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Eunjin B, Ji Y, Jo J, Kim Y, Lee JP, Won S, Lee J. Effects of polygenic risk score and sodium and potassium intake on hypertension in Asians: A nationwide prospective cohort study. Hypertens Res 2024:10.1038/s41440-024-01784-7. [PMID: 38982292 DOI: 10.1038/s41440-024-01784-7] [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: 07/28/2023] [Revised: 06/11/2024] [Accepted: 06/15/2024] [Indexed: 07/11/2024]
Abstract
Genetic factors, lifestyle, and diet have been shown to play important roles in the development of hypertension. Increased salt intake is an important risk factor for hypertension. However, research on the involvement of genetic factors in the relationship between salt intake and hypertension in Asians is lacking. We aimed to investigate the risk of hypertension in relation to sodium and potassium intake and the effects of genetic factors on their interactions. We used Korean Genome and Epidemiology Study data and calculated the polygenic risk score (PRS) for the effect of systolic and diastolic blood pressure (SBP and DBP). We also conducted multivariable logistic modeling to evaluate associations among incident hypertension, PRSSBP, PRSDBP, and sodium and potassium intake. In total, 41,351 subjects were included in the test set. The top 10% PRSSBP group was the youngest of the three groups (bottom 10%, middle, top 10%), had the highest proportion of women, and had the highest body mass index, baseline BP, red meat intake, and alcohol consumption. The multivariable logistic regression model revealed the risk of hypertension was significantly associated with higher PRSSBP, higher sodium intake, and lower potassium intake. There was significant interaction between sodium intake and PRSSBP for incident hypertension especially in sodium intake ≥2.0 g/day and PRSSBP top 10% group (OR 1.27 (1.07-1.51), P = 0.007). Among patients at a high risk of incident hypertension due to sodium intake, lifestyle modifications and sodium restriction were especially important to prevent hypertension.
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Affiliation(s)
- Bae Eunjin
- Department of Internal Medicine, Gyeongsang National University Changwon Hospital, Changwon, Republic of Korea
- Department of Internal Medicine, College of Medicine, Gyeongsang National University, Jinju, Republic of Korea
- Institute of Medical Science, College of Medicine, Gyeongsang National University, Jinju, Republic of Korea
| | - Yunmi Ji
- College of Natural Sciences, Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea
| | - Jinyeon Jo
- Department of Public Health Sciences, Institute of Health & Environment, Seoul National University, Seoul, Republic of Korea
| | - Yaerim Kim
- Department of Internal Medicine, College of Medicine, Keimyung University School of Medicine, Daegu, Republic of Korea
| | - Jung Pyo Lee
- Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul, Republic of Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Sungho Won
- Department of Public Health Sciences, Institute of Health & Environment, Seoul National University, Seoul, Republic of Korea.
- Interdisciplinary Program for Bioinformatics, College of Natural Science, Seoul National University, Seoul, Republic of Korea.
- RexSoft Corps, Seoul, Republic of Korea.
| | - Jeonghwan Lee
- Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul, Republic of Korea.
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.
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2
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Zou Z, Ohta T, Oki S. ChIP-Atlas 3.0: a data-mining suite to explore chromosome architecture together with large-scale regulome data. Nucleic Acids Res 2024; 52:W45-W53. [PMID: 38749504 PMCID: PMC11223792 DOI: 10.1093/nar/gkae358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Revised: 04/18/2024] [Accepted: 04/23/2024] [Indexed: 07/06/2024] Open
Abstract
ChIP-Atlas (https://chip-atlas.org/) presents a suite of data-mining tools for analyzing epigenomic landscapes, powered by the comprehensive integration of over 376 000 public ChIP-seq, ATAC-seq, DNase-seq and Bisulfite-seq experiments from six representative model organisms. To unravel the intricacies of chromatin architecture that mediates the regulome-initiated generation of transcriptional and phenotypic diversity within cells, we report ChIP-Atlas 3.0 that enhances clarity by incorporating additional tracks for genomic and epigenomic features within a newly consolidated 'annotation track' section. The tracks include chromosomal conformation (Hi-C and eQTL datasets), transcriptional regulatory elements (ChromHMM and FANTOM5 enhancers), and genomic variants associated with diseases and phenotypes (GWAS SNPs and ClinVar variants). These annotation tracks are easily accessible alongside other experimental tracks, facilitating better elucidation of chromatin architecture underlying the diversification of transcriptional and phenotypic traits. Furthermore, 'Diff Analysis,' a new online tool, compares the query epigenome data to identify differentially bound, accessible, and methylated regions using ChIP-seq, ATAC-seq and DNase-seq, and Bisulfite-seq datasets, respectively. The integration of annotation tracks and the Diff Analysis tool, coupled with continuous data expansion, renders ChIP-Atlas 3.0 a robust resource for mining the landscape of transcriptional regulatory mechanisms, thereby offering valuable perspectives, particularly for genetic disease research and drug discovery.
