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Infante T, Pepin ME, Ruocco A, Trama U, Mauro C, Napoli C. CDK5R1, GSE1, HSPG2 and WDFY3 as indirect epigenetic-sensitive genes in atrial fibrillation. Eur J Clin Invest 2024; 54:e14135. [PMID: 37991085 DOI: 10.1111/eci.14135] [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: 08/02/2023] [Revised: 11/14/2023] [Accepted: 11/14/2023] [Indexed: 11/23/2023]
Abstract
BACKGROUND Although mounting evidence supports that aberrant DNA methylation occurs in the hearts of patients with atrial fibrillation (AF), noninvasive epigenetic characterization of AF has not yet been defined. METHODS We investigated DNA methylome changes in peripheral blood CD4+ T cells isolated from 10 patients with AF relative to 11 healthy subjects (HS) who were enrolled in the DIANA clinical trial (NCT04371809) via reduced-representation bisulfite sequencing (RRBS). RESULTS An atrial-specific PPI network revealed 18 hub differentially methylated genes (DMGs), wherein ROC curve analysis revealed reasonable diagnostic performance of DNA methylation levels found within CDK5R1 (AUC = 0.76; p = 0.049), HSPG2 (AUC = 0.77; p = 0.038), WDFY3 (AUC = 0.78; p = 0.029), USP49 (AUC = 0.76; p = 0.049), GSE1 (AUC = 0.76; p = 0.049), AIFM1 (AUC = 0.76; p = 0.041), CDK5RAP2 (AUC = 0.81; p = 0.017), COL4A1 (AUC = 0.86; p < 0.001), SEPT8 (AUC = 0.90; p < 0.001), PFDN1 (AUC = 0.90; p < 0.01) and ACOT7 (AUC = 0.78; p = 0.032). Transcriptional profiling of the hub DMGs provided a significant overexpression of PSDM6 (p = 0.004), TFRC (p = 0.01), CDK5R1 (p < 0.001), HSPG2 (p = 0.01), WDFY3 (p < 0.001), USP49 (p = 0.004) and GSE1 (p = 0.021) in AF patients vs HS. CONCLUSIONS CDK5R1, GSE1, HSPG2 and WDFY3 resulted the best discriminatory genes both at methylation and gene expression level. Our results provide several candidate diagnostic biomarkers with the potential to advance precision medicine in AF.
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Affiliation(s)
- Teresa Infante
- Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Mark E Pepin
- Division of Internal Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- The Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Antonio Ruocco
- Cardiology Division, "A. Cardarelli" Hospital, Naples, Italy
| | - Ugo Trama
- General Direction of Health Care & Regional Health System Coordination, Drug & Device Politics, Campania Region, Naples, Italy
| | - Ciro Mauro
- Cardiology Division, "A. Cardarelli" Hospital, Naples, Italy
| | - Claudio Napoli
- Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania "Luigi Vanvitelli", Naples, Italy
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Grzeczka A, Graczyk S, Kordowitzki P. DNA Methylation and Telomeres-Their Impact on the Occurrence of Atrial Fibrillation during Cardiac Aging. Int J Mol Sci 2023; 24:15699. [PMID: 37958686 PMCID: PMC10650750 DOI: 10.3390/ijms242115699] [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: 09/20/2023] [Revised: 10/25/2023] [Accepted: 10/26/2023] [Indexed: 11/15/2023] Open
Abstract
Atrial fibrillation (AF) is the most common arrhythmia in humans. AF is characterized by irregular and increased atrial muscle activation. This high-frequency activation obliterates the synchronous work of the atria and ventricles, reducing myocardial performance, which can lead to severe heart failure or stroke. The risk of developing atrial fibrillation depends largely on the patient's history. Cardiovascular diseases are considered aging-related pathologies; therefore, deciphering the role of telomeres and DNA methylation (mDNA), two hallmarks of aging, is likely to contribute to a better understanding and prophylaxis of AF. In honor of Prof. Elizabeth Blackburn's 75th birthday, we dedicate this review to the discovery of telomeres and her contribution to research on aging.
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Affiliation(s)
| | | | - Pawel Kordowitzki
- Department for Basic and Preclinical Sciences, Faculty of Biological and Veterinary Sciences, Nicolaus Copernicus University, Szosa Bydgoska 13, 87-100 Torun, Poland
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3
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Yu Y, Wang S, Luo Y, Gu C, Shi X, Shen F. Quantitative Investigation of Methylation Heterogeneity by Digital Melting Curve Analysis on a SlipChip for Atrial Fibrillation. ACS Sens 2023; 8:3595-3603. [PMID: 37590470 DOI: 10.1021/acssensors.3c01309] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/19/2023]
Abstract
Methylation is an essential epigenetic modification involved in regulating gene expression and maintaining genome stability. Methylation patterns can be heterogeneous, exhibiting variations in both level and density. However, current methods of methylation analysis, including sequencing, methylation-specific PCR, and high-resolution melting curve analysis (HRM), face limitations of high cost, time-consuming workflows, and the difficulty of both accurate heterogeneity analysis and precise quantification. Here, a droplet array SlipChip-based (da-SlipChip-based) digital melting curve analysis (MCA) method was developed for the accurate quantification of both methylation level (ratio of methylated molecules to total molecules) and methylation density (ratio of methylated CpG sites to total CpG sites). The SlipChip-based digital MCA system supplements an in situ thermal cycler with a fluorescence imaging module for real-time MCA. The da-SlipChip can generate 10,656 droplets of 1 nL each, which can be separated into four lanes, enabling the simultaneous analysis of four samples. This method's clinical application was demonstrated by analyzing samples from ten healthy individuals and twenty patients with atrial fibrillation (AF), the most common arrhythmia. This method can distinguish healthy individuals from those with AF of both the paroxysmal and persistent types. It also holds potential for broader application in various research and clinical settings requiring methylation analysis.
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Affiliation(s)
- Yan Yu
- School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Hua Shan Road, Shanghai 200030, China
| | - Sheng Wang
- School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Hua Shan Road, Shanghai 200030, China
| | - Yang Luo
- School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Hua Shan Road, Shanghai 200030, China
| | - Chang Gu
- Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
- Department of Cardiothoracic Surgery, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200092, China
| | - Xin Shi
- Department of Cardiology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Feng Shen
- School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Hua Shan Road, Shanghai 200030, China
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4
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Krolevets M, Cate VT, Prochaska JH, Schulz A, Rapp S, Tenzer S, Andrade-Navarro MA, Horvath S, Niehrs C, Wild PS. DNA methylation and cardiovascular disease in humans: a systematic review and database of known CpG methylation sites. Clin Epigenetics 2023; 15:56. [PMID: 36991458 PMCID: PMC10061871 DOI: 10.1186/s13148-023-01468-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 03/19/2023] [Indexed: 03/31/2023] Open
Abstract
BACKGROUND Cardiovascular disease (CVD) is the leading cause of death worldwide and considered one of the most environmentally driven diseases. The role of DNA methylation in response to the individual exposure for the development and progression of CVD is still poorly understood and a synthesis of the evidence is lacking. RESULTS A systematic review of articles examining measurements of DNA cytosine methylation in CVD was conducted in accordance with PRISMA (preferred reporting items for systematic reviews and meta-analyses) guidelines. The search yielded 5,563 articles from PubMed and CENTRAL databases. From 99 studies with a total of 87,827 individuals eligible for analysis, a database was created combining all CpG-, gene- and study-related information. It contains 74,580 unique CpG sites, of which 1452 CpG sites were mentioned in ≥ 2, and 441 CpG sites in ≥ 3 publications. Two sites were referenced in ≥ 6 publications: cg01656216 (near ZNF438) related to vascular disease and epigenetic age, and cg03636183 (near F2RL3) related to coronary heart disease, myocardial infarction, smoking and air pollution. Of 19,127 mapped genes, 5,807 were reported in ≥ 2 studies. Most frequently reported were TEAD1 (TEA Domain Transcription Factor 1) and PTPRN2 (Protein Tyrosine Phosphatase Receptor Type N2) in association with outcomes ranging from vascular to cardiac disease. Gene set enrichment analysis of 4,532 overlapping genes revealed enrichment for Gene Ontology molecular function "DNA-binding transcription activator activity" (q = 1.65 × 10-11) and biological processes "skeletal system development" (q = 1.89 × 10-23). Gene enrichment demonstrated that general CVD-related terms are shared, while "heart" and "vasculature" specific genes have more disease-specific terms as PR interval for "heart" or platelet distribution width for "vasculature." STRING analysis revealed significant protein-protein interactions between the products of the differentially methylated genes (p = 0.003) suggesting that dysregulation of the protein interaction network could contribute to CVD. Overlaps with curated gene sets from the Molecular Signatures Database showed enrichment of genes in hemostasis (p = 2.9 × 10-6) and atherosclerosis (p = 4.9 × 10-4). CONCLUSION This review highlights the current state of knowledge on significant relationship between DNA methylation and CVD in humans. An open-access database has been compiled of reported CpG methylation sites, genes and pathways that may play an important role in this relationship.
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Affiliation(s)
- Mykhailo Krolevets
- Preventive Cardiology and Preventive Medicine, Department of Cardiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany
- Institute of Molecular Biology (IMB), 55128, Mainz, Germany
- Division of Molecular Embryology, DKFZ-ZMBH Alliance, 69120, Heidelberg, Germany
- Systems Medicine, Institute of Molecular Biology (IMB), Ackermannweg 4, 55128, Mainz, Germany
| | - Vincent Ten Cate
- Preventive Cardiology and Preventive Medicine, Department of Cardiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany
- Clinical Epidemiology and Systems Medicine, Center for Thrombosis and Hemostasis (CTH), Mainz, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Rhine Main, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Jürgen H Prochaska
- Preventive Cardiology and Preventive Medicine, Department of Cardiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany
- Clinical Epidemiology and Systems Medicine, Center for Thrombosis and Hemostasis (CTH), Mainz, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Rhine Main, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Andreas Schulz
- Preventive Cardiology and Preventive Medicine, Department of Cardiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany
| | - Steffen Rapp
- Preventive Cardiology and Preventive Medicine, Department of Cardiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany
- Clinical Epidemiology and Systems Medicine, Center for Thrombosis and Hemostasis (CTH), Mainz, Germany
| | - Stefan Tenzer
- Institute of Organismic and Molecular Evolution, Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Miguel A Andrade-Navarro
- Institute for Immunology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | | | - Christof Niehrs
- Institute of Molecular Biology (IMB), 55128, Mainz, Germany
- Division of Molecular Embryology, DKFZ-ZMBH Alliance, 69120, Heidelberg, Germany
| | - Philipp S Wild
- Preventive Cardiology and Preventive Medicine, Department of Cardiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany.
- Systems Medicine, Institute of Molecular Biology (IMB), Ackermannweg 4, 55128, Mainz, Germany.
- Clinical Epidemiology and Systems Medicine, Center for Thrombosis and Hemostasis (CTH), Mainz, Germany.
- German Center for Cardiovascular Research (DZHK), Partner Site Rhine Main, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
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Donniacuo M, De Angelis A, Telesca M, Bellocchio G, Riemma MA, Paolisso P, Scisciola L, Cianflone E, Torella D, Castaldo G, Capuano A, Urbanek K, Berrino L, Rossi F, Cappetta D. Atrial fibrillation: Epigenetic aspects and role of sodium-glucose cotransporter 2 inhibitors. Pharmacol Res 2023; 188:106591. [PMID: 36502999 DOI: 10.1016/j.phrs.2022.106591] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 11/30/2022] [Accepted: 11/30/2022] [Indexed: 12/13/2022]
Abstract
Atrial fibrillation (AF) is the most frequent arrhythmia and is associated with substantial morbidity and mortality. Pathophysiological aspects consist in the activation of pro-fibrotic signaling and Ca2+ handling abnormalities at atrial level. Structural and electrical remodeling creates a substrate for AF by triggering conduction abnormalities and cardiac arrhythmias. The care of AF patients focuses predominantly on anticoagulation, symptoms control and the management of risk factors and comorbidities. The goal of AF therapy points to restore sinus rhythm, re-establish atrioventricular synchrony and improve atrial contribution to the stroke volume. New layer of information to better comprehend AF pathophysiology, and identify targets for novel pharmacological interventions consists of the epigenetic phenomena including, among others, DNA methylation, histone modifications and noncoding RNAs. Moreover, the benefits of sodium-glucose cotransporter 2 inhibitors (SGLT2i) in diabetic and non-diabetic patients at cardiovascular risk as well as emerging evidence on the ability of SGLT2i to modify epigenetic signature in cardiovascular diseases provide a solid background to investigate a possible role of this drug class in the onset and progression of AF. In this review, following a summary of pathophysiology and management, epigenetic mechanisms in AF and the potential of sodium-glucose SGLT2i in AF patients are discussed.
