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Chen CY, Chen TT, Feng YCA, Yu M, Lin SC, Longchamps RJ, Wang SH, Hsu YH, Yang HI, Kuo PH, Daly MJ, Chen WJ, Huang H, Ge T, Lin YF. Analysis across Taiwan Biobank, Biobank Japan, and UK Biobank identifies hundreds of novel loci for 36 quantitative traits. Cell Genom 2023; 3:100436. [PMID: 38116116 PMCID: PMC10726425 DOI: 10.1016/j.xgen.2023.100436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 11/21/2021] [Accepted: 10/09/2023] [Indexed: 12/21/2023]
Abstract
Genome-wide association studies (GWASs) have identified tens of thousands of genetic loci associated with human complex traits. However, the majority of GWASs were conducted in individuals of European ancestries. Failure to capture global genetic diversity has limited genomic discovery and has impeded equitable delivery of genomic knowledge to diverse populations. Here we report findings from 102,900 individuals across 36 human quantitative traits in the Taiwan Biobank (TWB), a major biobank effort that broadens the population diversity of genetic studies in East Asia. We identified 968 novel genetic loci, pinpointed novel causal variants through statistical fine-mapping, compared the genetic architecture across TWB, Biobank Japan, and UK Biobank, and evaluated the utility of cross-phenotype, cross-population polygenic risk scores in disease risk prediction. These results demonstrated the potential to advance discovery through diversifying GWAS populations and provided insights into the common genetic basis of human complex traits in East Asia.
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Affiliation(s)
- Chia-Yen Chen
- Biogen, Cambridge, MA 02142, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Tzu-Ting Chen
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli 35053, Taiwan
| | - Yen-Chen Anne Feng
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Public Health & Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei 100025, Taiwan
- Institute of Health Data Analytics and Statistics, College of Public Health, National Taiwan University, Taipei 100025, Taiwan
| | - Mingrui Yu
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Shu-Chin Lin
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli 35053, Taiwan
| | - Ryan J. Longchamps
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Shi-Heng Wang
- National Center for Geriatrics and Welfare Research, National Health Research Institutes, Miaoli 35053, Taiwan
- Department of Public Health, College of Public Health, China Medical University, Taichung 40678, Taiwan
| | - Yi-Hsiang Hsu
- Marcus Institute for Aging Research and Harvard Medical School, Boston, MA 02131, USA
- Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
- Harvard School of Public Health, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Hwai-I. Yang
- Genomics Research Center, Academia Sinica, Taipei 115201, Taiwan
- Institute of Clinical Medicine, National Yang-Ming University, Taipei 112304, Taiwan
- Doctoral Program of Clinical and Experimental Medicine, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan
- Biomedical Translation Research Center, Academia Sinica, Taipei 115021, Taiwan
| | - Po-Hsiu Kuo
- Department of Public Health & Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei 100025, Taiwan
- Department of Psychiatry, College of Medicine and National Taiwan University Hospital, Taipei 106319, Taiwan
| | - Mark J. Daly
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, 00014 Helsinki, Finland
| | - Wei J. Chen
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli 35053, Taiwan
- Department of Public Health & Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei 100025, Taiwan
- Department of Psychiatry, College of Medicine and National Taiwan University Hospital, Taipei 106319, Taiwan
| | - Hailiang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02114, USA
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Yen-Feng Lin
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli 35053, Taiwan
- Department of Public Health & Medical Humanities, School of Medicine, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
- Institute of Behavioral Medicine, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan
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2
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Yuan K, Longchamps RJ, Pardiñas AF, Yu M, Chen TT, Lin SC, Chen Y, Lam M, Liu R, Xia Y, Guo Z, Shi W, Shen C, Daly MJ, Neale BM, Feng YCA, Lin YF, Chen CY, O'Donovan M, Ge T, Huang H. Fine-mapping across diverse ancestries drives the discovery of putative causal variants underlying human complex traits and diseases. medRxiv 2023:2023.01.07.23284293. [PMID: 36711496 PMCID: PMC9882563 DOI: 10.1101/2023.01.07.23284293] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Genome-wide association studies (GWAS) of human complex traits or diseases often implicate genetic loci that span hundreds or thousands of genetic variants, many of which have similar statistical significance. While statistical fine-mapping in individuals of European ancestries has made important discoveries, cross-population fine-mapping has the potential to improve power and resolution by capitalizing on the genomic diversity across ancestries. Here we present SuSiEx, an accurate and computationally efficient method for cross-population fine-mapping, which builds on the single-population fine-mapping framework, Sum of Single Effects (SuSiE). SuSiEx integrates data from an arbitrary number of ancestries, explicitly models population-specific allele frequencies and LD patterns, accounts for multiple causal variants in a genomic region, and can be applied to GWAS summary statistics. We comprehensively evaluated SuSiEx using simulations, a range of quantitative traits measured in both UK Biobank and Taiwan Biobank, and schizophrenia GWAS across East Asian and European ancestries. In all evaluations, SuSiEx fine-mapped more association signals, produced smaller credible sets and higher posterior inclusion probability (PIP) for putative causal variants, and captured population-specific causal variants.