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Affiliation(s)
- Zhaonan Zou
- Institute of Resource Development and Analysis, Kumamoto University, 2-2-1 Honjo, Chuo-ku, Kumamoto 860-0811, Japan
- Department of Drug Discovery Medicine, Kyoto University Graduate School of Medicine, 53 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Tazro Ohta
- Institute for Advanced Academic Research, Chiba University,1-33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan
- Department of Artificial Intelligence Medicine, Graduate School of Medicine, Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan
- Database Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Yata 1111, Mishima, Shizuoka 411-8540, Japan
| | - Shinya Oki
- Institute of Resource Development and Analysis, Kumamoto University, 2-2-1 Honjo, Chuo-ku, Kumamoto 860-0811, Japan
- Department of Drug Discovery Medicine, Kyoto University Graduate School of Medicine, 53 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
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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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Vad OB, Monfort LM, Paludan-Müller C, Kahnert K, Diederichsen SZ, Andreasen L, Lotta LA, Nielsen JB, Lundby A, Svendsen JH, Olesen MS. Rare and Common Genetic Variation Underlying Atrial Fibrillation Risk. JAMA Cardiol 2024:2820520. [PMID: 38922602 PMCID: PMC11209175 DOI: 10.1001/jamacardio.2024.1528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 04/16/2024] [Indexed: 06/27/2024]
Abstract
Importance Atrial fibrillation (AF) has a substantial genetic component. The importance of polygenic risk is well established, while the contribution of rare variants to disease risk warrants characterization in large cohorts. Objective To identify rare predicted loss-of-function (pLOF) variants associated with AF and elucidate their role in risk of AF, cardiomyopathy (CM), and heart failure (HF) in combination with a polygenic risk score (PRS). Design, Setting, and Participants This was a genetic association and nested case-control study. The impact of rare pLOF variants was evaluated on the risk of incident AF. HF and CM were assessed in cause-specific Cox regressions. End of follow-up was July 1, 2022. Data were analyzed from January to October 2023. The UK Biobank enrolled 502 480 individuals aged 40 to 69 years at inclusion in the United Kingdom between March 13, 2006, and October 1, 2010. UK residents of European ancestry were included. Individuals with prior diagnosis of AF were excluded from analyses of incident AF. Exposures Rare pLOF variants and an AF PRS. Main Outcomes and Measures Risk of AF and incident HF or CM prior to and subsequent to AF diagnosis. Results A total of 403 990 individuals (218 489 [54.1%] female) with a median (IQR) age of 58 (51-63) years were included; 24 447 were diagnosed with incident AF over a median (IQR) follow-up period of 13.3 (12.4-14.0) years. Rare pLOF variants in 6 genes (TTN, RPL3L, PKP2, CTNNA3, KDM5B, and C10orf71) were associated with AF. Of these, TTN, RPL3L, PKP2, CTNNA3, and KDM5B replicated in an external cohort. Combined with high PRS, rare pLOF variants conferred an odds ratio of 7.08 (95% CI, 6.03-8.28) for AF. Carriers with high PRS also had a substantial 10-year risk of AF (16% in female individuals and 24% in male individuals older than 60 years). Rare pLOF variants were associated with increased risk of CM both prior to AF (hazard ratio [HR], 3.13; 95% CI, 2.24-4.36) and subsequent to AF (HR, 2.98; 95% CI, 1.89-4.69). Conclusions and Relevance Rare and common genetic variation were associated with an increased risk of AF. The findings provide insights into the genetic underpinnings of AF and may aid in future genetic risk stratification.
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Affiliation(s)
- Oliver B. Vad
- Department of Cardiology, The Heart Centre, Copenhagen University Hospital – Rigshospitalet, Copenhagen, Denmark
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Laia M. Monfort
- Department of Cardiology, The Heart Centre, Copenhagen University Hospital – Rigshospitalet, Copenhagen, Denmark
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Christian Paludan-Müller
- Department of Cardiology, The Heart Centre, Copenhagen University Hospital – Rigshospitalet, Copenhagen, Denmark
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Konstantin Kahnert
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Søren Z. Diederichsen
- Department of Cardiology, The Heart Centre, Copenhagen University Hospital – Rigshospitalet, Copenhagen, Denmark
| | - Laura Andreasen
- Department of Cardiology, The Heart Centre, Copenhagen University Hospital – Rigshospitalet, Copenhagen, Denmark
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | | | - Alicia Lundby
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jesper H. Svendsen
- Department of Cardiology, The Heart Centre, Copenhagen University Hospital – Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Morten S. Olesen
- Department of Cardiology, The Heart Centre, Copenhagen University Hospital – Rigshospitalet, Copenhagen, Denmark
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Gibson JT, Rudd JHF. Polygenic risk scores in atrial fibrillation: Associations and clinical utility in disease prediction. Heart Rhythm 2024; 21:913-918. [PMID: 38336192 DOI: 10.1016/j.hrthm.2024.02.006] [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: 09/04/2023] [Revised: 02/02/2024] [Accepted: 02/03/2024] [Indexed: 02/12/2024]
Abstract
Atrial fibrillation (AF) is a common heart arrhythmia and a major cause of cardioembolic stroke. Therefore, accurate prediction is desirable to allow high-risk individuals to be identified early and their risk lowered before complications arise. Polygenic risk scores (PRSs) have become a popular method of quantifying aggregated genetic risk from common variants, but their clinical value in AF remains uncertain. This literature review summarizes the associations between PRS and AF risk and discusses the evidence for the clinical utility of PRS for AF prediction. Stroke risk in patients with AF is also considered. Despite consistent associations between PRS and AF risk, the performance of PRS as a stand-alone tool for AF prediction was poor. However, addition of PRS to the existing AF prediction models commonly improved the predictive performance above that of the clinical models alone, including in cohorts with comorbid cardiovascular disease. Associations between PRS and cardioembolic stroke risk in patients with AF have also been reported, but improvements in stroke prediction models from PRS have been minimal. PRS are likely to add value to the existing clinical AF prediction models; however, standardization of PRS across studies and populations will likely be required before they can be meaningfully adopted into routine clinical practice.
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Affiliation(s)
- Joel T Gibson
- Department of Medical Genetics, University of Cambridge, Lv 6 Addenbrooke's Treatment Centre, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - James H F Rudd
- Heart and Lung Research Institute, University of Cambridge, Cambridge, United Kingdom.
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6
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Seo Y, Bae H, Lee C. Bayesian colocalization of GWAS and eQTL signals reveals cell type-specific genes and regulatory variants for susceptibility to subtypes of ischemic stroke. Comput Biol Chem 2024; 110:108086. [PMID: 38744227 DOI: 10.1016/j.compbiolchem.2024.108086] [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: 02/14/2024] [Revised: 04/09/2024] [Accepted: 04/23/2024] [Indexed: 05/16/2024]
Abstract
A colocalization analysis of genome-wide association study (GWAS) signals and expression quantitative trait loci (eQTL) was conducted to pinpoint target genes and their regulatory nucleotide variants for subtypes of ischemic stroke. We utilized GWAS data from prominent meta-analysis consortia (MEGASTROKE and GIGASTROKE) and single-cell eQTL data in brain and blood tissues to enhance accuracy and minimize noise inherent in bulk RNA-seq. Employing Bayesian colocalization methods, we identified ten shared loci between GWAS and eQTL signals, targeting five eGenes. Specifically, RAPH1 and ICA1L were discovered for small vessel stroke (SVS), whereas SCYL3, CAV1, and CAV2 were for cardioembolic stroke (CS). However, no findings have been made for large artery stroke. The exploration and subsequent functional analysis of causal variants within the colocalized regions revealed their regulatory roles, particularly as enhancer variants (e.g., rs144505847 and rs72932755 targeting ICA1L; rs629234 targeting SCYL3; rs3807989 targeting CAV1 and CAV2). Notably, our study unveiled that all eQTL for CS were identified in oligodendrocytes, while those for SVS were across excitatory neurons, astrocytes, and oligodendrocyte precursor cells. This underscores the heterogeneous tissue-specific genetic factors by subtypes of ischemic stroke. The study emphasizes the need for intensive research efforts to discover causative genes and variants, unravelling the cell type-specific genetic architecture of ischemic stroke subtypes. This knowledge is crucial for advancing our understanding of the underlying pathophysiology and paving the way for precision neurology applications.