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Affiliation(s)
- M Donniacuo
- Department of Experimental Medicine, University of Campania "Luigi Vanvitelli", Via Costantinopoli 16, 80138 Naples, Italy
| | - A De Angelis
- Department of Experimental Medicine, University of Campania "Luigi Vanvitelli", Via Costantinopoli 16, 80138 Naples, Italy
| | - M Telesca
- Department of Experimental Medicine, University of Campania "Luigi Vanvitelli", Via Costantinopoli 16, 80138 Naples, Italy
| | - G Bellocchio
- Department of Experimental Medicine, University of Campania "Luigi Vanvitelli", Via Costantinopoli 16, 80138 Naples, Italy
| | - M A Riemma
- Department of Experimental Medicine, University of Campania "Luigi Vanvitelli", Via Costantinopoli 16, 80138 Naples, Italy
| | - P Paolisso
- Cardiovascular Center Aalst, OLV Hospital, Aalst, Belgium; Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via A. Pansini 5, 80131 Naples, Italy
| | - L Scisciola
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Via Costantinopoli 16, 80138 Naples, Italy
| | - E Cianflone
- Department of Medical and Surgical Sciences, Magna Graecia University, Viale Europa, 88100 Catanzaro, Italy
| | - D Torella
- Department of Experimental and Clinical Medicine, Magna Graecia University, Viale Europa, 88100 Catanzaro, Italy
| | - G Castaldo
- Department of Molecular Medicine and Medical Biotechnologies, University of Naples "Federico II", Via A. Pansini 5, 80131 Naples, Italy; CEINGE-Advanced, Via G. Salvatore 486, 80131 Naples, Italy
| | - A Capuano
- Department of Experimental Medicine, University of Campania "Luigi Vanvitelli", Via Costantinopoli 16, 80138 Naples, Italy
| | - K Urbanek
- Department of Molecular Medicine and Medical Biotechnologies, University of Naples "Federico II", Via A. Pansini 5, 80131 Naples, Italy; CEINGE-Advanced, Via G. Salvatore 486, 80131 Naples, Italy.
| | - L Berrino
- Department of Experimental Medicine, University of Campania "Luigi Vanvitelli", Via Costantinopoli 16, 80138 Naples, Italy
| | - F Rossi
- Department of Experimental Medicine, University of Campania "Luigi Vanvitelli", Via Costantinopoli 16, 80138 Naples, Italy
| | - D Cappetta
- Department of Experimental Medicine, University of Campania "Luigi Vanvitelli", Via Costantinopoli 16, 80138 Naples, Italy
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6
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Chew NWS, Loong SSE, Foo R. Progress in molecular biology and translational science: Epigenetics in cardiovascular health and disease. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2023; 197:105-134. [PMID: 37019589 DOI: 10.1016/bs.pmbts.2023.01.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
Abstract
Conrad Waddington's epigenetics landscape has provided a metaphorical framework for how cells progress from undifferentiated states to one of several discrete, distinct, differentiated cell fates. The understanding of epigenetics has evolved over time, with DNA methylation being the most studied epigenetic modification, followed by histone modifications and non-coding RNA. Cardiovascular diseases (CVD) are leading contributors to death worldwide, with the prevalence of CVDs increasing across the last couple of decades. Significant amount of resources being poured into researching key mechanisms and underpinnings of the various CVDs. These molecular studies looked at the genetics, epigenetics as well as the transcriptomics of various cardiovascular conditions, aiming to provide mechanistic insights. It has paved the way for therapeutics to be developed and in recent years, epi-drugs for the treatment of CVDs. This chapter aims to cover the various roles of epigenetics in the context of cardiovascular health and disease. The following will be examined in detail: the developments in basic experimental techniques used to study epigenetics, the role of epigenetics in various CVDs (hypertension, atrial fibrillation, atherosclerosis, and heart failure), and current advances in epi-therapeutics, providing a holistic view of the current concerted efforts in advancing the field of epigenetics in CVDs.
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Affiliation(s)
- Nicholas W S Chew
- Department of Cardiology, National University Heart Centre, National University Health System, Singapore, Singapore.
| | - Shaun S E Loong
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Roger Foo
- Department of Cardiology, National University Heart Centre, National University Health System, Singapore, Singapore; Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
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Wang Z, Lu Y, Fornage M, Jiao L, Shen J, Li D, Wei P. Identification of novel susceptibility methylation loci for pancreatic cancer in a two-phase epigenome-wide association study. Epigenetics 2022; 17:1357-1372. [PMID: 35030986 PMCID: PMC9586592 DOI: 10.1080/15592294.2022.2026591] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 12/31/2021] [Accepted: 01/04/2022] [Indexed: 02/07/2023] Open
Abstract
The role of DNA methylation and its interplay with gene expression in the susceptibility to pancreatic cancer (PanC) remains largely unexplored. To fill in this gap, we conducted an integrative two-phase epigenome-wide association study (EWAS) of PanC using genomic DNA from 44 cases and 556 controls (20 local controls and 536 public controls in the Framingham Heart Study) in phase 1 and 23 cases and 22 controls in phase 2. We validated the findings using pre-diagnostic blood samples from 13 cases and 26 controls in the Women's Health Initiative (WHI) Study. We further examined gene expression in peripheral leukocytes of 47 cases and 31 controls involved in the methylation study using RNA sequencing and performed bidirectional Mendelian randomization (MR) analysis using existing single nucleotide polymorphism (SNP) data. In phase 1, we identified 2776 significantly differentially methylated CpG sites (DMPs) and 154 significantly differentially methylated regions (DMRs). In phase 2, we validated six DMPs (in or near AIM2, DGKA, STK39, and TNFSF8) and three DMRs (in or near nc886, LY6G5C, and HLA-DPB1). The DMR near nc886 was further validated in the WHI samples (P = 6.69 × 10-5). MR analysis suggested that the CpG sites cg00308130 and cg16684184 for nc886 and cg16875057 for STK39 were causally related to PanC susceptibility and that PanC influenced methylation of cg15354065 for DGKA. This first integrative EWAS of PanC provides novel insights into the role of DNA methylation and its interplay with SNPs and gene expression in the disease susceptibility.
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Affiliation(s)
- Ziqiao Wang
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yue Lu
- Department of Epigenetics and Molecular Carcinogenesis, The Virginia Harris Cockrell Cancer Research Center at the University of Texas MD Anderson Cancer Center, Science Park, Smithville, TX, USA
| | - Myriam Fornage
- IBrown Foundation Institute of Molecular Medicine, McGovern Medical School, the University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Li Jiao
- Department of Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Jianjun Shen
- Department of Epigenetics and Molecular Carcinogenesis, The Virginia Harris Cockrell Cancer Research Center at the University of Texas MD Anderson Cancer Center, Science Park, Smithville, TX, USA
| | - Donghui Li
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Peng Wei
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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8
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Zhou Y, Wu Q, Ni G, Hong Y, Xiao S, Liu C, Yu Z. Immune-associated pivotal biomarkers identification and competing endogenous RNA network construction in post-operative atrial fibrillation by comprehensive bioinformatics and machine learning strategies. Front Immunol 2022; 13:974935. [PMID: 36341343 PMCID: PMC9630466 DOI: 10.3389/fimmu.2022.974935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 10/10/2022] [Indexed: 11/13/2022] Open
Abstract
Background Atrial fibrillation (AF) is the most common arrhythmia. Previous studies mainly focused on identifying potential diagnostic biomarkers and treatment strategies for AF, while few studies concentrated on post-operative AF (POAF), particularly using bioinformatics analysis and machine learning algorithms. Therefore, our study aimed to identify immune-associated genes and provide the competing endogenous RNA (ceRNA) network for POAF. Methods Three GSE datasets were downloaded from the GEO database, and we used a variety of bioinformatics strategies and machine learning algorithms to discover candidate hub genes. These techniques included identifying differentially expressed genes (DEGs) and circRNAs (DECs), building protein-protein interaction networks, selecting common genes, and filtering candidate hub genes via three machine learning algorithms. To assess the diagnostic value, we then created the nomogram and receiver operating curve (ROC). MiRNAs targeting DEGs and DECs were predicted using five tools and the competing endogenous RNA (ceRNA) network was built. Moreover, we performed the immune cell infiltration analysis to better elucidate the regulation of immune cells in POAF. Results We identified 234 DEGs (82 up-regulated and 152 down-regulated) of POAF via Limma, 75 node genes were visualized via PPI network, which were mainly enriched in immune regulation. 15 common genes were selected using three CytoHubba algorithms. Following machine learning selection, the nomogram was created based on the four candidate hub genes. The area under curve (AUC) of the nomogram and individual gene were all over 0.75, showing the ideal diagnostic value. The dysregulation of macrophages may be critical in POAF pathogenesis. A novel circ_0007738 was discovered in POAF and the ceRNA network was eventually built. Conclusion We identified four immune-associated candidate hub genes (C1QA, C1R, MET, and SDC4) for POAF diagnosis through the creation of a nomogram and evaluation of its diagnostic value. The modulation of macrophages and the ceRNA network may represent further therapy methods.
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Affiliation(s)
- Yufei Zhou
- Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Qianyun Wu
- Department of Cardiology, The First People’s Hospital of Kunshan Affiliated to Jiangsu University, Suzhou, China
| | - Gehui Ni
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yulu Hong
- Department of Computer Science and Technology, Central South University, Changsha, China
| | - Shengjue Xiao
- Department of Cardiology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Chunjiang Liu
- Department of General Surgery, Shaoxing People’s Hospital (Shaoxing Hospital of Zhejiang University), Shaoxing, China
| | - Zongliang Yu
- Department of Cardiology, The First People’s Hospital of Kunshan Affiliated to Jiangsu University, Suzhou, China
- *Correspondence: Zongliang Yu,
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9
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Fischer MA, Mahajan A, Cabaj M, Kimball TH, Morselli M, Soehalim E, Chapski DJ, Montoya D, Farrell CP, Scovotti J, Bueno CT, Mimila NA, Shemin RJ, Elashoff D, Pellegrini M, Monte E, Vondriska TM. DNA Methylation-Based Prediction of Post-operative Atrial Fibrillation. Front Cardiovasc Med 2022; 9:837725. [PMID: 35620521 PMCID: PMC9127230 DOI: 10.3389/fcvm.2022.837725] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 03/17/2022] [Indexed: 12/14/2022] Open
Abstract
BackgroundAtrial fibrillation (AF) is the most common sustained cardiac arrhythmia and post-operative atrial fibrillation (POAF) is a major healthcare burden, contributing to an increased risk of stroke, kidney failure, heart attack and death. Genetic studies have identified associations with AF, but no molecular diagnostic exists to predict POAF based on pre-operative measurements. Such a tool would be of great value for perioperative planning to improve patient care and reduce healthcare costs. In this pilot study of epigenetic precision medicine in the perioperative period, we carried out bisulfite sequencing to measure DNA methylation status in blood collected from patients prior to cardiac surgery to identify biosignatures of POAF.MethodsWe enrolled 221 patients undergoing cardiac surgery in this prospective observational study. DNA methylation measurements were obtained from blood samples drawn from awake patients prior to surgery. After controlling for clinical and methylation covariates, we analyzed DNA methylation loci in the discovery cohort of 110 patients for association with POAF. We also constructed predictive models for POAF using clinical and DNA methylation data. We subsequently performed targeted analyses of a separate cohort of 101 cardiac surgical patients to measure the methylation status solely of significant methylation loci in the discovery cohort.ResultsA total of 47 patients in the discovery cohort (42.7%) and 43 patients in the validation cohort (42.6%) developed POAF. We identified 12 CpGs that were statistically significant in the discovery cohort after correcting for multiple hypothesis testing. Of these sites, 6 were amenable to targeted bisulfite sequencing and chr16:24640902 was statistically significant in the validation cohort. In addition, the methylation POAF prediction model had an AUC of 0.79 in the validation cohort.ConclusionsWe have identified DNA methylation biomarkers that can predict future occurrence of POAF associated with cardiac surgery. This research demonstrates the use of precision medicine to develop models combining epigenomic and clinical data to predict disease.
