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Plaza-Florido A, Olvera-Rojas M, Alcantara JMA, Radom-Aizik S, Ortega FB. Targeted proteomics involved in cardiovascular health and heart rate variability in children with overweight/obesity. Am J Hum Biol 2024:e24113. [PMID: 38864311 DOI: 10.1002/ajhb.24113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 05/24/2024] [Accepted: 05/27/2024] [Indexed: 06/13/2024] Open
Abstract
BACKGROUND Children with overweight/obesity often exhibit alterations in their plasma protein profiles and reduced heart rate variability (HRV). Plasma proteomics is at the forefront of identifying biomarkers for various clinical conditions. We aimed to examine the association between plasma-targeted proteomics involved in cardiovascular health and resting vagal-related HRV parameters in children with overweight/obesity. METHODS Forty-four children with overweight/obesity (10.2 ± 1.1 years old; 52% boys) participated in the study. Olink's technology was used to quantify 92 proteins involved in cardiovascular health. HRV was measured using a heart rate monitor (Polar RS800CX). Four resting vagal-related HRV parameters were derived in time- and frequency-domain. RESULTS Eight proteins (KIM1, IgG Fc receptor II-b, IDUA, BOC, IL1RL2, TNFRSF11A, VSIG2, and TF) were associated with at least one out of the four vagal-related HRV parameters (β values ranging from -0.188 to 0.288; all p < .05), while KIM1, IDUA, and BOC associated with ≥ three vagal-related HRV parameters. Multiple hypothesis testing corrections did not reach statistical significance (false discovery rate [FDR >0.05]). CONCLUSION Plasma-targeted proteomics suggested novel biomarkers for resting vagal-related HRV parameters in children with overweight/obesity. Future studies using larger cohorts and longitudinal designs should confirm our findings and their potential clinical implications.
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Affiliation(s)
- Abel Plaza-Florido
- Department of Physical Education and Sports, Faculty of Sport Sciences, Sport and Health University Research Institute (iMUDS), University of Granada, Granada, Spain
- Pediatric Exercise and Genomics Research Center, Department of Pediatrics, School of Medicine, University of California at Irvine, Irvine, California, USA
| | - Marcos Olvera-Rojas
- Department of Physical Education and Sports, Faculty of Sport Sciences, Sport and Health University Research Institute (iMUDS), University of Granada, Granada, Spain
| | - Juan M A Alcantara
- Institute for Innovation & Sustainable Food Chain Development, Department of Health Sciences, Public University of Navarre, Pamplona, Spain
- Navarra Institute for Health Research, IdiSNA, Pamplona, Spain
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Shlomit Radom-Aizik
- Pediatric Exercise and Genomics Research Center, Department of Pediatrics, School of Medicine, University of California at Irvine, Irvine, California, USA
| | - Francisco B Ortega
- Department of Physical Education and Sports, Faculty of Sport Sciences, Sport and Health University Research Institute (iMUDS), University of Granada, Granada, Spain
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
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Yao Y, Li Y, Jin Q, Li X, Zhang X, Lv Q. Perioperative Treatment with Rivaroxaban and Dabigatran on Changes of Coagulation and Platelet Activation Biomarkers following Left Atrial Appendage Closure. Cardiovasc Ther 2024; 2024:4405152. [PMID: 38505191 PMCID: PMC10950400 DOI: 10.1155/2024/4405152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 11/12/2023] [Accepted: 01/13/2024] [Indexed: 03/21/2024] Open
Abstract
Insufficient data exist regarding the investigation of the impact of novel oral anticoagulants (NOACs) on coagulation activation biomarkers in the context of left atrial appendage closure (LAAC) and device-related thrombosis (DRT). The study was designed to investigate the changes and presence of coagulation activation biomarkers between different antithrombotic strategies following LAAC. A total of 120 nonvalvular atrial fibrillation patients intolerant of long-term anticoagulants, who underwent successful WATCHMAN closure implantation, were enrolled (rivaroxaban, n = 82; dabigatran, n = 38). Blood samples were obtained from left atrium (LA) and left atrial appendage (LAA) during the operation and fasting blood samples on the same day of LAAC and 45 days after discharge. The biochemical indicators, thrombin-antithrombin complex (TAT), soluble P-selectin (sP-selectin), von Willebrand factor (vWF), and CD40 ligand (CD40L), were measured by enzyme-linked immunosorbent assay. The primary endpoints of this study were the efficacy and safety characteristics of different antithrombotic strategies, including DRT incidence, stroke or transient ischemic attack, systemic embolism, and clinical major and nonmajor bleeding complications during the follow-up of 180 days. The results revealed that TAT, vWF, sP-selectin, and CD40L levels in vein were significantly reduced by 2.4% (p = 0.043), 5.0% (p < 0.001), 8.7% (p < 0.001), and 2.5% (p = 0.043) from their baseline levels after rivaroxaban treatment. Conversely, no significant changes were detected in the dabigatran group. Furthermore, the plasma levels of platelet activation biomarkers (CD40L and sP-selectin) in both LA and LAA groups were significantly lower after anticoagulation with rivaroxaban, as compared to dabigatran treatment (CD40L: 554.62 ± 155.54 vs. 445.02 ± 130.04 for LA p = 0.0013, 578.51 ± 156.28 vs. 480.13 ± 164.37 for LAA p = 0.0052; sP-selectin: 2849.07 ± 846.69 vs. 2225.54 ± 799.96 for LA p = 0.0105, 2915.52 ± 1402.40 vs. 2203.41 ± 1061.67 for LAA p = 0.0022). Notably, the present study suggests that rivaroxaban may be more effective in the prevention of DRT for patients undergoing LAAC.