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Affiliation(s)
- Yunji Seo
- Department of Bioinformatics and Life Science, Soongsil University, 369 Sangdo-ro, Dongjak-gu, Seoul 06978, South Korea
| | - Hojin Bae
- Department of Bioinformatics and Life Science, Soongsil University, 369 Sangdo-ro, Dongjak-gu, Seoul 06978, South Korea
| | - Chaeyoung Lee
- Department of Bioinformatics and Life Science, Soongsil University, 369 Sangdo-ro, Dongjak-gu, Seoul 06978, South Korea.
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Liuzzo G, Pedicino D. Weekly journal scan: the KCa2 potassium channel as a promising target for the pharmacologic cardioversion of atrial fibrillation. Eur Heart J 2024; 45:1699-1700. [PMID: 38558097 DOI: 10.1093/eurheartj/ehae138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/04/2024] Open
Affiliation(s)
- Giovanna Liuzzo
- Department of Cardiovascular Sciences, Fondazione Policlinico Universitario A. Gemelli-IRCCS, Largo A. Gemelli 8, Rome 00168, Italy
- Department of Cardiovascular and Pulmonary Sciences, Catholic University School of Medicine, Largo F.Vito 1, Rome 00168, Italy
| | - Daniela Pedicino
- Department of Cardiovascular Sciences, Fondazione Policlinico Universitario A. Gemelli-IRCCS, Largo A. Gemelli 8, Rome 00168, Italy
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Zhao S, Hulsurkar MM, Lahiri SK, Aguilar-Sanchez Y, Munivez E, Müller FU, Jain A, Malovannaya A, Yiu CHK, Reilly S, Wehrens XHT. Atrial proteomic profiling reveals a switch towards profibrotic gene expression program in CREM-IbΔC-X mice with persistent atrial fibrillation. J Mol Cell Cardiol 2024; 190:1-12. [PMID: 38514002 DOI: 10.1016/j.yjmcc.2024.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 02/19/2024] [Accepted: 03/18/2024] [Indexed: 03/23/2024]
Abstract
BACKGROUND Overexpression of the CREM (cAMP response element-binding modulator) isoform CREM-IbΔC-X in transgenic mice (CREM-Tg) causes the age-dependent development of spontaneous AF. PURPOSE To identify key proteome signatures and biological processes accompanying the development of persistent AF through integrated proteomics and bioinformatics analysis. METHODS Atrial tissue samples from three CREM-Tg mice and three wild-type littermates were subjected to unbiased mass spectrometry-based quantitative proteomics, differential expression and pathway enrichment analysis, and protein-protein interaction (PPI) network analysis. RESULTS A total of 98 differentially expressed proteins were identified. Gene ontology analysis revealed enrichment for biological processes regulating actin cytoskeleton organization and extracellular matrix (ECM) dynamics. Changes in ITGAV, FBLN5, and LCP1 were identified as being relevant to atrial fibrosis and structural based on expression changes, co-expression patterns, and PPI network analysis. Comparative analysis with previously published datasets revealed a shift in protein expression patterns from ion-channel and metabolic regulators in young CREM-Tg mice to profibrotic remodeling factors in older CREM-Tg mice. Furthermore, older CREM-Tg mice exhibited protein expression patterns reminiscent of those seen in humans with persistent AF. CONCLUSIONS This study uncovered distinct temporal changes in atrial protein expression patterns with age in CREM-Tg mice consistent with the progressive evolution of AF. Future studies into the role of the key differentially abundant proteins identified in this study in AF progression may open new therapeutic avenues to control atrial fibrosis and substrate development in AF.
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Affiliation(s)
- Shuai Zhao
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA; Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Mohit M Hulsurkar
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA; Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Satadru K Lahiri
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA; Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Yuriana Aguilar-Sanchez
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA; Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Elda Munivez
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA; Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Frank Ulrich Müller
- Institute of Pharmacology and Toxicology, University of Münster, Münster, Germany
| | - Antrix Jain
- Mass Spectrometry Proteomics Core, Baylor College of Medicine, Houston, TX, USA
| | - Anna Malovannaya
- Mass Spectrometry Proteomics Core, Baylor College of Medicine, Houston, TX, USA; Department of Biochemistry, Baylor College of Medicine, Houston, TX 77030, USA
| | - Chi Him Kendrick Yiu
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, British Heart Foundation Centre of Research Excellence, NIHR Oxford BRC, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Svetlana Reilly
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, British Heart Foundation Centre of Research Excellence, NIHR Oxford BRC, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Xander H T Wehrens
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA; Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA; Department of Medicine (in Cardiology), Baylor College of Medicine, Houston, TX 77030, USA; Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA; Department of Pediatrics (in Cardiology), Baylor College of Medicine, Houston, TX 77030, USA; Center for Space Medicine, Baylor College of Medicine, Houston, USA.
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Tsai PC, Ko AMS, Chen YL, Chiu CH, Yeh YH, Tsai FC. Exosomal miRNA Changes Associated with Restoration to Sinus Rhythm in Atrial Fibrillation Patients. Int J Mol Sci 2024; 25:3861. [PMID: 38612670 PMCID: PMC11011649 DOI: 10.3390/ijms25073861] [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: 03/12/2024] [Revised: 03/26/2024] [Accepted: 03/29/2024] [Indexed: 04/14/2024] Open
Abstract
We aimed to identify serum exosomal microRNAs (miRNAs) associated with the transition from atrial fibrillation (AF) to sinus rhythm (SR) and investigate their potential as biomarkers for the early recurrence of AF within three months post-treatment. We collected blood samples from eight AF patients at Chang Gung Memorial Hospital in Taiwan both immediately before and within 14 days following rhythm control treatment. Exosomes were isolated from these samples, and small RNA sequencing was performed. Using DESeq2 analysis, we identified nine miRNAs (16-2-3p, 22-3p, 23a-3p, 23b-3p, 125a-5p, 328-3p, 423-5p, 504-5p, and 582-3p) associated with restoration to SR. Further analysis using the DIABLO model revealed a correlation between the decreased expression of miR-125a-5p and miR-328-3p and the early recurrence of AF. Furthermore, early recurrence is associated with a longer duration of AF, presumably indicating a more extensive state of underlying cardiac remodeling. In addition, the reads were mapped to mRNA sequences, leading to the identification of 14 mRNAs (AC005041.1, ARHGEF12, AMT, ANO8, BCL11A, DIO3OS, EIF4ENIF1, G2E3-AS1, HERC3, LARS, NT5E, PITX1, SLC16A12, and ZBTB21) associated with restoration to SR. Monitoring these serum exosomal miRNA and mRNA expression patterns may be beneficial for optimizing treatment outcomes in AF patients.