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Affiliation(s)
- Kai Yuan
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, the Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Ryan J Longchamps
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, the Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Antonio F Pardiñas
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Cardiff, UK
| | - Mingrui Yu
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, the Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Tzu-Ting Chen
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan
| | - Shu-Chin Lin
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan
| | - Yu Chen
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Max Lam
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Human Genetics, Genome Institute of Singapore, Singapore, Singapore
- Division of Psychiatry Research, the Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
- Research Division Institute of Mental Health Singapore, Singapore, Singapore
| | - Ruize Liu
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, the Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Yan Xia
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, the Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Zhenglin Guo
- Stanley Center for Psychiatric Research, the Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Wenzhao Shi
- Digital Health China Technologies Corp. Ltd., Beijing, China
| | - Chengguo Shen
- Digital Health China Technologies Corp. Ltd., Beijing, China
| | - Mark J Daly
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, the Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Benjamin M Neale
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, the Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Yen-Chen A Feng
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Yen-Feng Lin
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan
- Department of Public Health & Medical Humanities, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Institute of Behavioral Medicine, College of Medicine, National Cheng Kung University
| | | | - Michael O'Donovan
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Cardiff, UK
| | - Tian Ge
- Stanley Center for Psychiatric Research, the Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Hailiang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, the Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
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3
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Longchamps RJ, Yang SY, Castellani CA, Shi W, Lane J, Grove ML, Bartz TM, Sarnowski C, Liu C, Burrows K, Guyatt AL, Gaunt TR, Kacprowski T, Yang J, De Jager PL, Yu L, Bergman A, Xia R, Fornage M, Feitosa MF, Wojczynski MK, Kraja AT, Province MA, Amin N, Rivadeneira F, Tiemeier H, Uitterlinden AG, Broer L, Van Meurs JBJ, Van Duijn CM, Raffield LM, Lange L, Rich SS, Lemaitre RN, Goodarzi MO, Sitlani CM, Mak ACY, Bennett DA, Rodriguez S, Murabito JM, Lunetta KL, Sotoodehnia N, Atzmon G, Ye K, Barzilai N, Brody JA, Psaty BM, Taylor KD, Rotter JI, Boerwinkle E, Pankratz N, Arking DE. Genome-wide analysis of mitochondrial DNA copy number reveals loci implicated in nucleotide metabolism, platelet activation, and megakaryocyte proliferation. Hum Genet 2022; 141:127-146. [PMID: 34859289 PMCID: PMC8758627 DOI: 10.1007/s00439-021-02394-w] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 10/22/2021] [Indexed: 12/18/2022]
Abstract
Mitochondrial DNA copy number (mtDNA-CN) measured from blood specimens is a minimally invasive marker of mitochondrial function that exhibits both inter-individual and intercellular variation. To identify genes involved in regulating mitochondrial function, we performed a genome-wide association study (GWAS) in 465,809 White individuals from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (UKB). We identified 133 SNPs with statistically significant, independent effects associated with mtDNA-CN across 100 loci. A combination of fine-mapping, variant annotation, and co-localization analyses was used to prioritize genes within each of the 133 independent sites. Putative causal genes were enriched for known mitochondrial DNA depletion syndromes (p = 3.09 × 10-15) and the gene ontology (GO) terms for mtDNA metabolism (p = 1.43 × 10-8) and mtDNA replication (p = 1.2 × 10-7). A clustering approach leveraged pleiotropy between mtDNA-CN associated SNPs and 41 mtDNA-CN associated phenotypes to identify functional domains, revealing three distinct groups, including platelet activation, megakaryocyte proliferation, and mtDNA metabolism. Finally, using mitochondrial SNPs, we establish causal relationships between mitochondrial function and a variety of blood cell-related traits, kidney function, liver function and overall (p = 0.044) and non-cancer mortality (p = 6.56 × 10-4).