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Affiliation(s)
- Yao Yao
- Department of Pharmacy, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Yanli Li
- Department of Pharmacy, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Qinchun Jin
- Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Xiaoye Li
- Department of Pharmacy, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Xiaochun Zhang
- Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Qianzhou Lv
- Department of Pharmacy, Zhongshan Hospital, Fudan University, Shanghai 200032, China
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Yuan S, Xu F, Zhang H, Chen J, Ruan X, Li Y, Burgess S, Åkesson A, Li X, Gill D, Larsson SC. Proteomic insights into modifiable risk of venous thromboembolism and cardiovascular comorbidities. J Thromb Haemost 2024; 22:738-748. [PMID: 38029854 PMCID: PMC7615672 DOI: 10.1016/j.jtha.2023.11.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 10/30/2023] [Accepted: 11/03/2023] [Indexed: 12/01/2023]
Abstract
BACKGROUND Venous thromboembolism (VTE) has been associated with several modifiable factors (MFs) and cardiovascular comorbidities. However, the mechanisms are largely unknown. OBJECTIVES We aimed to decipher proteomic pathways underlying the associations of VTE with MFs and cardiovascular comorbidities. METHODS A 2-stage network Mendelian randomization analysis was conducted to explore the associations between 15 MFs, 1151 blood proteins, and VTE using data from a genome-wide meta-analysis including 81 190 cases of VTE. We used protein data from 35 559 individuals as the discovery analysis, and from 2 independent studies including 10 708 and 54 219 participants as the replication analyses. Based on the identified proteins, we assessed the druggability and examined the cardiovascular pleiotropy. RESULTS The network Mendelian randomization analyses identified 10 MF-VTE, 86 MF-protein, and 34 protein-VTE associations. These associations were overall consistent in the replication analyses. Thirty-eight pathways with directionally consistent direct and indirect effects in the MF-protein-VTE pathway were identified. Low-density lipoprotein receptor-related protein 12 (LRP12: 34.3%-58.1%) and coagulation factor (F)XI (20.6%-39.6%) mediated most of the associations between 3 obesity indicators and VTE. Likewise, coagulation FXI mediated most of the smoking-VTE association (40%; 95% CI, 20%-60%) and insomnia-VTE association (27%; 95% CI, 5%-49%). Many VTE-associated proteins were highly druggable for thrombotic conditions. Five proteins (interleukin-6 receptor subunit alpha, LRP12, prothrombin, angiopoietin-1, and low-density lipoprotein receptor-related protein 4) were associated with VTE and its cardiovascular comorbidities. CONCLUSION This study suggests that coagulation FXI, a druggable target, is an important mediator of the associations of obesity, smoking, and insomnia with VTE risk.