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Affiliation(s)
- Pei-Chien Tsai
- Department of Biomedical Sciences, Chang Gung University, Taoyuan City 33302, Taiwan; (P.-C.T.); (A.M.-S.K.); (Y.-L.C.)
- Healthy Aging Research Center, Chang Gung University, Taoyuan City 33302, Taiwan
- Molecular Infectious Disease Research Center, Chang Gung Memorial Hospital, Taoyuan City 33305, Taiwan
| | - Albert Min-Shan Ko
- Department of Biomedical Sciences, Chang Gung University, Taoyuan City 33302, Taiwan; (P.-C.T.); (A.M.-S.K.); (Y.-L.C.)
- Healthy Aging Research Center, Chang Gung University, Taoyuan City 33302, Taiwan
- Cardiovascular Department, Chang Gung Memorial Hospital, Taoyuan City 33305, Taiwan
| | - Yu-Lin Chen
- Department of Biomedical Sciences, Chang Gung University, Taoyuan City 33302, Taiwan; (P.-C.T.); (A.M.-S.K.); (Y.-L.C.)
| | - Cheng-Hsun Chiu
- Molecular Infectious Disease Research Center, Chang Gung Memorial Hospital, Taoyuan City 33305, Taiwan
- Division of Pediatric Infectious Diseases, Department of Pediatrics, Chang Gung Memorial Hospital, Taoyuan City 33305, Taiwan
| | - Yung-Hsin Yeh
- Cardiovascular Department, Chang Gung Memorial Hospital, Taoyuan City 33305, Taiwan
- School of Medicine, Chang Gung University, Taoyuan City 33302, Taiwan
| | - Feng-Chun Tsai
- Department of Surgery, College of Medicine, Kaohsiung Medical University, Kaohsiung City 80708, Taiwan
- Division of Cardiovascular Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung City 80708, Taiwan
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10
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Wang H, Lin K, Zhang Q, Shi J, Song X, Wu J, Zhao C, He K. HyperTMO: a trusted multi-omics integration framework based on hypergraph convolutional network for patient classification. Bioinformatics 2024; 40:btae159. [PMID: 38530977 PMCID: PMC11212491 DOI: 10.1093/bioinformatics/btae159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 02/02/2024] [Accepted: 03/24/2024] [Indexed: 03/28/2024] Open
Abstract
MOTIVATION The rapid development of high-throughput biomedical technologies can provide researchers with detailed multi-omics data. The multi-omics integrated analysis approach based on machine learning contributes a more comprehensive perspective to human disease research. However, there are still significant challenges in representing single-omics data and integrating multi-omics information. RESULTS This article presents HyperTMO, a Trusted Multi-Omics integration framework based on Hypergraph convolutional network for patient classification. HyperTMO constructs hypergraph structures to represent the association between samples in single-omics data, then evidence extraction is performed by hypergraph convolutional network, and multi-omics information is integrated at an evidence level. Last, we experimentally demonstrate that HyperTMO outperforms other state-of-the-art methods in breast cancer subtype classification and Alzheimer's disease classification tasks using multi-omics data from TCGA (BRCA) and ROSMAP datasets. Importantly, HyperTMO is the first attempt to integrate hypergraph structure, evidence theory, and multi-omics integration for patient classification. Its accurate and robust properties bring great potential for applications in clinical diagnosis. AVAILABILITY AND IMPLEMENTATION HyperTMO and datasets are publicly available at https://github.com/ippousyuga/HyperTMO.
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Affiliation(s)
- Haohua Wang
- School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning 116024, China
| | - Kai Lin
- School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning 116024, China
| | - Qiang Zhang
- School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning 116024, China
| | - Jinlong Shi
- Research Center for Medical Big Data, Medical Innovation Research Division of Chinese PLA General Hospital, Beijing 100039, China
| | - Xinyu Song
- Research Center for Medical Big Data, Medical Innovation Research Division of Chinese PLA General Hospital, Beijing 100039, China
| | - Jue Wu
- Research Center for Medical Big Data, Medical Innovation Research Division of Chinese PLA General Hospital, Beijing 100039, China
| | - Chenghui Zhao
- Research Center for Medical Big Data, Medical Innovation Research Division of Chinese PLA General Hospital, Beijing 100039, China
| | - Kunlun He
- Research Center for Medical Big Data, Medical Innovation Research Division of Chinese PLA General Hospital, Beijing 100039, China
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11
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Yang ML, Xu C, Gupte T, Hoffmann TJ, Iribarren C, Zhou X, Ganesh SK. Sex-specific genetic architecture of blood pressure. Nat Med 2024; 30:818-828. [PMID: 38459180 DOI: 10.1038/s41591-024-02858-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 02/05/2024] [Indexed: 03/10/2024]
Abstract
The genetic and genomic basis of sex differences in blood pressure (BP) traits remain unstudied at scale. Here, we conducted sex-stratified and combined-sex genome-wide association studies of BP traits using the UK Biobank resource, identifying 1,346 previously reported and 29 new BP trait-associated loci. Among associated loci, 412 were female-specific (Pfemale ≤ 5 × 10-8; Pmale > 5 × 10-8) and 142 were male-specific (Pmale ≤ 5 × 10-8; Pfemale > 5 × 10-8); these sex-specific loci were enriched for hormone-related transcription factors, in particular, estrogen receptor 1. Analyses of gene-by-sex interactions and sexually dimorphic effects identified four genomic regions, showing female-specific associations with diastolic BP or pulse pressure, including the chromosome 13q34-COL4A1/COL4A2 locus. Notably, female-specific pulse pressure-associated loci exhibited enriched acetylated histone H3 Lys27 modifications in arterial tissues and a female-specific association with fibromuscular dysplasia, a female-biased vascular disease; colocalization signals included Chr13q34: COL4A1/COL4A2, Chr9p21: CDKN2B-AS1 and Chr4q32.1: MAP9 regions. Sex-specific and sex-biased polygenic associations of BP traits were associated with multiple cardiovascular traits. These findings suggest potentially clinically significant and BP sex-specific pleiotropic effects on cardiovascular diseases.
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Affiliation(s)
- Min-Lee Yang
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Chang Xu
- 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
| | - Trisha Gupte
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Thomas J Hoffmann
- Department of Epidemiology & Biostatistics, and Institute for Human Genetics, School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | | | - Xiang Zhou
- 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
| | - Santhi K Ganesh
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA.
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
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12
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Martin SS, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Barone Gibbs B, Beaton AZ, Boehme AK, Commodore-Mensah Y, Currie ME, Elkind MSV, Evenson KR, Generoso G, Heard DG, Hiremath S, Johansen MC, Kalani R, Kazi DS, Ko D, Liu J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Perman SM, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Tsao CW, Urbut SM, Van Spall HGC, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Palaniappan LP. 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association. Circulation 2024; 149:e347-e913. [PMID: 38264914 DOI: 10.1161/cir.0000000000001209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Abstract
BACKGROUND The American Heart Association (AHA), 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, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA 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 global data, 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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13
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Qin M, Wu Y, Fang X, Pan C, Zhong S. Polygenic risk score predicts all-cause death in East Asian patients with prior coronary artery disease. Front Cardiovasc Med 2024; 11:1296415. [PMID: 38414927 PMCID: PMC10896892 DOI: 10.3389/fcvm.2024.1296415] [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: 09/19/2023] [Accepted: 01/31/2024] [Indexed: 02/29/2024] Open
Abstract
Introduction Coronary artery disease (CAD) is a highly heritable and multifactorial disease. Numerous genome-wide association studies (GWAS) facilitated the construction of polygenic risk scores (PRS) for predicting future incidence of CAD, however, exclusively in European populations. Furthermore, identifying CAD patients with elevated risks of all-cause death presents a critical challenge in secondary prevention, which will contribute largely to reducing the burden for public healthcare. Methods We recruited a cohort of 1,776 Chinese CAD patients and performed medical follow-up for up to 11 years. A pruning and thresholding method was used to calculate PRS of CAD and its 14 risk factors. Their correlations with all-cause death were computed via Cox regression. Results and discussion We found that the PRS for CAD and its seven risk factors, namely myocardial infarction, ischemic stroke, angina, heart failure, low-density lipoprotein cholesterol, total cholesterol and C-reaction protein, were significantly associated with death (P ≤ 0.05), whereas the PRS of body mass index displayed moderate association (P < 0.1). Elastic-net Cox regression with 5-fold cross-validation was used to integrate these nine PRS models into a meta score, metaPRS, which performed well in stratifying patients at different risks for death (P < 0.0001). Combining metaPRS with clinical risk factors further increased the discerning power and a 4% increase in sensitivity. The metaPRS generated from the genetic susceptibility to CAD and its risk factors can well stratify CAD patients by their risks of death. Integrating metaPRS and clinical risk factors may contribute to identifying patients at higher risk of poor prognosis.
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Affiliation(s)
- Min Qin
- School of Medicine, South China University of Technology, Guangzhou, China
- Department of Pharmacy, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Yonglin Wu
- Department of Pharmacy, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), School of Life Sciences, Fudan University, Guangzhou, China
| | - Xianhong Fang
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Guangzhou, China
| | - Cuiping Pan
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), School of Life Sciences, Fudan University, Guangzhou, China
- Center for Evolutionary Biology, Fudan University, Shanghai, China
| | - Shilong Zhong
- School of Medicine, South China University of Technology, Guangzhou, China
- Department of Pharmacy, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Guangzhou, China
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14
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Zhao S, Hulsurkar MM, Lahiri SK, Aguilar-Sanchez Y, Munivez E, Müller FU, Jain A, Malovannaya A, Yiu K, Reilly S, Wehrens XH. Atrial Proteomic Profiling Reveals a Switch Towards Profibrotic Gene Expression Program in CREM-IbΔC-X Mice with Persistent Atrial Fibrillation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.10.575097. [PMID: 38260363 PMCID: PMC10802622 DOI: 10.1101/2024.01.10.575097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Background Overexpression of the CREM (cAMP response element-binding modulator) isoform CREM-IbΔC-X in transgenic mice (CREM-Tg) causes the age-dependent development of spontaneous AF. Purpose To identify key proteome signatures and biological processes accompanying the development of persistent AF through integrated proteomics and bioinformatics analysis. Methods Atrial tissue samples from three CREM-Tg mice and three wild-type littermates were subjected to unbiased mass spectrometry-based quantitative proteomics, differential expression and pathway enrichment analysis, and protein-protein interaction (PPI) network analysis. Results A total of 98 differentially expressed proteins were identified. Gene ontology analysis revealed enrichment for biological processes regulating actin cytoskeleton organization and extracellular matrix (ECM) dynamics. Changes in ITGAV, FBLN5, and LCP1 were identified as being relevant to atrial fibrosis and remodeling based on expression changes, co-expression patterns, and PPI network analysis. Comparative analysis with previously published datasets revealed a shift in protein expression patterns from ion-channel and metabolic regulators in young CREM-Tg mice to profibrotic remodeling factors in older CREM-Tg mice. Furthermore, older CREM-Tg mice exhibited protein expression patterns that resembled those of humans with persistent AF. Conclusions This study uncovered distinct temporal changes in atrial protein expression patterns with age in CREM-Tg mice consistent with the progressive evolution of AF. Future studies into the role of the key differentially abundant proteins identified in this study in AF progression may open new therapeutic avenues to control atrial fibrosis and substrate development in AF.
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Affiliation(s)
- Shuai Zhao
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Mohit M. Hulsurkar
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Satadru K. Lahiri
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Yuriana Aguilar-Sanchez
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Elda Munivez
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Frank Ulrich Müller
- Institute of Pharmacology and Toxicology, University of Münster, Münster, Germany
| | - Antrix Jain
- Mass Spectrometry Proteomics Core, Baylor College of Medicine, Houston, TX, USA
| | - Anna Malovannaya
- Mass Spectrometry Proteomics Core, Baylor College of Medicine, Houston, TX, USA
- Department of Biochemistry, Baylor College of Medicine, Houston, TX 77030, USA
| | - Kendrick Yiu
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, British Heart Foundation Centre of Research Excellence, NIHR Oxford BRC, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Svetlana Reilly
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, British Heart Foundation Centre of Research Excellence, NIHR Oxford BRC, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Xander H.T. Wehrens
- Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Medicine (in Cardiology), Baylor College of Medicine, Houston, TX 77030, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA
- Department of Pediatrics (in Cardiology), Baylor College of Medicine, Houston, TX 77030, USA
- Center for Space Medicine, Baylor College of Medicine, Houston, USA
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15
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Holst AG, Tomcsányi J, Vestbjerg B, Grunnet M, Sørensen US, Diness JG, Bentzen BH, Edvardsson N, Hohnloser SH, Bhatt DL, Dorian P. Inhibition of the K Ca2 potassium channel in atrial fibrillation: a randomized phase 2 trial. Nat Med 2024; 30:106-111. [PMID: 38092897 PMCID: PMC10803288 DOI: 10.1038/s41591-023-02679-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 11/01/2023] [Indexed: 01/24/2024]
Abstract
Existing antiarrhythmic drugs to treat atrial fibrillation (AF) have incomplete efficacy, contraindications and adverse effects, including proarrhythmia. AP30663, an inhibitor of the KCa2 channel, has demonstrated AF efficacy in animals; however, its efficacy in humans with AF is unknown. Here we conducted a phase 2 trial in which patients with a current episode of AF lasting for 7 days or less were randomized to receive an intravenous infusion of 3 or 5 mg kg-1 AP30663 or placebo. The trial was prematurely discontinued because of slow enrollment during the coronavirus disease 2019 pandemic. The primary endpoint of the trial was cardioversion from AF to sinus rhythm within 90 min from the start of the infusion, analyzed with Bayesian statistics. Among 59 patients randomized and included in the efficacy analyses, the primary endpoint occurred in 42% (5 of 12), 55% (12 of 22) and 0% (0 of 25) of patients treated with 3 mg kg-1 AP30663, 5 mg kg-1 AP30663 or placebo, respectively. Both doses demonstrated more than 99.9% probability of superiority over placebo, surpassing the prespecified 95% threshold. The mean time to cardioversion, a secondary endpoint, was 47 (s.d. = 23) and 41 (s.d. = 24) minutes for 3 mg kg-1 and 5 mg kg-1 AP30663, respectively. AP30663 caused a transient increase in the QTcF interval, with a maximum mean effect of 37.7 ms for the 5 mg kg-1 dose. For both dose groups, no ventricular arrhythmias occurred and adverse event rates were comparable to the placebo group. AP30663 demonstrated AF cardioversion efficacy in patients with recent-onset AF episodes. KCa2 channel inhibition may be an attractive mechanism for rhythm control of AF that should be studied further in randomized trials. ClinicalTrials.gov registration: NCT04571385 .
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Affiliation(s)
| | - János Tomcsányi
- Cardiology Department, St. John of God Hospital, Budapest, Hungary
| | | | | | | | | | | | - Nils Edvardsson
- Acesion Pharma, Copenhagen, Denmark
- Department of Molecular and Clinical Medicine/Cardiology, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | | | - Deepak L Bhatt
- Mount Sinai Heart, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Paul Dorian
- Department of Medicine, Division of Cardiology, University of Toronto, St. Michael's Hospital, Toronto, Ontario, Canada
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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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17
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Schuermans A, Pournamdari AB, Lee J, Bhukar R, Ganesh S, Darosa N, Small AM, Yu Z, Hornsby W, Koyama S, Januzzi JL, Honigberg MC, Natarajan P. Integrative proteomic analyses across common cardiac diseases yield new mechanistic insights and enhanced prediction. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.19.23300218. [PMID: 38196601 PMCID: PMC10775327 DOI: 10.1101/2023.12.19.23300218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
Cardiac diseases represent common highly morbid conditions for which underlying molecular mechanisms remain incompletely understood. Here, we leveraged 1,459 protein measurements in 44,313 UK Biobank participants to characterize the circulating proteome associated with incident coronary artery disease, heart failure, atrial fibrillation, and aortic stenosis. Multivariable-adjusted Cox regression identified 820 protein-disease associations-including 441 proteins-at Bonferroni-adjusted P <8.6×10 -6 . Cis -Mendelian randomization suggested causal roles that aligned with epidemiological findings for 6% of proteins identified in primary analyses, prioritizing novel therapeutic targets for different cardiac diseases (e.g., interleukin-4 receptor for heart failure and spondin-1 for atrial fibrillation). Interaction analyses identified seven protein-disease associations that differed Bonferroni-significantly by sex. Models incorporating proteomic data (vs. clinical risk factors alone) improved prediction for coronary artery disease, heart failure, and atrial fibrillation. These results lay a foundation for future investigations to uncover novel disease mechanisms and assess the clinical utility of protein-based prevention strategies for cardiac diseases.
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18
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Rosenberg MA, Adewumi J, Aleong RG. A Discussion of the Contemporary Prediction Models for Atrial Fibrillation. MEDICAL RESEARCH ARCHIVES 2023; 11:4481. [PMID: 38050581 PMCID: PMC10695401 DOI: 10.18103/mra.v11i10.4481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/06/2023]
Abstract
Atrial Fibrillation is a complex disease state with many environmental and genetic risk factors. While there are environmental factors that have been shown to increase an individual's risk of atrial fibrillation, it has become clear that atrial fibrillation has a genetic component that influences why some patients are at a higher risk of developing atrial fibrillation compared to others. This review will first discuss the clinical diagnosis of atrial fibrillation and the corresponding rhythm atrial flutter. We will then discuss how a patients' risk of stroke can be assessed by using other clinical co-morbidities. We will then review the clinical risk factors that can be used to help predict an individual patient's risk of atrial fibrillation. Many of the clinical risk factors have been used to create several different risk scoring methods that will be reviewed. We will then discuss how genetics can be used to identify individuals who are at higher risk for developing atrial fibrillation. We will discuss genome-wide association studies and other sequencing high-throughput sequencing studies. Finally, we will touch on how genetic variants derived from a genome-wide association studies can be used to calculate an individual's polygenic risk score for atrial fibrillation. An atrial fibrillation polygenic risk score can be used to identify patients at higher risk of developing atrial fibrillation and may allow for a reduction in some of the complications associated with atrial fibrillation such as cerebrovascular accidents and the development of heart failure. Finally, there is a brief discussion of how artificial intelligence models can be used to predict which patients will develop atrial fibrillation.
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Affiliation(s)
- Michael A. Rosenberg
- Department of Cardiac Electrophysiology, University of Colorado, Aurora, Colorado, USA
| | - Joseph Adewumi
- Department of Cardiac Electrophysiology, University of Colorado, Aurora, Colorado, USA
| | - Ryan G. Aleong
- Department of Cardiac Electrophysiology, University of Colorado, Aurora, Colorado, USA
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19
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Takahashi Y, Yamaguchi T, Otsubo T, Nakashima K, Shinzato K, Osako R, Shichida S, Kawano Y, Fukui A, Kawaguchi A, Aishima S, Saito T, Takahashi N, Node K. Histological validation of atrial structural remodelling in patients with atrial fibrillation. Eur Heart J 2023; 44:3339-3353. [PMID: 37350738 PMCID: PMC10499545 DOI: 10.1093/eurheartj/ehad396] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 05/03/2023] [Accepted: 06/01/2023] [Indexed: 06/24/2023] Open
Abstract
BACKGROUND AND AIMS This study aimed to histologically validate atrial structural remodelling associated with atrial fibrillation. METHODS AND RESULTS Patients undergoing atrial fibrillation ablation and endomyocardial atrial biopsy were included (n = 230; 67 ± 12 years old; 69 women). Electroanatomic mapping was performed during right atrial pacing. Voltage at the biopsy site (Vbiopsy), global left atrial voltage (VGLA), and the proportion of points with fractionated electrograms defined as ≥5 deflections in each electrogram (%Fractionated EGM) were evaluated. SCZtotal was calculated as the total width of slow conduction zones, defined as regions with a conduction velocity of <30 cm/s. Histological factors potentially associated with electroanatomic characteristics were evaluated using multiple linear regression analyses. Ultrastructural features and immune cell infiltration were evaluated by electron microscopy and immunohistochemical staining in 33 and 60 patients, respectively. Fibrosis, intercellular space, myofibrillar loss, and myocardial nuclear density were significantly associated with Vbiopsy (P = .014, P < .001, P < .001, and P = .002, respectively) and VGLA (P = .010, P < .001, P = .001, and P < .001, respectively). The intercellular space was associated with the %Fractionated EGM (P = .001). Fibrosis, intercellular space, and myofibrillar loss were associated with SCZtotal (P = .028, P < .001, and P = .015, respectively). Electron microscopy confirmed plasma components and immature collagen fibrils in the increased intercellular space and myofilament lysis in cardiomyocytes, depending on myofibrillar loss. Among the histological factors, the severity of myofibrillar loss was associated with an increase in macrophage infiltration. CONCLUSION Histological correlates of atrial structural remodelling were fibrosis, increased intercellular space, myofibrillar loss, and decreased nuclear density. Each histological component was defined using electron microscopy and immunohistochemistry studies.
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Affiliation(s)
- Yuya Takahashi
- Department of Cardiovascular Medicine, Saga University, 5-1-1 Nabeshima, Saga 849-8501, Japan
| | - Takanori Yamaguchi
- Department of Cardiovascular Medicine, Saga University, 5-1-1 Nabeshima, Saga 849-8501, Japan
| | - Toyokazu Otsubo
- Department of Cardiovascular Medicine, Saga University, 5-1-1 Nabeshima, Saga 849-8501, Japan
| | - Kana Nakashima
- Department of Cardiovascular Medicine, Saga University, 5-1-1 Nabeshima, Saga 849-8501, Japan
| | - Kodai Shinzato
- Department of Cardiovascular Medicine, Saga University, 5-1-1 Nabeshima, Saga 849-8501, Japan
| | - Ryosuke Osako
- Department of Cardiovascular Medicine, Saga University, 5-1-1 Nabeshima, Saga 849-8501, Japan
| | - Shigeki Shichida
- Department of Cardiovascular Medicine, Saga University, 5-1-1 Nabeshima, Saga 849-8501, Japan
| | - Yuki Kawano
- Division of Cardiology, Saiseikai Futsukaichi Hospital, 3-13-1, Yumachi, Chikushino, Fukoka 818-8516, Japan
| | - Akira Fukui
- Department of Cardiology and Clinical Examination, Faculty of Medicine, Oita University, 1-1, Idaigaoka, Hasama, Yufu, Oita 879-5593, Japan
| | - Atsushi Kawaguchi
- Education and Research Center for Community Medicine, Faculty of Medicine, Saga University, 5-1-1 Nabeshima, Saga 849-8501, Japan
| | - Shinichi Aishima
- Department of Pathology and Microbiology, Saga University, Saga, Japan
| | - Tsunenori Saito
- Department of Cardiovascular Medicine, Nippon Medical School Tama Nagayama Hospital, Tama, Tokyo, Japan
| | - Naohiko Takahashi
- Department of Cardiology and Clinical Examination, Faculty of Medicine, Oita University, 1-1, Idaigaoka, Hasama, Yufu, Oita 879-5593, Japan
| | - Koichi Node
- Department of Cardiovascular Medicine, Saga University, 5-1-1 Nabeshima, Saga 849-8501, Japan
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20
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Yuan S, Li Y, Wang L, Xu F, Chen J, Levin MG, Xiong Y, Voight BF, Damrauer SM, Gill D, Burgess S, Åkesson A, Michaëlsson K, Li X, Shen X, Larsson SC. Deciphering the genetic architecture of atrial fibrillation offers insights into disease prediction, pathophysiology and downstream sequelae. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.20.23292938. [PMID: 37546828 PMCID: PMC10402218 DOI: 10.1101/2023.07.20.23292938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Aims The study aimed to discover novel genetic loci for atrial fibrillation (AF), explore the shared genetic etiologies between AF and other cardiovascular and cardiometabolic traits, and uncover AF pathogenesis using Mendelian randomization analysis. Methods and results We conducted a genome-wide association study meta-analysis including 109,787 AF cases and 1,165,920 controls of European ancestry and identified 215 loci, among which 91 were novel. We performed Genomic Structural Equation Modeling analysis between AF and four cardiovascular comorbidities (coronary artery disease, ischemic stroke, heart failure, and vneous thromboembolism) and found 189 loci shared across these diseases as well as a universal genetic locus shared by atherosclerotic outcomes (i.e., rs1537373 near CDKN2B). Three genetic loci (rs10740129 near JMJD1C, rs2370982 near NRXN3, and rs9931494 near FTO) were associated with AF and cardiometabolic traits. A polygenic risk score derived from this genome-wide meta-analysis was associated with AF risk (odds ratio 2.36, 95% confidence interval 2.31-2.41 per standard deviation increase) in the UK biobank. This score, combined with age, sex, and basic clinical features, predicted AF risk (AUC 0.784, 95% CI 0.781-0.787) in Europeans. Phenome-wide association analysis of the polygenic risk score identified many AF-related comorbidities of the circulatory, endocrine, and respiratory systems. Phenome-wide and multi-omic Mendelian randomization analyses identified associations of blood lipids and pressure, diabetes, insomnia, obesity, short sleep, and smoking, 27 blood proteins, one gut microbe (genus.Catenibacterium), and 11 blood metabolites with risk to AF. Conclusions This genome-wide association study and trans-omic Mendelian randomization analysis provides insights into disease risk prediction, pathophysiology and downstream sequelae.