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Affiliation(s)
- R J Longchamps
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - S Y Yang
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - C A Castellani
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Pathology and Laboratory Medicine, Western University, London, ON, Canada
| | - W Shi
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - J Lane
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, USA
| | - M L Grove
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, Human Genetics Center, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - T M Bartz
- Cardiovascular Health Research Unit, Departments of Medicine and Biostatistics, University of Washington, Seattle, WA, USA
| | - C Sarnowski
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - C Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - K Burrows
- MRC Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - A L Guyatt
- Department of Health Sciences, University of Leicester, University Road, Leicester, UK
| | - T R Gaunt
- MRC Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - T Kacprowski
- Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
- Data Science in Biomedicine, Peter L. Reichertz Institute for Medical Informatics, TU Braunschweig and Hannover Medical School, Brunswick, Germany
| | - J Yang
- Rush Alzheimer's Disease Center and Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - P L De Jager
- Center for Translational and Systems Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, NY, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - L Yu
- Rush Alzheimer's Disease Center and Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - A Bergman
- Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - R Xia
- Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - M Fornage
- Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genetics Center, The University of Texas Health Science Center at Houston, Houston, USA
| | - M F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, USA
| | - M K Wojczynski
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, USA
| | - A T Kraja
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, USA
| | - M A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, USA
| | - N Amin
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - F Rivadeneira
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - H Tiemeier
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Social and Behavioral Science, Harvard T.H. School of Public Health, Boston, USA
| | - A G Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - L Broer
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - J B J Van Meurs
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - C M Van Duijn
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - L M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - L Lange
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - S S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - R N Lemaitre
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - M O Goodarzi
- Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - C M Sitlani
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - A C Y Mak
- Cardiovascular Research Institute and Institute for Human Genetics, University of California, San Francisco, CA, USA
| | - D A Bennett
- Rush Alzheimer's Disease Center and Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - S Rodriguez
- MRC Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - J M Murabito
- Boston University School of Medicine, Boston University, Boston, MA, USA
| | - K L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - N Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, WA, USA
| | - G Atzmon
- Department of Natural Science, University of Haifa, Haifa, Israel
- Departments of Medicine and Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - K Ye
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - N Barzilai
- Departments of Medicine and Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - J A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - B M Psaty
- Cardiovascular Health Research Unit, Departments of Epidemiology, Medicine and Health Services, University of Washington, Seattle, WA, USA
| | - K D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - J I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - E Boerwinkle
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, Human Genetics Center, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, TX, USA
| | - N Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, USA
| | - D E Arking
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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4
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Wang P, Castellani CA, Yao J, Huan T, Bielak LF, Zhao W, Haessler J, Joehanes R, Sun X, Guo X, Longchamps RJ, Manson JE, Grove ML, Bressler J, Taylor KD, Lappalainen T, Kasela S, Van Den Berg DJ, Hou L, Reiner A, Liu Y, Boerwinkle E, Smith JA, Peyser PA, Fornage M, Rich SS, Rotter JI, Kooperberg C, Arking DE, Levy D, Liu C. Epigenome-wide association study of mitochondrial genome copy number. Hum Mol Genet 2021; 31:309-319. [PMID: 34415308 PMCID: PMC8742999 DOI: 10.1093/hmg/ddab240] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 07/27/2021] [Accepted: 08/11/2021] [Indexed: 01/03/2023] Open
Abstract
We conducted cohort- and race-specific epigenome-wide association analyses of mitochondrial deoxyribonucleic acid (mtDNA) copy number (mtDNA CN) measured in whole blood from participants of African and European origins in five cohorts (n = 6182, mean age = 57-67 years, 65% women). In the meta-analysis of all the participants, we discovered 21 mtDNA CN-associated DNA methylation sites (CpG) (P < 1 × 10-7), with a 0.7-3.0 standard deviation increase (3 CpGs) or decrease (18 CpGs) in mtDNA CN corresponding to a 1% increase in DNA methylation. Several significant CpGs have been reported to be associated with at least two risk factors (e.g. chronological age or smoking) for cardiovascular disease (CVD). Five genes [PR/SET domain 16, nuclear receptor subfamily 1 group H member 3 (NR1H3), DNA repair protein, DNA polymerase kappa and decaprenyl-diphosphate synthase subunit 2], which harbor nine significant CpGs, are known to be involved in mitochondrial biosynthesis and functions. For example, NR1H3 encodes a transcription factor that is differentially expressed during an adipose tissue transition. The methylation level of cg09548275 in NR1H3 was negatively associated with mtDNA CN (effect size = -1.71, P = 4 × 10-8) and was positively associated with the NR1H3 expression level (effect size = 0.43, P = 0.0003), which indicates that the methylation level in NR1H3 may underlie the relationship between mtDNA CN, the NR1H3 transcription factor and energy expenditure. In summary, the study results suggest that mtDNA CN variation in whole blood is associated with DNA methylation levels in genes that are involved in a wide range of mitochondrial activities. These findings will help reveal molecular mechanisms between mtDNA CN and CVD.