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Affiliation(s)
- Matthew A. Fischer
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
- *Correspondence: Matthew A. Fischer
| | - Aman Mahajan
- Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Maximilian Cabaj
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Todd H. Kimball
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Marco Morselli
- Department of Molecular, Cellular and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Elizabeth Soehalim
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Douglas J. Chapski
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Dennis Montoya
- Department of Molecular, Cellular and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Colin P. Farrell
- Department of Molecular, Cellular and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Jennifer Scovotti
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Claudia T. Bueno
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Naomi A. Mimila
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Richard J. Shemin
- Division of Cardiac Surgery, Department of Surgery, University of California, Los Angeles, Los Angeles, CA, United States
| | - David Elashoff
- Department of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, United States
| | - Matteo Pellegrini
- Department of Molecular, Cellular and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Emma Monte
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Thomas M. Vondriska
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
- Department of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Physiology, University of California, Los Angeles, Los Angeles, CA, United States
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10
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Li D, Nie J, Han Y, Ni L. Epigenetic Mechanism and Therapeutic Implications of Atrial Fibrillation. Front Cardiovasc Med 2022; 8:763824. [PMID: 35127848 PMCID: PMC8815458 DOI: 10.3389/fcvm.2021.763824] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 12/08/2021] [Indexed: 12/28/2022] Open
Abstract
Atrial fibrillation (AF) is the most common arrhythmia attacking 1. 5–2.0% of general population worldwide. It has a significant impact on morbidity and mortality globally and its prevalence increases exponentially with age. Therapies like catheter ablation or conventional antiarrhythmic drugs have not provided effective solution to the recurrence for AF over the past decades. Over 100 genetic loci have been discovered to be associated with AF by Genome-wide association studies (GWAS) but none has led to a therapy. Recently potential involvement of epigenetics (DNA methylation, histone modification, and non-coding RNAs) in the initiation and maintenance of AF has partly emerged as proof-of-concept in the mechanism and management of AF. Here we reviewed the epigenetic features involved in AF pathophysiology and provided an update of their implications in AF therapy.
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11
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Lyu C, Huang M, Liu N, Chen Z, Lupo PJ, Tycko B, Witte JS, Hobbs CA, Li M. Detecting methylation quantitative trait loci using a methylation random field method. Brief Bioinform 2021; 22:bbab323. [PMID: 34414410 PMCID: PMC8575051 DOI: 10.1093/bib/bbab323] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 07/09/2021] [Accepted: 07/24/2021] [Indexed: 11/13/2022] Open
Abstract
DNA methylation may be regulated by genetic variants within a genomic region, referred to as methylation quantitative trait loci (mQTLs). The changes of methylation levels can further lead to alterations of gene expression, and influence the risk of various complex human diseases. Detecting mQTLs may provide insights into the underlying mechanism of how genotypic variations may influence the disease risk. In this article, we propose a methylation random field (MRF) method to detect mQTLs by testing the association between the methylation level of a CpG site and a set of genetic variants within a genomic region. The proposed MRF has two major advantages over existing approaches. First, it uses a beta distribution to characterize the bimodal and interval properties of the methylation trait at a CpG site. Second, it considers multiple common and rare genetic variants within a genomic region to identify mQTLs. Through simulations, we demonstrated that the MRF had improved power over other existing methods in detecting rare variants of relatively large effect, especially when the sample size is small. We further applied our method to a study of congenital heart defects with 83 cardiac tissue samples and identified two mQTL regions, MRPS10 and PSORS1C1, which were colocalized with expression QTL in cardiac tissue. In conclusion, the proposed MRF is a useful tool to identify novel mQTLs, especially for studies with limited sample sizes.
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Affiliation(s)
- Chen Lyu
- Department of Epidemiology and Biostatistics, Indiana University, Bloomington, IN, USA
| | - Manyan Huang
- Department of Epidemiology and Biostatistics, Indiana University, Bloomington, IN, USA
| | - Nianjun Liu
- Department of Epidemiology and Biostatistics, Indiana University, Bloomington, IN, USA
| | - Zhongxue Chen
- Department of Epidemiology and Biostatistics, Indiana University, Bloomington, IN, USA
| | - Philip J Lupo
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | | | - John S Witte
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | | | - Ming Li
- Department of Epidemiology and Biostatistics, Indiana University, Bloomington, IN, USA
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12
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Leblanc FJA, Hassani FV, Liesinger L, Qi X, Naud P, Birner-Gruenberger R, Lettre G, Nattel S. Transcriptomic Profiling of Canine Atrial Fibrillation Models After One Week of Sustained Arrhythmia. Circ Arrhythm Electrophysiol 2021; 14:e009887. [PMID: 34270327 PMCID: PMC8376273 DOI: 10.1161/circep.121.009887] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Supplemental Digital Content is available in the text. Atrial fibrillation (AF), the most common sustained arrhythmia, is associated with increased morbidity, mortality, and health care costs. AF develops over many years and is often related to substantial atrial structural and electrophysiological remodeling. AF may lack symptoms at onset, and atrial biopsy samples are generally obtained in subjects with advanced disease, so it is difficult to study earlier stage pathophysiology in humans.
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Affiliation(s)
- Francis J A Leblanc
- Faculty of Medicine, Université de Montréal (F.J.A.L., F.V.H., G.L., S.N.).,Montreal Heart Institute, Montreal, Quebec, Canada (F.J.A.L., F.V.H., X.Q., P.N., G.L., S.N.)
| | - Faezeh Vahdati Hassani
- Faculty of Medicine, Université de Montréal (F.J.A.L., F.V.H., G.L., S.N.).,Montreal Heart Institute, Montreal, Quebec, Canada (F.J.A.L., F.V.H., X.Q., P.N., G.L., S.N.)
| | - Laura Liesinger
- Medical University of Graz, Diagnostic and Research Institute of Pathology (L.L., R.B.-G.).,BioTechMed-Graz, Omics Center Graz (L.L., R.B.-G.)
| | - Xiaoyan Qi
- Montreal Heart Institute, Montreal, Quebec, Canada (F.J.A.L., F.V.H., X.Q., P.N., G.L., S.N.)
| | - Patrice Naud
- Montreal Heart Institute, Montreal, Quebec, Canada (F.J.A.L., F.V.H., X.Q., P.N., G.L., S.N.)
| | - Ruth Birner-Gruenberger
- Medical University of Graz, Diagnostic and Research Institute of Pathology (L.L., R.B.-G.).,BioTechMed-Graz, Omics Center Graz (L.L., R.B.-G.).,Technische Universität Wien, Institute of Chemical Technologies and Analytical Chemistry, Vienna, Austria (R.B.-G.)
| | - Guillaume Lettre
- Faculty of Medicine, Université de Montréal (F.J.A.L., F.V.H., G.L., S.N.).,Montreal Heart Institute, Montreal, Quebec, Canada (F.J.A.L., F.V.H., X.Q., P.N., G.L., S.N.)
| | - Stanley Nattel
- Faculty of Medicine, Université de Montréal (F.J.A.L., F.V.H., G.L., S.N.).,Montreal Heart Institute, Montreal, Quebec, Canada (F.J.A.L., F.V.H., X.Q., P.N., G.L., S.N.).,Institute of Pharmacology, West German Heart and Vascular Center, Faculty of Medicine, University Duisburg-Essen, Germany (S.N.).,Department of Pharmacology, McGill University, Montreal, Quebec, Canada (S.N.).,IHU LIFYC, Bordeaux, France (S.N.)
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13
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Kornej J, Hanger VA, Trinquart L, Ko D, Preis SR, Benjamin EJ, Lin H. New biomarkers from multiomics approaches: improving risk prediction of atrial fibrillation. Cardiovasc Res 2021; 117:1632-1644. [PMID: 33751041 PMCID: PMC8208748 DOI: 10.1093/cvr/cvab073] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 02/07/2021] [Accepted: 03/03/2021] [Indexed: 12/13/2022] Open
Abstract
Atrial fibrillation (AF) is a common cardiac arrhythmia leading to many adverse outcomes and increased mortality. Yet the molecular mechanisms underlying AF remain largely unknown. Recent advances in high-throughput technologies make large-scale molecular profiling possible. In the past decade, multiomics studies of AF have identified a number of potential biomarkers of AF. In this review, we focus on the studies of multiomics profiles with AF risk. We summarize recent advances in the discovery of novel biomarkers for AF through multiomics studies. We also discuss limitations and future directions in risk assessment and discovery of therapeutic targets for AF.
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Affiliation(s)
- Jelena Kornej
- National Heart, Lung, and Blood Institute’s Framingham Heart Study, 73 Mt Wayte Ave, Framingham, MA 01702, USA
- Section of Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | | | - Ludovic Trinquart
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Darae Ko
- Section of Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Sarah R Preis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Emelia J Benjamin
- National Heart, Lung, and Blood Institute’s Framingham Heart Study, 73 Mt Wayte Ave, Framingham, MA 01702, USA
- Section of Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Section of Preventive Medicine & Epidemiology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Honghuang Lin
- National Heart, Lung, and Blood Institute’s Framingham Heart Study, 73 Mt Wayte Ave, Framingham, MA 01702, USA
- Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
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14
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Fischer MA, Vondriska TM. Clinical epigenomics for cardiovascular disease: Diagnostics and therapies. J Mol Cell Cardiol 2021; 154:97-105. [PMID: 33561434 PMCID: PMC8330446 DOI: 10.1016/j.yjmcc.2021.01.011] [Citation(s) in RCA: 3] [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: 10/08/2020] [Revised: 01/05/2021] [Accepted: 01/10/2021] [Indexed: 12/28/2022]
Abstract
The study of epigenomics has advanced in recent years to span the regulation of a single genetic locus to the structure and orientation of entire chromosomes within the nucleus. In this review, we focus on the challenges and opportunities of clinical epigenomics in cardiovascular disease. As an integrator of genetic and environmental inputs, and because of advances in measurement techniques that are highly reproducible and provide sequence information, the epigenome is a rich source of potential biosignatures of cardiovascular health and disease. Most of the studies to date have focused on the latter, and herein we discuss observations on epigenomic changes in human cardiovascular disease, examining the role of protein modifiers of chromatin, noncoding RNAs and DNA modification. We provide an overview of cardiovascular epigenomics, discussing the challenges of data sovereignty, data analysis, doctor-patient ethics and innovations necessary to implement precision health.
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Affiliation(s)
- Matthew A Fischer
- Department of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine at UCLA, USA.
| | - Thomas M Vondriska
- Department of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine at UCLA, USA
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15
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Epigenetics in atrial fibrillation: A reappraisal. Heart Rhythm 2021; 18:824-832. [PMID: 33440248 DOI: 10.1016/j.hrthm.2021.01.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 12/23/2020] [Accepted: 01/01/2021] [Indexed: 11/21/2022]
Abstract
Atrial fibrillation (AF) is the most common cardiac arrhythmia and an important cause of morbidity and mortality globally. Atrial remodeling includes changes in ion channel expression and function, structural alterations, and neural remodeling, which create an arrhythmogenic milieu resulting in AF initiation and maintenance. Current therapeutic strategies for AF involving ablation and antiarrhythmic drugs are associated with relatively high recurrence and proarrhythmic side effects, respectively. Over the last 2 decades, in an effort to overcome these issues, research has sought to identify the genetic basis for AF thereby gaining insight into the regulatory mechanisms governing its pathophysiology. Despite identification of multiple gene loci associated with AF, thus far none has led to a therapy, indicating additional contributors to pathology. Recently, in the context of expanding knowledge of the epigenome (DNA methylation, histone modifications, and noncoding RNAs), its potential involvement in the onset and progression of AF pathophysiology has started to emerge. Probing the role of various epigenetic mechanisms that contribute to AF may improve our knowledge of this complex disease, identify potential therapeutic targets, and facilitate targeted therapies. Here, we provide a comprehensive review of growing epigenetic features involved in AF pathogenesis and summarize the emerging epigenomic targets for therapy that have been explored in preclinical models of AF.
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16
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Zhu X, Tang X, Chong H, Cao H, Fan F, Pan J, Wang D, Zhou Q. Expression Profiles of Circular RNA in Human Atrial Fibrillation With Valvular Heart Diseases. Front Cardiovasc Med 2020; 7:597932. [PMID: 33330659 PMCID: PMC7714832 DOI: 10.3389/fcvm.2020.597932] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Accepted: 10/29/2020] [Indexed: 01/22/2023] Open
Abstract
Circular RNAs (circRNA) are involved in a variety of human heart diseases, however, circRNA expression profiles and circRNA-miRNA-mRNA regulatory network in human atrial fibrillation (AF) especially with valvular heart diseases (VHD) remain poorly understood. A high-throughput RNA sequencing was used to investigate the differentially expressed circRNAs in left atrial appendage from VHD patients with or without persistent AF. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed to predict the potential functions of the host genes of differentially expressed circRNA and their downstream targets. CircRNA-miRNA-mRNA regulatory network was constructed to identify mechanisms underlying circRNAs. qRT-PCR and sanger sequencing were further performed to validate the results. Compared with sinus rhythm (SR) patients, there were 3094 upregulated and 4472 downregulated circRNAs in AF patients respectively. The expression of 10 most differentially expressed circRNAs (circ 255-ITGA7, circ 418-KCNN2, circ 13913-MIB1, circ 44670-BARD1, circ 44782-LAMA2, circ 81906-RYR2, circ 35880-ANO5, circ 22249-TNNI3K, circ 3136-TNNI3K, circ 56186-TNNI3K) between SR and persistent AF patients were verified by qRT-PCR. In addition, specific back-splicing sites of these circRNAs was confirmed by sanger sequencing. GO and KEGG pathway analysis indicated that cAMP signal pathway and Wnt signal pathway might play important role in the development of AF in VHD patients, which might be affected by circRNAs. This study provided a preliminary landscape of circRNAs expression profiles which are involved in persistent AF due to VHD, and established the possibility for future related researches in this field.
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Affiliation(s)
- Xiyu Zhu
- Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Xinlong Tang
- Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Hoshun Chong
- Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Hailong Cao
- Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Fudong Fan
- Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Jun Pan
- Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Dongjin Wang
- Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Qing Zhou
- Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
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17
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Chen X, Li G, Zhang J, Huang X, Ye Z, Zhao Y. Association Between GJA1 rs13216675 T>C Polymorphism and Risk of Atrial Fibrillation: A Systematic Review and Meta-Analysis. Front Cardiovasc Med 2020; 7:585268. [PMID: 33195471 PMCID: PMC7649778 DOI: 10.3389/fcvm.2020.585268] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Accepted: 09/11/2020] [Indexed: 01/11/2023] Open
Abstract
Background: Rs13216675 T>C polymorphism, an SNP (single-nucleotide polymorphism) close to the gap junction protein alpha 1 (GJA1) gene, has been reported to be associated with risk of atrial fibrillation (AF); however, the results remained inconclusive. We aimed to perform a systematic review to clarify the relationship between rs13216675 and risk of AF. Materials and methods: We systematically searched the databases of PubMed, EMBASE, Web of Science, and the Chinese National Knowledge Infrastructure up to July 15, 2020. Data were synthesized using the random-effects model. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to estimate the relationship between rs13216675 and risk of AF. Results: Seven studies involving 39,827 cases and 458,466 controls were analyzed in the meta-analysis. The overall pooled OR of rs13216675 polymorphism for AF was significant (OR = 1.10, 95% CI = 1.07–1.12, P < 0.001) under the additive genetic model. Subgroup analyses revealed that rs13216675 polymorphism was significantly associated with AF in both Asians (OR = 1.12, 95% CI = 1.07–1.17, P < 0.001) and Europeans (OR = 1.09, 95% CI = 1.06–1.12, P < 0.001). When data were stratified by control sources, rs13216675 polymorphism was significantly related to AF in studies with both population-based controls (OR = 1.09, 95% CI = 1.07–1.12) and hospital-based controls (OR = 1.12, 95% CI = 1.07–1.17). No evidence of publication bias was detected. Conclusion: Our meta-analysis suggested that rs13216675 was significantly related to risk of AF and, therefore, might serve as a potential biological marker of AF.
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Affiliation(s)
- Xuejiao Chen
- Center for Clinical Epidemiology and Methodology, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Guowei Li
- Center for Clinical Epidemiology and Methodology, Guangdong Second Provincial General Hospital, Guangzhou, China.,Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Junguo Zhang
- Center for Clinical Epidemiology and Methodology, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Xin Huang
- Center for Clinical Epidemiology and Methodology, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Zebing Ye
- Department of Cardiology, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Yahong Zhao
- Department of Cardiology, Guangdong Second Provincial General Hospital, Guangzhou, China
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18
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Lipovsky CE, Jimenez J, Guo Q, Li G, Yin T, Hicks SC, Bhatnagar S, Takahashi K, Zhang DM, Brumback BD, Goldsztejn U, Nadadur RD, Perez-Cervantez C, Moskowitz IP, Liu S, Zhang B, Rentschler SL. Chamber-specific transcriptional responses in atrial fibrillation. JCI Insight 2020; 5:135319. [PMID: 32841220 PMCID: PMC7526559 DOI: 10.1172/jci.insight.135319] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Accepted: 08/19/2020] [Indexed: 12/30/2022] Open
Abstract
Atrial fibrillation (AF) is the most common cardiac arrhythmia, yet the molecular signature of the vulnerable atrial substrate is not well understood. Here, we delineated a distinct transcriptional signature in right versus left atrial cardiomyocytes (CMs) at baseline and identified chamber-specific gene expression changes in patients with a history of AF in the setting of end-stage heart failure (AF+HF) that are not present in heart failure alone (HF). We observed that human left atrial (LA) CMs exhibited Notch pathway activation and increased ploidy in AF+HF but not in HF alone. Transient activation of Notch signaling within adult CMs in a murine genetic model is sufficient to increase ploidy in both atrial chambers. Notch activation within LA CMs generated a transcriptomic fingerprint resembling AF, with dysregulation of transcription factor and ion channel genes, including Pitx2, Tbx5, Kcnh2, Kcnq1, and Kcnip2. Notch activation also produced distinct cellular electrophysiologic responses in LA versus right atrial CMs, prolonging the action potential duration (APD) without altering the upstroke velocity in the left atrium and reducing the maximal upstroke velocity without altering the APD in the right atrium. Our results support a shared human/murine model of increased Notch pathway activity predisposing to AF. Distinct transcriptional changes occur in human left versus right atrial cardiomyocytes in atrial fibrillation, including Notch pathway activation, which alters electric properties and ploidy in murine models.
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Affiliation(s)
- Catherine E Lipovsky
- Department of Medicine, Cardiovascular Division.,Department of Developmental Biology, and
| | | | - Qiusha Guo
- Department of Medicine, Cardiovascular Division
| | - Gang Li
- Department of Medicine, Cardiovascular Division.,Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Tiankai Yin
- Department of Medicine, Cardiovascular Division
| | | | - Somya Bhatnagar
- Department of Medicine, Cardiovascular Division.,Department of Developmental Biology, and
| | | | | | - Brittany D Brumback
- Department of Medicine, Cardiovascular Division.,Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Uri Goldsztejn
- Department of Medicine, Cardiovascular Division.,Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Rangarajan D Nadadur
- Departments of Pediatrics, Pathology, and Human Genetics, Biological Sciences Division, University of Chicago, Chicago, Illinois, USA
| | - Carlos Perez-Cervantez
- Departments of Pediatrics, Pathology, and Human Genetics, Biological Sciences Division, University of Chicago, Chicago, Illinois, USA
| | - Ivan P Moskowitz
- Departments of Pediatrics, Pathology, and Human Genetics, Biological Sciences Division, University of Chicago, Chicago, Illinois, USA
| | | | - Bo Zhang
- Department of Developmental Biology, and
| | - Stacey L Rentschler
- Department of Medicine, Cardiovascular Division.,Department of Developmental Biology, and.,Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
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19
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Genetics and Epigenetics of Atrial Fibrillation. Int J Mol Sci 2020; 21:ijms21165717. [PMID: 32784971 PMCID: PMC7460853 DOI: 10.3390/ijms21165717] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Revised: 07/22/2020] [Accepted: 07/27/2020] [Indexed: 12/13/2022] Open
Abstract
Atrial fibrillation (AF) is known to be the most common supraventricular arrhythmia affecting up to 1% of the general population. Its prevalence exponentially increases with age and could reach up to 8% in the elderly population. The management of AF is a complex issue that is addressed by extensive ongoing basic and clinical research. AF centers around different types of disturbances, including ion channel dysfunction, Ca2+-handling abnormalities, and structural remodeling. Genome-wide association studies (GWAS) have uncovered over 100 genetic loci associated with AF. Most of these loci point to ion channels, distinct cardiac-enriched transcription factors, as well as to other regulatory genes. Recently, the discovery of post-transcriptional regulatory mechanisms, involving non-coding RNAs (especially microRNAs), DNA methylation, and histone modification, has allowed to decipher how a normal heart develops and which modifications are involved in reshaping the processes leading to arrhythmias. This review aims to provide a current state of the field regarding the identification and functional characterization of AF-related epigenetic regulatory networks
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20
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Huang X, Li Y, Zhang J, Wang X, Li Z, Li G. The molecular genetic basis of atrial fibrillation. Hum Genet 2020; 139:1485-1498. [PMID: 32617797 DOI: 10.1007/s00439-020-02203-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Accepted: 06/26/2020] [Indexed: 12/15/2022]
Abstract
As the most common cardiac arrhythmia, atrial fibrillation (AF) is a major risk factor for stroke, heart failure, and premature death with considerable associated costs. However, no available treatment options have optimal benefit-harm profiles currently, reflecting an incomplete understanding of the biological mechanisms underlying this complex arrhythmia. Recently, molecular epidemiological studies, especially genome-wide association studies, have emphasized the substantial genetic component of AF etiology. A comprehensive mapping of the genetic underpinnings for AF can expand our knowledge of AF mechanism and further facilitate the process of locating novel therapeutics for AF. Here we provide a state-of-the-art review of the molecular genetics of AF incorporating evidence from linkage analysis and candidate gene, as well as genome-wide association studies of common variations and rare copy number variations; potential epigenetic modifications (e.g., DNA methylation, histone modification, and non-coding RNAs) are also involved. We also outline the challenges in mechanism investigation and potential future directions in this article.
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Affiliation(s)
- Xin Huang
- Center for Clinical Epidemiology and Methodology (CCEM), Guangdong Second Provincial General Hospital, 466 Newport Middle Road, Haizhu District, Guangzhou, 510317, Guangdong, China
| | - Yuhui Li
- Department of Cardiology, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Junguo Zhang
- Center for Clinical Epidemiology and Methodology (CCEM), Guangdong Second Provincial General Hospital, 466 Newport Middle Road, Haizhu District, Guangzhou, 510317, Guangdong, China
| | - Xiaojie Wang
- Center for Clinical Epidemiology and Methodology (CCEM), Guangdong Second Provincial General Hospital, 466 Newport Middle Road, Haizhu District, Guangzhou, 510317, Guangdong, China
| | - Ziyi Li
- Center for Clinical Epidemiology and Methodology (CCEM), Guangdong Second Provincial General Hospital, 466 Newport Middle Road, Haizhu District, Guangzhou, 510317, Guangdong, China
| | - Guowei Li
- Center for Clinical Epidemiology and Methodology (CCEM), Guangdong Second Provincial General Hospital, 466 Newport Middle Road, Haizhu District, Guangzhou, 510317, Guangdong, China. .,Department of Health Research Methods, Evidence, and Impact (HEI), McMaster University Hamilton, 1280 Main St West, Hamilton, ON, L8S 4L8, Canada.
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21
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Abstract
Atrial fibrillation is a common heart rhythm disorder that leads to an increased risk for stroke and heart failure. Atrial fibrillation is a complex disease with both environmental and genetic risk factors that contribute to the arrhythmia. Over the last decade, rapid progress has been made in identifying the genetic basis for this common condition. In this review, we provide an overview of the primary types of genetic analyses performed for atrial fibrillation, including linkage studies, genome-wide association studies, and studies of rare coding variation. With these results in mind, we aim to highlighting the existing knowledge gaps and future directions for atrial fibrillation genetics research.
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Affiliation(s)
- Carolina Roselli
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, MA, USA
- Department of Cardiology, University of Groningen, University Medical Center Groningen Groningen, the Netherlands
| | - Michiel Rienstra
- Department of Cardiology, University of Groningen, University Medical Center Groningen Groningen, the Netherlands
| | - Patrick T. Ellinor
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston, MA, USA
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22
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van Ouwerkerk AF, Hall AW, Kadow ZA, Lazarevic S, Reyat JS, Tucker NR, Nadadur RD, Bosada FM, Bianchi V, Ellinor PT, Fabritz L, Martin J, de Laat W, Kirchhof P, Moskowitz I, Christoffels VM. Epigenetic and Transcriptional Networks Underlying Atrial Fibrillation. Circ Res 2020; 127:34-50. [PMID: 32717170 PMCID: PMC8315291 DOI: 10.1161/circresaha.120.316574] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Genome-wide association studies have uncovered over a 100 genetic loci associated with atrial fibrillation (AF), the most common arrhythmia. Many of the top AF-associated loci harbor key cardiac transcription factors, including PITX2, TBX5, PRRX1, and ZFHX3. Moreover, the vast majority of the AF-associated variants lie within noncoding regions of the genome where causal variants affect gene expression by altering the activity of transcription factors and the epigenetic state of chromatin. In this review, we discuss a transcriptional regulatory network model for AF defined by effector genes in Genome-wide association studies loci. We describe the current state of the field regarding the identification and function of AF-relevant gene regulatory networks, including variant regulatory elements, dose-sensitive transcription factor functionality, target genes, and epigenetic states. We illustrate how altered transcriptional networks may impact cardiomyocyte function and ionic currents that impact AF risk. Last, we identify the need for improved tools to identify and functionally test transcriptional components to define the links between genetic variation, epigenetic gene regulation, and atrial function.
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Affiliation(s)
- Antoinette F. van Ouwerkerk
- Department of Medical Biology, Amsterdam University Medical Centers, Academic Medical Center, 1105 AZ Amsterdam, The Netherlands
| | - Amelia W. Hall
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Zachary A. Kadow
- Program in Developmental Biology, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA
- Medical Scientist Training Program, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA
| | - Sonja Lazarevic
- Departments of Pediatrics, Pathology, and Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Jasmeet S. Reyat
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
| | - Nathan R. Tucker
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Masonic Medical Research Institute, Utica, NY, USA
| | - Rangarajan D. Nadadur
- Departments of Pediatrics, Pathology, and Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Fernanda M. Bosada
- Department of Medical Biology, Amsterdam University Medical Centers, Academic Medical Center, 1105 AZ Amsterdam, The Netherlands
| | - Valerio Bianchi
- Oncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, the Netherlands
| | - Patrick T. Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Larissa Fabritz
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
- SWBH and UHB NHS Trusts, Birmingham, UK
| | - Jim Martin
- Program in Developmental Biology, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA
- Department of Molecular Physiology and Biophysics, Baylor College of Medicine, One Baylor Plaza, Houston, Texas, 77030
- Texas Heart Institute, Houston, Texas, 77030
| | - Wouter de Laat
- Oncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, the Netherlands
| | - Paulus Kirchhof
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
- SWBH and UHB NHS Trusts, Birmingham, UK
- University Heart and Vascular Center Hamburg, Hamburg, Germany
| | - Ivan Moskowitz
- Departments of Pediatrics, Pathology, and Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Vincent M. Christoffels
- Department of Medical Biology, Amsterdam University Medical Centers, Academic Medical Center, 1105 AZ Amsterdam, The Netherlands
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23
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Kornej J, Börschel CS, Benjamin EJ, Schnabel RB. Epidemiology of Atrial Fibrillation in the 21st Century: Novel Methods and New Insights. Circ Res 2020; 127:4-20. [PMID: 32716709 DOI: 10.1161/circresaha.120.316340] [Citation(s) in RCA: 627] [Impact Index Per Article: 156.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Accompanying the aging of populations worldwide, and increased survival with chronic diseases, the incidence and prevalence of atrial fibrillation (AF) are rising, justifying the term global epidemic. This multifactorial arrhythmia is intertwined with common concomitant cardiovascular diseases, which share classical cardiovascular risk factors. Targeted prevention programs are largely missing. Prevention needs to start at an early age with primordial interventions at the population level. The public health dimension of AF motivates research in modifiable AF risk factors and improved precision in AF prediction and management. In this review, we summarize current knowledge in an attempt to untangle these multifaceted associations from an epidemiological perspective. We discuss disease trends, preventive opportunities offered by underlying risk factors and concomitant disorders, current developments in diagnosis and risk prediction, and prognostic implications of AF and its complications. Finally, we review current technological (eg, eHealth) and methodological (artificial intelligence) advances and their relevance for future prevention and disease management.
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Affiliation(s)
- Jelena Kornej
- From the National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, Massachusetts & Sections of Cardiovascular Medicine and Preventive Medicine, Boston Medical Center (J.K., E.J.B.), Boston University School of Medicine, MA
| | - Christin S Börschel
- Department of General and Interventional Cardiology, University Heart & Vascular Center Hamburg Eppendorf, Hamburg, Germany (C.B., R.B.S.)
- German Center for Cardiovascular Research (DZHK) partner site Hamburg/Kiel/Lübeck (C.B., R.B.S.)
| | - Emelia J Benjamin
- From the National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, Massachusetts & Sections of Cardiovascular Medicine and Preventive Medicine, Boston Medical Center (J.K., E.J.B.), Boston University School of Medicine, MA
- Department of Epidemiology (E.J.B.), Boston University School of Medicine, MA
| | - Renate B Schnabel
- Department of General and Interventional Cardiology, University Heart & Vascular Center Hamburg Eppendorf, Hamburg, Germany (C.B., R.B.S.)
- German Center for Cardiovascular Research (DZHK) partner site Hamburg/Kiel/Lübeck (C.B., R.B.S.)
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24
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Liu B, Shi X, Ding K, Lv M, Qian Y, Zhu S, Guo C, Zhang Y. The Joint Analysis of Multi-Omics Data Revealed the Methylation-Expression Regulations in Atrial Fibrillation. Front Bioeng Biotechnol 2020; 8:187. [PMID: 32226785 PMCID: PMC7080960 DOI: 10.3389/fbioe.2020.00187] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 02/26/2020] [Indexed: 02/05/2023] Open
Abstract
Atrial fibrillation (AF) is one of the most prevalent heart rhythm disorder. The causes of AF include age, male sex, diabetes, hypertension, valve disease, and systolic/diastolic dysfunction. But on molecular level, its mechanisms are largely unknown. In this study, we collected 10 patients with persistent atrial fibrillation, 10 patients with paroxymal atrial fibrillation and 10 healthy individuals and did Methylation EPICBead Chip and RNA sequencing. By analyzing the methylation and gene expression data using machine learning based feature selection method Boruta, we identified the key genes that were strongly associated with AF and found their interconnections. The results suggested that the methylation of KIF15 may regulate the expression of PSMC3, TINAG, and NUDT6. The identified AF associated methylation-expression regulations may help understand the molecular mechanisms of AF from a multi-omics perspective.
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Affiliation(s)
- Ban Liu
- Department of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
| | - Xin Shi
- Department of Pediatric Cardiovascular, Xin Hua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Keke Ding
- Department of Cardiology, Shanghai Tongji Hospital, Tongji University School of Medicine, Shanghai, China
| | - Mengwei Lv
- Shanghai East Hospital of Clinical Medical College, Nanjing Medical University, Shanghai, China.,Department of Cardiovascular Surgery, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
| | - Yongjun Qian
- Department of Cardiovascular Surgery, National Clinical Research Center for Geriatric, West China Hospital, Sichuan University, Chengdu, China
| | - Shijie Zhu
- Department of Cardiovascular Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Changfa Guo
- Department of Cardiovascular Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yangyang Zhang
- Department of Cardiovascular Surgery, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
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25
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Wang B, Lunetta KL, Dupuis J, Lubitz SA, Trinquart L, Yao L, Ellinor PT, Benjamin EJ, Lin H. Integrative Omics Approach to Identifying Genes Associated With Atrial Fibrillation. Circ Res 2020; 126:350-360. [PMID: 31801406 PMCID: PMC7004281 DOI: 10.1161/circresaha.119.315179] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Accepted: 12/03/2019] [Indexed: 12/12/2022]
Abstract
Rationale: GWAS (Genome-Wide Association Studies) have identified hundreds of genetic loci associated with atrial fibrillation (AF). However, these loci explain only a small proportion of AF heritability. Objective: To develop an approach to identify additional AF-related genes by integrating multiple omics data. Methods and Results: Three types of omics data were integrated: (1) summary statistics from the AFGen 2017 GWAS; (2) a whole blood EWAS (Epigenome-Wide Association Study) of AF; and (3) a whole blood TWAS (Transcriptome-Wide Association Study) of AF. The variant-level GWAS results were collapsed into gene-level associations using fast set-based association analysis. The CpG-level EWAS results were also collapsed into gene-level associations by an adapted SNP-set Kernel Association Test approach. Both GWAS and EWAS gene-based associations were then meta-analyzed with TWAS using a fixed-effects model weighted by the sample size of each data set. A tissue-specific network was subsequently constructed using the NetWAS (Network-Wide Association Study). The identified genes were then compared with the AFGen 2018 GWAS that contained more than triple the number of AF cases compared with AFGen 2017 GWAS. We observed that the multiomics approach identified many more relevant AF-related genes than using AFGen 2018 GWAS alone (1931 versus 206 genes). Many of these genes are involved in the development and regulation of heart- and muscle-related biological processes. Moreover, the gene set identified by multiomics approach explained much more AF variance than those identified by GWAS alone (10.4% versus 3.5%). Conclusions: We developed a strategy to integrate multiple omics data to identify AF-related genes. Our integrative approach may be useful to improve the power of traditional GWAS, which might be particularly useful for rare traits and diseases with limited sample size.
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Affiliation(s)
- Biqi Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Kathryn L. Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
- Boston University and National Heart, Lung and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts, USA
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
- Boston University and National Heart, Lung and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts, USA
| | - Steven A. Lubitz
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, The Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
- Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Ludovic Trinquart
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
- Boston University and National Heart, Lung and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts, USA
| | - Lixia Yao
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Patrick T. Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, The Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
- Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Emelia J. Benjamin
- Boston University and National Heart, Lung and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts, USA
- Sections of Preventive Medicine and Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Honghuang Lin
- Boston University and National Heart, Lung and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts, USA
- Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts, USA
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26
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Lin H, Lunetta KL, Zhao Q, Mandaviya PR, Rong J, Benjamin EJ, Joehanes R, Levy D, van Meurs JBJ, Larson MG, Murabito JM. Whole Blood Gene Expression Associated With Clinical Biological Age. J Gerontol A Biol Sci Med Sci 2019; 74:81-88. [PMID: 30010802 DOI: 10.1093/gerona/gly164] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Accepted: 07/12/2018] [Indexed: 12/11/2022] Open
Abstract
Background Biologic age may better reflect an individual's rate of aging than chronologic age. Methods We conducted a transcriptome-wide association study with biologic age estimated with clinical biomarkers, which included: systolic blood pressure, forced expiratory volume at 1 second (FEV1), total cholesterol, fasting glucose, C-reactive protein, and serum creatinine. We assessed the association between the difference between biologic age and chronologic age (∆age) and gene expression in whole blood measured using the Affymetrix Human Exon 1.0st Array. Results Our discovery sample included 2,163 participants from the Framingham Offspring cohort (mean age 67 ± 9 years, 55% women). A total of 481 genes were significantly associated with ∆age (p < 2.8 × 10-6). Among them, 415 genes were validated (p < .05/481 = 1.0 × 10-4) in 2,946 participants from the Framingham Third Generation cohort (mean age 46 ± 9 years, 53% women). Many of the significant genes were involved in the ubiquitin-mediated proteolysis pathway. The replication in 414 Rotterdam Study participants (mean age 59 ± 8, 52% women) found 104 of 415 validated genes reached nominal significance (p < .05). Conclusion We identified and validated 415 genes associated with ∆age in a community-based cohort. Future functional characterization of the biologic age-related gene network may identify targets to test for interventions to delay aging in older adults.
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Affiliation(s)
- Honghuang Lin
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Massachusetts.,Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Massachusetts
| | - Kathryn L Lunetta
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Massachusetts.,Department of Biostatistics, Boston University School of Public Health, Massachusetts
| | - Qiang Zhao
- Department of Biostatistics, Boston University School of Public Health, Massachusetts
| | - Pooja R Mandaviya
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Jian Rong
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Massachusetts.,Department of Biostatistics, Boston University School of Public Health, Massachusetts
| | - Emelia J Benjamin
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Massachusetts.,Section of Cardiovascular Medicine and Preventive Medicine, Department of Medicine, Boston University School of Medicine, Massachusetts.,Department of Epidemiology, Boston University School of Public Health, Massachusetts
| | - Roby Joehanes
- Hebrew SeniorLife, Harvard Medical School, Boston, Massachusetts
| | - Daniel Levy
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Massachusetts.,Population Sciences Branch, National Heart, Lung, and Blood Institute, Bethesda, Maryland
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Martin G Larson
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Massachusetts.,Department of Biostatistics, Boston University School of Public Health, Massachusetts
| | - Joanne M Murabito
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Massachusetts.,Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Massachusetts
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27
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Abstract
Supplemental Digital Content is available in the text. If unifying principles could be revealed for how the same genome encodes different eukaryotic cells and for how genetic variability and environmental input are integrated to impact cardiovascular health, grand challenges in basic cell biology and translational medicine may succumb to experimental dissection. A rich body of work in model systems has implicated chromatin-modifying enzymes, DNA methylation, noncoding RNAs, and other transcriptome-shaping factors in adult health and in the development, progression, and mitigation of cardiovascular disease. Meanwhile, deployment of epigenomic tools, powered by next-generation sequencing technologies in cardiovascular models and human populations, has enabled description of epigenomic landscapes underpinning cellular function in the cardiovascular system. This essay aims to unpack the conceptual framework in which epigenomes are studied and to stimulate discussion on how principles of chromatin function may inform investigations of cardiovascular disease and the development of new therapies.
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Affiliation(s)
- Manuel Rosa-Garrido
- From the Departments of Anesthesiology, Medicine, and Physiology, David Geffen School of Medicine, University of California, Los Angeles
| | - Douglas J Chapski
- From the Departments of Anesthesiology, Medicine, and Physiology, David Geffen School of Medicine, University of California, Los Angeles
| | - Thomas M Vondriska
- From the Departments of Anesthesiology, Medicine, and Physiology, David Geffen School of Medicine, University of California, Los Angeles.
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28
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Andersson C, Johnson AD, Benjamin EJ, Levy D, Vasan RS. 70-year legacy of the Framingham Heart Study. Nat Rev Cardiol 2019; 16:687-698. [DOI: 10.1038/s41569-019-0202-5] [Citation(s) in RCA: 84] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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29
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Yang Y, Wu L, Shu X, Lu Y, Shu XO, Cai Q, Beeghly-Fadiel A, Li B, Ye F, Berchuck A, Anton-Culver H, Banerjee S, Benitez J, Bjørge L, Brenton JD, Butzow R, Campbell IG, Chang-Claude J, Chen K, Cook LS, Cramer DW, deFazio A, Dennis J, Doherty JA, Dörk T, Eccles DM, Edwards DV, Fasching PA, Fortner RT, Gayther SA, Giles GG, Glasspool RM, Goode EL, Goodman MT, Gronwald J, Harris HR, Heitz F, Hildebrandt MA, Høgdall E, Høgdall CK, Huntsman DG, Kar SP, Karlan BY, Kelemen LE, Kiemeney LA, Kjaer SK, Koushik A, Lambrechts D, Le ND, Levine DA, Massuger LF, Matsuo K, May T, McNeish IA, Menon U, Modugno F, Monteiro AN, Moorman PG, Moysich KB, Ness RB, Nevanlinna H, Olsson H, Onland-Moret NC, Park SK, Paul J, Pearce CL, Pejovic T, Phelan CM, Pike MC, Ramus SJ, Riboli E, Rodriguez-Antona C, Romieu I, Sandler DP, Schildkraut JM, Setiawan VW, Shan K, Siddiqui N, Sieh W, Stampfer MJ, Sutphen R, Swerdlow AJ, Szafron LM, Teo SH, Tworoger SS, Tyrer JP, Webb PM, Wentzensen N, White E, Willett WC, Wolk A, Woo YL, Wu AH, Yan L, Yannoukakos D, Chenevix-Trench G, Sellers TA, Pharoah PDP, Zheng W, Long J. Genetic Data from Nearly 63,000 Women of European Descent Predicts DNA Methylation Biomarkers and Epithelial Ovarian Cancer Risk. Cancer Res 2019; 79:505-517. [PMID: 30559148 PMCID: PMC6359948 DOI: 10.1158/0008-5472.can-18-2726] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2018] [Revised: 10/16/2018] [Accepted: 12/06/2018] [Indexed: 12/12/2022]
Abstract
DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study (N = 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of P < 7.94 × 10-7. Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely MAPT, HOXB3, ABHD8, ARHGAP27, and SKAP1. We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression. SIGNIFICANCE: Identification of novel DNA methylation markers associated with EOC risk suggests that methylation at multiple CpG may affect EOC risk through regulation of gene expression.
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Affiliation(s)
- Yaohua Yang
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Lang Wu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Xiang Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Yingchang Lu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Alicia Beeghly-Fadiel
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Bingshan Li
- Department of Molecular Physiology & Biophysics, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, Tennessee
| | - Fei Ye
- Division of Cancer Biostatistics, Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Andrew Berchuck
- Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, North Carolina
| | - Hoda Anton-Culver
- Department of Epidemiology, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, California
| | - Susana Banerjee
- Gynaecology Unit, Royal Marsden Hospital, London, United Kingdom
| | - Javier Benitez
- Human Cancer Genetics Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Biomedical Network on Rare Diseases (CIBERER), Madrid, Spain
| | - Line Bjørge
- Department of Gynecology and Obstetrics, Haukeland University Hospital, Bergen, Norway
- Center for Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - James D Brenton
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Ralf Butzow
- Department of Pathology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Ian G Campbell
- Peter MacCallum Cancer Center, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Cancer Epidemiology Group, University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Kexin Chen
- Department of Epidemiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Linda S Cook
- University of New Mexico Health Sciences Center, University of New Mexico, Albuquerque, New Mexico
- Department of Cancer Epidemiology and Prevention Research, Alberta Health Services, Calgary, Alberta, Canada
| | - Daniel W Cramer
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Obstetrics and Gynecology Epidemiology Center, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Anna deFazio
- Centre for Cancer Research, The Westmead Institute for Medical Research, The University of Sydney, Sydney, New South Wales, Australia
- Department of Gynaecological Oncology, Westmead Hospital, Sydney, New South Wales, Australia
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Jennifer A Doherty
- Huntsman Cancer Institute, Department of Population Health Sciences, University of Utah, Salt Lake City, Utah
| | - Thilo Dörk
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
| | - Diana M Eccles
- Cancer Sciences Academic Unit, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Digna Velez Edwards
- Vanderbilt Epidemiology Center, Vanderbilt Genetics Institute, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Peter A Fasching
- David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California at Los Angeles, Los Angeles, California
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center ER-EMN, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
| | - Renée T Fortner
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Simon A Gayther
- The Center for Bioinformatics and Functional Genomics at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Graham G Giles
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | | | - Ellen L Goode
- Department of Health Science Research, Division of Epidemiology, Mayo Clinic, Rochester, Minnesota
| | - Marc T Goodman
- Samuel Oschin Comprehensive Cancer Institute, Cancer Prevention and Genetics Program, Cedars-Sinai Medical Center, Los Angeles, California
| | - Jacek Gronwald
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Holly R Harris
- Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington
- Department of Epidemiology, University of Washington, Seattle, Washington
| | - Florian Heitz
- Department of Gynecology and Gynecologic Oncology, Dr. Horst Schmidt Kliniken Wiesbaden, Wiesbaden, Germany
- Department of Gynecology and Gynecologic Oncology, Kliniken Essen-Mitte/Evang. Huyssens-Stiftung/Knappschaft GmbH, Essen, Germany
| | - Michelle A Hildebrandt
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Estrid Høgdall
- Department of Virus, Lifestyle and Genes, Danish Cancer Society Research Center, Copenhagen, Denmark
- Molecular Unit, Department of Pathology, Herlev Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Claus K Høgdall
- The Juliane Marie Centre, Department of Gynecology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - David G Huntsman
- Department of Molecular Oncology, BC Cancer Research Centre, Vancouver, British Columbia, Canada
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Obstetrics and Gynecology, University of British Columbia, Vancouver, British Columbia, Canada
- OVCARE, Vancouver Coastal Health Research Centre, Vancouver General Hospital and University of British Columbia, Vancouver, British Columbia, Canada
| | - Siddhartha P Kar
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Beth Y Karlan
- Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Linda E Kelemen
- Hollings Cancer Center and Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina
| | - Lambertus A Kiemeney
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Susanne K Kjaer
- Department of Virus, Lifestyle and Genes, Danish Cancer Society Research Center, Copenhagen, Denmark
- Department of Gynaecology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Anita Koushik
- CHUM Research Centre (CRCHUM) and Département de Médicine Sociale et Préventive, Université de Montréal, Montréal, Quebec, Canada
| | - Diether Lambrechts
- VIB Center for Cancer Biology, VIB and Laboratory for Translational Genetics, Department of Human Genetics, University of Leuven, Leuven, Belgium
| | - Nhu D Le
- Cancer Control Research, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Douglas A Levine
- Gynecology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
- Gynecologic Oncology, Laura and Isaac Pearlmutter Cancer Center, NYU Langone Medical Center, New York, New York
| | - Leon F Massuger
- Department of Gynaecology, Radboud Institute for Molecular Life sciences, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Keitaro Matsuo
- Division of Molecular Medicine, Aichi Cancer Center Research Institute, Nagoya, Japan
- Department of Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Taymaa May
- Division of Gynecologic Oncology, University Health Network, Princess Margaret Hospital, Toronto, Ontario, Canada
| | - Iain A McNeish
- Department Surgery & Cancer, Imperial College London, London, United Kingdom
- Institute of Cancer Sciences, University of Glasgow, Wolfson Wohl Cancer Research Centre, Beatson Institute for Cancer Research, Glasgow, United Kingdom
| | - Usha Menon
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, University College London, London, United Kingdom
| | - Francesmary Modugno
- Womens Cancer Research Center, Magee-Womens Research Institute and Hillman Cancer Center, Pittsburgh, Pennsylvania
- Division of Gynecologic Oncology, Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Alvaro N Monteiro
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, Florida
| | - Patricia G Moorman
- Department of Community and Family Medicine, Duke University Medical Center, Durham, North Carolina
| | - Kirsten B Moysich
- Division of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, New York
| | - Roberta B Ness
- School of Public Health, University of Texas Health Science Center at Houston (UTHealth), Houston, Texas
| | - Heli Nevanlinna
- Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Håkan Olsson
- Department of Cancer Epidemiology, Clinical Sciences, Lund University, Lund, Sweden
| | - N Charlotte Onland-Moret
- Julius Center for Health Sciences and Primary Care, University Utrecht, UMC Utrecht, Utrecht, the Netherlands
| | - Sue K Park
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
- Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, Korea
- Cancer Research Institute, Seoul National University, Seoul, Korea
| | - James Paul
- The Beatson West of Scotland Cancer Centre, Glasgow, United Kingdom
| | - Celeste L Pearce
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California Norris Comprehensive Cancer Center, Los Angeles, California
| | - Tanja Pejovic
- Department of Obstetrics and Gynecology, Oregon Health & Science University, Portland, Oregon
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon
| | - Catherine M Phelan
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, Florida
| | - Malcolm C Pike
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California Norris Comprehensive Cancer Center, Los Angeles, California
- Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, New York
| | - Susan J Ramus
- School of Women's and Children's Health, Faculty of Medicine, University of New South Wales Sydney, Sydney, New South Wales, Australia
- The Kinghorn Cancer Centre, Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Elio Riboli
- Imperial College London, London, United Kingdom
| | - Cristina Rodriguez-Antona
- Human Cancer Genetics Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Biomedical Network on Rare Diseases (CIBERER), Madrid, Spain
| | - Isabelle Romieu
- Nutrition and Metabolism Section, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, North Carolina
| | - Joellen M Schildkraut
- Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia
| | - Veronica W Setiawan
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Kang Shan
- Department of Obstetrics and Gynaecology, Hebei Medical University, Fourth Hospital, Shijiazhuang, China
| | - Nadeem Siddiqui
- Department of Gynaecological Oncology, Glasgow Royal Infirmary, Glasgow, United Kingdom
| | - Weiva Sieh
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Meir J Stampfer
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Rebecca Sutphen
- Epidemiology Center, College of Medicine, University of South Florida, Tampa, Florida
| | - Anthony J Swerdlow
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom
- Division of Breast Cancer Research, The Institute of Cancer Research, London, United Kingdom
| | - Lukasz M Szafron
- Department of Immunology, Maria Sklodowska-Curie Institute - Oncology Center, Warsaw, Poland
| | - Soo Hwang Teo
- Cancer Research Malaysia, Subang Jaya, Selangor, Malaysia
- Breast Cancer Research Unit, Cancer Research Institute, University Malaya Medical Centre, Kuala Lumpur, Malaysia
| | - Shelley S Tworoger
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, Florida
- Research Institute and Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Jonathan P Tyrer
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, United Kingdom
| | - Penelope M Webb
- Population Health Department, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Nicolas Wentzensen
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland
| | - Emily White
- Fred Hutchinson Cancer Research Center, Seattle, Washington
- Department of Epidemiology, University of Washington, Seattle, Washington
| | - Walter C Willett
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Alicja Wolk
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Yin Ling Woo
- Department of Obstetrics and Gynaecology, University Malaya Medical Centre, University Malaya, Kuala Lumpur, Malaysia
| | - Anna H Wu
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Li Yan
- Department of Molecular Biology, Hebei Medical University, Fourth Hospital, Shijiazhuang, China
| | - Drakoulis Yannoukakos
- Molecular Diagnostics Laboratory, INRASTES, National Centre for Scientific Research "Demokritos", Athens, Greece
| | - Georgia Chenevix-Trench
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Thomas A Sellers
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, Florida
| | - Paul D P Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, United Kingdom
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee.
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Feng X, Wang S, Liu Q, Li H, Liu J, Xu C, Yang W, Shu Y, Zheng W, Yu B, Qi M, Zhou W, Zhou F. Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances. J Vis Exp 2018:57738. [PMID: 30371672 PMCID: PMC6235481 DOI: 10.3791/57738] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Biomarker detection is one of the more important biomedical questions for high-throughput 'omics' researchers, and almost all existing biomarker detection algorithms generate one biomarker subset with the optimized performance measurement for a given dataset. However, a recent study demonstrated the existence of multiple biomarker subsets with similarly effective or even identical classification performances. This protocol presents a simple and straightforward methodology for detecting biomarker subsets with binary classification performances, better than a user-defined cutoff. The protocol consists of data preparation and loading, baseline information summarization, parameter tuning, biomarker screening, result visualization and interpretation, biomarker gene annotations, and result and visualization exportation at publication quality. The proposed biomarker screening strategy is intuitive and demonstrates a general rule for developing biomarker detection algorithms. A user-friendly graphical user interface (GUI) was developed using the programming language Python, allowing biomedical researchers to have direct access to their results. The source code and manual of kSolutionVis can be downloaded from http://www.healthinformaticslab.org/supp/resources.php.
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Affiliation(s)
- Xin Feng
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University
| | - Shaofei Wang
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University
| | - Quewang Liu
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University
| | - Han Li
- College of Software, Jilin University
| | | | - Cheng Xu
- College of Software, Jilin University
| | | | - Yayun Shu
- College of Software, Jilin University
| | - Weiwei Zheng
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University
| | - Bingxin Yu
- Ultrasonography Department, China-Japan Union Hospital of Jilin University
| | - Mingran Qi
- Department of Pathogenobiology, College of Basic Medical Science, Jilin University
| | - Wenyang Zhou
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University
| | - Fengfeng Zhou
- College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University;
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Doñate Puertas R, Jalabert A, Meugnier E, Euthine V, Chevalier P, Rome S. Analysis of the microRNA signature in left atrium from patients with valvular heart disease reveals their implications in atrial fibrillation. PLoS One 2018; 13:e0196666. [PMID: 29723239 PMCID: PMC5933750 DOI: 10.1371/journal.pone.0196666] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2017] [Accepted: 04/17/2018] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Among the potential factors which may contribute to the development and perpetuation of atrial fibrillation, dysregulation of miRNAs has been suggested. Thus in this study, we have quantified the basal expressions of 662 mature human miRNAs in left atrium (LA) from patients undergoing cardiac surgery for valve repair, suffering or not from atrial fibrillation (AF) by using TaqMan® Low Density arrays (v2.0). RESULTS Among the 299 miRNAs expressed in all patients, 42 miRNAs had altered basal expressions in patients with AF. Binding-site predictions with Targetscan (conserved sites among species) indicated that the up- and down-regulated miRNAs controlled respectively 3,310 and 5,868 genes. To identify the most relevant cellular functions under the control of the altered miRNAs, we focused on the 100 most targeted genes of each list and identified 5 functional protein-protein networks among these genes. Up-regulated networks were involved in synchronisation of circadian rythmicity and in the control of the AKT/PKC signaling pathway (i.e., proliferation/adhesion). Down-regulated networks were the IGF-1 pathway and TGF-beta signaling pathway and a network involved in RNA-mediated gene silencing, suggesting for the first time that alteration of miRNAs in AF would also perturbate the whole miRNA machinery. Then we crossed the list of miRNA predicted genes, and the list of mRNAs altered in similar patients suffering from AF and we found that respectively 44.5% and 55% of the up- and down-regulated mRNA are predicted to be conserved targets of the altered miRNAs (at least one binding site in 3'-UTR). As they were involved in the same biological processes mentioned above, these data demonstrated that a great part of the transcriptional defects previously published in LA from AF patients are likely due to defects at the post-transcriptional level and involved the miRNAs. CONCLUSIONS Our stringent analysis permitted us to identify highly targeted protein-protein networks under the control of miRNAs in LA and, among them, to highlight those specifically affected in AF patients with altered miRNA signature. Further studies are now required to determine whether alterations of miRNA levels in AF pathology are causal or represent an adaptation to prevent cardiac electrical and structural remodeling.
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Affiliation(s)
- Rosa Doñate Puertas
- Institut NeuroMyoGene (INMG), UMR CNRS 5310-INSERM U1217 / University of Lyon, Lyon, France
| | - Audrey Jalabert
- CarMeN Laboratory (UMR INSERM 1060-INRA 1397, INSA), Lyon-Sud Faculty of Medicine, University of Lyon, Pierre-Bénite, France
| | - Emmanuelle Meugnier
- CarMeN Laboratory (UMR INSERM 1060-INRA 1397, INSA), Lyon-Sud Faculty of Medicine, University of Lyon, Pierre-Bénite, France
| | - Vanessa Euthine
- CarMeN Laboratory (UMR INSERM 1060-INRA 1397, INSA), Lyon-Sud Faculty of Medicine, University of Lyon, Pierre-Bénite, France
| | - Philippe Chevalier
- Institut NeuroMyoGene (INMG), UMR CNRS 5310-INSERM U1217 / University of Lyon, Lyon, France
- Rhythmology Unit, Louis Pradel Cardiology Hospital, Hospices Civils de Lyon, Bron, France
- * E-mail: (SR); (PC)
| | - Sophie Rome
- CarMeN Laboratory (UMR INSERM 1060-INRA 1397, INSA), Lyon-Sud Faculty of Medicine, University of Lyon, Pierre-Bénite, France
- * E-mail: (SR); (PC)
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Xu C, Liu J, Yang W, Shu Y, Wei Z, Zheng W, Feng X, Zhou F. An OMIC biomarker detection algorithm TriVote and its application in methylomic biomarker detection. Epigenomics 2018; 10:335-347. [DOI: 10.2217/epi-2017-0097] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
Aim: Transcriptomic and methylomic patterns represent two major OMIC data sources impacted by both inheritable genetic information and environmental factors, and have been widely used as disease diagnosis and prognosis biomarkers. Materials & methods: Modern transcriptomic and methylomic profiling technologies detect the status of tens of thousands or even millions of probing residues in the human genome, and introduce a major computational challenge for the existing feature selection algorithms. This study proposes a three-step feature selection algorithm, TriVote, to detect a subset of transcriptomic or methylomic residues with highly accurate binary classification performance. Results & conclusion: TriVote outperforms both filter and wrapper feature selection algorithms with both higher classification accuracy and smaller feature number on 17 transcriptomes and two methylomes. Biological functions of the methylome biomarkers detected by TriVote were discussed for their disease associations. An easy-to-use Python package is also released to facilitate the further applications.
