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Fu C, Yu F, Liu X, Li B, Li X, Zhang G. The causal relationship between sarcopenia-related traits and ECG indices - A mendelian randomization study. Arch Gerontol Geriatr 2024; 125:105520. [PMID: 38878672 DOI: 10.1016/j.archger.2024.105520] [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: 04/12/2024] [Revised: 05/26/2024] [Accepted: 06/02/2024] [Indexed: 07/13/2024]
Abstract
BACKGROUND Sarcopenia is a common geriatric condition closely associated with cardiovascular diseases and other health issues. This study aims to investigate the causal relationship between sarcopenia-related traits and electrocardiogram(ECG) indices. METHODS We conducted a comprehensive analysis utilizing summary data from genome-wide association studies (GWAS) associated with sarcopenia-related traits, including hand grip strength, lean body mass, and walking pace. ECG indices included PR interval, PP interval, ST duration, QRS duration and T wave duration. The primary analytical method employed was the inverse variance-weighted method (IVW). RESULTS According to our study findings, we identified a significant association between sarcopenia-related traits and ECG indices. Specifically, we observed a positive correlation between increased muscle mass and certain ECG indices. For instance, increased limb muscle mass (including left arm, right arm, left leg, and right leg) was associated with prolonged PR interval and QRS duration. This suggests that enhancing muscle mass may impact the timing of cardiac electrical activity. Additionally, increased whole-body fat-free mass showed similar associations with cardiac electrical activity. CONCLUSION Sarcopenia-related traits have a unidirectional causal relationship with ECG indices, indicating that sarcopenia affects cardiac electrical activity.
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Affiliation(s)
- Chunli Fu
- Department of Geriatric Medicine, Qilu Hospital of Shandong University, Jinan, China; Key Laboratory of Cardiovascular Proteomics of Shandong Province, Qilu Hospital of Shandong University, Jinan, China; Jinan Clinical Research Center for Geriatric Medicine 202132001, Jinan, China
| | - Fei Yu
- Department of Geriatric Medicine, Qilu Hospital of Shandong University, Jinan, China; Key Laboratory of Cardiovascular Proteomics of Shandong Province, Qilu Hospital of Shandong University, Jinan, China; Jinan Clinical Research Center for Geriatric Medicine 202132001, Jinan, China
| | - Xiangju Liu
- Department of Geriatric Medicine, Qilu Hospital of Shandong University, Jinan, China; Key Laboratory of Cardiovascular Proteomics of Shandong Province, Qilu Hospital of Shandong University, Jinan, China; Jinan Clinical Research Center for Geriatric Medicine 202132001, Jinan, China
| | - Baoying Li
- Key Laboratory of Cardiovascular Proteomics of Shandong Province, Qilu Hospital of Shandong University, Jinan, China; Health Management Center (East Area), Qilu Hospital of Shandong University, Jinan, China
| | - Xiaoli Li
- Department of Pharmacy, Qilu Hospital of Shandong University, Jinan, China
| | - Guangyu Zhang
- Department of Radiation Oncology, Qilu Hospital of Shandong University, Jinan, China.
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2
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Vafaeipour Z, Imenshahidi M, Mohammadpour AH, Taghdisi SM, Danesh NM, Moshiri M, Jafarian AH, Abnous K. Evaluation of the Protective Effects of Lugol's Solution in Rats Poisoned with Aluminum Phosphide (Rice Tablets). Cardiovasc Toxicol 2024:10.1007/s12012-024-09890-1. [PMID: 38990500 DOI: 10.1007/s12012-024-09890-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 07/01/2024] [Indexed: 07/12/2024]
Abstract
Aluminum phosphide (AlP) is the main component of rice tablets (a pesticide), which produces phosphine gas (PH3) when exposed to stomach acid. The most important symptoms of PH3 toxicity include, lethargy, tachycardia, hypotension, and cardiac shock. It was shown that Iodine can chemically react with PH3, and the purpose of this study is to investigate the protective effects of Lugol solution in poisoning with rice tablets. Five doses (12, 15, 21, 23, and 25 mg/kg) of AlP were selected, for calculating its lethal dose (LD50). Then, the rats were divided into 4 groups: AlP, Lugol, AlP + Lugol, and Almond oil (as a control). After 4 h, the blood pressure and electrocardiogram (ECG) were recorded, and blood samples were obtained for biochemical tests, then liver, lung, kidney, heart, and brain tissues were removed for histopathological examination. The results of the blood pressure showed no significant changes (P > 0.05). In ECG, the PR interval showed a significant decrease in the AlP + Lugol group (P < 0.05). In biochemical tests, LDH, Ca2+, Creatinine, ALP, Mg2+, and K+ represented significant decreases in AlP + Lugol compared to the AlP group (P < 0.05). Also, the administration of Lugol's solution to AlP-poisoned rats resulted in a significant decrease in malondialdehyde levels and a significant increase in catalase activity (P < 0.05). Histopathological evaluation indicates that Lugol improves changes in the lungs, kidneys, brain, and heart. Our results showed that the Lugol solution could reduce tissue damage and oxidative stress in AlP-poisoned rats. We assume that the positive effects of Lugol on pulmonary and cardiac tissues are due to its ability to react directly with PH3.
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Affiliation(s)
- Zeinab Vafaeipour
- Department of Pharmacodynamics and Toxicology, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, 9177948954, Iran
| | - Mohsen Imenshahidi
- Department of Pharmacodynamics and Toxicology, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, 9177948954, Iran
- Pharmaceutical Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Amir Hooshang Mohammadpour
- Department of Clinical Pharmacy, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Seyed Mohammad Taghdisi
- Targeted Drug Delivery Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran
- Department of Pharmaceutical Biotechnology, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran
| | | | - Mohammad Moshiri
- Medical Toxicology Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Amir Hossein Jafarian
- Cancer and Molecular Research Center, Department of Pathology, Ghaem Hospital, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Khalil Abnous
- Pharmaceutical Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran.
- Department of Medicinal Chemistry, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran.
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3
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Ishikawa T, Masuda T, Hachiya T, Dina C, Simonet F, Nagata Y, Tanck MWT, Sonehara K, Glinge C, Tadros R, Khongphatthanayothin A, Lu TP, Higuchi C, Nakajima T, Hayashi K, Aizawa Y, Nakano Y, Nogami A, Morita H, Ohno S, Aiba T, Krijger Juárez C, Mauleekoonphairoj J, Poovorawan Y, Gourraud JB, Shimizu W, Probst V, Horie M, Wilde AAM, Redon R, Juang JMJ, Nademanee K, Bezzina CR, Barc J, Tanaka T, Okada Y, Schott JJ, Makita N. Brugada syndrome in Japan and Europe: a genome-wide association study reveals shared genetic architecture and new risk loci. Eur Heart J 2024; 45:2320-2332. [PMID: 38747976 DOI: 10.1093/eurheartj/ehae251] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Revised: 03/02/2024] [Accepted: 04/08/2024] [Indexed: 07/10/2024] Open
Abstract
BACKGROUND AND AIMS Brugada syndrome (BrS) is an inherited arrhythmia with a higher disease prevalence and more lethal arrhythmic events in Asians than in Europeans. Genome-wide association studies (GWAS) have revealed its polygenic architecture mainly in European populations. The aim of this study was to identify novel BrS-associated loci and to compare allelic effects across ancestries. METHODS A GWAS was conducted in Japanese participants, involving 940 cases and 1634 controls, followed by a cross-ancestry meta-analysis of Japanese and European GWAS (total of 3760 cases and 11 635 controls). The novel loci were characterized by fine-mapping, gene expression, and splicing quantitative trait associations in the human heart. RESULTS The Japanese-specific GWAS identified one novel locus near ZSCAN20 (P = 1.0 × 10-8), and the cross-ancestry meta-analysis identified 17 association signals, including six novel loci. The effect directions of the 17 lead variants were consistent (94.1%; P for sign test = 2.7 × 10-4), and their allelic effects were highly correlated across ancestries (Pearson's R = .91; P = 2.9 × 10-7). The genetic risk score derived from the BrS GWAS of European ancestry was significantly associated with the risk of BrS in the Japanese population [odds ratio 2.12 (95% confidence interval 1.94-2.31); P = 1.2 × 10-61], suggesting a shared genetic architecture across ancestries. Functional characterization revealed that a lead variant in CAMK2D promotes alternative splicing, resulting in an isoform switch of calmodulin kinase II-δ, favouring a pro-inflammatory/pro-death pathway. CONCLUSIONS This study demonstrates novel susceptibility loci implicating potentially novel pathogenesis underlying BrS. Despite differences in clinical expressivity and epidemiology, the polygenic architecture of BrS was substantially shared across ancestries.
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Affiliation(s)
- Taisuke Ishikawa
- Omics Research Center, National Cerebral and Cardiovascular Center, Suita, Japan
| | - Tatsuo Masuda
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- StemRIM Institute of Regeneration-Inducing Medicine, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Obstetrics and Gynecology, Osaka University Graduate School of Medicine, Suita, Japan
| | - Tsuyoshi Hachiya
- Institute for Biomedical Sciences, Iwate Medical University, Iwate, Japan
| | - Christian Dina
- L'institut du thorax, Nantes Université, CHU Nantes, CNRS, INSERM, Nantes, France
| | - Floriane Simonet
- L'institut du thorax, Nantes Université, CHU Nantes, CNRS, INSERM, Nantes, France
| | - Yuki Nagata
- Bioresource Research Center, Tokyo Medical and Dental University, Tokyo, Japan
- Department of Human Genetics and Disease Diversity, Tokyo Medical and Dental University, Tokyo, Japan
| | - Michael W T Tanck
- Epidemiology and Data Science, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands
| | - Kyuto Sonehara
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
| | - Charlotte Glinge
- Department of Experimental Cardiology, Amsterdam UMC location University of Amsterdam, Heart Centre, Amsterdam, The Netherlands
- Heart Failure & Arrhythmias, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands
- Department of Cardiology, The Heart Centre, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
- European Reference Network for Rare and Low Prevalence Complex Diseases of the Heart (ERN GUARD-HEART https://guardheart.ern-net.eu)
| | - Rafik Tadros
- Department of Experimental Cardiology, Amsterdam UMC location University of Amsterdam, Heart Centre, Amsterdam, The Netherlands
- Heart Failure & Arrhythmias, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands
- Montreal Heart Institute, Universite de Montreal, Cardiovascular Genetics Centre, Montreal, Quebec, Canada
| | - Apichai Khongphatthanayothin
- Department of Medicine, Center of Excellence in Arrhythmia Research Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Department of Pediatrics, Division of Cardiology Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Department of Cardiology, Bangkok Hospital, Bangkok, Thailand
| | - Tzu-Pin Lu
- Department of Public Health, Institute of Health Data Analytics and Statistics, National Taiwan University, Taipei, Taiwan
| | - Chihiro Higuchi
- Bioresource Research Center, Tokyo Medical and Dental University, Tokyo, Japan
- Artificial Intelligence Center for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health and Nutrition, Settsu, Japan
| | - Tadashi Nakajima
- Department of Cardiovascular Medicine, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Kenshi Hayashi
- Department of Cardiovascular Medicine, Kanazawa University Graduate School of Medical Sciences, Kanazawa, Japan
| | - Yoshiyasu Aizawa
- Department of Cardiovascular Medicine, International University of Health and Welfare, Narita, Japan
| | - Yukiko Nakano
- Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, Japan
| | - Akihiko Nogami
- Department of Cardiology, University of Tsukuba, Tsukuba, Japan
| | - Hiroshi Morita
- Department of Cardiovascular Therapeutics, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan
| | - Seiko Ohno
- Medical Genome Center, National Cerebral and Cardiovascular Center, Suita, Japan
- Department of Cardiovascular Medicine, Shiga University of Medical Sciences, Otsu, Japan
| | - Takeshi Aiba
- Department of Cardiovascular Medicine, National Cerebral and Cardiovascular Center, Suita, Japan
| | - Christian Krijger Juárez
- Department of Experimental Cardiology, Amsterdam UMC location University of Amsterdam, Heart Centre, Amsterdam, The Netherlands
- Heart Failure & Arrhythmias, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands
| | - John Mauleekoonphairoj
- Department of Medicine, Center of Excellence in Arrhythmia Research Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Yong Poovorawan
- Center of Excellence in Clinical Virology Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Jean-Baptiste Gourraud
- L'institut du thorax, Nantes Université, CHU Nantes, CNRS, INSERM, Nantes, France
- European Reference Network for Rare and Low Prevalence Complex Diseases of the Heart (ERN GUARD-HEART https://guardheart.ern-net.eu)
| | - Wataru Shimizu
- Department of Cardiovascular Medicine, Nippon Medical School, Tokyo, Japan
| | - Vincent Probst
- L'institut du thorax, Nantes Université, CHU Nantes, CNRS, INSERM, Nantes, France
- European Reference Network for Rare and Low Prevalence Complex Diseases of the Heart (ERN GUARD-HEART https://guardheart.ern-net.eu)
| | - Minoru Horie
- Department of Cardiovascular Medicine, Shiga University of Medical Sciences, Otsu, Japan
| | - Arthur A M Wilde
- Heart Failure & Arrhythmias, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands
- European Reference Network for Rare and Low Prevalence Complex Diseases of the Heart (ERN GUARD-HEART https://guardheart.ern-net.eu)
- Department of Cardiology, Amsterdam UMC location University of Amsterdam, Heart Centre, Amsterdam, The Netherlands
| | - Richard Redon
- L'institut du thorax, Nantes Université, CHU Nantes, CNRS, INSERM, Nantes, France
| | - Jyh-Ming Jimmy Juang
- Cardiovascular Center, Heart Failure Center and Department of Internal Medicine, Division of Cardiology, National Taiwan University Hospital, Taipei, Taiwan
- Department of Medicine, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Koonlawee Nademanee
- Department of Medicine, Center of Excellence in Arrhythmia Research Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Pacific Rim Electrophysiology Research Institute, Bumrungrad International Hospital, Bangkok, Thailand
| | - Connie R Bezzina
- Department of Experimental Cardiology, Amsterdam UMC location University of Amsterdam, Heart Centre, Amsterdam, The Netherlands
- Heart Failure & Arrhythmias, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands
- European Reference Network for Rare and Low Prevalence Complex Diseases of the Heart (ERN GUARD-HEART https://guardheart.ern-net.eu)
| | - Julien Barc
- L'institut du thorax, Nantes Université, CHU Nantes, CNRS, INSERM, Nantes, France
- European Reference Network for Rare and Low Prevalence Complex Diseases of the Heart (ERN GUARD-HEART https://guardheart.ern-net.eu)
| | - Toshihiro Tanaka
- Bioresource Research Center, Tokyo Medical and Dental University, Tokyo, Japan
- Department of Human Genetics and Disease Diversity, Tokyo Medical and Dental University, Tokyo, Japan
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center, Osaka University, Suita, Japan
| | - Jean-Jacques Schott
- L'institut du thorax, Nantes Université, CHU Nantes, CNRS, INSERM, Nantes, France
- European Reference Network for Rare and Low Prevalence Complex Diseases of the Heart (ERN GUARD-HEART https://guardheart.ern-net.eu)
| | - Naomasa Makita
- Department of Cardiology, Sapporo Teishinkai Hospital, N33, E1, Sapporo 065-0033, Japan
- Department of Cell Biology, National Cerebral and Cardiovascular Center Research Institute, 6-1, Kishibe Shimmachi, 564-8565 Suita, Japan
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4
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Kukendrarajah K, Farmaki AE, Lambiase PD, Schilling R, Finan C, Floriaan Schmidt A, Providencia R. Advancing drug development for atrial fibrillation by prioritising findings from human genetic association studies. EBioMedicine 2024; 105:105194. [PMID: 38941956 PMCID: PMC11260865 DOI: 10.1016/j.ebiom.2024.105194] [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: 09/22/2023] [Revised: 05/14/2024] [Accepted: 05/28/2024] [Indexed: 06/30/2024] Open
Abstract
BACKGROUND Drug development for atrial fibrillation (AF) has failed to yield new approved compounds. We sought to identify and prioritise potential druggable targets with support from human genetics, by integrating the available evidence with bioinformatics sources relevant for AF drug development. METHODS Genetic hits for AF and related traits were identified through structured search of MEDLINE. Genes derived from each paper were cross-referenced with the OpenTargets platform for drug interactions. Confirmation/validation was demonstrated through structured searches and review of evidence on MEDLINE and ClinialTrials.gov for each drug and its association with AF. FINDINGS 613 unique drugs were identified, with 21 already included in AF Guidelines. Cardiovascular drugs from classes not currently used for AF (e.g. ranolazine and carperitide) and anti-inflammatory drugs (e.g. dexamethasone and mehylprednisolone) had evidence of potential benefit. Further targets were considered druggable but remain open for drug development. INTERPRETATION Our systematic approach, combining evidence from different bioinformatics platforms, identified drug repurposing opportunities and druggable targets for AF. FUNDING KK is supported by Barts Charity grant G-002089 and is mentored on the AFGen 2023-24 Fellowship funded by the AFGen NIH/NHLBI grant R01HL092577. RP is supported by the UCL BHF Research Accelerator AA/18/6/34223 and NIHR grant NIHR129463. AFS is supported by the BHF grants PG/18/5033837, PG/22/10989 and UCL BHF Accelerator AA/18/6/34223 as well as the UK Research and Innovation (UKRI) under the UK government's Horizon Europe funding guarantee EP/Z000211/1 and by the UKRI-NIHR grant MR/V033867/1 for the Multimorbidity Mechanism and Therapeutics Research Collaboration. AF is supported by UCL BHF Accelerator AA/18/6/34223. CF is supported by UCL BHF Accelerator AA/18/6/34223.
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Affiliation(s)
- Kishore Kukendrarajah
- Institute of Health Informatics, University College London, 222 Euston Road, NW1 2DA, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, EC1A 7BE, United Kingdom.
| | - Aliki-Eleni Farmaki
- Institute of Health Informatics, University College London, 222 Euston Road, NW1 2DA, United Kingdom
| | - Pier D Lambiase
- Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, EC1A 7BE, United Kingdom; Institute of Cardiovascular Science, University College London, Gower Street, WC1E 6HX, United Kingdom
| | - Richard Schilling
- Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, EC1A 7BE, United Kingdom
| | - Chris Finan
- Institute of Cardiovascular Science, University College London, Gower Street, WC1E 6HX, United Kingdom; UCL British Heart Foundation Research Accelerator, United Kingdom; Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, the Netherlands
| | - Amand Floriaan Schmidt
- Institute of Cardiovascular Science, University College London, Gower Street, WC1E 6HX, United Kingdom; UCL British Heart Foundation Research Accelerator, United Kingdom; Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, the Netherlands; Department of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centres, University of Amsterdam, the Netherlands
| | - Rui Providencia
- Institute of Health Informatics, University College London, 222 Euston Road, NW1 2DA, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, EC1A 7BE, United Kingdom
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5
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Pastika L, Sau A, Patlatzoglou K, Sieliwonczyk E, Ribeiro AH, McGurk KA, Khan S, Mandic D, Scott WR, Ware JS, Peters NS, Ribeiro ALP, Kramer DB, Waks JW, Ng FS. Artificial intelligence-enhanced electrocardiography derived body mass index as a predictor of future cardiometabolic disease. NPJ Digit Med 2024; 7:167. [PMID: 38918595 PMCID: PMC11199586 DOI: 10.1038/s41746-024-01170-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 06/14/2024] [Indexed: 06/27/2024] Open
Abstract
The electrocardiogram (ECG) can capture obesity-related cardiac changes. Artificial intelligence-enhanced ECG (AI-ECG) can identify subclinical disease. We trained an AI-ECG model to predict body mass index (BMI) from the ECG alone. Developed from 512,950 12-lead ECGs from the Beth Israel Deaconess Medical Center (BIDMC), a secondary care cohort, and validated on UK Biobank (UKB) (n = 42,386), the model achieved a Pearson correlation coefficient (r) of 0.65 and 0.62, and an R2 of 0.43 and 0.39 in the BIDMC cohort and UK Biobank, respectively for AI-ECG BMI vs. measured BMI. We found delta-BMI, the difference between measured BMI and AI-ECG-predicted BMI (AI-ECG-BMI), to be a biomarker of cardiometabolic health. The top tertile of delta-BMI showed increased risk of future cardiometabolic disease (BIDMC: HR 1.15, p < 0.001; UKB: HR 1.58, p < 0.001) and diabetes mellitus (BIDMC: HR 1.25, p < 0.001; UKB: HR 2.28, p < 0.001) after adjusting for covariates including measured BMI. Significant enhancements in model fit, reclassification and improvements in discriminatory power were observed with the inclusion of delta-BMI in both cohorts. Phenotypic profiling highlighted associations between delta-BMI and cardiometabolic diseases, anthropometric measures of truncal obesity, and pericardial fat mass. Metabolic and proteomic profiling associates delta-BMI positively with valine, lipids in small HDL, syntaxin-3, and carnosine dipeptidase 1, and inversely with glutamine, glycine, colipase, and adiponectin. A genome-wide association study revealed associations with regulators of cardiovascular/metabolic traits, including SCN10A, SCN5A, EXOG and RXRG. In summary, our AI-ECG-BMI model accurately predicts BMI and introduces delta-BMI as a non-invasive biomarker for cardiometabolic risk stratification.
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Affiliation(s)
- Libor Pastika
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Arunashis Sau
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Department of Cardiology, Imperial College Healthcare NHS Trust, London, United Kingdom
| | | | - Ewa Sieliwonczyk
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- MRC Laboratory of Medical Sciences, Imperial College London, London, United Kingdom
| | - Antônio H Ribeiro
- Department of Information Technology, Uppsala University, Uppsala, Sweden
| | - Kathryn A McGurk
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- MRC Laboratory of Medical Sciences, Imperial College London, London, United Kingdom
| | - Sadia Khan
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Chelsea and Westminster NHS Foundation Trust, London, United Kingdom
| | - Danilo Mandic
- Department of Electrical and Electronic Engineering, Imperial College London, London, United Kingdom
| | - William R Scott
- MRC Laboratory of Medical Sciences, Imperial College London, London, United Kingdom
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - James S Ware
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- MRC Laboratory of Medical Sciences, Imperial College London, London, United Kingdom
| | - Nicholas S Peters
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Department of Cardiology, Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Antonio Luiz P Ribeiro
- Department of Internal Medicine, Faculdade de Medicina, and Telehealth Center and Cardiology Service, Hospital das Clínicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Daniel B Kramer
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Jonathan W Waks
- Harvard-Thorndike Electrophysiology Institute, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Fu Siong Ng
- National Heart and Lung Institute, Imperial College London, London, United Kingdom.
- Department of Cardiology, Imperial College Healthcare NHS Trust, London, United Kingdom.
- Chelsea and Westminster NHS Foundation Trust, London, United Kingdom.
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6
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Weng LC, Khurshid S, Hall AW, Nauffal V, Morrill VN, Sun YV, Rämö JT, Beer D, Lee S, Nadkarni G, Johnson R, Andreasen L, Clayton A, Pullinger CR, Yoneda ZT, Friedman DJ, Hyman MC, Judy RL, Skanes AC, Orland KM, Jordà P, Treu TM, Oetjens MT, Subbiah R, Hartmann JP, May HT, Kane JP, Issa TZ, Nafissi NA, Leong-Sit P, Dubé MP, Roselli C, Choi SH, Tardif JC, Khan HR, Knight S, Svendsen JH, Walker B, Linnér RK, Gaziano JM, Tadros R, Fatkin D, Rader DJ, Shah SH, Roden DM, Marcus GM, Loos RJ, Damrauer SM, Haggerty CM, Cho K, Palotie A, Olesen MS, Eckhardt LL, Roberts JD, Cutler MJ, Shoemaker MB, Wilson PW, Ellinor PT, Lubitz SA. Meta-Analysis of Genome-Wide Association Studies Reveals Genetic Mechanisms of Supraventricular Arrhythmias. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2024; 17:e004320. [PMID: 38804128 PMCID: PMC11187659 DOI: 10.1161/circgen.123.004320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 03/31/2024] [Indexed: 05/29/2024]
Abstract
BACKGROUND Substantial data support a heritable basis for supraventricular tachycardias, but the genetic determinants and molecular mechanisms of these arrhythmias are poorly understood. We sought to identify genetic loci associated with atrioventricular nodal reentrant tachycardia (AVNRT) and atrioventricular accessory pathways or atrioventricular reciprocating tachycardia (AVAPs/AVRT). METHODS We performed multiancestry meta-analyses of genome-wide association studies to identify genetic loci for AVNRT (4 studies) and AVAP/AVRT (7 studies). We assessed evidence supporting the potential causal effects of candidate genes by analyzing relations between associated variants and cardiac gene expression, performing transcriptome-wide analyses, and examining prior genome-wide association studies. RESULTS Analyses comprised 2384 AVNRT cases and 106 489 referents, and 2811 AVAP/AVRT cases and 1,483 093 referents. We identified 2 significant loci for AVNRT, which implicate NKX2-5 and TTN as disease susceptibility genes. A transcriptome-wide association analysis supported an association between reduced predicted cardiac expression of NKX2-5 and AVNRT. We identified 3 significant loci for AVAP/AVRT, which implicate SCN5A, SCN10A, and TTN/CCDC141. Variant associations at several loci have been previously reported for cardiac phenotypes, including atrial fibrillation, stroke, Brugada syndrome, and electrocardiographic intervals. CONCLUSIONS Our findings highlight gene regions associated with ion channel function (AVAP/AVRT), as well as cardiac development and the sarcomere (AVAP/AVRT and AVNRT) as important potential effectors of supraventricular tachycardia susceptibility.
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Affiliation(s)
- Lu-Chen Weng
- Cardiovascular Rsrch Ctr, Dept of Medicine, Dept of Neurology & Dept of Psychiatry, MGH, Boston
- Cardiovascular Disease Initiative, The Broad Institute of MIT & Harvard, Cambridge
- VA Boston Healthcare System
| | - Shaan Khurshid
- Cardiovascular Disease Initiative, The Broad Institute of MIT & Harvard, Cambridge
- Demoulas Ctr for Cardiac Arrhythmias, Dept of Medicine, Dept of Neurology & Dept of Psychiatry, MGH, Boston
| | - Amelia Weber Hall
- Gene Regulation Observatory, The Broad Institute of MIT & Harvard, Cambridge
| | - Victor Nauffal
- Cardiovascular Disease Initiative, The Broad Institute of MIT & Harvard, Cambridge
- VA Boston Healthcare System
- Cardiovascular Medicine Division, Brigham and Women’s Hospital, Boston, MA
| | - Valerie N. Morrill
- Cardiovascular Disease Initiative, The Broad Institute of MIT & Harvard, Cambridge
| | - Yan V. Sun
- Dept of Epidemiology, Emory Univ Rollins School of Public Health, Atlanta
- VA Atlanta Healthcare System, Decatur, GA
| | - Joel T. Rämö
- Inst for Molecular Medicine Finland (FIMM), Helsinki Inst of Life Science (HiLIFE), Univ of Helsinki, Helsinki, Finland
- The Broad Inst of MIT & Harvard, Cambridge, MA
| | | | - Simon Lee
- Icahn School of Medicine at Mount Sinai, New York, NY
| | | | - Renee Johnson
- Victor Chang Cardiac Rsrch Inst, Darlinghurst
- School of Clinical Medicine, Faculty of Medicine & Health, UNSW Sydney, Kensington, NSW, Australia
| | - Laura Andreasen
- Laboratory for Molecular Cardiology, Dept of Cardiology, Copenhagen Univ Hospital, Rigshospitalet
- Dept of Biomedical Sciences, Univ of Copenhagen, Copenhagen, Denmark
| | - Anne Clayton
- Intermountain Heart Inst, Intermountain Medical Ctr, Murray, UT
| | - Clive R. Pullinger
- Cardiovascular Rsrch Inst & Dept of Physiological Nursing, Univ of California, San Francisco, CA
| | - Zachary T. Yoneda
- Dept of Medicine, Division of Cardiovascular Medicine, Vanderbilt Univ Medical Ctr, Nashville, TN
| | - Daniel J. Friedman
- Division of Cardiology, Dept of Medicine, Duke Univ School of Medicine, Durham, NC
| | - Matthew C. Hyman
- Division of Cardiac Electrophysiology, Hospital of the Univ of Pennsylvania
| | - Renae L. Judy
- Dept of Surgery, Perelman School of Medicine, Univ of Pennsylvania, Philadelphia, PA
| | - Allan C. Skanes
- Section of Cardiac Electrophysiology, Division of Cardiology, Dept of Medicine, Western Univ, London, ON, Canada
| | - Kate M. Orland
- Dept of Medicine, Division of Cardiovascular Medicine, Univ of Wisconsin–Madison, Madison, WI
| | - Paloma Jordà
- Montreal Heart Inst Rsrch Ctr & Faculty of Medicine, Université de Montréal, Montreal, QC, Canada
| | | | | | - Rajesh Subbiah
- Victor Chang Cardiac Rsrch Inst, Darlinghurst
- School of Clinical Medicine, Faculty of Medicine & Health, UNSW Sydney, Kensington, NSW, Australia
- St Vincent’s Hospital, Darlinghurst
| | - Jacob P. Hartmann
- Laboratory for Molecular Cardiology, Dept of Cardiology, Copenhagen Univ Hospital, Rigshospitalet
| | - Heidi T. May
- Intermountain Heart Inst, Intermountain Medical Ctr, Murray, UT
| | - John P. Kane
- Cardiovascular Rsrch Inst, Univ of California, San Francisco, CA
- Dept of Medicine, Univ of California, San Francisco, CA
- Dept of Biochemistry & Biophysics, Univ of California, San Francisco, CA
| | - Tariq Z. Issa
- Feinberg School of Medicine, Northwestern Univ, Chicago, IL
| | - Navid A. Nafissi
- Division of Cardiology, Dept of Medicine, Duke Univ School of Medicine, Durham, NC
| | - Peter Leong-Sit
- Section of Cardiac Electrophysiology, Division of Cardiology, Dept of Medicine, Western Univ, London, ON, Canada
| | - Marie-Pierre Dubé
- Montreal Heart Inst Rsrch Ctr & Faculty of Medicine, Université de Montréal, Montreal, QC, Canada
- Beaulieu-Saucier Pharmacogenomics Ctr, Montreal, Canada
| | - Carolina Roselli
- Cardiovascular Disease Initiative, The Broad Institute of MIT & Harvard, Cambridge
- Dept of Cardiology, Univ of Groningen, University Medical Ctr Groningen, the Netherlands
| | - Seung Hoan Choi
- Cardiovascular Disease Initiative, The Broad Institute of MIT & Harvard, Cambridge
| | | | | | | | - Jean-Claude Tardif
- Montreal Heart Inst Rsrch Ctr & Faculty of Medicine, Université de Montréal, Montreal, QC, Canada
| | - Habib R. Khan
- Section of Cardiac Electrophysiology, Division of Cardiology, Dept of Medicine, Western Univ, London, ON, Canada
| | - Stacey Knight
- Intermountain Heart Inst, Intermountain Medical Ctr, Murray, UT
- Dept of Medicine, Univ of Utah, Salt Lake City, UT
| | - Jesper H. Svendsen
- Laboratory for Molecular Cardiology, Dept of Cardiology, Copenhagen Univ Hospital, Rigshospitalet
- Dept of Clinical Medicine, Univ of Copenhagen, Copenhagen, Denmark
| | - Bruce Walker
- School of Clinical Medicine, Faculty of Medicine & Health, UNSW Sydney, Kensington, NSW, Australia
- St Vincent’s Hospital, Darlinghurst
| | - Richard Karlsson Linnér
- Autism & Developmental Medicine Inst, Geisinger, Lewisburg, PA
- Dept of Economics, Leiden Law School, Leiden Univ, Leiden, the Netherlands
| | - J. Michael Gaziano
- VA Boston Healthcare System
- Cardiovascular Medicine Division, Brigham and Women’s Hospital, Boston, MA
- Harvard Medical School, Boston, MA
| | - Rafik Tadros
- Montreal Heart Inst Rsrch Ctr & Faculty of Medicine, Université de Montréal, Montreal, QC, Canada
| | - Diane Fatkin
- Victor Chang Cardiac Rsrch Inst, Darlinghurst
- School of Clinical Medicine, Faculty of Medicine & Health, UNSW Sydney, Kensington, NSW, Australia
- St Vincent’s Hospital, Darlinghurst
| | - Daniel J. Rader
- Division of Cardiovascular Medicine, Dept of Medicine, Perelman School of Medicine, Univ of Pennsylvania, Philadelphia, PA
| | - Svati H. Shah
- Division of Cardiology, Dept of Medicine, Duke Univ School of Medicine, Durham, NC
- Duke Molecular Physiology Inst, Duke Univ School of Medicine, Durham, NC
| | | | | | - Ruth J.F. Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY & Novo Nordisk Foundation Ctr for Basic Metabolic Rsrch, Dept of Health & Medical Sciences, Univ of Copenhagen, Copenhagen, Denmark
| | - Scott M. Damrauer
- Dept of Surgery & Dept of Genetics, Perelman School of Medicine, Univ of Pennsylvania, Philadelphia, PA
- Corporal Michael Crescenz VA Medical Ctr, Philadelphia
| | - Christopher M. Haggerty
- Heart Inst, Geisinger, Danville, PA
- Dept of Translational Data Science & Informatics, Geisinger, Danville, PA
| | - Kelly Cho
- VA Boston Healthcare System
- Cardiovascular Medicine Division, Brigham and Women’s Hospital, Boston, MA
| | - Aarno Palotie
- Inst for Molecular Medicine Finland (FIMM), Helsinki Inst of Life Science (HiLIFE), Univ of Helsinki, Helsinki, Finland
- The Stanley Center for Psychiatric Rsrch & Program in Medical & Population Genetics, The Broad Institute of MIT & Harvard, Cambridge
- Analytic & Translational Genetics Unit, Dept of Medicine, Dept of Neurology & Dept of Psychiatry, MGH, Boston
| | - Morten S. Olesen
- Laboratory for Molecular Cardiology, Dept of Cardiology, Copenhagen Univ Hospital, Rigshospitalet
- Dept of Biomedical Sciences, Univ of Copenhagen, Copenhagen, Denmark
| | - Lee L. Eckhardt
- Dept of Medicine, Division of Cardiovascular Medicine, Univ of Wisconsin–Madison, Madison, WI
| | - Jason D. Roberts
- Section of Cardiac Electrophysiology, Division of Cardiology, Dept of Medicine, Western Univ, London, ON, Canada
| | | | - M. Benjamin Shoemaker
- Dept of Medicine, Division of Cardiovascular Medicine, Vanderbilt Univ Medical Ctr, Nashville, TN
| | - Peter W.F. Wilson
- VA Atlanta Healthcare System, Decatur, GA
- Dept of Medicine, Emory Univ School of Medicine, Atlanta, GA
| | - Patrick T. Ellinor
- Cardiovascular Disease Initiative, The Broad Institute of MIT & Harvard, Cambridge
- Demoulas Ctr for Cardiac Arrhythmias, Dept of Medicine, Dept of Neurology & Dept of Psychiatry, MGH, Boston
| | - Steven A. Lubitz
- Cardiovascular Disease Initiative, The Broad Institute of MIT & Harvard, Cambridge
- Demoulas Ctr for Cardiac Arrhythmias, Dept of Medicine, Dept of Neurology & Dept of Psychiatry, MGH, Boston
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7
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Cull J, Cooper S, Alharbi H, Chothani S, Rackham O, Meijles D, Dash P, Kerkelä R, Ruparelia N, Sugden P, Clerk A. Striatin plays a major role in angiotensin II-induced cardiomyocyte and cardiac hypertrophy in mice in vivo. Clin Sci (Lond) 2024; 138:573-597. [PMID: 38718356 PMCID: PMC11130554 DOI: 10.1042/cs20240496] [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: 03/18/2024] [Revised: 05/07/2024] [Accepted: 05/08/2024] [Indexed: 05/23/2024]
Abstract
The three striatins (STRN, STRN3, STRN4) form the core of STRiatin-Interacting Phosphatase and Kinase (STRIPAK) complexes. These place protein phosphatase 2A (PP2A) in proximity to protein kinases thereby restraining kinase activity and regulating key cellular processes. Our aim was to establish if striatins play a significant role in cardiac remodelling associated with cardiac hypertrophy and heart failure. All striatins were expressed in control human hearts, with up-regulation of STRN and STRN3 in failing hearts. We used mice with global heterozygote gene deletion to assess the roles of STRN and STRN3 in cardiac remodelling induced by angiotensin II (AngII; 7 days). Using echocardiography, we detected no differences in baseline cardiac function or dimensions in STRN+/- or STRN3+/- male mice (8 weeks) compared with wild-type littermates. Heterozygous gene deletion did not affect cardiac function in mice treated with AngII, but the increase in left ventricle mass induced by AngII was inhibited in STRN+/- (but not STRN3+/-) mice. Histological staining indicated that cardiomyocyte hypertrophy was inhibited. To assess the role of STRN in cardiomyocytes, we converted the STRN knockout line for inducible cardiomyocyte-specific gene deletion. There was no effect of cardiomyocyte STRN knockout on cardiac function or dimensions, but the increase in left ventricle mass induced by AngII was inhibited. This resulted from inhibition of cardiomyocyte hypertrophy and cardiac fibrosis. The data indicate that cardiomyocyte striatin is required for early remodelling of the heart by AngII and identify the striatin-based STRIPAK system as a signalling paradigm in the development of pathological cardiac hypertrophy.
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Affiliation(s)
- Joshua J. Cull
- School of Biological Sciences, University of Reading, Reading, U.K
| | - Susanna T.E. Cooper
- Molecular and Clinical Sciences Institute, St. George’s University of London, London, U.K
| | - Hajed O. Alharbi
- School of Biological Sciences, University of Reading, Reading, U.K
| | - Sonia P. Chothani
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore Medical School, Singapore
| | - Owen J.L. Rackham
- Program in Cardiovascular and Metabolic Disorders, Duke-National University of Singapore Medical School, Singapore
- School of Biological Sciences, University of Southampton, Southampton, U.K
| | - Daniel N. Meijles
- Molecular and Clinical Sciences Institute, St. George’s University of London, London, U.K
| | - Philip R. Dash
- School of Biological Sciences, University of Reading, Reading, U.K
| | - Risto Kerkelä
- Research Unit of Biomedicine and Internal Medicine, Medical Research Centre Oulu (Oulu University Hospital) and Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Neil Ruparelia
- School of Biological Sciences, University of Reading, Reading, U.K
- Department of Cardiology, Royal Berkshire Hospital, Reading, U.K
| | - Peter H. Sugden
- School of Biological Sciences, University of Reading, Reading, U.K
| | - Angela Clerk
- School of Biological Sciences, University of Reading, Reading, U.K
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8
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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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9
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Joglar JA, Chung MK, Armbruster AL, Benjamin EJ, Chyou JY, Cronin EM, Deswal A, Eckhardt LL, Goldberger ZD, Gopinathannair R, Gorenek B, Hess PL, Hlatky M, Hogan G, Ibeh C, Indik JH, Kido K, Kusumoto F, Link MS, Linta KT, Marcus GM, McCarthy PM, Patel N, Patton KK, Perez MV, Piccini JP, Russo AM, Sanders P, Streur MM, Thomas KL, Times S, Tisdale JE, Valente AM, Van Wagoner DR. 2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation 2024; 149:e1-e156. [PMID: 38033089 PMCID: PMC11095842 DOI: 10.1161/cir.0000000000001193] [Citation(s) in RCA: 218] [Impact Index Per Article: 218.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/02/2023]
Abstract
AIM The "2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation" provides recommendations to guide clinicians in the treatment of patients with atrial fibrillation. METHODS A comprehensive literature search was conducted from May 12, 2022, to November 3, 2022, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Library, the Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. Additional relevant studies, published through November 2022, during the guideline writing process, were also considered by the writing committee and added to the evidence tables, where appropriate. STRUCTURE Atrial fibrillation is the most sustained common arrhythmia, and its incidence and prevalence are increasing in the United States and globally. Recommendations from the "2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" and the "2019 AHA/ACC/HRS Focused Update of the 2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" have been updated with new evidence to guide clinicians. In addition, new recommendations addressing atrial fibrillation and thromboembolic risk assessment, anticoagulation, left atrial appendage occlusion, atrial fibrillation catheter or surgical ablation, and risk factor modification and atrial fibrillation prevention have been developed.
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Affiliation(s)
| | | | | | | | | | | | - Anita Deswal
- ACC/AHA Joint Committee on Clinical Practice Guidelines liaison
| | | | | | | | | | - Paul L Hess
- ACC/AHA Joint Committee on Performance Measures liaison
| | | | | | | | | | - Kazuhiko Kido
- American College of Clinical Pharmacy representative
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10
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Joglar JA, Chung MK, Armbruster AL, Benjamin EJ, Chyou JY, Cronin EM, Deswal A, Eckhardt LL, Goldberger ZD, Gopinathannair R, Gorenek B, Hess PL, Hlatky M, Hogan G, Ibeh C, Indik JH, Kido K, Kusumoto F, Link MS, Linta KT, Marcus GM, McCarthy PM, Patel N, Patton KK, Perez MV, Piccini JP, Russo AM, Sanders P, Streur MM, Thomas KL, Times S, Tisdale JE, Valente AM, Van Wagoner DR. 2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. J Am Coll Cardiol 2024; 83:109-279. [PMID: 38043043 PMCID: PMC11104284 DOI: 10.1016/j.jacc.2023.08.017] [Citation(s) in RCA: 66] [Impact Index Per Article: 66.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/04/2023]
Abstract
AIM The "2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Patients With Atrial Fibrillation" provides recommendations to guide clinicians in the treatment of patients with atrial fibrillation. METHODS A comprehensive literature search was conducted from May 12, 2022, to November 3, 2022, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Library, the Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. Additional relevant studies, published through November 2022, during the guideline writing process, were also considered by the writing committee and added to the evidence tables, where appropriate. STRUCTURE Atrial fibrillation is the most sustained common arrhythmia, and its incidence and prevalence are increasing in the United States and globally. Recommendations from the "2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" and the "2019 AHA/ACC/HRS Focused Update of the 2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" have been updated with new evidence to guide clinicians. In addition, new recommendations addressing atrial fibrillation and thromboembolic risk assessment, anticoagulation, left atrial appendage occlusion, atrial fibrillation catheter or surgical ablation, and risk factor modification and atrial fibrillation prevention have been developed.
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11
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Wang X, Qi M, Zhang H, Yang Y, Zhao H. Genome-wide association and Mendelian randomization analysis provide insights into the shared genetic architecture between high-dimensional electrocardiographic features and ischemic heart disease. Hum Genet 2024; 143:49-58. [PMID: 38180560 DOI: 10.1007/s00439-023-02614-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Accepted: 10/27/2023] [Indexed: 01/06/2024]
Abstract
Observational studies have revealed that ischemic heart disease (IHD) has a unique manifestation on electrocardiographic (ECG). However, the genetic relationships between IHD and ECG remain unclear. We took 12-lead ECG as phenotypes to conduct genome-wide association studies (GWAS) for 41,960 samples from UK-Biobank (UKB). By leveraging large-scale GWAS summary of ECG and IHD (downloaded from FinnGen database), we performed LD score regression (LDSC), Mendelian randomization (MR), and polygenic risk score (PRS) regression to explore genetic relationships between IHD and ECG. Finally, we constructed an XGBoost model to predict IHD by integrating PRS and ECG. The GWAS identified 114 independent SNPs significantly (P value < 5 × 10-8/800, where 800 denotes the number of ECG features) associated with ECG. LDSC analysis indicated significant (P value < 0.05) genetic correlations between 39 ECG features and IHD. MR analysis performed by five approaches showed a putative causal effect of IHD on four S wave related ECG features at lead III. Integrating PRS for these ECG features with age and gender, the XGBoost model achieved Area Under Curve (AUC) 0.72 in predicting IHD. Here, we provide genetic evidence supporting S wave related ECG features at lead III to monitor the IHD risk, and open up a unique approach to integrate ECG with genetic factors for pre-warning IHD.
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Affiliation(s)
- Xinfeng Wang
- College of Computer Science and Engineering, Jishou University, Jishou, China
- Department of Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, 107 Yan Jiang West Road, Guangzhou, 500001, People's Republic of China
- Key Laboratory of Machine Intelligence and Advanced Computing of MOE, Guangzhou, China
| | - Mengling Qi
- Department of Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, 107 Yan Jiang West Road, Guangzhou, 500001, People's Republic of China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangzhou, China
| | - Haoyang Zhang
- School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou, China
| | - Yuedong Yang
- School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou, China
| | - Huiying Zhao
- Department of Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, 107 Yan Jiang West Road, Guangzhou, 500001, People's Republic of China.
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangzhou, China.
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12
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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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13
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Ahles A, Engelhardt S. Genetic Variants of Adrenoceptors. Handb Exp Pharmacol 2023. [PMID: 37578621 DOI: 10.1007/164_2023_676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Adrenoceptors are class A G-protein-coupled receptors grouped into three families (α1-, α2-, and β-adrenoceptors), each one including three members. All nine corresponding adrenoceptor genes display genetic variation in their coding and adjacent non-coding genomic region. Coding variants, i.e., nucleotide exchanges within the transcribed and translated receptor sequence, may result in a difference in amino acid sequence thus altering receptor function and signaling. Such variants have been intensely studied in vitro in overexpression systems and addressed in candidate-gene studies for distinct clinical parameters. In recent years, large cohorts were analyzed in genome-wide association studies (GWAS), where variants are detected as significant in context with specific traits. These studies identified two of the in-depth characterized 18 coding variants in adrenoceptors as repeatedly statistically significant genetic risk factors - p.Arg389Gly in the β1- and p.Thr164Ile in the β2-adrenoceptor, along with 56 variants in the non-coding regions adjacent to the adrenoceptor gene loci, the functional role of which is largely unknown at present. This chapter summarizes current knowledge on the two coding variants in adrenoceptors that have been consistently validated in GWAS and provides a prospective overview on the numerous non-coding variants more recently attributed to adrenoceptor gene loci.
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Affiliation(s)
- Andrea Ahles
- Institute of Pharmacology and Toxicology, Technical University of Munich (TUM), Munich, Germany
| | - Stefan Engelhardt
- Institute of Pharmacology and Toxicology, Technical University of Munich (TUM), Munich, Germany.
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany.
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14
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Wang Q, Liang X, Shang S, Fan Y, Lv H, Tang B, Lu Y. Desmosomal Junctions and Connexin-43 Remodeling in High-Pacing-Induced Heart Failure Dogs. Anatol J Cardiol 2023; 27:462-471. [PMID: 37288855 PMCID: PMC10406148 DOI: 10.14744/anatoljcardiol.2023.2823] [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: 11/26/2022] [Accepted: 03/22/2023] [Indexed: 06/09/2023] Open
Abstract
BACKGROUND While desmosomal junctions and gap junction remodeling are among the arrhythmogenic substrates, the fate of desmosomal and gap junctions in high-pacing-induced heart failure remains unclear. This aim of this study was to determine the fate of desmosomal junctions in high-pacing-induced heart failure. METHODS Dogs were randomly divided into 2 equal groups, a high-pacing-induced heart failure model group (heart failure group, n = 6) and a sham operation group (control group, n = 6). Echocardiography and cardiac electrophysiological examination were performed. Cardiac tissue was analyzed by immunofluorescence and transmission electron microscopy. The expression of desmoplakin and desmoglein-2 proteins was detected by western blot. RESULTS A significant decrease in ejection fraction, significant cardiac dilatation, diastolic and systolic dysfunction, and ventricular thinning occurred after 4 weeks in high-pacing-induced dog model of heart failure. Effective refractory period action potential duration at 90% repolarization was prolonged in the heart failure group. Immunofluorescence analysis and transmission electron microscopy demonstrated connexin-43 lateralization accompanies desmoglein-2 and desmoplakin remodeling in the heart failure group. Western blotting showed that the expression of desmoplakin and desmoglein-2 proteins was higher in heart failure than in normal tissue. CONCLUSION Desmosome (desmoglein-2 and desmoplakin) redistribution and desmosome (desmoglein-2) overexpression accompanying connexin-43 lateralization were parts of a complex remodeling in high-pacing-induced heart failure.
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Affiliation(s)
- Qing Wang
- Department of Pacing and Electrophysiology, The First Affiliated Hospital of Xinjiang Medical University, Xinjiang, China
- Xinjiang Key Laboratory of Cardiac Electrophysiology and Cardiac Remodeling, The First Affiliated Hospital of Xinjiang Medical University, Xinjiang, China
| | - Xiaoyan Liang
- Department of Pacing and Electrophysiology, The First Affiliated Hospital of Xinjiang Medical University, Xinjiang, China
- Xinjiang Key Laboratory of Cardiac Electrophysiology and Cardiac Remodeling, The First Affiliated Hospital of Xinjiang Medical University, Xinjiang, China
| | - Shuai Shang
- Department of Pacing and Electrophysiology, The First Affiliated Hospital of Xinjiang Medical University, Xinjiang, China
- Xinjiang Key Laboratory of Cardiac Electrophysiology and Cardiac Remodeling, The First Affiliated Hospital of Xinjiang Medical University, Xinjiang, China
| | - Yongqiang Fan
- Department of Pacing and Electrophysiology, The First Affiliated Hospital of Xinjiang Medical University, Xinjiang, China
- Xinjiang Key Laboratory of Cardiac Electrophysiology and Cardiac Remodeling, The First Affiliated Hospital of Xinjiang Medical University, Xinjiang, China
| | - Huasheng Lv
- Department of Pacing and Electrophysiology, The First Affiliated Hospital of Xinjiang Medical University, Xinjiang, China
- Xinjiang Key Laboratory of Cardiac Electrophysiology and Cardiac Remodeling, The First Affiliated Hospital of Xinjiang Medical University, Xinjiang, China
| | - Baopeng Tang
- Department of Pacing and Electrophysiology, The First Affiliated Hospital of Xinjiang Medical University, Xinjiang, China
- Xinjiang Key Laboratory of Cardiac Electrophysiology and Cardiac Remodeling, The First Affiliated Hospital of Xinjiang Medical University, Xinjiang, China
| | - Yanmei Lu
- Department of Pacing and Electrophysiology, The First Affiliated Hospital of Xinjiang Medical University, Xinjiang, China
- Xinjiang Key Laboratory of Cardiac Electrophysiology and Cardiac Remodeling, The First Affiliated Hospital of Xinjiang Medical University, Xinjiang, China
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15
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Lake J, Warly Solsberg C, Kim JJ, Acosta-Uribe J, Makarious MB, Li Z, Levine K, Heutink P, Alvarado CX, Vitale D, Kang S, Gim J, Lee KH, Pina-Escudero SD, Ferrucci L, Singleton AB, Blauwendraat C, Nalls MA, Yokoyama JS, Leonard HL. Multi-ancestry meta-analysis and fine-mapping in Alzheimer's disease. Mol Psychiatry 2023; 28:3121-3132. [PMID: 37198259 PMCID: PMC10615750 DOI: 10.1038/s41380-023-02089-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 03/27/2023] [Accepted: 03/31/2023] [Indexed: 05/19/2023]
Abstract
Genome-wide association studies (GWAS) of Alzheimer's disease are predominantly carried out in European ancestry individuals despite the known variation in genetic architecture and disease prevalence across global populations. We leveraged published GWAS summary statistics from European, East Asian, and African American populations, and an additional GWAS from a Caribbean Hispanic population using previously reported genotype data to perform the largest multi-ancestry GWAS meta-analysis of Alzheimer's disease and related dementias to date. This method allowed us to identify two independent novel disease-associated loci on chromosome 3. We also leveraged diverse haplotype structures to fine-map nine loci with a posterior probability >0.8 and globally assessed the heterogeneity of known risk factors across populations. Additionally, we compared the generalizability of multi-ancestry- and single-ancestry-derived polygenic risk scores in a three-way admixed Colombian population. Our findings highlight the importance of multi-ancestry representation in uncovering and understanding putative factors that contribute to risk of Alzheimer's disease and related dementias.
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Affiliation(s)
- Julie Lake
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Caroline Warly Solsberg
- Pharmaceutical Sciences and Pharmacogenomics, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
| | - Jonggeol Jeffrey Kim
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Preventive Neurology Unit, Centre for Prevention Diagnosis and Detection, Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | - Juliana Acosta-Uribe
- Neuroscience Research Institute and the department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA, USA
- Neuroscience Group of Antioquia, University of Antioquia, Medellín, Colombia
| | - Mary B Makarious
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK
- UCL Movement Disorders Centre, University College London, London, UK
| | - Zizheng Li
- Pharmaceutical Sciences and Pharmacogenomics, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Kristin Levine
- Data Tecnica International LLC, Washington, DC, USA
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
| | - Peter Heutink
- Alector, Inc. 131 Oyster Point Blvd, Suite 600, South San Francisco, CA, 94080, USA
| | - Chelsea X Alvarado
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International LLC, Washington, DC, USA
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
| | - Dan Vitale
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International LLC, Washington, DC, USA
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
| | - Sarang Kang
- Gwangju Alzheimer's disease and Related Dementia Cohort Research Center, Chosun University, Gwangju, 61452, Korea
- BK FOUR Department of Integrative Biological Sciences, Chosun University, Gwangju, 61452, Korea
| | - Jungsoo Gim
- Gwangju Alzheimer's disease and Related Dementia Cohort Research Center, Chosun University, Gwangju, 61452, Korea
- BK FOUR Department of Integrative Biological Sciences, Chosun University, Gwangju, 61452, Korea
- Department of Biomedical Science, Chosun University, Gwangju, 61452, Korea
| | - Kun Ho Lee
- Gwangju Alzheimer's disease and Related Dementia Cohort Research Center, Chosun University, Gwangju, 61452, Korea
- BK FOUR Department of Integrative Biological Sciences, Chosun University, Gwangju, 61452, Korea
- Department of Biomedical Science, Chosun University, Gwangju, 61452, Korea
- Korea Brain Research Institute, Daegu, 41062, Korea
| | - Stefanie D Pina-Escudero
- Pharmaceutical Sciences and Pharmacogenomics, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
| | - Luigi Ferrucci
- Longitudinal Studies Section, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Andrew B Singleton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
| | - Cornelis Blauwendraat
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
- Integrative Neurogenomics Unit, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International LLC, Washington, DC, USA
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
| | - Jennifer S Yokoyama
- Pharmaceutical Sciences and Pharmacogenomics, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Hampton L Leonard
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.
- Data Tecnica International LLC, Washington, DC, USA.
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA.
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany.
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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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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: 42] [Impact Index Per Article: 42.0] [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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18
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Kukshal P, Joshi RO, Kumar A, Ahamad S, Murthy PR, Sathe Y, Manohar K, Guhathakurta S, Chellappan S. Case-control association study of congenital heart disease from a tertiary paediatric cardiac centre from North India. BMC Pediatr 2023; 23:290. [PMID: 37322441 PMCID: PMC10268439 DOI: 10.1186/s12887-023-04095-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 05/27/2023] [Indexed: 06/17/2023] Open
Abstract
BACKGROUND Congenital Heart diseases (CHDs) account for 1/3rd of all congenital birth defects. Etiopathogenesis of CHDs remain elusive despite extensive investigations globally. Phenotypic heterogeneity witnessed in this developmental disorder reiterate gene-environment interactions with periconceptional factors as risk conferring; and genetic analysis of both sporadic and familial forms of CHD suggest its multigenic basis. Significant association of de novo and inherited variants have been observed. Approximately 1/5th of CHDs are documented in the ethnically distinct Indian population but genetic insights have been very limited. This pilot case-control based association study was undertaken to investigate the status of Caucasian SNPs in a north Indian cohort. METHOD A total of 306 CHD cases sub-classified into n = 198 acyanotic and n = 108 cyanotic types were recruited from a dedicated tertiary paediatric cardiac centre in Palwal, Haryana. 23 SNPs primarily prioritized from Genome-wide association studies (GWAS) on Caucasians were genotyped using Agena MassARRAY Technology and test of association was performed with adequately numbered controls. RESULTS Fifty percent of the studied SNPs were substantially associated in either allelic, genotypic or sub-phenotype categories validating their strong correlation with disease manifestation. Of note, strongest allelic association was observed for rs73118372 in CRELD1 (p < 0.0001) on Chr3, rs28711516 in MYH6 (p = 0.00083) and rs735712 in MYH7 (p = 0.0009) both on Chr 14 and were also significantly associated with acyanotic, and cyanotic categories separately. rs28711516 (p = 0.003) and rs735712 (p = 0.002) also showed genotypic association. Strongest association was observed with rs735712(p = 0.003) in VSD and maximum association was observed for ASD sub-phenotypes. CONCLUSIONS Caucasian findings were partly replicated in the north Indian population. The findings suggest the contribution of genetic, environmental and sociodemographic factors, warranting continued investigations in this study population.
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Affiliation(s)
- Prachi Kukshal
- Sri Sathya Sai Sanjeevani Research Foundation, NH-2, Delhi-Mathura Highway, Baghola, Haryana, District Palwal, Pin- 121102, India.
| | - Radha O Joshi
- Present address Sri Sathya Sai Sanjeevani Research Foundation, Kharghar, Navi Mumbai- 410210, Maharashtra, India
| | - Ajay Kumar
- Sri Sathya Sai Sanjeevani Research Foundation, NH-2, Delhi-Mathura Highway, Baghola, Haryana, District Palwal, Pin- 121102, India
| | - Shadab Ahamad
- Sri Sathya Sai Sanjeevani Research Foundation, NH-2, Delhi-Mathura Highway, Baghola, Haryana, District Palwal, Pin- 121102, India
| | - Prabhatha Rashmi Murthy
- Sri Sathya Sai Sanjeevani Centre for Child Heart Care and Training in Paediatric Cardiac Skills, Navi Mumbai Maharashtra, India
| | - Yogesh Sathe
- Sri Sathya Sai Sanjeevani International Centre for Child Heart Care & Research, NH-2, Delhi-Mathura Highway, Baghola, District Palwal, Haryana, Pin 121102, India
| | - Krishna Manohar
- Sri Sathya Sai Sanjeevani International Centre for Child Heart Care & Research, NH-2, Delhi-Mathura Highway, Baghola, District Palwal, Haryana, Pin 121102, India
| | - Soma Guhathakurta
- Sri Sathya Sai Sanjeevani Research Foundation, NH-2, Delhi-Mathura Highway, Baghola, Haryana, District Palwal, Pin- 121102, India
| | - Subramanian Chellappan
- Sri Sathya Sai Sanjeevani International Centre for Child Heart Care & Research, NH-2, Delhi-Mathura Highway, Baghola, District Palwal, Haryana, Pin 121102, India.
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19
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Treur JL, Thijssen AB, Smit DJ, Tadros R, Veeneman RR, Denys D, Vermeulen JM, Barc J, Bergstedt J, Pasman JA, Bezzina CR, Verweij KJH. Associations of schizophrenia with arrhythmic disorders and electrocardiogram traits: an in-depth genetic exploration of population samples. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.21.23290286. [PMID: 37292618 PMCID: PMC10246121 DOI: 10.1101/2023.05.21.23290286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Background An important contributor to the decreased life expectancy of individuals with schizophrenia is sudden cardiac death. While arrhythmic disorders play an important role in this, the nature of the relation between schizophrenia and arrhythmia is not fully understood. Methods We leveraged summary-level data of large-scale genome-wide association studies of schizophrenia (53,386 cases 77,258 controls), arrhythmic disorders (atrial fibrillation, 55,114 cases 482,295 controls; Brugada syndrome, 2,820 cases 10,001 controls) and electrocardiogram traits (heart rate (variability), PR interval, QT interval, JT interval, and QRS duration, n=46,952-293,051). First, we examined shared genetic liability by assessing global and local genetic correlations and conducting functional annotation. Next, we explored bidirectional causal relations between schizophrenia and arrhythmic disorders and electrocardiogram traits using Mendelian randomization. Outcomes There was no evidence for global genetic correlations, except between schizophrenia and Brugada (rg=0·14, p=4·0E-04). In contrast, strong positive and negative local genetic correlations between schizophrenia and all cardiac traits were found across the genome. In the strongest associated regions, genes related to immune system and viral response mechanisms were overrepresented. Mendelian randomization indicated a causal, increasing effect of liability to schizophrenia on Brugada syndrome (OR=1·15, p=0·009) and heart rate during activity (beta=0·25, p=0·015). Interpretation While there was little evidence for global genetic correlations, specific genomic regions and biological pathways important for both schizophrenia and arrhythmic disorders and electrocardiogram traits emerged. The putative causal effect of liability to schizophrenia on Brugada warrants increased cardiac monitoring and potentially early medical intervention in patients with schizophrenia. Funding European Research Council Starting Grant.
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Affiliation(s)
- Jorien L Treur
- Genetic Epidemiology, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, the Netherlands
| | - Anaiïs B Thijssen
- Genetic Epidemiology, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, the Netherlands
| | - Dirk Ja Smit
- Genetic Epidemiology, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, the Netherlands
| | - Rafik Tadros
- Cardiovascular Genetics Center, Montreal Heart Institute, Faculty of Medicine, 5000 Rue Bélanger, Montréal, QC H1T 1C8, Canada
| | - Rada R Veeneman
- Genetic Epidemiology, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, the Netherlands
| | - Damiaan Denys
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, the Netherlands
| | - Jentien M Vermeulen
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, the Netherlands
| | - Julien Barc
- Université de Nantes, CHU Nantes, CNRS, INSERM, l'institut du thorax, 8 Quai Moncousu, 44007 Nantes, France
| | - Jacob Bergstedt
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Joëlle A Pasman
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 65 Stockholm, Sweden
| | - Connie R Bezzina
- Department of Experimental Cardiology, Heart Center, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands
| | - Karin J H Verweij
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, the Netherlands
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20
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Vukadinovic M, Kwan AC, Yuan V, Salerno M, Lee DC, Albert CM, Cheng S, Li D, Ouyang D, Clarke SL. Deep learning-enabled analysis of medical images identifies cardiac sphericity as an early marker of cardiomyopathy and related outcomes. MED 2023; 4:252-262.e3. [PMID: 36996817 PMCID: PMC10106428 DOI: 10.1016/j.medj.2023.02.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 01/02/2023] [Accepted: 02/15/2023] [Indexed: 03/31/2023]
Abstract
BACKGROUND Quantification of chamber size and systolic function is a fundamental component of cardiac imaging. However, the human heart is a complex structure with significant uncharacterized phenotypic variation beyond traditional metrics of size and function. Examining variation in cardiac shape can add to our ability to understand cardiovascular risk and pathophysiology. METHODS We measured the left ventricle (LV) sphericity index (short axis length/long axis length) using deep learning-enabled image segmentation of cardiac magnetic resonance imaging data from the UK Biobank. Subjects with abnormal LV size or systolic function were excluded. The relationship between LV sphericity and cardiomyopathy was assessed using Cox analyses, genome-wide association studies, and two-sample Mendelian randomization. FINDINGS In a cohort of 38,897 subjects, we show that a one standard deviation increase in sphericity index is associated with a 47% increased incidence of cardiomyopathy (hazard ratio [HR]: 1.47, 95% confidence interval [CI]: 1.10-1.98, p = 0.01) and a 20% increased incidence of atrial fibrillation (HR: 1.20, 95% CI: 1.11-1.28, p < 0.001), independent of clinical factors and traditional magnetic resonance imaging (MRI) measurements. We identify four loci associated with sphericity at genome-wide significance, and Mendelian randomization supports non-ischemic cardiomyopathy as causal for LV sphericity. CONCLUSIONS Variation in LV sphericity in otherwise normal hearts predicts risk for cardiomyopathy and related outcomes and is caused by non-ischemic cardiomyopathy. FUNDING This study was supported by grants K99-HL157421 (D.O.) and KL2TR003143 (S.L.C.) from the National Institutes of Health.
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Affiliation(s)
- Milos Vukadinovic
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA 90095, USA; Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Alan C Kwan
- Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Victoria Yuan
- School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Michael Salerno
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA 94306, USA
| | - Daniel C Lee
- Department of Medicine and Radiology, Northwestern Medicine, Chicago, IL 60611, USA
| | - Christine M Albert
- Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Susan Cheng
- Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Debiao Li
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - David Ouyang
- Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Division of Artificial Intelligence in Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
| | - Shoa L Clarke
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA 94306, USA.
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21
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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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22
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Khurshid S, Lazarte J, Pirruccello JP, Weng LC, Choi SH, Hall AW, Wang X, Friedman SF, Nauffal V, Biddinger KJ, Aragam KG, Batra P, Ho JE, Philippakis AA, Ellinor PT, Lubitz SA. Clinical and genetic associations of deep learning-derived cardiac magnetic resonance-based left ventricular mass. Nat Commun 2023; 14:1558. [PMID: 36944631 PMCID: PMC10030590 DOI: 10.1038/s41467-023-37173-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 03/04/2023] [Indexed: 03/23/2023] Open
Abstract
Left ventricular mass is a risk marker for cardiovascular events, and may indicate an underlying cardiomyopathy. Cardiac magnetic resonance is the gold-standard for left ventricular mass estimation, but is challenging to obtain at scale. Here, we use deep learning to enable genome-wide association study of cardiac magnetic resonance-derived left ventricular mass indexed to body surface area within 43,230 UK Biobank participants. We identify 12 genome-wide associations (1 known at TTN and 11 novel for left ventricular mass), implicating genes previously associated with cardiac contractility and cardiomyopathy. Cardiac magnetic resonance-derived indexed left ventricular mass is associated with incident dilated and hypertrophic cardiomyopathies, and implantable cardioverter-defibrillator implant. An indexed left ventricular mass polygenic risk score ≥90th percentile is also associated with incident implantable cardioverter-defibrillator implant in separate UK Biobank (hazard ratio 1.22, 95% CI 1.05-1.44) and Mass General Brigham (hazard ratio 1.75, 95% CI 1.12-2.74) samples. Here, we perform a genome-wide association study of cardiac magnetic resonance-derived indexed left ventricular mass to identify 11 novel variants and demonstrate that cardiac magnetic resonance-derived and genetically predicted indexed left ventricular mass are associated with incident cardiomyopathy.
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Affiliation(s)
- Shaan Khurshid
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA, USA
| | - Julieta Lazarte
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - James P Pirruccello
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA
| | - Lu-Chen Weng
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Seung Hoan Choi
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Amelia W Hall
- Gene Regulation Observatory, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Xin Wang
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Samuel F Friedman
- Data Sciences Platform, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Victor Nauffal
- Division of Cardiology, Brigham and Women's Hospital, Boston, MA, USA
| | - Kiran J Biddinger
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Krishna G Aragam
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA
| | - Puneet Batra
- Data Sciences Platform, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jennifer E Ho
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- CardioVascular Institute and Division of Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Anthony A Philippakis
- Data Sciences Platform, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Patrick T Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA, USA
| | - Steven A Lubitz
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA.
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA, USA.
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23
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Young WJ, Haessler J, Benjamins JW, Repetto L, Yao J, Isaacs A, Harper AR, Ramirez J, Garnier S, van Duijvenboden S, Baldassari AR, Concas MP, Duong T, Foco L, Isaksen JL, Mei H, Noordam R, Nursyifa C, Richmond A, Santolalla ML, Sitlani CM, Soroush N, Thériault S, Trompet S, Aeschbacher S, Ahmadizar F, Alonso A, Brody JA, Campbell A, Correa A, Darbar D, De Luca A, Deleuze JF, Ellervik C, Fuchsberger C, Goel A, Grace C, Guo X, Hansen T, Heckbert SR, Jackson RD, Kors JA, Lima-Costa MF, Linneberg A, Macfarlane PW, Morrison AC, Navarro P, Porteous DJ, Pramstaller PP, Reiner AP, Risch L, Schotten U, Shen X, Sinagra G, Soliman EZ, Stoll M, Tarazona-Santos E, Tinker A, Trajanoska K, Villard E, Warren HR, Whitsel EA, Wiggins KL, Arking DE, Avery CL, Conen D, Girotto G, Grarup N, Hayward C, Jukema JW, Mook-Kanamori DO, Olesen MS, Padmanabhan S, Psaty BM, Pattaro C, Ribeiro ALP, Rotter JI, Stricker BH, van der Harst P, van Duijn CM, Verweij N, Wilson JG, Orini M, Charron P, Watkins H, Kooperberg C, Lin HJ, Wilson JF, Kanters JK, Sotoodehnia N, Mifsud B, Lambiase PD, Tereshchenko LG, Munroe PB. Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease. Nat Commun 2023; 14:1411. [PMID: 36918541 PMCID: PMC10015012 DOI: 10.1038/s41467-023-36997-w] [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: 05/27/2022] [Accepted: 02/26/2023] [Indexed: 03/15/2023] Open
Abstract
The 3-dimensional spatial and 2-dimensional frontal QRS-T angles are measures derived from the vectorcardiogram. They are independent risk predictors for arrhythmia, but the underlying biology is unknown. Using multi-ancestry genome-wide association studies we identify 61 (58 previously unreported) loci for the spatial QRS-T angle (N = 118,780) and 11 for the frontal QRS-T angle (N = 159,715). Seven out of the 61 spatial QRS-T angle loci have not been reported for other electrocardiographic measures. Enrichments are observed in pathways related to cardiac and vascular development, muscle contraction, and hypertrophy. Pairwise genome-wide association studies with classical ECG traits identify shared genetic influences with PR interval and QRS duration. Phenome-wide scanning indicate associations with atrial fibrillation, atrioventricular block and arterial embolism and genetically determined QRS-T angle measures are associated with fascicular and bundle branch block (and also atrioventricular block for the frontal QRS-T angle). We identify potential biology involved in the QRS-T angle and their genetic relationships with cardiovascular traits and diseases, may inform future research and risk prediction.
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Affiliation(s)
- William J Young
- William Harvey Research Institute, Clinical Pharmacology, Queen Mary University of London, London, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS trust, London, UK
| | - Jeffrey Haessler
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Jan-Walter Benjamins
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Groningen, the Netherlands
| | - Linda Repetto
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland
| | - Jie Yao
- Institute for Translational Genomics and Population Sciences/The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Aaron Isaacs
- Dept. of Physiology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands
- Maastricht Center for Systems Biology (MaCSBio), Maastricht University, Maastricht, the Netherlands
| | - Andrew R Harper
- Radcliffe Department of Medicine, University of Oxford, Division of Cardiovascular Medicine, John Radcliffe Hospital, Oxford, UK
- Wellcome Centre for Human Genetics, Roosevelt Drive, Oxford, UK
| | - Julia Ramirez
- William Harvey Research Institute, Clinical Pharmacology, Queen Mary University of London, London, UK
- Institute of Cardiovascular Sciences, University of College London, London, UK
- Aragon Institute of Engineering Research, University of Zaragoza, Zaragoza, Spain and Center of Biomedical Research Network, Bioengineering, Biomaterials and Nanomedicine, Zaragoza, Spain
| | - Sophie Garnier
- Sorbonne Universite, INSERM, UMR-S1166, Research Unit on Cardiovascular Disorders, Metabolism and Nutrition, Team Genomics & Pathophysiology of Cardiovascular Disease, Paris, 75013, France
- ICAN Institute for Cardiometabolism and Nutrition, Paris, 75013, France
| | - Stefan van Duijvenboden
- William Harvey Research Institute, Clinical Pharmacology, Queen Mary University of London, London, UK
- Institute of Cardiovascular Sciences, University of College London, London, UK
| | - Antoine R Baldassari
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Maria Pina Concas
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, Italy
| | - ThuyVy Duong
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Luisa Foco
- Eurac Research, Institute for Biomedicine (affiliated with the University of Lübeck), Bolzano, Italy
| | - Jonas L Isaksen
- Laboratory of Experimental Cardiology, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Hao Mei
- Department of Data Science, University of Mississippi Medical Center, Jackson, MS, USA
| | - Raymond Noordam
- Department of Internal Medicine, section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Casia Nursyifa
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Anne Richmond
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, Scotland
| | - Meddly L Santolalla
- Department of Genetics, Ecology and Evolution, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
- Emerge, Emerging Diseases and Climate Change Research Unit, School of Public Health and Administration, Universidad Peruana Cayetano Heredia, Lima, 15152, Peru
| | - Colleen M Sitlani
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Negin Soroush
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Sébastien Thériault
- Population Health Research Institute, McMaster University, Hamilton, ON, Canada
- Department of Molecular Biology, Medical Biochemistry and Pathology, Université Laval, Quebec, QC, Canada
| | - Stella Trompet
- Department of Internal Medicine, section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Stefanie Aeschbacher
- Cardiovascular Research Institute Basel, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Fariba Ahmadizar
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Julius Global Health, University Utrecht Medical Center, Utrecht, the Netherlands
| | - Alvaro Alonso
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Archie Campbell
- Usher Institute, University of Edinburgh, Nine, Edinburgh Bioquarter, 9 Little France Road, Edinburgh, UK
- Health Data Research UK, University of Edinburgh, Nine, Edinburgh Bioquarter, 9 Little France Road, Edinburgh, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Adolfo Correa
- Departments of Medicine, Pediatrics and Population Health Science, University of Mississippi Medical Center, Jackson, MS, USA
| | - Dawood Darbar
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Antonio De Luca
- Cardiothoracovascular Department, Division of Cardiology, Azienda Sanitaria Universitaria Giuliano Isontina and University of Trieste, Trieste, Italy
| | - Jean-François Deleuze
- Université Paris-Saclay, CEA, Centre National de Recherche en Génomique Humaine (CNRGH), 91057, Evry, France
- Laboratory of Excellence GENMED (Medical Genomics), Paris, France
- Centre d'Etude du Polymorphisme Humain, Fondation Jean Dausset, Paris, France
| | - Christina Ellervik
- Department of Data and Data Support, Region Zealand, 4180, Sorø, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2100, Copenhagen, Denmark
- Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
| | - Christian Fuchsberger
- Eurac Research, Institute for Biomedicine (affiliated with the University of Lübeck), Bolzano, Italy
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Anuj Goel
- Radcliffe Department of Medicine, University of Oxford, Division of Cardiovascular Medicine, John Radcliffe Hospital, Oxford, UK
- Wellcome Centre for Human Genetics, Roosevelt Drive, Oxford, UK
| | - Christopher Grace
- Radcliffe Department of Medicine, University of Oxford, Division of Cardiovascular Medicine, John Radcliffe Hospital, Oxford, UK
- Wellcome Centre for Human Genetics, Roosevelt Drive, Oxford, UK
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences/The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
- Department of Pediatrics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Susan R Heckbert
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Rebecca D Jackson
- Center for Clinical and Translational Science, Ohio State Medical Center, Columbus, OH, USA
| | - Jan A Kors
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, the Netherlands
| | | | - Allan Linneberg
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, København, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Peter W Macfarlane
- Institute of Health and Wellbeing, School of Health and Wellbeing, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Pau Navarro
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, Scotland
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Peter P Pramstaller
- Eurac Research, Institute for Biomedicine (affiliated with the University of Lübeck), Bolzano, Italy
- Department of Neurology, University of Lübeck, Lübeck, Germany
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Fred Hutchinson Cancer Center, University of Washington, Seattle, WA, USA
| | - Lorenz Risch
- Labormedizinisches zentrum Dr. Risch, Vaduz, Liechtenstein
- Faculty of Medical Sciences, Private University in the Principality of Liechtenstein, Triesen, Liechtenstein
- Center of Laboratory Medicine, University Institute of Clinical Chemistry, University of Bern, Inselspital, Bern, Switzerland
| | - Ulrich Schotten
- Dept. of Physiology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands
| | - Xia Shen
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Nansha District, Guangzhou, China
| | - Gianfranco Sinagra
- Cardiothoracovascular Department, Division of Cardiology, Azienda Sanitaria Universitaria Giuliano Isontina and University of Trieste, Trieste, Italy
| | - Elsayed Z Soliman
- Epidemiological Cardiology Research Center (EPICARE), Wake Forest School of Medicine, Winston Salem, NC, USA
| | - Monika Stoll
- Maastricht Center for Systems Biology (MaCSBio), Maastricht University, Maastricht, the Netherlands
- Dept. of Biochemistry, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands
- Institute of Human Genetics, Genetic Epidemiology, University of Muenster, Muenster, Germany
| | - Eduardo Tarazona-Santos
- Department of Genetics, Ecology and Evolution, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Andrew Tinker
- William Harvey Research Institute, Clinical Pharmacology, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Katerina Trajanoska
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Eric Villard
- Sorbonne Universite, INSERM, UMR-S1166, Research Unit on Cardiovascular Disorders, Metabolism and Nutrition, Team Genomics & Pathophysiology of Cardiovascular Disease, Paris, 75013, France
- ICAN Institute for Cardiometabolism and Nutrition, Paris, 75013, France
| | - Helen R Warren
- William Harvey Research Institute, Clinical Pharmacology, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Kerri L Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Dan E Arking
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Christy L Avery
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - David Conen
- Population Health Research Institute, McMaster University, Hamilton, ON, Canada
| | - Giorgia Girotto
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, Italy
- Department of Medical, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Netherlands Heart Institute, Utrecht, the Netherlands
- Durrer Center for Cardiovascular Research, Amsterdam, the Netherlands
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands, Leiden, the Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands, Leiden, the Netherlands
| | | | - Sandosh Padmanabhan
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattte, WA, USA
| | - Cristian Pattaro
- Eurac Research, Institute for Biomedicine (affiliated with the University of Lübeck), Bolzano, Italy
| | - Antonio Luiz P Ribeiro
- Department of Internal Medicine, Faculdade de Medicina, Universidade Federal de Minas Gerais, Brazil, Belo Horizonte, Minas Gerais, Brazil
- Cardiology Service and Telehealth Center, Hospital das Clínicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil, Belo Horizonte, Minas Gerais, Brazil
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences/The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
- Departments of Pediatrics and Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Bruno H Stricker
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - 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
| | - Cornelia M van Duijn
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Niek Verweij
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Groningen, the Netherlands
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA
- Department of Cardiology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Michele Orini
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS trust, London, UK
- Institute of Cardiovascular Sciences, University of College London, London, UK
| | - Philippe Charron
- Sorbonne Universite, INSERM, UMR-S1166, Research Unit on Cardiovascular Disorders, Metabolism and Nutrition, Team Genomics & Pathophysiology of Cardiovascular Disease, Paris, 75013, France
- ICAN Institute for Cardiometabolism and Nutrition, Paris, 75013, France
- APHP, Cardiology Department, Pitié-Salpêtrière Hospital, Paris, 75013, France
- APHP, Département de Génétique, Centre de Référence Maladies Cardiaques Héréditaires, Pitié-Salpêtrière Hospital, Paris, 75013, France
| | - Hugh Watkins
- Radcliffe Department of Medicine, University of Oxford, Division of Cardiovascular Medicine, John Radcliffe Hospital, Oxford, UK
- Wellcome Centre for Human Genetics, Roosevelt Drive, Oxford, UK
| | - Charles Kooperberg
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Henry J Lin
- Institute for Translational Genomics and Population Sciences/The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
- Department of Pediatrics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, Scotland
| | - Jørgen K Kanters
- Laboratory of Experimental Cardiology, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Borbala Mifsud
- William Harvey Research Institute, Clinical Pharmacology, Queen Mary University of London, London, UK
- Genomics and Translational Biomedicine, College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
| | - Pier D Lambiase
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS trust, London, UK
- Institute of Cardiovascular Sciences, University of College London, London, UK
| | - Larisa G Tereshchenko
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA.
- Department of Medicine, Cardiovascular Division, Johns Hopkins University, School of Medicine, Baltimore, MD, USA.
| | - Patricia B Munroe
- William Harvey Research Institute, Clinical Pharmacology, Queen Mary University of London, London, UK.
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
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24
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Tsao CW, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Beaton AZ, Boehme AK, Buxton AE, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Fugar S, Generoso G, Heard DG, Hiremath S, Ho JE, Kalani R, Kazi DS, Ko D, Levine DA, Liu J, Ma J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Virani SS, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association. Circulation 2023; 147:e93-e621. [PMID: 36695182 DOI: 10.1161/cir.0000000000001123] [Citation(s) in RCA: 1250] [Impact Index Per Article: 1250.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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25
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Cunningham JW, Di Achille P, Morrill VN, Weng LC, Hoan Choi S, Khurshid S, Nauffal V, Pirruccello JP, Solomon SD, Batra P, Ho JE, Philippakis AA, Ellinor PT, Lubitz SA. Machine Learning to Understand Genetic and Clinical Factors Associated With the Pulse Waveform Dicrotic Notch. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2023; 16:e003676. [PMID: 36580284 PMCID: PMC9975074 DOI: 10.1161/circgen.121.003676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Accepted: 09/30/2022] [Indexed: 12/30/2022]
Abstract
BACKGROUND Absence of a dicrotic notch on finger photoplethysmography is an easily ascertainable and inexpensive trait that has been associated with age and prevalent cardiovascular disease. However, the trait exists along a continuum, and little is known about its genetic underpinnings or prognostic value for incident cardiovascular disease. METHODS In 169 787 participants in the UK Biobank, we identified absent dicrotic notch on photoplethysmography and created a novel continuous trait reflecting notch smoothness using machine learning. Next, we determined the heritability, genetic basis, polygenic risk, and clinical relations for the binary absent notch trait and the newly derived continuous notch smoothness trait. RESULTS Heritability of the continuous notch smoothness trait was 7.5%, compared with 5.6% for the binary absent notch trait. A genome-wide association study of notch smoothness identified 15 significant loci, implicating genes including NT5C2 (P=1.2×10-26), IGFBP3 (P=4.8×10-18), and PHACTR1 (P=1.4×10-13), compared with 6 loci for the binary absent notch trait. Notch smoothness stratified risk of incident myocardial infarction or coronary artery disease, stroke, heart failure, and aortic stenosis. A polygenic risk score for notch smoothness was associated with incident cardiovascular disease and all-cause death in UK Biobank participants without available photoplethysmography data. CONCLUSIONS We found that a machine learning derived continuous trait reflecting dicrotic notch smoothness on photoplethysmography was heritable and associated with genes involved in vascular stiffness. Greater notch smoothness was associated with greater risk of incident cardiovascular disease. Raw digital phenotyping may identify individuals at risk for disease via specific genetic pathways.
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Affiliation(s)
- Jonathan W. Cunningham
- Cardiovascular Division, Brigham & Women’s Hospital, Boston
- Cardiovascular Disease Initiative, The Broad Institute of MIT & Harvard, Cambridge
| | - Paolo Di Achille
- Data Sciences Platform, The Broad Institute of MIT & Harvard, Cambridge
| | - Valerie N. Morrill
- Cardiovascular Disease Initiative, The Broad Institute of MIT & Harvard, Cambridge
| | - Lu-Chen Weng
- Cardiovascular Disease Initiative, The Broad Institute of MIT & Harvard, Cambridge
- Cardiovascular Research Center, Massachusetts General Hospital
| | - Seung Hoan Choi
- Cardiovascular Disease Initiative, The Broad Institute of MIT & Harvard, Cambridge
| | - Shaan Khurshid
- Cardiovascular Disease Initiative, The Broad Institute of MIT & Harvard, Cambridge
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital
| | - Victor Nauffal
- Cardiovascular Division, Brigham & Women’s Hospital, Boston
- Cardiovascular Disease Initiative, The Broad Institute of MIT & Harvard, Cambridge
| | - James P Pirruccello
- Cardiovascular Disease Initiative, The Broad Institute of MIT & Harvard, Cambridge
- Division of Cardiology, Massachusetts General Hospital
| | | | - Puneet Batra
- Data Sciences Platform, The Broad Institute of MIT & Harvard, Cambridge
| | - Jennifer E. Ho
- Cardiovascular Disease Initiative, The Broad Institute of MIT & Harvard, Cambridge
- CardioVascular Institute and Division of Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | | | - Patrick T. Ellinor
- Cardiovascular Disease Initiative, The Broad Institute of MIT & Harvard, Cambridge
- Cardiovascular Research Center, Massachusetts General Hospital
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital
| | - Steven A. Lubitz
- Cardiovascular Disease Initiative, The Broad Institute of MIT & Harvard, Cambridge
- Cardiovascular Research Center, Massachusetts General Hospital
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital
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26
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Libiseller-Egger J, Phelan JE, Attia ZI, Benavente ED, Campino S, Friedman PA, Lopez-Jimenez F, Leon DA, Clark TG. Deep learning-derived cardiovascular age shares a genetic basis with other cardiac phenotypes. Sci Rep 2022; 12:22625. [PMID: 36587059 PMCID: PMC9805465 DOI: 10.1038/s41598-022-27254-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 12/28/2022] [Indexed: 01/01/2023] Open
Abstract
Artificial intelligence (AI)-based approaches can now use electrocardiograms (ECGs) to provide expert-level performance in detecting heart abnormalities and diagnosing disease. Additionally, patient age predicted from ECGs by AI models has shown great potential as a biomarker for cardiovascular age, where recent work has found its deviation from chronological age ("delta age") to be associated with mortality and co-morbidities. However, despite being crucial for understanding underlying individual risk, the genetic underpinning of delta age is unknown. In this work we performed a genome-wide association study using UK Biobank data (n=34,432) and identified eight loci associated with delta age ([Formula: see text]), including genes linked to cardiovascular disease (CVD) (e.g. SCN5A) and (heart) muscle development (e.g. TTN). Our results indicate that the genetic basis of cardiovascular ageing is predominantly determined by genes directly involved with the cardiovascular system rather than those connected to more general mechanisms of ageing. Our insights inform the epidemiology of CVD, with implications for preventative and precision medicine.
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Affiliation(s)
- Julian Libiseller-Egger
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK
| | - Jody E Phelan
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK
| | - Zachi I Attia
- Department of Cardiovascular Medicine, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Ernest Diez Benavente
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK
- Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Susana Campino
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK
| | - Paul A Friedman
- Department of Cardiovascular Medicine, Mayo Clinic College of Medicine, Rochester, MN, USA
| | | | - David A Leon
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
- Department of Community Medicine, UiT the Arctic University of Norway, Tromsø, Norway
| | - Taane G Clark
- Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK.
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.
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27
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Hoffmann TJ, Lu M, Oni-Orisan A, Lee C, Risch N, Iribarren C. A large genome-wide association study of QT interval length utilizing electronic health records. Genetics 2022; 222:iyac157. [PMID: 36271874 PMCID: PMC9713425 DOI: 10.1093/genetics/iyac157] [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: 07/09/2022] [Accepted: 09/22/2022] [Indexed: 12/13/2022] Open
Abstract
QT interval length is an important risk factor for adverse cardiovascular outcomes; however, the genetic architecture of QT interval remains incompletely understood. We conducted a genome-wide association study of 76,995 ancestrally diverse Kaiser Permanente Northern California members enrolled in the Genetic Epidemiology Research on Adult Health and Aging cohort using 448,517 longitudinal QT interval measurements, uncovering 9 novel variants, most replicating in 40,537 individuals in the UK Biobank and Population Architecture using Genomics and Epidemiology studies. A meta-analysis of all 3 cohorts (n = 117,532) uncovered an additional 19 novel variants. Conditional analysis identified 15 additional variants, 3 of which were novel. Little, if any, difference was seen when adjusting for putative QT interval lengthening medications genome-wide. Using multiple measurements in Genetic Epidemiology Research on Adult Health and Aging increased variance explained by 163%, and we show that the ≈6 measurements in Genetic Epidemiology Research on Adult Health and Aging was equivalent to a 2.4× increase in sample size of a design with a single measurement. The array heritability was estimated at ≈17%, approximately half of our estimate of 36% from family correlations. Heritability enrichment was estimated highest and most significant in cardiovascular tissue (enrichment 7.2, 95% CI = 5.7-8.7, P = 2.1e-10), and many of the novel variants included expression quantitative trait loci in heart and other relevant tissues. Comparing our results to other cardiac function traits, it appears that QT interval has a multifactorial genetic etiology.
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Affiliation(s)
- Thomas J Hoffmann
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94143, USA
| | - Meng Lu
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
| | - Akinyemi Oni-Orisan
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Clinical Pharmacy, University of California San Francisco, San Francisco, CA 94143, USA
| | - Catherine Lee
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
| | - Neil Risch
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94143, USA
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
| | - Carlos Iribarren
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
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28
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Ramírez J, van Duijvenboden S, Young WJ, Tinker A, Lambiase PD, Orini M, Munroe PB. Prediction of Coronary Artery Disease and Major Adverse Cardiovascular Events Using Clinical and Genetic Risk Scores for Cardiovascular Risk Factors. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2022; 15:e003441. [PMID: 35861959 PMCID: PMC9584057 DOI: 10.1161/circgen.121.003441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
BACKGROUND Coronary artery disease (CAD) and major adverse cardiovascular events (MACE) are the leading causes of death in the general population, but risk stratification remains suboptimal. CAD genetic risk scores (GRSs) predict risk independently from clinical tools, like QRISK3. We assessed the added value of GRSs for a variety of cardiovascular traits (CV GRSs) for predicting CAD and MACE and tested their early-life screening potential by comparing against the CAD GRS only. METHODS We used data from 379 581 participants in the UK Biobank without known cardiovascular conditions (follow-up, 11.3 years; 3.3% CAD cases and 5.2% MACE cases). In a training subset (50%) we built 3 scores: QRISK3; QRISK3 and an established CAD GRS; and QRISK3, the CAD GRS and the CV GRSs. In an independent subset (50%), we evaluated each score's performance using the concordance index, odds ratio and net reclassification index. We then repeated the analyses without considering QRISK3. RESULTS For CAD, the combination of QRISK3 and the CAD GRS had a better performance than QRISK3 alone (concordance index, 0.766 versus 0.753; odds ratio, 5.47 versus 4.82; net reclassification index, 7.7%). Adding the CV GRSs did not significantly improve risk stratification. When only looking at genetic information, the combination of CV GRSs and the CAD GRS had a better performance than the CAD GRS alone (concordance index, 0.637 versus 0.625; odds ratio, 2.17 versus 2.07; net reclassification index, 3.3%). Similar results were obtained for MACE. CONCLUSIONS In individuals without known cardiovascular disease, the inclusion of CV GRSs to a clinical tool and an established CAD GRS does not improve CAD or MACE risk stratification. However, their combination only with the CAD GRS increases prediction performance indicating potential use in early-life screening before the advanced development of conventional cardiovascular risk factors.
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Affiliation(s)
- Julia Ramírez
- Clinical Pharmacology and Precision Medicine Deparment, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom (J.R., S.v.D., W.J.Y., A.T., P.B.M.).,Electronic Engineering and Communications Department, Aragon Institute of Engineering Research, University of Zaragoza, Spain and CIBER's Bioengineering, Biomaterials and Nanomedicine, Spain. (J.R.)
| | - Stefan van Duijvenboden
- Clinical Pharmacology and Precision Medicine Deparment, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom (J.R., S.v.D., W.J.Y., A.T., P.B.M.).,Institute of Cardiovascular Science, University College London, London, United Kingdom (S.v.D., P.D.L., M.O.)
| | - William J Young
- Clinical Pharmacology and Precision Medicine Deparment, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom (J.R., S.v.D., W.J.Y., A.T., P.B.M.).,Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom (W.J.Y., P.D.L., M.O.)
| | - Andrew Tinker
- Clinical Pharmacology and Precision Medicine Deparment, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom (J.R., S.v.D., W.J.Y., A.T., P.B.M.).,NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom (A.T., P.B.M.)
| | - Pier D Lambiase
- Institute of Cardiovascular Science, University College London, London, United Kingdom (S.v.D., P.D.L., M.O.).,Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom (W.J.Y., P.D.L., M.O.)
| | - Michele Orini
- Institute of Cardiovascular Science, University College London, London, United Kingdom (S.v.D., P.D.L., M.O.).,Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom (W.J.Y., P.D.L., M.O.)
| | - Patricia B Munroe
- Clinical Pharmacology and Precision Medicine Deparment, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom (J.R., S.v.D., W.J.Y., A.T., P.B.M.).,NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom (A.T., P.B.M.)
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29
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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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30
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McLendon JM, Zhang X, Matasic DS, Kumar M, Koval OM, Grumbach IM, Sadayappan S, London B, Boudreau RL. Knockout of Sorbin And SH3 Domain Containing 2 (Sorbs2) in Cardiomyocytes Leads to Dilated Cardiomyopathy in Mice. J Am Heart Assoc 2022; 11:e025687. [PMID: 35730644 PMCID: PMC9333371 DOI: 10.1161/jaha.122.025687] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Background Sorbin and SH3 domain containing 2 (Sorbs2) protein is a cytoskeletal adaptor with an emerging role in cardiac biology and disease; yet, its potential relevance to adult‐onset cardiomyopathies remains underexplored. Sorbs2 global knockout mice display lethal arrhythmogenic cardiomyopathy; however, the causative mechanisms remain unclear. Herein, we examine Sorbs2 dysregulation in heart failure, characterize novel Sorbs2 cardiomyocyte‐specific knockout mice (Sorbs2‐cKO), and explore associations between Sorbs2 genetic variations and human cardiovascular disease. Methods and Results Bioinformatic analyses show myocardial Sorbs2 mRNA is consistently upregulated in humans with adult‐onset cardiomyopathies and in heart failure models. We generated Sorbs2‐cKO mice and report that they develop progressive systolic dysfunction and enlarged cardiac chambers, and they die with congestive heart failure at about 1 year old. After 3 months, Sorbs2‐cKO mice begin to show atrial enlargement and P‐wave anomalies, without dysregulation of action potential–associated ion channel and gap junction protein expressions. After 6 months, Sorbs2‐cKO mice exhibit impaired contractility in dobutamine‐treated hearts and skinned myofibers, without dysregulation of contractile protein expressions. From our comprehensive survey of potential mechanisms, we found that within 4 months, Sorbs2‐cKO hearts have defective microtubule polymerization and compensatory upregulation of structural cytoskeletal and adapter proteins, suggesting that this early intracellular structural remodeling is responsible for contractile dysfunction. Finally, we identified genetic variants that associate with decreased Sorbs2 expression and human cardiac phenotypes, including conduction abnormalities, atrial enlargement, and dilated cardiomyopathy, consistent with Sorbs2‐cKO mice phenotypes. Conclusions Our studies show that Sorbs2 is essential for maintaining structural integrity in cardiomyocytes, likely through strengthening the interactions between microtubules and other cytoskeletal proteins at cross‐link sites.
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Affiliation(s)
- Jared M McLendon
- Department of Internal Medicine University of Iowa Carver College of Medicine Iowa City IA.,Abboud Cardiovascular Research Center University of Iowa Carver College of Medicine Iowa City IA
| | - Xiaoming Zhang
- Department of Internal Medicine University of Iowa Carver College of Medicine Iowa City IA.,Abboud Cardiovascular Research Center University of Iowa Carver College of Medicine Iowa City IA
| | - Daniel S Matasic
- Department of Internal Medicine University of Iowa Carver College of Medicine Iowa City IA.,Department of Molecular Physiology and Biophysics University of Iowa Carver College of Medicine Iowa City IA
| | - Mohit Kumar
- Department of Pharmacology and Systems Physiology University of Cincinnati OH.,Division of Cardiovascular Health and Disease Department of Internal Medicine Heart, Lung, and Vascular Institute University of Cincinnati OH
| | - Olha M Koval
- Department of Internal Medicine University of Iowa Carver College of Medicine Iowa City IA.,Abboud Cardiovascular Research Center University of Iowa Carver College of Medicine Iowa City IA
| | - Isabella M Grumbach
- Department of Internal Medicine University of Iowa Carver College of Medicine Iowa City IA.,Abboud Cardiovascular Research Center University of Iowa Carver College of Medicine Iowa City IA
| | - Sakthivel Sadayappan
- Department of Pharmacology and Systems Physiology University of Cincinnati OH.,Division of Cardiovascular Health and Disease Department of Internal Medicine Heart, Lung, and Vascular Institute University of Cincinnati OH
| | - Barry London
- Department of Internal Medicine University of Iowa Carver College of Medicine Iowa City IA.,Abboud Cardiovascular Research Center University of Iowa Carver College of Medicine Iowa City IA
| | - Ryan L Boudreau
- Department of Internal Medicine University of Iowa Carver College of Medicine Iowa City IA.,Abboud Cardiovascular Research Center University of Iowa Carver College of Medicine Iowa City IA
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31
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Nauffal V, Morrill VN, Jurgens SJ, Choi SH, Hall AW, Weng LC, Halford JL, Austin-Tse C, Haggerty CM, Harris SL, Wong EK, Alonso A, Arking DE, Benjamin EJ, Boerwinkle E, Min YI, Correa A, Fornwalt BK, Heckbert SR, Kooperberg C, Lin HJ, J F Loos R, Rice KM, Gupta N, Blackwell TW, Mitchell BD, Morrison AC, Psaty BM, Post WS, Redline S, Rehm HL, Rich SS, Rotter JI, Soliman EZ, Sotoodehnia N, Lunetta KL, Ellinor PT, Lubitz SA. Monogenic and Polygenic Contributions to QTc Prolongation in the Population. Circulation 2022; 145:1524-1533. [PMID: 35389749 PMCID: PMC9117504 DOI: 10.1161/circulationaha.121.057261] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Rare sequence variation in genes underlying cardiac repolarization and common polygenic variation influence QT interval duration. However, current clinical genetic testing of individuals with unexplained QT prolongation is restricted to examination of monogenic rare variants. The recent emergence of large-scale biorepositories with sequence data enables examination of the joint contribution of rare and common variations to the QT interval in the population. METHODS We performed a genome-wide association study of the QTc in 84 630 UK Biobank participants and created a polygenic risk score (PRS). Among 26 976 participants with whole-genome sequencing and ECG data in the TOPMed (Trans-Omics for Precision Medicine) program, we identified 160 carriers of putative pathogenic rare variants in 10 genes known to be associated with the QT interval. We examined QTc associations with the PRS and with rare variants in TOPMed. RESULTS Fifty-four independent loci were identified by genome-wide association study in the UK Biobank. Twenty-one loci were novel, of which 12 were replicated in TOPMed. The PRS composed of 1 110 494 common variants was significantly associated with the QTc in TOPMed (ΔQTc/decile of PRS=1.4 ms [95% CI, 1.3 to 1.5]; P=1.1×10-196). Carriers of putative pathogenic rare variants had longer QTc than noncarriers (ΔQTc=10.9 ms [95% CI, 7.4 to 14.4]). Of individuals with QTc>480 ms, 23.7% carried either a monogenic rare variant or had a PRS in the top decile (3.4% monogenic, 21% top decile of PRS). CONCLUSIONS QTc duration in the population is influenced by both rare variants in genes underlying cardiac repolarization and polygenic risk, with a sizeable contribution from polygenic risk. Comprehensive assessment of the genetic determinants of QTc prolongation includes incorporation of both polygenic and monogenic risk.
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Affiliation(s)
- Victor Nauffal
- Division of Cardiovascular Medicine (V.N.), Brigham and Women's Hospital, Boston, MA
- Cardiovascular Disease Initiative (V.N., V.N.M., S.J.J., S.H.C., L.-C.W., J.L.H., P.T.E., S.A.L.), Broad Institute, Cambridge, MA
| | - Valerie N Morrill
- Cardiovascular Disease Initiative (V.N., V.N.M., S.J.J., S.H.C., L.-C.W., J.L.H., P.T.E., S.A.L.), Broad Institute, Cambridge, MA
| | - Sean J Jurgens
- Cardiovascular Disease Initiative (V.N., V.N.M., S.J.J., S.H.C., L.-C.W., J.L.H., P.T.E., S.A.L.), Broad Institute, Cambridge, MA
- Department of Experimental Cardiology, Amsterdam University Medical Centers, The Netherlands (S.J.J.)
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge (N.G., S.J.J., S.H.C., L.C.W., J.L.H., C.A.T., H.L.R., P.T.E., S.A.L.)
| | - Seung Hoan Choi
- Cardiovascular Disease Initiative (V.N., V.N.M., S.J.J., S.H.C., L.-C.W., J.L.H., P.T.E., S.A.L.), Broad Institute, Cambridge, MA
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge (N.G., S.J.J., S.H.C., L.C.W., J.L.H., C.A.T., H.L.R., P.T.E., S.A.L.)
| | - Amelia W Hall
- Gene Regulation Observatory (A.W.H.), Broad Institute, Cambridge, MA
| | - Lu-Chen Weng
- Cardiovascular Disease Initiative (V.N., V.N.M., S.J.J., S.H.C., L.-C.W., J.L.H., P.T.E., S.A.L.), Broad Institute, Cambridge, MA
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge (N.G., S.J.J., S.H.C., L.C.W., J.L.H., C.A.T., H.L.R., P.T.E., S.A.L.)
| | - Jennifer L Halford
- Cardiovascular Disease Initiative (V.N., V.N.M., S.J.J., S.H.C., L.-C.W., J.L.H., P.T.E., S.A.L.), Broad Institute, Cambridge, MA
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge (N.G., S.J.J., S.H.C., L.C.W., J.L.H., C.A.T., H.L.R., P.T.E., S.A.L.)
| | - Christina Austin-Tse
- Center for Genomic Medicine (C.A.-T., H.L.R.), Massachusetts General Hospital, Boston
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge (N.G., S.J.J., S.H.C., L.C.W., J.L.H., C.A.T., H.L.R., P.T.E., S.A.L.)
| | - Christopher M Haggerty
- Department of Translational Data Science and Informatics, Geisinger, Danville, PA (C.M.H., B.K.F.)
| | - Stephanie L Harris
- Cardiovascular Genetics Program (S.L.H., E.K.W.), Massachusetts General Hospital, Boston
| | - Eugene K Wong
- Cardiovascular Genetics Program (S.L.H., E.K.W.), Massachusetts General Hospital, Boston
| | - Alvaro Alonso
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA (A.A.)
| | - Dan E Arking
- McKusick-Nathans Institute, Department of Genetic Medicine (D.E.A.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Emelia J Benjamin
- Boston University School of Public Health, MA (E.J.B., K.L.L.)
- Boston University School of Medicine, MA (E.J.B.)
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston (E.B., A.C.M.)
| | - Yuan-I Min
- Department of Medicine, University of Mississippi Medical Center, Jackson (Y.-I.M., A.C.)
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson (Y.-I.M., A.C.)
| | - Brandon K Fornwalt
- Department of Translational Data Science and Informatics, Geisinger, Danville, PA (C.M.H., B.K.F.)
| | - Susan R Heckbert
- Cardiovascular Health Research Unit and Department of Epidemiology (S.R.H.)
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA (C.K.)
| | - Henry J Lin
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-University of California-Los Angeles Medical Center, Torrance (H.J.L., J.I.R.)
| | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York (R.J.F.L.)
| | | | - Namrata Gupta
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge (N.G., S.J.J., S.H.C., L.C.W., J.L.H., C.A.T., H.L.R., P.T.E., S.A.L.)
| | - Thomas W Blackwell
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor (T.W.B.)
| | - Braxton D Mitchell
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore (B.D.M.)
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston (E.B., A.C.M.)
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology and Health Systems and Population Health, University of Washington, Seattle, WA (B.M.P.)
| | - Wendy S Post
- Division of Cardiology, Department of Medicine (W.S.P.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Susan Redline
- Harvard Medical School (S.R.), Brigham and Women's Hospital, Boston, MA
| | - Heidi L Rehm
- Center for Genomic Medicine (C.A.-T., H.L.R.), Massachusetts General Hospital, Boston
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge (N.G., S.J.J., S.H.C., L.C.W., J.L.H., C.A.T., H.L.R., P.T.E., S.A.L.)
| | - Stephen S Rich
- Center for Public Health Genomics and Department of Public Health Sciences, University of Virginia, Charlottesville (S.S.R.)
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-University of California-Los Angeles Medical Center, Torrance (H.J.L., J.I.R.)
| | - Elsayed Z Soliman
- Epidemiological Cardiology Research Center, Wake Forest School of Medicine, Winston-Salem, NC (E.Z.S.)
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, Cardiology, University of Washington, Seattle, WA (N.S.)
| | | | - Patrick T Ellinor
- Cardiovascular Disease Initiative (V.N., V.N.M., S.J.J., S.H.C., L.-C.W., J.L.H., P.T.E., S.A.L.), Broad Institute, Cambridge, MA
- Cardiac Arrhythmia Service and Cardiovascular Research Center (P.T.E., S.A.L.), Massachusetts General Hospital, Boston
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge (N.G., S.J.J., S.H.C., L.C.W., J.L.H., C.A.T., H.L.R., P.T.E., S.A.L.)
| | - Steven A Lubitz
- Cardiovascular Disease Initiative (V.N., V.N.M., S.J.J., S.H.C., L.-C.W., J.L.H., P.T.E., S.A.L.), Broad Institute, Cambridge, MA
- Cardiac Arrhythmia Service and Cardiovascular Research Center (P.T.E., S.A.L.), Massachusetts General Hospital, Boston
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge (N.G., S.J.J., S.H.C., L.C.W., J.L.H., C.A.T., H.L.R., P.T.E., S.A.L.)
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Roselli C, Yu M, Nauffal V, Georges A, Yang Q, Love K, Weng LC, Delling FN, Maurya SR, Schrölkamp M, Tfelt-Hansen J, Hagège A, Jeunemaitre X, Debette S, Amouyel P, Guan W, Muehlschlegel JD, Body SC, Shah S, Samad Z, Kyryachenko S, Haynes C, Rienstra M, Le Tourneau T, Probst V, Roussel R, Wijdh-Den Hamer IJ, Siland JE, Knowlton KU, Jacques Schott J, Levine RA, Benjamin EJ, Vasan RS, Horne BD, Muhlestein JB, Benfari G, Enriquez-Sarano M, Natale A, Mohanty S, Trivedi C, Shoemaker MB, Yoneda ZT, Wells QS, Baker MT, Farber-Eger E, Michelena HI, Lundby A, Norris RA, Slaugenhaupt SA, Dina C, Lubitz SA, Bouatia-Naji N, Ellinor PT, Milan DJ. Genome-wide association study reveals novel genetic loci: a new polygenic risk score for mitral valve prolapse. Eur Heart J 2022; 43:1668-1680. [PMID: 35245370 PMCID: PMC9649914 DOI: 10.1093/eurheartj/ehac049] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 08/18/2021] [Accepted: 02/01/2022] [Indexed: 11/12/2022] Open
Abstract
AIMS Mitral valve prolapse (MVP) is a common valvular heart disease with a prevalence of >2% in the general adult population. Despite this high incidence, there is a limited understanding of the molecular mechanism of this disease, and no medical therapy is available for this disease. We aimed to elucidate the genetic basis of MVP in order to better understand this complex disorder. METHODS AND RESULTS We performed a meta-analysis of six genome-wide association studies that included 4884 cases and 434 649 controls. We identified 14 loci associated with MVP in our primary analysis and 2 additional loci associated with a subset of the samples that additionally underwent mitral valve surgery. Integration of epigenetic, transcriptional, and proteomic data identified candidate MVP genes including LMCD1, SPTBN1, LTBP2, TGFB2, NMB, and ALPK3. We created a polygenic risk score (PRS) for MVP and showed an improved MVP risk prediction beyond age, sex, and clinical risk factors. CONCLUSION We identified 14 genetic loci that are associated with MVP. Multiple analyses identified candidate genes including two transforming growth factor-β signalling molecules and spectrin β. We present the first PRS for MVP that could eventually aid risk stratification of patients for MVP screening in a clinical setting. These findings advance our understanding of this common valvular heart disease and may reveal novel therapeutic targets for intervention.
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Affiliation(s)
- Carolina Roselli
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA,Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Mengyao Yu
- Université de Paris, PARCC, Inserm, F-75015 Paris, France
| | - Victor Nauffal
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA,Division of Cardiovascular Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Adrien Georges
- Université de Paris, PARCC, Inserm, F-75015 Paris, France
| | - Qiong Yang
- School of Public Health, Boston University, Boston, MA, USA
| | - Katie Love
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Lu Chen Weng
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA,Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Francesca N Delling
- Division of Cardiology, University of California San Francisco, San Francisco, CA, USA
| | - Svetlana R Maurya
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, København 2200, Denmark
| | - Maren Schrölkamp
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, København 2200, Denmark
| | - Jacob Tfelt-Hansen
- Department of Cardiology, The Heart Centre, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark,Department of Forensic Medicine, Faculty of Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Albert Hagège
- Université de Paris, PARCC, Inserm, F-75015 Paris, France,Assistance Publique–Hôpitaux de Paris, Departments of Cardiology and Genetics, Hôpital Européen Georges Pompidou, 75015 Paris, France
| | - Xavier Jeunemaitre
- Université de Paris, PARCC, Inserm, F-75015 Paris, France,Assistance Publique–Hôpitaux de Paris, Departments of Cardiology and Genetics, Hôpital Européen Georges Pompidou, 75015 Paris, France
| | - Stéphanie Debette
- Bordeaux Population Health Research Center, Inserm Center U1219, University of Bordeaux, Bordeaux, France,Department of Neurology, Bordeaux University Hospital, Inserm U1219, Bordeaux, France
| | - Philippe Amouyel
- Univ. Lille, Inserm, Centre Hosp. Univ Lille, Institut Pasteur de Lille, UMR1167 – RID-AGE- Risk factors and molecular determinants of aging-related diseases, F-59000 Lille, France
| | - Wyliena Guan
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA,Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA,Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA, USA
| | - Jochen D Muehlschlegel
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Simon C Body
- Department of Anesthesiology, Boston University School of Medicine, Boston, MA, USA
| | - Svati Shah
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA,Division of Cardiology, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Zainab Samad
- Division of Cardiology, Department of Medicine, Duke University School of Medicine, Durham, NC, USA,Department of Medicine, Aga Khan University, Karachi, Pakistan
| | | | - Carol Haynes
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA
| | - Michiel Rienstra
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Thierry Le Tourneau
- l’institut du thorax, INSERM, CNRS, Univ Nantes, CHU Nantes, Nantes, France,l’institut du thorax, CHU Nantes, Nantes, France
| | - Vincent Probst
- l’institut du thorax, INSERM, CNRS, Univ Nantes, CHU Nantes, Nantes, France
| | - Ronan Roussel
- Cordeliers Research Centre, ImMeDiab Team, INSERM, Université de Paris, Paris, France,Hôpital Bichat-Claude-Bernard, APHP, Department of Diabetology, Paris, France
| | - Inez J Wijdh-Den Hamer
- Department of Cardiothoracic Surgery, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Joylene E Siland
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Kirk U Knowlton
- Intermountain Medical Center Heart Institute, Salt Lake City, UT, USA,Division of Cardiovascular Medicine, Department of Medicine, University of California San Diego, San Diego, CA, USA
| | | | - Robert A Levine
- Cardiac Ultrasound Laboratory, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Emelia J Benjamin
- National Heart, Lung, and Blood Institute’s and Boston University’s, The Framingham Heart Study, Framingham, MA, USA,Section of Cardiovascular Medicine, Boston University School of Medicine, Boston, MA, USA,Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Ramachandran S Vasan
- School of Public Health, Boston University, Boston, MA, USA,National Heart, Lung, and Blood Institute’s and Boston University’s, The Framingham Heart Study, Framingham, MA, USA,School of Medicine, Boston University, Boston, MA, USA
| | - Benjamin D Horne
- Intermountain Medical Center Heart Institute, Salt Lake City, UT, USA,Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, CA, USA
| | - Joseph B Muhlestein
- Intermountain Medical Center Heart Institute, Salt Lake City, UT, USA,Cardiology Division, Department of Internal Medicine, University of Utah, Salt Lake City, UT, USA
| | - Giovanni Benfari
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | | | - Andrea Natale
- Texas Cardiac Arrhythmia Institute, St David’s Medical Center, Austin, TX, USA
| | - Sanghamitra Mohanty
- Texas Cardiac Arrhythmia Institute, St David’s Medical Center, Austin, TX, USA
| | - Chintan Trivedi
- Texas Cardiac Arrhythmia Institute, St David’s Medical Center, Austin, TX, USA
| | - Moore B Shoemaker
- Department of Medicine, Division of Cardiovascular Diseases, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Zachary T Yoneda
- Department of Medicine, Division of Cardiovascular Diseases, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Quinn S Wells
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA,Department of Pharmacology, Vanderbilt University Medical Center, Nashville, TN, USA,Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Michael T Baker
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Eric Farber-Eger
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Alicia Lundby
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, København 2200, Denmark,The Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, København 2200, Denmark
| | - Russell A Norris
- Cardiovascular Developmental Biology Center, Department of Regenerative Medicine and Cell Biology, Medical University of South Carolina, Charleston, SC, USA
| | | | | | | | | | - Patrick T Ellinor
- Corresponding authors. Tel: +1 617 459 4688, (D.J.M.); Tel: +1 617 724 8729, (P.T.E.)
| | - David J Milan
- Corresponding authors. Tel: +1 617 459 4688, (D.J.M.); Tel: +1 617 724 8729, (P.T.E.)
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Jurgens SJ, Choi SH, Morrill VN, Chaffin M, Pirruccello JP, Halford JL, Weng LC, Nauffal V, Roselli C, Hall AW, Oetjens MT, Lagerman B, vanMaanen DP, Aragam KG, Lunetta KL, Haggerty CM, Lubitz SA, Ellinor PT. Analysis of rare genetic variation underlying cardiometabolic diseases and traits among 200,000 individuals in the UK Biobank. Nat Genet 2022; 54:240-250. [PMID: 35177841 PMCID: PMC8930703 DOI: 10.1038/s41588-021-01011-w] [Citation(s) in RCA: 59] [Impact Index Per Article: 29.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 12/22/2021] [Indexed: 12/30/2022]
Abstract
Cardiometabolic diseases are the leading cause of death worldwide. Despite a known genetic component, our understanding of these diseases remains incomplete. Here, we analyzed the contribution of rare variants to 57 diseases and 26 cardiometabolic traits, using data from 200,337 UK Biobank participants with whole-exome sequencing. We identified 57 gene-based associations, with broad replication of novel signals in Geisinger MyCode. There was a striking risk associated with mutations in known Mendelian disease genes, including MYBPC3, LDLR, GCK, PKD1 and TTN. Many genes showed independent convergence of rare and common variant evidence, including an association between GIGYF1 and type 2 diabetes. We identified several large effect associations for height and 18 unique genes associated with blood lipid or glucose levels. Finally, we found that between 1.0% and 2.4% of participants carried rare potentially pathogenic variants for cardiometabolic disorders. These findings may facilitate studies aimed at therapeutics and screening of these common disorders.
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Affiliation(s)
- Sean J. Jurgens
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Department of Experimental Cardiology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Seung Hoan Choi
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Valerie N. Morrill
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mark Chaffin
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - James P. Pirruccello
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Jennifer L. Halford
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Lu-Chen Weng
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Victor Nauffal
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Carolina Roselli
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Amelia W. Hall
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | | | - Braxton Lagerman
- Department of Translational Data Science and Informatics, Geisinger, Danville, PA, USA
| | - David P. vanMaanen
- Department of Translational Data Science and Informatics, Geisinger, Danville, PA, USA
| | | | - Krishna G. Aragam
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Kathryn L. Lunetta
- NHLBI and Boston University’s Framingham Heart Study, Framingham, MA, USA.,Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Christopher M. Haggerty
- Department of Translational Data Science and Informatics, Geisinger, Danville, PA, USA.,Heart Institute, Geisinger, Danville, PA, USA
| | - Steven A. Lubitz
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.,Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA, USA
| | - Patrick T. Ellinor
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.,Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA, USA.,
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Tsao CW, Aday AW, Almarzooq ZI, Alonso A, Beaton AZ, Bittencourt MS, Boehme AK, Buxton AE, Carson AP, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Ferguson JF, Generoso G, Ho JE, Kalani R, Khan SS, Kissela BM, Knutson KL, Levine DA, Lewis TT, Liu J, Loop MS, Ma J, Mussolino ME, Navaneethan SD, Perak AM, Poudel R, Rezk-Hanna M, Roth GA, Schroeder EB, Shah SH, Thacker EL, VanWagner LB, Virani SS, Voecks JH, Wang NY, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association. Circulation 2022; 145:e153-e639. [PMID: 35078371 DOI: 10.1161/cir.0000000000001052] [Citation(s) in RCA: 2460] [Impact Index Per Article: 1230.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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35
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Yu M, Tcheandjieu C, Georges A, Xiao K, Tejeda H, Dina C, Le Tourneau T, Fiterau M, Judy R, Tsao NL, Amgalan D, Munger CJ, Engreitz JM, Damrauer SM, Bouatia-Naji N, Priest JR. Computational estimates of annular diameter reveal genetic determinants of mitral valve function and disease. JCI Insight 2022; 7:146580. [PMID: 35132965 PMCID: PMC8855800 DOI: 10.1172/jci.insight.146580] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Accepted: 12/21/2021] [Indexed: 11/17/2022] Open
Abstract
The fibrous annulus of the mitral valve plays an important role in valvular function and cardiac physiology, while normal variation in the size of cardiovascular anatomy may share a genetic link with common and rare disease. We derived automated estimates of mitral valve annular diameter in the 4-chamber view from 32,220 MRI images from the UK Biobank at ventricular systole and diastole as the basis for GWAS. Mitral annular dimensions corresponded to previously described anatomical norms, and GWAS inclusive of 4 population strata identified 10 loci, including possibly novel loci (GOSR2, ERBB4, MCTP2, MCPH1) and genes related to cardiac contractility (BAG3, TTN, RBFOX1). ATAC-Seq of primary mitral valve tissue localized multiple variants to regions of open chromatin in biologically relevant cell types and rs17608766 to an algorithmically predicted enhancer element in GOSR2. We observed strong genetic correlation with measures of contractility and mitral valve disease and clinical correlations with heart failure, cerebrovascular disease, and ventricular arrhythmias. Polygenic scoring of mitral valve annular diameter in systole was predictive of risk mitral valve prolapse across 4 cohorts. In summary, genetic and clinical studies of mitral valve annular diameter revealed genetic determinants of mitral valve biology, while highlighting clinical associations. Polygenic determinants of mitral valve annular diameter may represent an independent risk factor for mitral prolapse. Overall, computationally estimated phenotypes derived at scale from medical imaging represent an important substrate for genetic discovery and clinical risk prediction.
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Affiliation(s)
| | - Catherine Tcheandjieu
- Department of Pediatrics and.,Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Adrien Georges
- Paris Cardiovascular Research Center, INSERM, University of Paris, Paris, France
| | - Ke Xiao
- College of Information & Computer Sciences at University of Massachusetts Amherst, Amherst, Massachusetts, USA
| | | | - Christian Dina
- University of Nantes, INSERM, CNRS, CHU Nantes, The Thorax Institute, Nantes, France
| | - Thierry Le Tourneau
- University of Nantes, INSERM, CNRS, CHU Nantes, The Thorax Institute, Nantes, France
| | - Madalina Fiterau
- College of Information & Computer Sciences at University of Massachusetts Amherst, Amherst, Massachusetts, USA
| | - Renae Judy
- Department of Surgery, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Noah L Tsao
- Department of Surgery, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Dulguun Amgalan
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA.,Basic Science & Engineering Initiative & Betty Irene Moore Children's Heart Center, Lucile Packard Children's Hospital, Stanford, California, USA
| | - Chad J Munger
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA.,Basic Science & Engineering Initiative & Betty Irene Moore Children's Heart Center, Lucile Packard Children's Hospital, Stanford, California, USA
| | - Jesse M Engreitz
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA.,Basic Science & Engineering Initiative & Betty Irene Moore Children's Heart Center, Lucile Packard Children's Hospital, Stanford, California, USA
| | - Scott M Damrauer
- Department of Surgery, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Nabila Bouatia-Naji
- Paris Cardiovascular Research Center, INSERM, University of Paris, Paris, France
| | - James R Priest
- Department of Pediatrics and.,Chan-Zuckerberg Biohub, San Francisco, California, USA
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36
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Lam DD, Nikolic AA, Zhao C, Mirza-Schreiber N, Krężel W, Oexle K, Winkelmann J. Intronic elements associated with insomnia and restless legs syndrome exhibit cell type-specific epigenetic features contributing to MEIS1 regulation. Hum Mol Genet 2021; 31:1733-1746. [PMID: 34888668 DOI: 10.1093/hmg/ddab355] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 11/25/2021] [Accepted: 12/05/2021] [Indexed: 12/13/2022] Open
Abstract
A highly evolutionarily conserved MEIS1 intronic region is strongly associated with restless legs syndrome (RLS) and insomnia. To understand its regulatory function, we dissected the region by analyzing chromatin accessibility, enhancer-promoter contacts, DNA methylation, and eQTLs in different human neural cell types and tissues. We observed specific activity with respect to cell type and developmental maturation, indicating a prominent role for distinct highly conserved intronic elements in forebrain inhibitory neuron differentiation. Two elements were hypomethylated in neural cells with higher MEIS1 expression, suggesting a role of enhancer demethylation in gene regulation. MEIS1 eQTLs showed a striking modular chromosomal distribution, with forebrain eQTLs clustering in intron 8/9. CRISPR interference targeting of individual elements in this region attenuated MEIS1 expression, revealing a complex regulatory interplay of distinct elements. In summary, we found that MEIS1 regulation is organized in a modular pattern. Disease-associated intronic regulatory elements control MEIS1 expression with cell type and maturation stage specificity, particularly in the inhibitory neuron lineage. The precise spatiotemporal activity of these elements likely contributes to the pathogenesis of insomnia and RLS.
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Affiliation(s)
- Daniel D Lam
- Institute of Neurogenomics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Human Genetics, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Germany
| | - Ana Antic Nikolic
- Institute of Neurogenomics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Human Genetics, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Germany
| | - Chen Zhao
- Institute of Neurogenomics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Human Genetics, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Germany
| | - Nazanin Mirza-Schreiber
- Institute of Neurogenomics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany
| | - Wojciech Krężel
- Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France.,Institut de la Santé et de la Recherche Médicale, U964, Illkirch, France.,Centre National de la Recherche Scientifique, UMR 7104, Illkirch, France.,Université de Strasbourg, Illkirch, France
| | - Konrad Oexle
- Institute of Neurogenomics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Human Genetics, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Germany
| | - Juliane Winkelmann
- Institute of Neurogenomics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Human Genetics, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Germany.,Chair of Neurogenetics, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
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37
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van Duijvenboden S, Ramírez J, Young WJ, Orini M, Mifsud B, Tinker A, Lambiase PD, Munroe PB. Genomic and pleiotropic analyses of resting QT interval identifies novel loci and overlap with atrial electrical disorders. Hum Mol Genet 2021; 30:2513-2523. [PMID: 34274964 PMCID: PMC8643508 DOI: 10.1093/hmg/ddab197] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 05/26/2021] [Accepted: 06/17/2021] [Indexed: 11/13/2022] Open
Abstract
The resting QT interval, an electrocardiographic (ECG) measure of ventricular myocardial repolarization, is a heritable risk marker of cardiovascular mortality, but the mechanisms remain incompletely understood. Previously reported candidate genes have provided insights into the regulatory mechanisms of the QT interval. However, there are still important knowledge gaps. We aimed to gain new insights by (i) providing new candidate genes, (ii) identifying pleiotropic associations with other cardiovascular traits, and (iii) scanning for sexually dimorphic genetic effects. We conducted a genome-wide association analysis for resting QT interval with ~9.8 million variants in 52 107 individuals of European ancestry without known cardiovascular disease from the UK Biobank. We identified 40 loci, 13 of which were novel, including 2 potential sex-specific loci, explaining ~11% of the trait variance. Candidate genes at novel loci were involved in myocardial structure and arrhythmogenic cardiomyopathy. Investigation of pleiotropic effects of QT interval variants using phenome-wide association analyses in 302 000 unrelated individuals from the UK Biobank and pairwise genome-wide comparisons with other ECG and cardiac imaging traits revealed genetic overlap with atrial electrical pathology. These findings provide novel insights into how abnormal myocardial repolarization and increased cardiovascular mortality may be linked.
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Affiliation(s)
- Stefan van Duijvenboden
- Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
| | - Julia Ramírez
- Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, 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 EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew’s Hospital, London EC1A 7BE, UK
| | - Michele Orini
- Institute of Cardiovascular Science, University College London, London WC1E 6BT, 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
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha PO 34110, Qatar
| | - 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 Unit, 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 Bartholomew’s 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 Unit, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
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38
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Habibe JJ, Clemente-Olivo MP, de Vries CJ. How (Epi)Genetic Regulation of the LIM-Domain Protein FHL2 Impacts Multifactorial Disease. Cells 2021; 10:cells10102611. [PMID: 34685595 PMCID: PMC8534169 DOI: 10.3390/cells10102611] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 09/23/2021] [Accepted: 09/24/2021] [Indexed: 01/13/2023] Open
Abstract
Susceptibility to complex pathological conditions such as obesity, type 2 diabetes and cardiovascular disease is highly variable among individuals and arises from specific changes in gene expression in combination with external factors. The regulation of gene expression is determined by genetic variation (SNPs) and epigenetic marks that are influenced by environmental factors. Aging is a major risk factor for many multifactorial diseases and is increasingly associated with changes in DNA methylation, leading to differences in gene expression. Four and a half LIM domains 2 (FHL2) is a key regulator of intracellular signal transduction pathways and the FHL2 gene is consistently found as one of the top hyper-methylated genes upon aging. Remarkably, FHL2 expression increases with methylation. This was demonstrated in relevant metabolic tissues: white adipose tissue, pancreatic β-cells, and skeletal muscle. In this review, we provide an overview of the current knowledge on regulation of FHL2 by genetic variation and epigenetic DNA modification, and the potential consequences for age-related complex multifactorial diseases.
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Affiliation(s)
- Jayron J. Habibe
- Department of Medical Biochemistry, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, and Amsterdam Gastroenterology, Endocrinology and Metabolism, 1105 AZ Amsterdam, The Netherlands; (J.J.H.); (M.P.C.-O.)
- Department of Physiology, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, 1081 HV Amsterdam, The Netherlands
| | - Maria P. Clemente-Olivo
- Department of Medical Biochemistry, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, and Amsterdam Gastroenterology, Endocrinology and Metabolism, 1105 AZ Amsterdam, The Netherlands; (J.J.H.); (M.P.C.-O.)
| | - Carlie J. de Vries
- Department of Medical Biochemistry, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, and Amsterdam Gastroenterology, Endocrinology and Metabolism, 1105 AZ Amsterdam, The Netherlands; (J.J.H.); (M.P.C.-O.)
- Correspondence:
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39
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Premont A, Balthes S, Marr CM, Jeevaratnam K. Fundamentals of arrhythmogenic mechanisms and treatment strategies for equine atrial fibrillation. Equine Vet J 2021; 54:262-282. [PMID: 34564902 DOI: 10.1111/evj.13518] [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: 12/21/2020] [Revised: 09/13/2021] [Accepted: 09/16/2021] [Indexed: 11/26/2022]
Abstract
Atrial fibrillation (AF) is the most common pathological arrhythmia in horses. Although it is not usually a life-threatening condition on its own, it can cause poor performance and make the horse unsafe to ride. It is a complex multifactorial disease influenced by both genetic and environmental factors including exercise training, comorbidities or ageing. The interactions between all these factors in horses are still not completely understood and the pathophysiology of AF remains poorly defined. Exciting progress has been recently made in equine cardiac electrophysiology in terms of diagnosis and documentation methods such as cardiac mapping, implantable electrocardiogram (ECG) recording devices or computer-based ECG analysis that will hopefully improve our understanding of this disease. The available pharmaceutical and electrophysiological treatments have good efficacy and lead to a good prognosis for AF, but recurrence is a frequent issue that veterinarians have to face. This review aims to summarise our current understanding of equine cardiac electrophysiology and pathophysiology of equine AF while providing an overview of the mechanism of action for currently available treatments for equine AF.
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Affiliation(s)
- Antoine Premont
- Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Samantha Balthes
- Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Celia M Marr
- Rossdales Equine Hospital and Diagnostic Centre, Newmarket, UK
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40
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Duong T, Rose R, Blazeski A, Fine N, Woods CE, Thole JF, Sotoodehnia N, Soliman EZ, Tung L, McCallion AS, Arking DE. Development and optimization of an in vivo electrocardiogram recording method and analysis program for adult zebrafish. Dis Model Mech 2021; 14:dmm048827. [PMID: 34378773 PMCID: PMC8380046 DOI: 10.1242/dmm.048827] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Accepted: 06/30/2021] [Indexed: 12/18/2022] Open
Abstract
Clinically pertinent electrocardiogram (ECG) data from model systems, such as zebrafish, are crucial for illuminating factors contributing to human cardiac electrophysiological abnormalities and disease. Current zebrafish ECG collection strategies have not adequately addressed the consistent acquisition of high-quality traces or sources of phenotypic variation that could obscure data interpretation. Thus, we developed a novel platform to ensure high-quality recording of in vivo subdermal adult zebrafish ECGs and zebrafish ECG reading GUI (zERG), a program to acquire measurements from traces that commercial software cannot examine owing to erroneous peak calling. We evaluate normal ECG trait variation, revealing highly reproducible intervals and wave amplitude variation largely driven by recording artifacts, and identify sex and body size as potential confounders to PR, QRS and QT intervals. With this framework, we characterize the effect of the class I anti-arrhythmic drug flecainide acetate on adults, provide support for the impact of a Long QT syndrome model, and establish power calculations for this and other studies. These results highlight our pipeline as a robust approach to evaluate zebrafish models of human cardiac electrophysiological phenotypes.
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Affiliation(s)
- ThuyVy Duong
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Rebecca Rose
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Adriana Blazeski
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Noah Fine
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Courtney E. Woods
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Joseph F. Thole
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Departments of Medicine and Epidemiology, University of Washington, Seattle, WA 98101, USA
| | - Elsayed Z. Soliman
- Epidemiological Cardiology Research Center (EPICARE), Wake Forest School of Medicine, Winston Salem, NC 27101, USA
| | - Leslie Tung
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Andrew S. McCallion
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Dan E. Arking
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
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41
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Choi SH, Jurgens SJ, Haggerty CM, Hall AW, Halford JL, Morrill VN, Weng LC, Lagerman B, Mirshahi T, Pettinger M, Guo X, Lin HJ, Alonso A, Soliman EZ, Kornej J, Lin H, Moscati A, Nadkarni GN, Brody JA, Wiggins KL, Cade BE, Lee J, Austin-Tse C, Blackwell T, Chaffin MD, Lee CJY, Rehm HL, Roselli C, Redline S, Mitchell BD, Sotoodehnia N, Psaty BM, Heckbert SR, Loos RJ, Vasan RS, Benjamin EJ, Correa A, Boerwinkle E, Arking DE, Rotter JI, Rich SS, Whitsel EA, Perez M, Kooperberg C, Fornwalt BK, Lunetta KL, Ellinor PT, Lubitz SA, Lubitz SA. Rare Coding Variants Associated With Electrocardiographic Intervals Identify Monogenic Arrhythmia Susceptibility Genes: A Multi-Ancestry Analysis. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2021; 14:e003300. [PMID: 34319147 PMCID: PMC8373440 DOI: 10.1161/circgen.120.003300] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND Alterations in electrocardiographic (ECG) intervals are well-known markers for arrhythmia and sudden cardiac death (SCD) risk. While the genetics of arrhythmia syndromes have been studied, relations between electrocardiographic intervals and rare genetic variation at a population level are poorly understood. METHODS Using a discovery sample of 29 000 individuals with whole-genome sequencing from Trans-Omics in Precision Medicine and replication in nearly 100 000 with whole-exome sequencing from the UK Biobank and MyCode, we examined associations between low-frequency and rare coding variants with 5 routinely measured electrocardiographic traits (RR, P-wave, PR, and QRS intervals and corrected QT interval). RESULTS We found that rare variants associated with population-based electrocardiographic intervals identify established monogenic SCD genes (KCNQ1, KCNH2, and SCN5A), a controversial monogenic SCD gene (KCNE1), and novel genes (PAM and MFGE8) involved in cardiac conduction. Loss-of-function and pathogenic SCN5A variants, carried by 0.1% of individuals, were associated with a nearly 6-fold increased odds of the first-degree atrioventricular block (P=8.4×10-5). Similar variants in KCNQ1 and KCNH2 (0.2% of individuals) were associated with a 23-fold increased odds of marked corrected QT interval prolongation (P=4×10-25), a marker of SCD risk. Incomplete penetrance of such deleterious variation was common as over 70% of carriers had normal electrocardiographic intervals. CONCLUSIONS Our findings indicate that large-scale high-depth sequence data and electrocardiographic analysis identifies monogenic arrhythmia susceptibility genes and rare variants with large effects. Known pathogenic variation in conventional arrhythmia and SCD genes exhibited incomplete penetrance and accounted for only a small fraction of marked electrocardiographic interval prolongation.
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Affiliation(s)
- Seung Hoan Choi
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (S.H.C., S.J.J., A.W.H., J.L.H., V.N.M., L.-C.W., M.D.C., C.J.-Y.L., H.L.R., C.R., P.T.E., S.A.L.)
| | - Sean J. Jurgens
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (S.H.C., S.J.J., A.W.H., J.L.H., V.N.M., L.-C.W., M.D.C., C.J.-Y.L., H.L.R., C.R., P.T.E., S.A.L.)
| | - Christopher M. Haggerty
- Department of Translational Data Science and Informatics (C.M.H., B.K.F.), Geisinger, Danville, PA.,Heart Institute (C.M.H., B.K.F.), Geisinger, Danville, PA
| | - Amelia W. Hall
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (S.H.C., S.J.J., A.W.H., J.L.H., V.N.M., L.-C.W., M.D.C., C.J.-Y.L., H.L.R., C.R., P.T.E., S.A.L.).,Cardiovascular Research Center (A.W.H., V.N.M., L.-C.W., P.T.E., S.A.L.), Boston, MA
| | - Jennifer L. Halford
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (S.H.C., S.J.J., A.W.H., J.L.H., V.N.M., L.-C.W., M.D.C., C.J.-Y.L., H.L.R., C.R., P.T.E., S.A.L.).,Harvard Medical School (J.L.H., C.A.-T., H.L.R.), Boston, MA
| | - Valerie N. Morrill
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (S.H.C., S.J.J., A.W.H., J.L.H., V.N.M., L.-C.W., M.D.C., C.J.-Y.L., H.L.R., C.R., P.T.E., S.A.L.).,Cardiovascular Research Center (A.W.H., V.N.M., L.-C.W., P.T.E., S.A.L.), Boston, MA
| | - Lu-Chen Weng
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (S.H.C., S.J.J., A.W.H., J.L.H., V.N.M., L.-C.W., M.D.C., C.J.-Y.L., H.L.R., C.R., P.T.E., S.A.L.).,Cardiovascular Research Center (A.W.H., V.N.M., L.-C.W., P.T.E., S.A.L.), Boston, MA
| | - Braxton Lagerman
- Phenomic Analytics and Clinical Data Core (B.L.), Geisinger, Danville, PA
| | - Tooraj Mirshahi
- Department of Molecular and Functional Genomics (T.M.), Geisinger, Danville, PA
| | - Mary Pettinger
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA (M.P., C.K.)
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Insti for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA (X.G., H.J.L., J.I.R.)
| | - Henry J. Lin
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Insti for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA (X.G., H.J.L., J.I.R.)
| | - Alvaro Alonso
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA (A.A.)
| | - Elsayed Z. Soliman
- Epidemiological Cardiology Research Center, Wake Forest School of Medicine, Winston Salem, NC (E.Z.S.)
| | - Jelena Kornej
- NHLBI and Boston University’s Framingham Heart Study (J.K., E.J.B., R.S.V).,Sections of Cardiovascular Medicine and Preventive Medicine, Boston Medical Center (J.K., R.S.V), Boston University School of Medicine, MA
| | - Honghuang Lin
- Section of Computational Biomedicine, Department of Medicine (H.L.), Boston University School of Medicine, MA
| | - Arden Moscati
- The Charles Bronfman Institute for Personalized Medicine (A.M., G.N., R.J.F.L.), Icahn School of Medicine, Mount Sinai, New York, NY
| | - Girish N. Nadkarni
- The Charles Bronfman Institute for Personalized Medicine (A.M., G.N., R.J.F.L.), Icahn School of Medicine, Mount Sinai, New York, NY.,Division of Nephrology, Department of Medicine (G.N.), Icahn School of Medicine, Mount Sinai, New York, NY
| | - Jennifer A. Brody
- Cardiovascular Health Research Unit, Department of Medicine (J.A.B., K.L.W., N.S., B.M.P., S.R.H.), University of Washington, Seattle
| | - Kerri L. Wiggins
- Cardiovascular Health Research Unit, Department of Medicine (J.A.B., K.L.W., N.S., B.M.P., S.R.H.), University of Washington, Seattle
| | - Brian E. Cade
- Massachusetts General Hospital. Division of Sleep Medicine, Department of Medicine (B.E.C.), Boston, MA.,Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology (B.E.C.), Harvard Medical School, Brigham and Women’s Hospital, Boston
| | - Jiwon Lee
- Division of Sleep and Circadian Disorders (J.L.), Harvard Medical School, Brigham and Women’s Hospital, Boston
| | - Christina Austin-Tse
- Center for Genomic Medicine (C.A.-T., H.L.R.), Boston, MA.,Harvard Medical School (J.L.H., C.A.-T., H.L.R.), Boston, MA.,Laboratory for Molecular Medicine, Partners Healthcare Personalized Medicine, Cambridge, MA (C.A.-T.)
| | - Tom Blackwell
- Department of Biostatistics, University of Michigan, Ann Arbor (T.B.)
| | - Mark D. Chaffin
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (S.H.C., S.J.J., A.W.H., J.L.H., V.N.M., L.-C.W., M.D.C., C.J.-Y.L., H.L.R., C.R., P.T.E., S.A.L.)
| | - Christina J.-Y. Lee
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (S.H.C., S.J.J., A.W.H., J.L.H., V.N.M., L.-C.W., M.D.C., C.J.-Y.L., H.L.R., C.R., P.T.E., S.A.L.)
| | - Heidi L. Rehm
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (S.H.C., S.J.J., A.W.H., J.L.H., V.N.M., L.-C.W., M.D.C., C.J.-Y.L., H.L.R., C.R., P.T.E., S.A.L.).,Center for Genomic Medicine (C.A.-T., H.L.R.), Boston, MA.,Harvard Medical School (J.L.H., C.A.-T., H.L.R.), Boston, MA
| | - Carolina Roselli
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (S.H.C., S.J.J., A.W.H., J.L.H., V.N.M., L.-C.W., M.D.C., C.J.-Y.L., H.L.R., C.R., P.T.E., S.A.L.)
| | - Susan Redline
- Regeneron Genetics Center, Tarrytown, NY. Departments of Medicine, Brigham and Women’s Hospital, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA (S.R.)
| | - Braxton D. Mitchell
- University of Maryland School of Medicine (B.D.M.).,Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, MD (B.D.M.)
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Department of Medicine (J.A.B., K.L.W., N.S., B.M.P., S.R.H.), University of Washington, Seattle.,Division of Cardiology, Department of Epidemiology (N.S.), University of Washington, Seattle
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine (J.A.B., K.L.W., N.S., B.M.P., S.R.H.), University of Washington, Seattle.,Department of Epidemiology (B.M.P., S.R.H.), University of Washington, Seattle.,Department of Health Services (B.M.P.), University of Washington, Seattle.,Kaiser Permanente Washington Health Research Institute, Seattle (B.M.P.)
| | - Susan R. Heckbert
- Cardiovascular Health Research Unit, Department of Medicine (J.A.B., K.L.W., N.S., B.M.P., S.R.H.), University of Washington, Seattle.,Department of Epidemiology (B.M.P., S.R.H.), University of Washington, Seattle
| | - Ruth J.F. Loos
- The Charles Bronfman Institute for Personalized Medicine (A.M., G.N., R.J.F.L.), Icahn School of Medicine, Mount Sinai, New York, NY.,The Mindich Child Health and Development Institute (R.J.F.L.), Icahn School of Medicine, Mount Sinai, New York, NY
| | - Ramachandran S. Vasan
- NHLBI and Boston University’s Framingham Heart Study (J.K., E.J.B., R.S.V).,Sections of Cardiovascular Medicine and Preventive Medicine, Boston Medical Center (J.K., R.S.V), Boston University School of Medicine, MA.,Department of Medicine (E.J.B., R.S.V), Boston University School of Medicine, MA
| | - Emelia J. Benjamin
- NHLBI and Boston University’s Framingham Heart Study (J.K., E.J.B., R.S.V).,Department of Medicine (E.J.B., R.S.V), Boston University School of Medicine, MA.,Department of Epidemiology (E.J.B.), Boston University School of Public Health, MA
| | - Adolfo Correa
- Departments of Medicine, Pediatrics, and Population Health Science, University of Mississippi Medical Center, Jackson (A.C.)
| | - Eric Boerwinkle
- Human Genetics Center, University of Texas Health Science Center, Houston (E.B.)
| | - Dan E. Arking
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (D.E.A.)
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Insti for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA (X.G., H.J.L., J.I.R.)
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville (S.S.R.)
| | - Eric A. Whitsel
- Department of Epidemiology, Gillings School of Global Public Health (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill.,Department of Medicine (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill
| | - Marco Perez
- Division of Cardiovascular Medicine, Stanford University, CA (M.P.). Dr Sotoodehnia is supported by NIH grant R01HL141989, by AHA grant 19SFRN34830063, and by the Laughlin Family
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA (M.P., C.K.)
| | - Brandon K. Fornwalt
- Department of Translational Data Science and Informatics (C.M.H., B.K.F.), Geisinger, Danville, PA.,Heart Institute (C.M.H., B.K.F.), Geisinger, Danville, PA.,Department of Radiology (B.K.F.), Geisinger, Danville, PA
| | - Kathryn L. Lunetta
- Department of Biostatistics (K.L.L.), Boston University School of Public Health, MA
| | - Patrick T. Ellinor
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (S.H.C., S.J.J., A.W.H., J.L.H., V.N.M., L.-C.W., M.D.C., C.J.-Y.L., H.L.R., C.R., P.T.E., S.A.L.).,Cardiovascular Research Center (A.W.H., V.N.M., L.-C.W., P.T.E., S.A.L.), Boston, MA.,Cardiac Arrhythmia Service (P.T.E., S.A.L.), Boston, MA
| | - Steven A. Lubitz
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (S.H.C., S.J.J., A.W.H., J.L.H., V.N.M., L.-C.W., M.D.C., C.J.-Y.L., H.L.R., C.R., P.T.E., S.A.L.).,Cardiovascular Research Center (A.W.H., V.N.M., L.-C.W., P.T.E., S.A.L.), Boston, MA.,Cardiac Arrhythmia Service (P.T.E., S.A.L.), Boston, MA
| | - Steven A Lubitz
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (S.H.C., S.J.J., A.W.H., J.L.H., V.N.M., L.-C.W., M.D.C., C.J.-Y.L., H.L.R., C.R., P.T.E., S.A.L.).,Cardiovascular Research Center (A.W.H., V.N.M., L.-C.W., P.T.E., S.A.L.), Boston, MA.,Cardiac Arrhythmia Service (P.T.E., S.A.L.), Boston, MA
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42
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Shi M, Manouchehri AM, Shaffer CM, Vaitinadin NS, Hellwege JN, Salem JE, Davis LK, Simmons JH, Roden DM, Shoemaker MB, Ferguson JF, Mosley JD. Genetic Thyrotropin Regulation of Atrial Fibrillation Risk Is Mediated Through an Effect on Height. J Clin Endocrinol Metab 2021; 106:2124-2132. [PMID: 33895829 PMCID: PMC8208678 DOI: 10.1210/clinem/dgab272] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 03/31/2021] [Indexed: 12/23/2022]
Abstract
CONTEXT A genetic predisposition to lower thyrotropin (TSH) levels is associated with increased atrial fibrillation (AF) risk through undefined mechanisms. OBJECTIVE Defining the genetic mediating mechanisms could lead to improved targeted therapies to mitigate AF risk. METHODS We used 2-sample mendelian randomization (MR) to test associations between TSH-associated single-nucleotide variations and 16 candidate mediators. We then performed multivariable mendelian randomization (MVMR) to test for a significant attenuation of the genetic association between TSH and AF, after adjusting for each mediator significantly associated with TSH. RESULTS Four candidate mediators (free thyroxine, systolic blood pressure, heart rate, and height) were significantly inversely associated with genetically predicted TSH after adjusting for multiple testing. In MVMR analyses, adjusting for height significantly decreased the magnitude of the association between TSH and AF from -0.12 (SE 0.02) occurrences of AF per SD change in height to -0.06 (0.02) (P = .005). Adjusting for the other candidate mediators did not significantly attenuate the association. CONCLUSION The genetic association between TSH and increased AF risk is mediated, in part, by taller stature. Thus, some genetic mechanisms underlying TSH variability may contribute to AF risk through mechanisms determining height occurring early in life that differ from those driven by thyroid hormone-level elevations in later life.
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Affiliation(s)
- Mingjian Shi
- Department of Biomedical Informatics & Center for Precision Medicine, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA
| | - Ali M Manouchehri
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA
| | - Christian M Shaffer
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA
| | | | - Jacklyn N Hellwege
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA
| | - Joe-Elie Salem
- Département de Pharmacologie, APHP, Sorbonne Université, INSERM, UNICO-GRECO Cardio-oncology Program, F75013 Paris, France
| | - Lea K Davis
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA
| | - Jill H Simmons
- Division of Pediatric Endocrinology, Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA
| | - Dan M Roden
- Department of Biomedical Informatics & Center for Precision Medicine, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA
- Department of Pharmacology, Vanderbilt University, Nashville, Tennessee 37212, USA
| | - M Benjamin Shoemaker
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA
| | - Jane F Ferguson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA
| | - Jonathan D Mosley
- Department of Biomedical Informatics & Center for Precision Medicine, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA
- Correspondence: Jonathan D. Mosley, MD, PhD, Vanderbilt University Medical Center, 1285 Medical Research Building IV, Nashville, TN 37232, USA.
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43
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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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44
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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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45
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Man JCK, Bosada FM, Scholman KT, Offerhaus JA, Walsh R, van Duijvenboden K, van Eif VWW, Bezzina CR, Verkerk AO, Boukens BJ, Barnett P, Christoffels VM. Variant Intronic Enhancer Controls SCN10A-short Expression and Heart Conduction. Circulation 2021; 144:229-242. [PMID: 33910361 DOI: 10.1161/circulationaha.121.054083] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
BACKGROUND Genetic variants in SCN10A, encoding the neuronal voltage-gated sodium channel NaV1.8, are strongly associated with atrial fibrillation, Brugada syndrome, cardiac conduction velocities, and heart rate. The cardiac function of SCN10A has not been resolved, however, and diverging mechanisms have been proposed. Here, we investigated the cardiac expression of SCN10A and the function of a variant-sensitive intronic enhancer previously linked to the regulation of SCN5A, encoding the major essential cardiac sodium channel NaV1.5. METHODS The expression of SCN10A was investigated in mouse and human hearts. With the use of CRISPR/Cas9 genome editing, the mouse intronic enhancer was disrupted, and mutant mice were characterized by transcriptomic and electrophysiological analyses. The association of genetic variants at SCN5A-SCN10A enhancer regions and gene expression were evaluated by genome-wide association studies single-nucleotide polymorphism mapping and expression quantitative trait loci analysis. RESULTS We found that cardiomyocytes of the atria, sinoatrial node, and ventricular conduction system express a short transcript comprising the last 7 exons of the gene (Scn10a-short). Transcription occurs from an intronic enhancer-promoter complex, whereas full-length Scn10a transcript was undetectable in the human and mouse heart. Expression quantitative trait loci analysis revealed that the genetic variants in linkage disequilibrium with genetic variant rs6801957 in the intronic enhancer associate with SCN10A transcript levels in the heart. Genetic modification of the enhancer in the mouse genome led to reduced cardiac Scn10a-short expression in atria and ventricles, reduced cardiac sodium current in atrial cardiomyocytes, atrial conduction slowing and arrhythmia, whereas the expression of Scn5a, the presumed enhancer target gene, remained unaffected. In patch-clamp transfection experiments, expression of Scn10a-short-encoded NaV1.8-short increased NaV1.5-mediated sodium current. We propose that noncoding genetic variation modulates transcriptional regulation of Scn10a-short in cardiomyocytes that impacts NaV1.5-mediated sodium current and heart rhythm. CONCLUSIONS Genetic variants in and around SCN10A modulate enhancer function and expression of a cardiac-specific SCN10A-short transcript. We propose that noncoding genetic variation modulates transcriptional regulation of a functional C-terminal portion of NaV1.8 in cardiomyocytes that impacts on NaV1.5 function, cardiac conduction velocities, and arrhythmia susceptibility.
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Affiliation(s)
- Joyce C K Man
- Department of Medical Biology (J.C.K.M., F.M.B., K.T.S., K.v.D., V.W.W.v.E., A.O.V., B.J.B., P.B., V.M.C.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands.,Amsterdam Cardiovascular Sciences, Amsterdam Reproduction and Development (J.C.K.M., F.M.B., K.T.S., K.v.D., V.W.W.v.E., A.O.V., B.J.B., P.B., V.M.C.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands
| | - Fernanda M Bosada
- Department of Medical Biology (J.C.K.M., F.M.B., K.T.S., K.v.D., V.W.W.v.E., A.O.V., B.J.B., P.B., V.M.C.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands.,Amsterdam Cardiovascular Sciences, Amsterdam Reproduction and Development (J.C.K.M., F.M.B., K.T.S., K.v.D., V.W.W.v.E., A.O.V., B.J.B., P.B., V.M.C.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands
| | - Koen T Scholman
- Department of Medical Biology (J.C.K.M., F.M.B., K.T.S., K.v.D., V.W.W.v.E., A.O.V., B.J.B., P.B., V.M.C.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands.,Amsterdam Cardiovascular Sciences, Amsterdam Reproduction and Development (J.C.K.M., F.M.B., K.T.S., K.v.D., V.W.W.v.E., A.O.V., B.J.B., P.B., V.M.C.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands
| | - Joost A Offerhaus
- Department of Experimental Cardiology (J.A.O., R.W., C.R.B., A.O.V., B.J.B.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands
| | - Roddy Walsh
- Department of Experimental Cardiology (J.A.O., R.W., C.R.B., A.O.V., B.J.B.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands
| | - Karel van Duijvenboden
- Department of Medical Biology (J.C.K.M., F.M.B., K.T.S., K.v.D., V.W.W.v.E., A.O.V., B.J.B., P.B., V.M.C.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands.,Amsterdam Cardiovascular Sciences, Amsterdam Reproduction and Development (J.C.K.M., F.M.B., K.T.S., K.v.D., V.W.W.v.E., A.O.V., B.J.B., P.B., V.M.C.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands
| | - Vincent W W van Eif
- Department of Medical Biology (J.C.K.M., F.M.B., K.T.S., K.v.D., V.W.W.v.E., A.O.V., B.J.B., P.B., V.M.C.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands.,Amsterdam Cardiovascular Sciences, Amsterdam Reproduction and Development (J.C.K.M., F.M.B., K.T.S., K.v.D., V.W.W.v.E., A.O.V., B.J.B., P.B., V.M.C.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands
| | - Connie R Bezzina
- Department of Experimental Cardiology (J.A.O., R.W., C.R.B., A.O.V., B.J.B.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands
| | - Arie O Verkerk
- Department of Medical Biology (J.C.K.M., F.M.B., K.T.S., K.v.D., V.W.W.v.E., A.O.V., B.J.B., P.B., V.M.C.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands.,Department of Experimental Cardiology (J.A.O., R.W., C.R.B., A.O.V., B.J.B.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands.,Amsterdam Cardiovascular Sciences, Amsterdam Reproduction and Development (J.C.K.M., F.M.B., K.T.S., K.v.D., V.W.W.v.E., A.O.V., B.J.B., P.B., V.M.C.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands
| | - Bastiaan J Boukens
- Department of Medical Biology (J.C.K.M., F.M.B., K.T.S., K.v.D., V.W.W.v.E., A.O.V., B.J.B., P.B., V.M.C.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands.,Department of Experimental Cardiology (J.A.O., R.W., C.R.B., A.O.V., B.J.B.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands.,Amsterdam Cardiovascular Sciences, Amsterdam Reproduction and Development (J.C.K.M., F.M.B., K.T.S., K.v.D., V.W.W.v.E., A.O.V., B.J.B., P.B., V.M.C.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands
| | - Phil Barnett
- Department of Medical Biology (J.C.K.M., F.M.B., K.T.S., K.v.D., V.W.W.v.E., A.O.V., B.J.B., P.B., V.M.C.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands.,Amsterdam Cardiovascular Sciences, Amsterdam Reproduction and Development (J.C.K.M., F.M.B., K.T.S., K.v.D., V.W.W.v.E., A.O.V., B.J.B., P.B., V.M.C.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands
| | - Vincent M Christoffels
- Department of Medical Biology (J.C.K.M., F.M.B., K.T.S., K.v.D., V.W.W.v.E., A.O.V., B.J.B., P.B., V.M.C.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands.,Amsterdam Cardiovascular Sciences, Amsterdam Reproduction and Development (J.C.K.M., F.M.B., K.T.S., K.v.D., V.W.W.v.E., A.O.V., B.J.B., P.B., V.M.C.), Amsterdam UMC, University of Amsterdam, location AMC, The Netherlands
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Sebastian S, Nobles M, Tsisanova E, Ludwig A, Munroe PB, Tinker A. The role of resistance to inhibitors of cholinesterase 8b in the control of heart rate. Physiol Genomics 2021; 53:150-159. [PMID: 33719582 DOI: 10.1152/physiolgenomics.00157.2020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
We have assessed the role of ric-b8 in the control of heart rate after the gene was implicated in a recent genome-wide association study of resting heart rate. We developed a novel murine model in which it was possible to conditionally delete ric-8b in the sinoatrial (SA) node after the addition of tamoxifen. Despite this, we were unable to obtain homozygotes and thus studied heterozygotes. Haploinsufficiency of ric-8b in the sinoatrial node induced by the addition of tamoxifen in adult animals leads to mice with a reduced heart rate. However, other electrocardiographic intervals (e.g., PR and QRS) were normal, and there was no apparent arrhythmia such as heart block. The positive chronotropic response to isoprenaline was abrogated, whereas the response to carbachol was unchanged. The pacemaker current If (funny current) has an important role in regulating heart rate, and its function is modulated by both isoprenaline and carbachol. Using a heterologous system expressing HCN4, we show that ric-8b can modulate the HCN4 current. Overexpression of ric-8b led to larger HCN4 currents, whereas silencing ric-8b led to smaller currents. Ric-8b modulates heart rate responses in vivo likely via its actions on the stimulatory G-protein.
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Affiliation(s)
- Sonia Sebastian
- Centre for Clinical Pharmacology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Muriel Nobles
- Centre for Clinical Pharmacology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Elena Tsisanova
- Centre for Clinical Pharmacology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Andreas Ludwig
- Institut für Experimentelle und Klinische Pharmakologie und Toxikologie, Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Patricia B Munroe
- Centre for Clinical Pharmacology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Andrew Tinker
- Centre for 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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Network-driven discovery yields new insight into Shox2-dependent cardiac rhythm control. BIOCHIMICA ET BIOPHYSICA ACTA-GENE REGULATORY MECHANISMS 2021; 1864:194702. [PMID: 33706013 DOI: 10.1016/j.bbagrm.2021.194702] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 02/22/2021] [Accepted: 02/23/2021] [Indexed: 11/23/2022]
Abstract
The homeodomain transcription factor SHOX2 is involved in the development and function of the heart's primary pacemaker, the sinoatrial node (SAN), and has been associated with cardiac conduction-related diseases such as atrial fibrillation and sinus node dysfunction. To shed light on Shox2-dependent genetic processes involved in these diseases, we established a murine embryonic stem cell (ESC) cardiac differentiation model to investigate Shox2 pathways in SAN-like cardiomyocytes. Differential RNA-seq-based expression profiling of Shox2+/+ and Shox2-/- ESCs revealed 94 dysregulated transcripts in Shox2-/- ESC-derived SAN-like cells. Of these, 15 putative Shox2 target genes were selected for further validation based on comparative expression analysis with SAN- and right atria-enriched genes. Network-based analyses, integrating data from the Mouse Organogenesis Cell Atlas and the Ingenuity pathways, as well as validation in mouse and zebrafish models confirmed a regulatory role for the novel identified Shox2 target genes including Cav1, Fkbp10, Igfbp5, Mcf2l and Nr2f2. Our results indicate that genetic networks involving SHOX2 may contribute to conduction traits through the regulation of these genes.
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48
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Weng LC, Hall AW, Choi SH, Jurgens SJ, Haessler J, Bihlmeyer NA, Grarup N, Lin H, Teumer A, Li-Gao R, Yao J, Guo X, Brody JA, Müller-Nurasyid M, Schramm K, Verweij N, van den Berg ME, van Setten J, Isaacs A, Ramírez J, Warren HR, Padmanabhan S, Kors JA, de Boer RA, van der Meer P, Sinner MF, Waldenberger M, Psaty BM, Taylor KD, Völker U, Kanters JK, Li M, Alonso A, Perez MV, Vaartjes I, Bots ML, Huang PL, Heckbert SR, Lin HJ, Kornej J, Munroe PB, van Duijn CM, Asselbergs FW, Stricker BH, van der Harst P, Kääb S, Peters A, Sotoodehnia N, Rotter JI, Mook-Kanamori DO, Dörr M, Felix SB, Linneberg A, Hansen T, Arking DE, Kooperberg C, Benjamin EJ, Lunetta KL, Ellinor PT, Lubitz SA. Genetic Determinants of Electrocardiographic P-Wave Duration and Relation to Atrial Fibrillation. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2020; 13:387-395. [PMID: 32822252 PMCID: PMC7578098 DOI: 10.1161/circgen.119.002874] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
BACKGROUND The P-wave duration (PWD) is an electrocardiographic measurement that represents cardiac conduction in the atria. Shortened or prolonged PWD is associated with atrial fibrillation (AF). We used exome-chip data to examine the associations between common and rare variants with PWD. METHODS Fifteen studies comprising 64 440 individuals (56 943 European, 5681 African, 1186 Hispanic, 630 Asian) and ≈230 000 variants were used to examine associations with maximum PWD across the 12-lead ECG. Meta-analyses summarized association results for common variants; gene-based burden and sequence kernel association tests examined low-frequency variant-PWD associations. Additionally, we examined the associations between PWD loci and AF using previous AF genome-wide association studies. RESULTS We identified 21 common and low-frequency genetic loci (14 novel) associated with maximum PWD, including several AF loci (TTN, CAND2, SCN10A, PITX2, CAV1, SYNPO2L, SOX5, TBX5, MYH6, RPL3L). The top variants at known sarcomere genes (TTN, MYH6) were associated with longer PWD and increased AF risk. However, top variants at other loci (eg, PITX2 and SCN10A) were associated with longer PWD but lower AF risk. CONCLUSIONS Our results highlight multiple novel genetic loci associated with PWD, and underscore the shared mechanisms of atrial conduction and AF. Prolonged PWD may be an endophenotype for several different genetic mechanisms of AF.
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Affiliation(s)
- Lu-Chen Weng
- Cardiovascular Rsrch Ctr, MGH, Boston
- Cardiovascular Disease Initiative, The Broad Inst of MIT & Harvard, Cambridge, MA
| | - Amelia Weber Hall
- Cardiovascular Rsrch Ctr, MGH, Boston
- Cardiovascular Disease Initiative, The Broad Inst of MIT & Harvard, Cambridge, MA
| | - Seung Hoan Choi
- Cardiovascular Disease Initiative, The Broad Inst of MIT & Harvard, Cambridge, MA
| | - Sean J. Jurgens
- Cardiovascular Disease Initiative, The Broad Inst of MIT & Harvard, Cambridge, MA
| | - Jeffrey Haessler
- Fred Hutchinson Cancer Rsrch Ctr, Division of Public Health Sciences, Seattle WA
| | - Nathan A. Bihlmeyer
- McKusick-Nathans Dept of Genetic Medicine, Johns Hopkins Univ School of Med, Baltimore, MD
| | - Niels Grarup
- Novo Nordisk Foundation Ctr for Basic Metabolic Rsrch, Faculty of Health & Med Sciences, Univ of Copenhagen, Copenhagen, Denmark
| | - Honghuang Lin
- Boston Univ & NHLBI’s Framingham Heart Study, Framingham
- Section of Computational Biomedicine, Dept of Med, Boston Univ School of Med, Boston, MA
| | - Alexander Teumer
- DZHK (German Ctr for Cardiovascular Rsrch), partner site Greifswald
- Inst for Community Med, Univ Medicine Greifswald, Greifswald, Germany
| | - Ruifang Li-Gao
- Dept of Clinical Epidemiology, Leiden Univ Medical Ctr, the Netherlands
| | - Jie Yao
- The Inst for Translational Genomics & Population Sciences at Harbor-UCLA Medical Ctr, Torrance
| | - Xiuqing Guo
- The Inst for Translational Genomics & Population Sciences at Harbor-UCLA Medical Ctr, Torrance
- Dept of Pediatrics, David Geffen School of Med at UCLA, Los Angeles, CA
| | - Jennifer A. Brody
- Cardiovascular Health Rsrch Unit, Dept of Med, Dept of Epidemiology, Univ of Washington
| | - Martina Müller-Nurasyid
- Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich
- Dept of Internal Med I (Cardiology), Hospital of the Ludwig-Maximilians-Univ (LMU) Munich, Munich
- Inst of Genetic Epidemiology, Helmholtz Zentrum München - German Rsrch Ctr for Environmental Health, Neuherberg, Germany
| | - Katharina Schramm
- Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich
- Dept of Internal Med I (Cardiology), Hospital of the Ludwig-Maximilians-Univ (LMU) Munich, Munich
- Inst of Genetic Epidemiology, Helmholtz Zentrum München - German Rsrch Ctr for Environmental Health, Neuherberg, Germany
| | - Niek Verweij
- Genomics plc, Oxford, UK
- Dept of Cardiology, Univ of Groningen & Univ Medical Ctr, Groningen
| | - Marten E. van den Berg
- Dept of Epidemiology, Division of Heart & Lungs, Univ of Utrecht, Univ Medical Ctr Utrecht
| | - Jessica van Setten
- Dept of Cardiology, Division of Heart & Lungs, Univ of Utrecht, Univ Medical Ctr Utrecht
| | - Aaron Isaacs
- CARIM School for Cardiovascular Diseases, Maastricht Univ, Maastricht, the Netherlands
- Dept of Physiology, Maastricht Univ, Maastricht, the Netherlands
| | - Julia Ramírez
- Nat Inst for Health Rsrch, Barts Cardiovascular Biomedical Rsrch Ctr, Barts & The London School of Med & Dentistry, Queen Mary Univ of London, London
- William Harvey Rsrch Inst, Barts & The London School of Med & Dentistry, Queen Mary Univ of London, London
| | - Helen R. Warren
- Nat Inst for Health Rsrch, Barts Cardiovascular Biomedical Rsrch Ctr, Barts & The London School of Med & Dentistry, Queen Mary Univ of London, London
- William Harvey Rsrch Inst, Barts & The London School of Med & Dentistry, Queen Mary Univ of London, London
| | - Sandosh Padmanabhan
- Inst of Cardiovascular & Medical Sciences, College of Medical, Veterinary & Life Sciences, Univ of Glasgow, Glasgow, UK
| | - Jan A. Kors
- Dept of Med Informatics, Erasmus Univ Medical Ctr, Rotterdam, the Netherlands
| | | | | | - Moritz F. Sinner
- Dept of Internal Med I (Cardiology), Hospital of the Ludwig-Maximilians-Univ (LMU) Munich, Munich
- DZHK (German Ctr for Cardiovascular Rsrch), partner site Munich Heart Alliance, Munich
| | - Melanie Waldenberger
- DZHK (German Ctr for Cardiovascular Rsrch), partner site Munich Heart Alliance, Munich
- Inst of Epidemiology, Helmholtz Zentrum München - German Rsrch Ctr for Environmental Health, Neuherberg, Germany
- Rsrch unit of Molecular Epidemiology, Helmholtz Zentrum München - German Rsrch Ctr for Environmental Health, Neuherberg, Germany
| | - Bruce M. Psaty
- Cardiovascular Health Rsrch Unit, Depts of Med, Epidemiology & Health Services, Dept of Epidemiology, Univ of Washington
- Kaiser Permanente Washington Health Rsrch Inst, Seattle, WA
| | - Kent D. Taylor
- The Inst for Translational Genomics & Population Sciences at Harbor-UCLA Medical Ctr, Torrance
- Dept of Pediatrics, David Geffen School of Med at UCLA, Los Angeles, CA
| | - Uwe Völker
- DZHK (German Ctr for Cardiovascular Rsrch), partner site Greifswald
- Interfaculty Inst for Genetics & Functional Genomics, Univ Medicine Greifswald, Greifswald, Germany
| | - Jørgen K. Kanters
- Lab of Experimental Cardiology, Faculty of Health & Med Sciences, Univ of Copenhagen, Copenhagen, Denmark
| | - Man Li
- Division of Nephrology & Hypertensions, Dept of Internal Med, Univ of Utah School of Med, Salt Lake City, UT
| | - Alvaro Alonso
- Dept of Epidemiology, Rollins School of Public Health, Emory Univ, Atlanta, GA
| | | | - Ilonca Vaartjes
- Julius Ctr for Health Sciences & Primary Care, Univ Medical Ctr Utrecht, Utrecht Univ, the Netherlands
| | - Michiel L. Bots
- Julius Ctr for Health Sciences & Primary Care, Univ Medical Ctr Utrecht, Utrecht Univ, the Netherlands
| | | | - Susan R. Heckbert
- Cardiovascular Health Rsrch Unit, Dept of Epidemiology, Univ of Washington
| | - Henry J. Lin
- The Inst for Translational Genomics & Population Sciences at Harbor-UCLA Medical Ctr, Torrance
- Dept of Pediatrics, David Geffen School of Med at UCLA, Los Angeles, CA
| | - Jelena Kornej
- Boston Univ & NHLBI’s Framingham Heart Study, Framingham
| | - Patricia B. Munroe
- Nat Inst for Health Rsrch, Barts Cardiovascular Biomedical Rsrch Ctr, Barts & The London School of Med & Dentistry, Queen Mary Univ of London, London
- William Harvey Rsrch Inst, Barts & The London School of Med & Dentistry, Queen Mary Univ of London, London
| | - Cornelia M. van Duijn
- Dept of Epidemiology, Erasmus Univ Medical Ctr, Rotterdam, the Netherlands
- Nuffield Dept of Population Health, Medical Sciences Division, St. Cross College, Oxford Univ, Oxford
| | - Folkert W. Asselbergs
- Dept of Cardiology, Division of Heart & Lungs, Univ of Utrecht, Univ Medical Ctr Utrecht
- Health Data Rsrch UK & Inst of Health Informatics, Faculty of Population Health Sciences, Univ College London, London, UK
- Inst of Cardiovascular Science, Faculty of Population Health Sciences, Univ College London, London, UK
| | - Bruno H. Stricker
- Dept of Internal Medicine, Division of Heart & Lungs, Univ of Utrecht, Univ Medical Ctr Utrecht
- Dept of Med Informatics, Erasmus MC, Medical Ctr Rotterdam, Division of Heart & Lungs, Univ of Utrecht, Univ Medical Ctr Utrecht
- Inspectorate of Health Care
| | - Pim van der Harst
- Dept of Cardiology, Univ of Groningen & Univ Medical Ctr, Groningen
- Durrer Ctr for Cardiogenetic Rsrch, ICIN-Netherlands Heart Inst, Utrecht, the Netherlands
- Dept of Genetics, Univ of Groningen & Univ Medical Ctr, Groningen
| | - Stefan Kääb
- Dept of Internal Med I (Cardiology), Hospital of the Ludwig-Maximilians-Univ (LMU) Munich, Munich
- DZHK (German Ctr for Cardiovascular Rsrch), partner site Munich Heart Alliance, Munich
| | - Annette Peters
- DZHK (German Ctr for Cardiovascular Rsrch), partner site Munich Heart Alliance, Munich
- Inst of Epidemiology, Helmholtz Zentrum München - German Rsrch Ctr for Environmental Health, Neuherberg, Germany
- German Ctr for Diabetes Rsrch, Neuherberg, Germany
| | - Nona Sotoodehnia
- Cardiovascular Health Rsrch Unit, Dept of Med, Dept of Epidemiology, Univ of Washington
| | - Jerome I. Rotter
- The Inst for Translational Genomics & Population Sciences at Harbor-UCLA Medical Ctr, Torrance
- Depts of Pediatrics & Human Genetics, David Geffen School of Med at UCLA, Los Angeles, CA
| | - Dennis O. Mook-Kanamori
- Dept of Clinical Epidemiology, Leiden Univ Medical Ctr, the Netherlands
- Dept of Public Health & Primary Care, Leiden Univ Medical Ctr, the Netherlands
| | - Marcus Dörr
- DZHK (German Ctr for Cardiovascular Rsrch), partner site Greifswald
- Dept of Internal Med B, Univ Medicine Greifswald, Greifswald, Germany
| | - Stephan B. Felix
- DZHK (German Ctr for Cardiovascular Rsrch), partner site Greifswald
- Dept of Internal Med B, Univ Medicine Greifswald, Greifswald, Germany
| | - Allan Linneberg
- Ctr for Clinical Rsrch & Prevention, Bispebjerg & Frederiksberg Hospital, Copenhagen, Denamrk
- Dept of Clinical Med, Faculty of Health & Med Sciences, Univ of Copenhagen, Copenhagen, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Ctr for Basic Metabolic Rsrch, Faculty of Health & Med Sciences, Univ of Copenhagen, Copenhagen, Denmark
| | - Dan E. Arking
- McKusick-Nathans Dept of Genetic Medicine, Johns Hopkins Univ School of Med, Baltimore, MD
| | - Charles Kooperberg
- Fred Hutchinson Cancer Rsrch Ctr, Division of Public Health Sciences, Seattle WA
| | - Emelia J. Benjamin
- Boston Univ & NHLBI’s Framingham Heart Study, Framingham
- Dept of Epidemiology, Boston Univ School of Public Health, Boston, MA
- Dept of Med, Boston Univ School of Med, Boston, MA
| | - Kathryn L. Lunetta
- Boston Univ & NHLBI’s Framingham Heart Study, Framingham
- Dept of Biostatistics, Boston Univ School of Public Health, Boston, MA
| | - Patrick T. Ellinor
- Cardiovascular Rsrch Ctr, MGH, Boston
- Cardiovascular Disease Initiative, The Broad Inst of MIT & Harvard, Cambridge, MA
- Cardiac Arrhythmia Service, MGH, Boston
| | - Steven A. Lubitz
- Cardiovascular Rsrch Ctr, MGH, Boston
- Cardiovascular Disease Initiative, The Broad Inst of MIT & Harvard, Cambridge, MA
- Cardiac Arrhythmia Service, MGH, Boston
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49
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Ramírez J, van Duijvenboden S, Young WJ, Orini M, Lambiase PD, Munroe PB, Tinker A. Common Genetic Variants Modulate the Electrocardiographic Tpeak-to-Tend Interval. Am J Hum Genet 2020; 106:764-778. [PMID: 32386560 PMCID: PMC7273524 DOI: 10.1016/j.ajhg.2020.04.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Accepted: 04/08/2020] [Indexed: 02/06/2023] Open
Abstract
Sudden cardiac death is responsible for half of all deaths from cardiovascular disease. The analysis of the electrophysiological substrate for arrhythmias is crucial for optimal risk stratification. A prolonged T-peak-to-Tend (Tpe) interval on the electrocardiogram is an independent predictor of increased arrhythmic risk, and Tpe changes with heart rate are even stronger predictors. However, our understanding of the electrophysiological mechanisms supporting these risk factors is limited. We conducted genome-wide association studies (GWASs) for resting Tpe and Tpe response to exercise and recovery in ∼30,000 individuals, followed by replication in independent samples (∼42,000 for resting Tpe and ∼22,000 for Tpe response to exercise and recovery), all from UK Biobank. Fifteen and one single-nucleotide variants for resting Tpe and Tpe response to exercise, respectively, were formally replicated. In a full dataset GWAS, 13 further loci for resting Tpe, 1 for Tpe response to exercise and 1 for Tpe response to exercise were genome-wide significant (p ≤ 5 × 10-8). Sex-specific analyses indicated seven additional loci. In total, we identify 32 loci for resting Tpe, 3 for Tpe response to exercise and 3 for Tpe response to recovery modulating ventricular repolarization, as well as cardiac conduction and contraction. Our findings shed light on the genetic basis of resting Tpe and Tpe response to exercise and recovery, unveiling plausible candidate genes and biological mechanisms underlying ventricular excitability.
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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
| | - William J Young
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK; Barts Heart Centre, St Bartholomew's Hospital, London EC1A 7BE, UK
| | - Michele Orini
- 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; Barts Heart Centre, St Bartholomew's Hospital, London EC1A 7BE, UK
| | - Pier D Lambiase
- Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK; Barts Heart Centre, St Bartholomew's 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 Unit, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, 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 Unit, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK.
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