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Affiliation(s)
- Penglong Wang
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Christina A Castellani
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
- Department of Pathology and Laboratory Medicine, Western University, London, Ontario N6A 5C1, Canada
| | - Jie Yao
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Tianxiao Huan
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jeffrey Haessler
- Division of Public Health Science, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Roby Joehanes
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Xianbang Sun
- Department of Biostatistics, Boston University, Boston, MA 02118, USA
| | - Xiuqing Guo
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Ryan J Longchamps
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - JoAnn E Manson
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Megan L Grove
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Jan Bressler
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Kent D Taylor
- Department of Pathology and Laboratory Medicine, Western University, London, Ontario N6A 5C1, Canada
| | - Tuuli Lappalainen
- New York Genome Center, New York, NY 10013, USA
- Department of Systems Biology, Columbia University, New York, NY 10034, USA
| | - Silva Kasela
- New York Genome Center, New York, NY 10013, USA
- Department of Systems Biology, Columbia University, New York, NY 10034, USA
| | - David J Van Den Berg
- Department of Population and Public Health Sciences, Center for Genetic Epidemiology, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90033, USA
| | - Lifang Hou
- Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Alexander Reiner
- Division of Public Health Science, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Yongmei Liu
- Department of Medicine, Divisions of Cardiology and Neurology, Duke University Medical Center, Durham, NC 27704, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22903, USA
| | - Jerome I Rotter
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Charles Kooperberg
- Division of Public Health Science, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Dan E Arking
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
- Framingham Heart Study, National Heart, Lung, and Blood Institute (NHLBI), Framingham, MA 01702, USA
| | - Chunyu Liu
- Department of Biostatistics, Boston University, Boston, MA 02118, USA
- Framingham Heart Study, National Heart, Lung, and Blood Institute (NHLBI), Framingham, MA 01702, USA
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5
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Yang SY, Castellani CA, Longchamps RJ, Pillalamarri VK, O'Rourke B, Guallar E, Arking DE. Blood-derived mitochondrial DNA copy number is associated with gene expression across multiple tissues and is predictive for incident neurodegenerative disease. Genome Res 2021; 31:349-358. [PMID: 33441415 PMCID: PMC7919448 DOI: 10.1101/gr.269381.120] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 01/06/2021] [Indexed: 12/12/2022]
Abstract
Mitochondrial DNA copy number (mtDNA-CN) is a proxy for mitochondrial function and is associated with aging-related diseases. However, it is unclear how mtDNA-CN measured in blood can reflect diseases that primarily manifest in other tissues. Using the Genotype-Tissue Expression Project, we interrogated relationships between mtDNA-CN measured in whole blood and gene expression from whole blood and 47 additional tissues in 419 individuals. mtDNA-CN was significantly associated with expression of 700 genes in whole blood, including nuclear genes required for mtDNA replication. Significant enrichment was observed for splicing and ubiquitin-mediated proteolysis pathways, as well as target genes for the mitochondrial transcription factor NRF1. In nonblood tissues, there were more significantly associated genes than expected in 30 tissues, suggesting that global gene expression in those tissues is correlated with blood-derived mtDNA-CN. Neurodegenerative disease pathways were significantly associated in multiple tissues, and in an independent data set, the UK Biobank, we observed that higher mtDNA-CN was significantly associated with lower rates of both prevalent (OR = 0.89, CI = 0.83; 0.96) and incident neurodegenerative disease (HR = 0.95, 95% CI = 0.91;0.98). The observation that mtDNA-CN measured in blood is associated with gene expression in other tissues suggests that blood-derived mtDNA-CN can reflect metabolic health across multiple tissues. Identification of key pathways including splicing, RNA binding, and catalysis reinforces the importance of mitochondria in maintaining cellular homeostasis. Finally, validation of the role of mtDNA CN in neurodegenerative disease in a large independent cohort study solidifies the link between blood-derived mtDNA-CN, altered gene expression in multiple tissues, and aging-related disease.
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Affiliation(s)
- Stephanie Y Yang
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | - Christina A Castellani
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | - Ryan J Longchamps
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | - Vamsee K Pillalamarri
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | - Brian O'Rourke
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | - Eliseo Guallar
- Departments of Epidemiology and Medicine, and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland 21205, USA
| | - Dan E Arking
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.,Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
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6
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Castellani CA, Longchamps RJ, Sumpter JA, Newcomb CE, Lane JA, Grove ML, Bressler J, Brody JA, Floyd JS, Bartz TM, