouse genome of one of the regions caused increased cardiac expression of only Tbx3, PR interval shortening and increased QRS duration. Combined, our findings address the mechanistic link between trait-associated variants in the gene desert, TBX3 regulation and cardiac conduction.
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Affiliation(s)
- Jan Hendrik van Weerd
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Rajiv A Mohan
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands.,Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Karel van Duijvenboden
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Ingeborg B Hooijkaas
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Vincent Wakker
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Bastiaan J Boukens
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands.,Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Phil Barnett
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Vincent M Christoffels
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
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van de Vegte YJ, Said MA, Rienstra M, van der Harst P, Verweij N. Genome-wide association studies and Mendelian randomization analyses for leisure sedentary behaviours. Nat Commun 2020; 11:1770. [PMID: 32317632 PMCID: PMC7174427 DOI: 10.1038/s41467-020-15553-w] [Citation(s) in RCA: 65] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Accepted: 03/11/2020] [Indexed: 01/02/2023] Open
Abstract
Leisure sedentary behaviours are associated with increased risk of cardiovascular disease, but whether this relationship is causal is unknown. The aim of this study is to identify genetic determinants associated with leisure sedentary behaviours and to estimate the potential causal effect on coronary artery disease (CAD). Genome wide association analyses of leisure television watching, leisure computer use and driving behaviour in the UK Biobank identify 145, 36 and 4 genetic loci (P < 1×10-8), respectively. High genetic correlations are observed between sedentary behaviours and neurological traits, including education and body mass index (BMI). Two-sample Mendelian randomization (MR) analysis estimates a causal effect between 1.5 hour increase in television watching and CAD (OR 1.44, 95%CI 1.25-1.66, P = 5.63 × 10-07), that is partially independent of education and BMI in multivariable MR analyses. This study finds independent observational and genetic support for the hypothesis that increased sedentary behaviour by leisure television watching is a risk factor for CAD.
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Affiliation(s)
- Yordi J van de Vegte
- Department of Cardiology, University of Groningen, University Medical Center Groningen, 9700 RB, Groningen, The Netherlands
| | - M Abdullah Said
- Department of Cardiology, University of Groningen, University Medical Center Groningen, 9700 RB, Groningen, The Netherlands
| | - Michiel Rienstra
- Department of Cardiology, University of Groningen, University Medical Center Groningen, 9700 RB, Groningen, The Netherlands
| | - Pim van der Harst
- Department of Cardiology, University of Groningen, University Medical Center Groningen, 9700 RB, Groningen, The Netherlands.
- Department of Genetics, University of Groningen, University Medical Center Groningen, 9700 RB, Groningen, The Netherlands.
- Durrer Center for Cardiogenetic Research, Netherlands Heart Institute, 3511GC, Utrecht, The Netherlands.
- Department of Cardiology, University Medical Center Utrecht, 3584 CX, Utrecht, The Netherlands.
| | - Niek Verweij
- Department of Cardiology, University of Groningen, University Medical Center Groningen, 9700 RB, Groningen, The Netherlands.
- Genomics plc, OX1 1JD, Oxford, UK.
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Siedlinski M, Jozefczuk E, Xu X, Teumer A, Evangelou E, Schnabel RB, Welsh P, Maffia P, Erdmann J, Tomaszewski M, Caulfield MJ, Sattar N, Holmes MV, Guzik TJ. White Blood Cells and Blood Pressure: A Mendelian Randomization Study. Circulation 2020; 141:1307-1317. [PMID: 32148083 PMCID: PMC7176352 DOI: 10.1161/circulationaha.119.045102] [Citation(s) in RCA: 102] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND High blood pressure (BP) is a risk factor for cardiovascular morbidity and mortality. While BP is regulated by the function of kidney, vasculature, and sympathetic nervous system, recent experimental data suggest that immune cells may play a role in hypertension. METHODS We studied the relationship between major white blood cell types and blood pressure in the UK Biobank population and used Mendelian randomization (MR) analyses using the ≈750 000 UK-Biobank/International Consortium of Blood Pressure-Genome-Wide Association Studies to examine which leukocyte populations may be causally linked to BP. RESULTS A positive association between quintiles of lymphocyte, monocyte, and neutrophil counts, and increased systolic BP, diastolic BP, and pulse pressure was observed (eg, adjusted systolic BP mean±SE for 1st versus 5th quintile respectively: 140.13±0.08 versus 141.62±0.07 mm Hg for lymphocyte, 139.51±0.08 versus 141.84±0.07 mm Hg for monocyte, and 137.96±0.08 versus 142.71±0.07 mm Hg for neutrophil counts; all P<10-50). Using 121 single nucleotide polymorphisms in MR, implemented through the inverse-variance weighted approach, we identified a potential causal relationship of lymphocyte count with systolic BP and diastolic BP (causal estimates: 0.69 [95% CI, 0.19-1.20] and 0.56 [95% CI, 0.23-0.90] of mm Hg per 1 SD genetically elevated lymphocyte count, respectively), which was directionally concordant to the observational findings. These inverse-variance weighted estimates were consistent with other robust MR methods. The exclusion of rs3184504 SNP in the SH2B3 locus attenuated the magnitude of the signal in some of the MR analyses. MR in the reverse direction found evidence of positive effects of BP indices on counts of monocytes, neutrophils, and eosinophils but not lymphocytes or basophils. Subsequent MR testing of lymphocyte count in the context of genetic correlation with renal function or resting and postexercise heart rate demonstrated a positive association of lymphocyte count with urine albumin-to-creatinine ratio. CONCLUSIONS Observational and genetic analyses demonstrate a concordant, positive and potentially causal relationship of lymphocyte count with systolic BP and diastolic BP.
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Affiliation(s)
- Mateusz Siedlinski
- Department of Internal and Agricultural Medicine, Faculty of Medicine, Jagiellonian University Medical College, Krakow, Poland (M.S., E.J., T.J.G.).,Institute of Cardiovascular and Medical Sciences (M.S., P.W., N.S., T.J.G.), University of Glasgow, United Kingdom
| | - Ewelina Jozefczuk
- Department of Internal and Agricultural Medicine, Faculty of Medicine, Jagiellonian University Medical College, Krakow, Poland (M.S., E.J., T.J.G.)
| | - Xiaoguang Xu
- Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, United Kingdom (X.X., M.T.)
| | - Alexander Teumer
- Department SHIP/Clinical-Epidemiological Research, Institute for Community Medicine, University Medicine Greifswald, Germany (A.T.).,German Centre for Cardiovascular Research partner site Greifswald, Germany (A.T.)
| | - Evangelos Evangelou
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, United Kingdom (E.E.)
| | - Renate B Schnabel
- University Heart Center Hamburg Eppendorf, German Center for Cardiovascular Research partner site Hamburg/Kiel/Lübeck, Germany (R.B.S.)
| | - Paul Welsh
- Institute of Cardiovascular and Medical Sciences (M.S., P.W., N.S., T.J.G.), University of Glasgow, United Kingdom
| | - Pasquale Maffia
- Institute of Infection, Immunity, and Inflammation (P.M.), University of Glasgow, United Kingdom.,Department of Pharmacy, University of Naples Federico II, Italy (P.M.)
| | - Jeanette Erdmann
- Institute for Cardiogenetics, University of Lübeck, Germany (J.E.)
| | - Maciej Tomaszewski
- Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, United Kingdom (X.X., M.T.)
| | - Mark J Caulfield
- William Harvey Research Institute, National Institute for Health Research Biomedical Research Centre at Barts, Queen Mary University of London, United Kingdom (M.J.C.)
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences (M.S., P.W., N.S., T.J.G.), University of Glasgow, United Kingdom
| | - Michael V Holmes
- Medical Research Council Population Health Research Unit, Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom (M.V.H.)
| | - Tomasz J Guzik
- Department of Internal and Agricultural Medicine, Faculty of Medicine, Jagiellonian University Medical College, Krakow, Poland (M.S., E.J., T.J.G.).,Institute of Cardiovascular and Medical Sciences (M.S., P.W., N.S., T.J.G.), University of Glasgow, United Kingdom
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van de Vegte YJ, Tegegne BS, Verweij N, Snieder H, van der Harst P. Genetics and the heart rate response to exercise. Cell Mol Life Sci 2019; 76:2391-2409. [PMID: 30919020 PMCID: PMC6529381 DOI: 10.1007/s00018-019-03079-4] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Accepted: 03/18/2019] [Indexed: 01/01/2023]
Abstract
The acute heart rate response to exercise, i.e., heart rate increase during and heart rate recovery after exercise, has often been associated with all-cause and cardiovascular mortality. The long-term response of heart rate to exercise results in favourable changes in chronotropic function, including decreased resting and submaximal heart rate as well as increased heart rate recovery. Both the acute and long-term heart rate response to exercise have been shown to be heritable. Advances in genetic analysis enable researchers to investigate this hereditary component to gain insights in possible molecular mechanisms underlying interindividual differences in the heart rate response to exercise. In this review, we comprehensively searched candidate gene, linkage, and genome-wide association studies that investigated the heart rate response to exercise. A total of ten genes were associated with the acute heart rate response to exercise in candidate gene studies. Only one gene (CHRM2), related to heart rate recovery, was replicated in recent genome-wide association studies (GWASs). Additional 17 candidate causal genes were identified for heart rate increase and 26 for heart rate recovery in these GWASs. Nine of these genes were associated with both acute increase and recovery of the heart rate during exercise. These genes can be broadly categorized into four categories: (1) development of the nervous system (CCDC141, PAX2, SOX5, and CAV2); (2) prolongation of neuronal life span (SYT10); (3) cardiac development (RNF220 and MCTP2); (4) cardiac rhythm (SCN10A and RGS6). Additional 10 genes were linked to long-term modification of the heart rate response to exercise, nine with heart rate increase and one with heart rate recovery. Follow-up will be essential to get functional insights in how candidate causal genes affect the heart rate response to exercise. Future work will be required to translate these findings to preventive and therapeutic applications.
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Affiliation(s)
- Yordi J van de Vegte
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 RB, Groningen, The Netherlands
| | - Balewgizie S Tegegne
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, 9700 RB, Groningen, The Netherlands
| | - Niek Verweij
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 RB, Groningen, The Netherlands
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, 9700 RB, Groningen, The Netherlands
| | - Pim van der Harst
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 RB, Groningen, The Netherlands.
- Department of Genetics, University of Groningen, University Medical Center Groningen, 9700 RB, Groningen, The Netherlands.
- Durrer Center for Cardiogenetic Research, Netherlands Heart Institute, 3511 GC, Utrecht, The Netherlands.
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The hypertension advantage and natural selection: Since type 2 diabetes associates with co-morbidities and premature death, why have the genetic variants remained in the human genome? Med Hypotheses 2019; 129:109237. [PMID: 31371084 DOI: 10.1016/j.mehy.2019.109237] [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: 03/29/2019] [Accepted: 05/18/2019] [Indexed: 12/30/2022]
Abstract
Type 2 diabetes is a major public health crisis around the world. It is estimated that more than 300 million people worldwide have type 2 diabetes. Furthermore, the World Health Organization estimates that deaths from the complications of diabetes will increase by two thirds between 2008 and 2030. Since type 2 diabetes is a major public health crisis, why have the genetic variants for diabetes not been removed from the genome by natural selection? We hypothesize that insulin resistance, a predisposition to type 2 diabetes, and the associated elevation in sympathetic nervous system activity and arterial blood pressure provided an advantage to humans who lived as hunter-gatherers. Specifically, sympathetic hyperactivity stimulates the renin-angiotensin aldosterone system, promotes sodium reabsorption, and increases blood volume, heart rate, stroke volume and peripheral vascular resistance, thus inducing hypertension. The hypertension in turn provides a hemodynamic advantage for hunter-gatherers. Specifically, sympathetic hyperactivity and increased blood pressure increases blood flow delivery to working muscles by increasing cardiac output and shunting blood from non-active tissue. This natural selection for hypertension occurred during the time in human evolutionary history when the lifespan of most individuals was probably 30-40 years, and morbidity and mortality from cardiovascular disorders was limited. Thus, the selection pressure for elevation in sympathetic nervous system activity and blood pressure provided an advantage for hunting and gathering that would be greater than the selection pressure exerted by the manifestations of cardiovascular disease in aged individuals.
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Landen S, Voisin S, Craig JM, McGee SL, Lamon S, Eynon N. Genetic and epigenetic sex-specific adaptations to endurance exercise. Epigenetics 2019; 14:523-535. [PMID: 30957644 DOI: 10.1080/15592294.2019.1603961] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
In recent years, the interest in personalised interventions such as medicine, nutrition, and exercise is rapidly rising to maximize health outcomes and ensure the most appropriate treatments. Exercising regularly is recommended for both healthy and diseased populations to improve health. However, there are sex-specific adaptations to exercise that often are not taken into consideration. While endurance exercise training alters the human skeletal muscle epigenome and subsequent gene expression, it is still unknown whether it does so differently in men and women, potentially leading to sex-specific physiological adaptations. Elucidating sex differences in genetics, epigenetics, gene regulation and expression in response to exercise will have great health implications, as it may enable gene targets in future clinical interventions and may better individualised interventions. This review will cover this topic and highlight the recent findings of sex-specific genetic, epigenetic, and gene expression studies, address the gaps in the field, and offer recommendations for future research.
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Affiliation(s)
- Shanie Landen
- a Institute for Health and Sport (iHeS) , Victoria University , Melbourne , Australia
| | - Sarah Voisin
- a Institute for Health and Sport (iHeS) , Victoria University , Melbourne , Australia
| | - Jeffrey M Craig
- b Centre for Molecular and Medical Research , Deakin University, Geelong Waurn Ponds Campus , Geelong , Australia.,c Environmental & Genetic Epidemiology Research , Murdoch Children's Research Institute, Royal Children's Hospital , Parkville , Australia
| | - Sean L McGee
- d Metabolic Research Unit, School of Medicine and Centre for Molecular and Medical Research , Deakin University , Geelong , Australia
| | - Séverine Lamon
- e Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences , Deakin University , Geelong , Australia
| | - Nir Eynon
- a Institute for Health and Sport (iHeS) , Victoria University , Melbourne , Australia.,f Royal Children's Hospital , Murdoch Children's Research Institute , Melbourne , Australia
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Gourine AV, Ackland GL. Cardiac Vagus and Exercise. Physiology (Bethesda) 2019; 34:71-80. [PMID: 30540229 PMCID: PMC6383634 DOI: 10.1152/physiol.00041.2018] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2018] [Revised: 10/26/2018] [Accepted: 10/29/2018] [Indexed: 01/09/2023] Open
Abstract
Lower resting heart rate and high autonomic vagal activity are strongly associated with superior exercise capacity, maintenance of which is essential for general well-being and healthy aging. Recent evidence obtained in experimental studies using the latest advances in molecular neuroscience, combined with human exercise physiology, physiological modeling, and genomic data suggest that the strength of cardiac vagal activity causally determines our ability to exercise.
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Affiliation(s)
- Alexander V Gourine
- Centre for Cardiovascular and Metabolic Neuroscience, Neuroscience, Physiology and Pharmacology, University College London , London , United Kingdom
| | - Gareth L Ackland
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London , London , United Kingdom
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48
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Abbott TEF, Pearse RM, Cuthbertson BH, Wijeysundera DN, Ackland GL. Cardiac vagal dysfunction and myocardial injury after non-cardiac surgery: a planned secondary analysis of the measurement of Exercise Tolerance before surgery study. Br J Anaesth 2018; 122:188-197. [PMID: 30686304 PMCID: PMC6354047 DOI: 10.1016/j.bja.2018.10.060] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Revised: 10/19/2018] [Accepted: 10/20/2018] [Indexed: 12/14/2022] Open
Abstract
Background The aetiology of perioperative myocardial injury is poorly understood and not clearly linked to pre-existing cardiovascular disease. We hypothesised that loss of cardioprotective vagal tone [defined by impaired heart rate recovery ≤12 beats min−1 (HRR ≤12) 1 min after cessation of preoperative cardiopulmonary exercise testing] was associated with perioperative myocardial injury. Methods We conducted a pre-defined, secondary analysis of a multi-centre prospective cohort study of preoperative cardiopulmonary exercise testing. Participants were aged ≥40 yr undergoing non-cardiac surgery. The exposure was impaired HRR (HRR≤12). The primary outcome was postoperative myocardial injury, defined by serum troponin concentration within 72 h after surgery. The analysis accounted for established markers of cardiac risk [Revised Cardiac Risk Index (RCRI), N-terminal pro-brain natriuretic peptide (NT pro-BNP)]. Results A total of 1326 participants were included [mean age (standard deviation), 64 (10) yr], of whom 816 (61.5%) were male. HRR≤12 occurred in 548 patients (41.3%). Myocardial injury was more frequent amongst patients with HRR≤12 [85/548 (15.5%) vs HRR>12: 83/778 (10.7%); odds ratio (OR), 1.50 (1.08–2.08); P=0.016, adjusted for RCRI). HRR declined progressively in patients with increasing numbers of RCRI factors. Patients with ≥3 RCRI factors were more likely to have HRR≤12 [26/36 (72.2%) vs 0 factors: 167/419 (39.9%); OR, 3.92 (1.84–8.34); P<0.001]. NT pro-BNP greater than a standard prognostic threshold (>300 pg ml−1) was more frequent in patients with HRR≤12 [96/529 (18.1%) vs HRR>12 59/745 (7.9%); OR, 2.58 (1.82–3.64); P<0.001]. Conclusions Impaired HRR is associated with an increased risk of perioperative cardiac injury. These data suggest a mechanistic role for cardiac vagal dysfunction in promoting perioperative myocardial injury.
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Affiliation(s)
- T E F Abbott
- William Harvey Research Institute, Queen Mary University of London, London, UK; University College London Hospital, London, UK
| | - R M Pearse
- William Harvey Research Institute, Queen Mary University of London, London, UK; Barts Health NHS Trust, London, UK
| | - B H Cuthbertson
- Department of Critical Care Medicine, Sunnybrook Health Sciences Centre, Toronto, ON, Canada; University of Toronto, Toronto, ON, Canada
| | - D N Wijeysundera
- University of Toronto, Toronto, ON, Canada; Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada; Toronto General Hospital, Toronto, ON, Canada
| | - G L Ackland
- William Harvey Research Institute, Queen Mary University of London, London, UK; Barts Health NHS Trust, London, UK.
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49
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Huffman JE. Examining the current standards for genetic discovery and replication in the era of mega-biobanks. Nat Commun 2018; 9:5054. [PMID: 30498205 PMCID: PMC6265242 DOI: 10.1038/s41467-018-07348-x] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Accepted: 10/26/2018] [Indexed: 01/27/2023] Open
Abstract
With the recent deluge of mega-biobank data, it is time to revisit what constitutes “replication” for genome-wide association studies. Many replication samples are unavailable or underpowered, therefore alternatives beyond strict statistical replication are needed until the required resources become available. Genome-wide association studies (GWAS) have become a mainstay in genetics research to understand genotype-phenotype relationships. Following the second release of UK Biobank data and the flood of publications using these data, here the author revisits the standards for discovery, replication and follow-up in GWAS today.
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Affiliation(s)
- J E Huffman
- Center for Population Genomics, MAVERIC, VA Boston Healthcare System, Boston, MA, 02130, USA.
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50
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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: 8.8] [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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