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Affiliation(s)
- Shuai Yuan
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden
| | - Fengzhe Xu
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
| | - Han Zhang
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jie Chen
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xixian Ruan
- Department of Gastroenterology, the Third Xiangya Hospital, Central South University, Changsha, China
| | - Yuying Li
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Stephen Burgess
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Agneta Åkesson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden
| | - Xue Li
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Susanna C. Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
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Li H, Zhang Z, Qiu Y, Weng H, Yuan S, Zhang Y, Zhang Y, Xi L, Xu F, Ji X, Hao R, Yang P, Chen G, Zuo X, Zhai Z, Wang C. Proteome-wide mendelian randomization identifies causal plasma proteins in venous thromboembolism development. J Hum Genet 2023; 68:805-812. [PMID: 37537391 PMCID: PMC10678328 DOI: 10.1038/s10038-023-01186-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 06/19/2023] [Accepted: 07/23/2023] [Indexed: 08/05/2023]
Abstract
Genome-wide association studies (GWAS) have identified numerous risk loci for venous thromboembolism (VTE), but it is challenging to decipher the underlying mechanisms. We employed an integrative analytical pipeline to transform genetic associations to identify novel plasma proteins for VTE. Proteome-wide association studies (PWAS) were determined by functional summary-based imputation leveraging data from a genome-wide association analysis (14,429 VTE patients, 267,037 controls), blood proteomes (1348 cases), followed by Mendelian randomization, Bayesian colocalization, protein-protein interaction, and pathway enrichment analysis. Twenty genetically regulated circulating protein abundances (F2, F11, ABO, PLCG2, LRP4, PLEK, KLKB1, PROC, KNG1, THBS2, SERPINA1, RARRES2, CEL, GP6, SERPINE2, SERPINA10, OBP2B, EFEMP1, F5, and MSR1) were associated with VTE. Of these 13 proteins demonstrated Mendelian randomized correlations. Six proteins (F2, F11, PLEK, SERPINA1, RARRES2, and SERPINE2) had strong support in colocalization analysis. Utilizing multidimensional data, this study suggests PLEK, SERPINA1, and SERPINE2 as compelling proteins that may provide key hints for future research and possible diagnostic and therapeutic targets for VTE.
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Affiliation(s)
- Haobo Li
- National Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
- China-Japan Friendship Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Zhu Zhang
- National Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China.
| | - Yuting Qiu
- Capital Medical University, Beijing, China
| | - Haoyi Weng
- WeGene, Shenzhen, China; Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, China
| | - Shuai Yuan
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Yunxia Zhang
- National Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Yu Zhang
- National Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
- Capital Medical University, Beijing, China
| | - Linfeng Xi
- National Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
- Capital Medical University, Beijing, China
| | - Feiya Xu
- National Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
- Capital Medical University, Beijing, China
| | - Xiaofan Ji
- National Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
- China-Japan Friendship Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Risheng Hao
- National Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
- Capital Medical University, Beijing, China
| | - Peiran Yang
- State Key Laboratory of Respiratory Health and Multimorbidity, Department of Physiology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College; National Center for Respiratory Medicine; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; National Clinical Research Center for Respiratory Diseases, Beijing, China
| | - Gang Chen
- WeGene, Shenzhen, China; Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, China
| | - Xianbo Zuo
- Department of Pharmacy, China-Japan Friendship Hospital, Beijing, China
| | - Zhenguo Zhai
- National Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China.
| | - Chen Wang
- National Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China.
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Sun B, Cheng X, Zhang M, Shi Q, Zhao X, Wang X, Zhang Y. Dynamic observation of circRNA and mRNA profiles in a rat model of deep vein thrombosis. Exp Ther Med 2023; 26:467. [PMID: 37664678 PMCID: PMC10469585 DOI: 10.3892/etm.2023.12166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 07/20/2023] [Indexed: 09/05/2023] Open
Abstract
The goal of the present study was to identify different transcriptome expression profiles involved in the pathogenesis of deep vein thrombosis (DVT), and to illustrate the diagnostic and therapeutic potential of circular RNAs (circRNAs) and mRNAs in DVT progression. A Sprague-Dawley rat model of DVT was successfully established through the stenosis method and samples were sequenced at four time points (1, 6 and 12 h, and 3 days after ligation) to observe the dynamic changes in circRNAs and mRNAs during DVT progression. RNA sequencing was used to analyze the circRNA and mRNA expression profiles, and associated functions and pathways, in the blood of DVT rats at the four time points. In addition, Short Time Series Expression Miner (STEM) analysis was performed to explore temporal gene expression. Differential expression of 1,680, 4,018, 3,724, and 3,036 circRNAs, and 400, 1,176, 373, and 573 mRNAs was observed in the 1, 6 and 12 h, and 3-day groups, respectively, compared with the sham group (fold change >2.0 or <-2.0, P<0.05). Functional enrichment analysis indicated that differentially expressed mRNAs were associated with the following terms: Immune response, cell activation, blood stasis facilitated organelle, extracellular membrane-bounded organelle, and blood microparticle, oxygen transporter activity. STEM analysis indicated that the expression of 366 circRNAs in circRNA profile 45 and 270 mRNAs in mRNA profile 45 was consistent with thrombus progression. Enrichment analysis was performed on mRNA profile 45. The main Gene Ontology annotations were chromosome segregation, mitotic sister chromatid segregation, cell cycle process, and ligand-dependent nuclear receptor transcription coactivator activity. Pathway enrichment analysis identified the platelet-associated pathway, immune-associated pathway, and inflammation-relation pathway. According to the enriched platelet-associated pathways, four mRNAs and ten candidate circRNAs were selected for reverse transcription-quantitative PCR verification. The expression of nine of the ten circRNAs and all four mRNAs was consistent with the sequencing results. In summary, differentially expressed circRNAs and mRNAs are dynamically involved in DVT development. Dysregulated transcriptome profiles and the corresponding functions and pathways may provide mechanistic insights into DVT diagnosis and treatment.
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Affiliation(s)
- Baolan Sun
- Department of Laboratory, Affiliated Hospital of Nantong University, Nantong, Jiangsu 226001, P.R. China
| | - Xi Cheng
- Department of Gynecology and Obstetrics, Affiliated Hospital of Nantong University, Nantong, Jiangsu 226001, P.R. China
| | - Mu Zhang
- Department of Ophthalmology, Affiliated Hospital of Nantong University, Nantong, Jiangsu 226001, P.R. China
| | - Qin Shi
- Department of Gynecology and Obstetrics, Affiliated Hospital of Nantong University, Nantong, Jiangsu 226001, P.R. China
| | - Xinxin Zhao
- Department of Gynecology and Obstetrics, Affiliated Hospital of Nantong University, Nantong, Jiangsu 226001, P.R. China
| | - Xudong Wang
- Department of Laboratory, Affiliated Hospital of Nantong University, Nantong, Jiangsu 226001, P.R. China
| | - Yuquan Zhang
- Department of Gynecology and Obstetrics, Affiliated Hospital of Nantong University, Nantong, Jiangsu 226001, P.R. China
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Yuan S, Li Y, Wang L, Xu F, Chen J, Levin MG, Xiong Y, Voight BF, Damrauer SM, Gill D, Burgess S, Åkesson A, Michaëlsson K, Li X, Shen X, Larsson SC. Deciphering the genetic architecture of atrial fibrillation offers insights into disease prediction, pathophysiology and downstream sequelae. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.20.23292938. [PMID: 37546828 PMCID: PMC10402218 DOI: 10.1101/2023.07.20.23292938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Aims The study aimed to discover novel genetic loci for atrial fibrillation (AF), explore the shared genetic etiologies between AF and other cardiovascular and cardiometabolic traits, and uncover AF pathogenesis using Mendelian randomization analysis. Methods and results We conducted a genome-wide association study meta-analysis including 109,787 AF cases and 1,165,920 controls of European ancestry and identified 215 loci, among which 91 were novel. We performed Genomic Structural Equation Modeling analysis between AF and four cardiovascular comorbidities (coronary artery disease, ischemic stroke, heart failure, and vneous thromboembolism) and found 189 loci shared across these diseases as well as a universal genetic locus shared by atherosclerotic outcomes (i.e., rs1537373 near CDKN2B). Three genetic loci (rs10740129 near JMJD1C, rs2370982 near NRXN3, and rs9931494 near FTO) were associated with AF and cardiometabolic traits. A polygenic risk score derived from this genome-wide meta-analysis was associated with AF risk (odds ratio 2.36, 95% confidence interval 2.31-2.41 per standard deviation increase) in the UK biobank. This score, combined with age, sex, and basic clinical features, predicted AF risk (AUC 0.784, 95% CI 0.781-0.787) in Europeans. Phenome-wide association analysis of the polygenic risk score identified many AF-related comorbidities of the circulatory, endocrine, and respiratory systems. Phenome-wide and multi-omic Mendelian randomization analyses identified associations of blood lipids and pressure, diabetes, insomnia, obesity, short sleep, and smoking, 27 blood proteins, one gut microbe (genus.Catenibacterium), and 11 blood metabolites with risk to AF. Conclusions This genome-wide association study and trans-omic Mendelian randomization analysis provides insights into disease risk prediction, pathophysiology and downstream sequelae.
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Affiliation(s)
- Shuai Yuan
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Yuying Li
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Lijuan Wang
- School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Fengzhe Xu
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
| | - Jie Chen
- School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Michael G Levin
- Division of Cardiovascular Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Ying Xiong
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Benjamin F. Voight
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Scott M Damrauer
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Agneta Åkesson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Karl Michaëlsson
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Xue Li
- School of Public Health and The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xia Shen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Susanna C. Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
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