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Affiliation(s)
- Shuai Yuan
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Yuying Li
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Lijuan Wang
- School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Fengzhe Xu
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
| | - Jie Chen
- School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Michael G Levin
- Division of Cardiovascular Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Ying Xiong
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Benjamin F. Voight
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Scott M Damrauer
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Agneta Åkesson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Karl Michaëlsson
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Xue Li
- School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xia Shen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Susanna C. Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
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21
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Igarashi W, Takagi D, Okada D, Kobayashi D, Oka M, Io T, Ishii K, Ono K, Yamamoto H, Okamoto Y. Bioinformatic Identification of Potential RNA Alterations on the Atrial Fibrillation Remodeling from Human Pulmonary Veins. Int J Mol Sci 2023; 24:10501. [PMID: 37445678 DOI: 10.3390/ijms241310501] [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: 03/18/2023] [Revised: 05/16/2023] [Accepted: 06/20/2023] [Indexed: 07/15/2023] Open
Abstract
Atrial fibrillation (AF) is the most frequent persistent arrhythmia. Many genes have been reported as a genetic background for AF. However, most transcriptome analyses of AF are limited to the atrial samples and have not been evaluated by multiple cardiac regions. In this study, we analyzed the expression levels of protein-coding and long noncoding RNAs (lncRNAs) in six cardiac regions by RNA-seq. Samples were donated from six subjects with or without persistent AF for left atria, left atrial appendages, right atria, sinoatrial nodes, left ventricles, right ventricles, and pulmonary veins (PVs), and additional four right atrial appendages samples were collected from patients undergoing mitral valve replacement. In total, 23 AF samples were compared to 23 non-AF samples. Surprisingly, the most influenced heart region in gene expression by AF was the PV, not the atria. The ion channel-related gene set was significantly enriched upon analysis of these significant genes. In addition, some significant genes are cancer-related lncRNAs in PV in AF. A co-expression network analysis could detect the functional gene clusters. In particular, the cancer-related lncRNA, such as SAMMSON and FOXCUT, belong to the gene network with the cancer-related transcription factor FOXC1. Thus, they may also play an aggravating role in the pathogenesis of AF, similar to carcinogenesis. In the least, this study suggests that (1) RNA alteration is most intense in PVs and (2) post-transcriptional gene regulation by lncRNA may contribute to the progression of AF. Through the screening analysis across the six cardiac regions, the possibility that the PV region can play a role other than paroxysmal triggering in the pathogenesis of AF was demonstrated for the first time. Future research with an increase in the number of PV samples will lead to a novel understanding of the pathophysiology of AF.
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Affiliation(s)
- Wataru Igarashi
- Department of Cardiovascular Surgery, Akita University Graduate School of Medicine, 1-1-1 Hondo, Akita 010-8543, Japan
| | - Daichi Takagi
- Department of Cardiovascular Surgery, Akita University Graduate School of Medicine, 1-1-1 Hondo, Akita 010-8543, Japan
| | - Daigo Okada
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Shogoinkawahara-cho, Kyoto 606-8507, Japan
| | - Daiki Kobayashi
- Department of Cell Physiology, Akita University Graduate School of Medicine, 1-1-1 Hondo, Akita 010-8543, Japan
| | - Miho Oka
- Research Department, Ono Pharmaceutical Co., Ltd., Kyutaromachi, Osaka 541-0056, Japan
| | - Toshiro Io
- Research Department, Ono Pharmaceutical Co., Ltd., Kyutaromachi, Osaka 541-0056, Japan
| | - Kuniaki Ishii
- Department of Pharmacology, Faculty of Medicine, Yamagata University, Iida-Nishi, Yamagata 990-9585, Japan
| | - Kyoichi Ono
- Department of Cell Physiology, Akita University Graduate School of Medicine, 1-1-1 Hondo, Akita 010-8543, Japan
| | - Hiroshi Yamamoto
- Department of Cardiovascular Surgery, Akita University Graduate School of Medicine, 1-1-1 Hondo, Akita 010-8543, Japan
| | - Yosuke Okamoto
- Department of Cell Physiology, Akita University Graduate School of Medicine, 1-1-1 Hondo, Akita 010-8543, Japan
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22
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Abstract
PURPOSE OF REVIEW Atrial fibrillation is the most common cardiac arrhythmia worldwide. There is considerable interest in better understanding the molecular genetics and biology of atrial fibrillation to inform the development of new therapies and improve clinical management. This review summarizes recent advances in our understanding of the genetic basis of atrial fibrillation and new efforts to utilize genetics to inform clinical management. RECENT FINDINGS Genome-wide association studies in diverse populations have increased the number of genetic loci associated with atrial fibrillation and its specific subtypes. Large-scale biobanks with deep phenotyping have provided invaluable data to study the impact of both common and rare variants on atrial fibrillation, susceptibility, and prognosis. Polygenic risk scores help improve individual atrial fibrillation risk stratification and prognostication. SUMMARY Our understanding of atrial fibrillation genetics is rapidly improving with larger and more diverse genome-wide association studies. Translating genetic discoveries into molecular pathways and new therapeutic targets remains a bottleneck in the development of new therapies for atrial fibrillation. Genetic risk scores have shown early promise in improving atrial fibrillation risk stratification; however, their broader utility for the general population remains unclear.
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Affiliation(s)
- David S M Lee
- Medical Scientist Training Program, University of Pennsylvania Perelman School of Medicine
| | - Scott M Damrauer
- Corporal Michael J. Crescenz VA Medical Center.,Department of Surgery.,Department of Genetics, University of Pennsylvania Perelman School of Medicine
| | - Michael G Levin
- Corporal Michael J. Crescenz VA Medical Center.,Division of Cardiovascular Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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