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Affiliation(s)
- Cheng Xu
- College of Software, Jilin University, Changchun, Jilin 130012, PR China
| | - Jiamei Liu
- College of Software, Jilin University, Changchun, Jilin 130012, PR China
| | - Weifeng Yang
- College of Software, Jilin University, Changchun, Jilin 130012, PR China
| | - Yayun Shu
- College of Software, Jilin University, Changchun, Jilin 130012, PR China
| | - Zhipeng Wei
- Key Laboratory of Symbolic Computation & Knowledge Engineering of Ministry of Education, College of Computer Science & Technology, Jilin University, Changchun, Jilin 130012, PR China
| | - Weiwei Zheng
- Key Laboratory of Symbolic Computation & Knowledge Engineering of Ministry of Education, College of Computer Science & Technology, Jilin University, Changchun, Jilin 130012, PR China
| | - Xin Feng
- Key Laboratory of Symbolic Computation & Knowledge Engineering of Ministry of Education, College of Computer Science & Technology, Jilin University, Changchun, Jilin 130012, PR China
| | - Fengfeng Zhou
- College of Software, Jilin University, Changchun, Jilin 130012, PR China
- Key Laboratory of Symbolic Computation & Knowledge Engineering of Ministry of Education, College of Computer Science & Technology, Jilin University, Changchun, Jilin 130012, PR China
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Titus AJ, Gallimore RM, Salas LA, Christensen BC. Cell-type deconvolution from DNA methylation: a review of recent applications. Hum Mol Genet 2018; 26:R216-R224. [PMID: 28977446 PMCID: PMC5886462 DOI: 10.1093/hmg/ddx275] [Citation(s) in RCA: 119] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2017] [Accepted: 07/11/2017] [Indexed: 02/07/2023] Open
Abstract
Recent advances in cell-type deconvolution approaches are adding to our understanding of the biology underlying disease development and progression. DNA methylation (DNAm) can be used as a biomarker of cell types, and through deconvolution approaches, to infer underlying cell type proportions. Cell-type deconvolution algorithms have two main categories: reference-based and reference-free. Reference-based algorithms are supervised methods that determine the underlying composition of cell types within a sample by leveraging differentially methylated regions (DMRs) specific to cell type, identified from DNAm measures of purified cell populations. Reference-free algorithms are unsupervised methods for use when cell-type specific DMRs are not available, allowing scientists to estimate putative cellular proportions or control for potential confounding from cell type. Reference-based deconvolution is typically applied to blood samples and has potentiated our understanding of the relation between immune profiles and disease by allowing estimation of immune cell proportions from archival DNA. Bioinformatic analyses using DNAm to infer immune cell proportions, part of a new field known as Immunomethylomics, provides a new direction for consideration in epigenome wide association studies (EWAS).
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Affiliation(s)
- Alexander J Titus
- Program in Quantitative Biomedical Sciences.,Department of Epidemiology
| | | | | | - Brock C Christensen
- Department of Epidemiology.,Department of Molecular and Systems Biology.,Department of Community and Family Medicine, Geisel School of Medicine at Dartmouth College, Hanover, NH 03755, USA
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Affiliation(s)
- Jordi Heijman
- From the Department of Cardiology, Cardiovascular Research Institute Maastricht, Faculty of Health, Medicine, and Life Sciences, Maastricht University, The Netherlands (J.H.); Department of Medicine, Montreal Heart Institute and Université de Montréal, Canada (J.-B.G., S.N.); University Hospital of Saint-Étienne, University Jean Monnet, Saint-Étienne, France (J.-B.G.); Institute of Pharmacology, West German Heart and Vascular Center, Faculty of Medicine, University Duisburg-Essen (D.D., S.N.); and
| | - Jean-Baptiste Guichard
- From the Department of Cardiology, Cardiovascular Research Institute Maastricht, Faculty of Health, Medicine, and Life Sciences, Maastricht University, The Netherlands (J.H.); Department of Medicine, Montreal Heart Institute and Université de Montréal, Canada (J.-B.G., S.N.); University Hospital of Saint-Étienne, University Jean Monnet, Saint-Étienne, France (J.-B.G.); Institute of Pharmacology, West German Heart and Vascular Center, Faculty of Medicine, University Duisburg-Essen (D.D., S.N.); and
| | - Dobromir Dobrev
- From the Department of Cardiology, Cardiovascular Research Institute Maastricht, Faculty of Health, Medicine, and Life Sciences, Maastricht University, The Netherlands (J.H.); Department of Medicine, Montreal Heart Institute and Université de Montréal, Canada (J.-B.G., S.N.); University Hospital of Saint-Étienne, University Jean Monnet, Saint-Étienne, France (J.-B.G.); Institute of Pharmacology, West German Heart and Vascular Center, Faculty of Medicine, University Duisburg-Essen (D.D., S.N.); and
| | - Stanley Nattel
- From the Department of Cardiology, Cardiovascular Research Institute Maastricht, Faculty of Health, Medicine, and Life Sciences, Maastricht University, The Netherlands (J.H.); Department of Medicine, Montreal Heart Institute and Université de Montréal, Canada (J.-B.G., S.N.); University Hospital of Saint-Étienne, University Jean Monnet, Saint-Étienne, France (J.-B.G.); Institute of Pharmacology, West German Heart and Vascular Center, Faculty of Medicine, University Duisburg-Essen (D.D., S.N.); and
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35
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Lin H, Lunetta KL, Zhao Q, Rong J, Benjamin EJ, Mendelson MM, Joehanes R, Levy D, Larson MG, Murabito JM. Transcriptome-wide association study of inflammatory biologic age. Aging (Albany NY) 2017; 9:2288-2301. [PMID: 29135455 PMCID: PMC5723687 DOI: 10.18632/aging.101321] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2017] [Accepted: 11/02/2017] [Indexed: 05/16/2023]
Abstract
Chronic low grade inflammation is a fundamental mechanism of aging. We estimated biologic age using nine biomarkers from diverse inflammatory pathways and we hypothesized that genes associated with inflammatory biological age would provide insights into human aging. In Framingham Offspring Study participants at examination 8 (2005 to 2008), we used the Klemera-Doubal method to estimate inflammatory biologic age and we computed the difference (∆Age) between biologic age and chronologic age. Gene expression in whole blood was measured using the Affymetrix Human Exon 1.0 ST Array. We used linear mixed effect models to test associations between inflammatory ∆Age and gene expression (dependent variable) adjusting for age, sex, imputed cell counts, and technical covariates. Our study sample included 2386 participants (mean age 67A±9 years, 55% women). There were 448 genes significantly were associated with inflammatory ∆Age (P<2.8x10-6), 302 genes were positively associated and 146 genes were negatively associated. Pathway analysis among the identified genes highlighted the NOD-like receptor signaling and ubiquitin mediated proteolysis pathways. In summary, we identified 448 genes that were significantly associated with inflammatory biologic age. Future functional characterization may identify molecular interventions to delay aging and prolong healthspan in older adults.
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Affiliation(s)
- Honghuang Lin
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA 01702, USA
- Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA
| | - Kathryn L. Lunetta
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA 01702, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Qiang Zhao
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Jian Rong
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA 01702, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
| | - Emelia J. Benjamin
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA 01702, USA
- Section of Cardiovascular Medicine and Preventive Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA
| | - Michael M. Mendelson
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA 01702, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
- Department of Cardiology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Roby Joehanes
- Hebrew SeniorLife, Harvard Medical School, Boston, MA 02115, USA
| | - Daniel Levy
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA 01702, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Martin G. Larson
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA 01702, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Joanne M. Murabito
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA 01702, USA
- Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA
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36
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RIFS: a randomly restarted incremental feature selection algorithm. Sci Rep 2017; 7:13013. [PMID: 29026108 PMCID: PMC5638869 DOI: 10.1038/s41598-017-13259-6] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2017] [Accepted: 09/21/2017] [Indexed: 11/24/2022] Open
Abstract
The advent of big data era has imposed both running time and learning efficiency challenges for the machine learning researchers. Biomedical OMIC research is one of these big data areas and has changed the biomedical research drastically. But the high cost of data production and difficulty in participant recruitment introduce the paradigm of “large p small n” into the biomedical research. Feature selection is usually employed to reduce the high number of biomedical features, so that a stable data-independent classification or regression model may be achieved. This study randomly changes the first element of the widely-used incremental feature selection (IFS) strategy and selects the best feature subset that may be ranked low by the statistical association evaluation algorithms, e.g. t-test. The hypothesis is that two low-ranked features may be orchestrated to achieve a good classification performance. The proposed Randomly re-started Incremental Feature Selection (RIFS) algorithm demonstrates both higher classification accuracy and smaller feature number than the existing algorithms. RIFS also outperforms the existing methylomic diagnosis model for the prostate malignancy with a larger accuracy and a lower number of transcriptomic features.
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37
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van der Harst P, de Windt LJ, Chambers JC. Translational Perspective on Epigenetics in Cardiovascular Disease. J Am Coll Cardiol 2017; 70:590-606. [PMID: 28750703 PMCID: PMC5543329 DOI: 10.1016/j.jacc.2017.05.067] [Citation(s) in RCA: 61] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Revised: 05/30/2017] [Accepted: 05/31/2017] [Indexed: 12/19/2022]
Abstract
A plethora of environmental and behavioral factors interact, resulting in changes in gene expression and providing a basis for the development and progression of cardiovascular diseases. Heterogeneity in gene expression responses among cells and individuals involves epigenetic mechanisms. Advancing technology allowing genome-scale interrogation of epigenetic marks provides a rapidly expanding view of the complexity and diversity of the epigenome. In this review, the authors discuss the expanding landscape of epigenetic modifications and highlight their importance for future understanding of disease. The epigenome provides a mechanistic link between environmental exposures and gene expression profiles ultimately leading to disease. The authors discuss the current evidence for transgenerational epigenetic inheritance and summarize the data linking epigenetics to cardiovascular disease. Furthermore, the potential targets provided by the epigenome for the development of future diagnostics, preventive strategies, and therapy for cardiovascular disease are reviewed. Finally, the authors provide some suggestions for future directions.
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Affiliation(s)
- Pim van der Harst
- Departments of Cardiology and Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Durrer Center for Cardiovascular Research, Netherlands Heart Institute, Utrecht, the Netherlands.
| | - Leon J de Windt
- Department of Cardiology, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands
| | - John C Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom; Ealing Hospital NHS Trust, Middlesex, United Kingdom
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38
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Monte E, Fischer MA, Vondriska TM. Epigenomic Disruption of Cardiovascular Care: What It Will Take. Circ Res 2017; 120:1692-1693. [PMID: 28546346 DOI: 10.1161/circresaha.117.311072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Emma Monte
- From the Department of Genetics, Stanford University, CA (E.M.); and Department of Anesthesiology and Perioperative Medicine (M.A.F., T.M.V.), Department of Medicine/Cardiology (T.M.V.), and Department of Physiology (T.M.V.), David Geffen School of Medicine, University of California, Los Angeles
| | - Matthew A Fischer
- From the Department of Genetics, Stanford University, CA (E.M.); and Department of Anesthesiology and Perioperative Medicine (M.A.F., T.M.V.), Department of Medicine/Cardiology (T.M.V.), and Department of Physiology (T.M.V.), David Geffen School of Medicine, University of California, Los Angeles
| | - Thomas M Vondriska
- From the Department of Genetics, Stanford University, CA (E.M.); and Department of Anesthesiology and Perioperative Medicine (M.A.F., T.M.V.), Department of Medicine/Cardiology (T.M.V.), and Department of Physiology (T.M.V.), David Geffen School of Medicine, University of California, Los Angeles.
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Abstract
PURPOSE OF REVIEW Atrial fibrillation is an important cause of morbidity in the aging population. The mechanisms responsible for the triggering and maintenance of the chaotic atrial rhythm are still poorly understood. In this review, we will focus on the genetic aspects of atrial fibrillation, to understand causality, with special emphasis on recent studies published in the field. RECENT FINDINGS Diseases such as hypertension, valvular heart disease, and heart failure may induce atrial fibrillation, which increases the risk of stroke and sudden cardiac death. Clinical studies published in these last two decades have provided evidence that genetics play a key role in atrial fibrillation. Thus, a family history of the disease has been identified in up to 30% of clinically diagnosed patients. In those genotyped families, most carry rare genetic variants in genes associated with ionic channels, calcium handling protein, or predisposing to fibrosis, conduction system disease, and inflammatory processes. SUMMARY Currently, atrial fibrillation is the most common sustained arrhythmia in clinical practice. The pathophysiological mechanisms of atrial fibrillation are complex. A better understanding of the molecular basis will help improve both current risk stratification and clinical management.
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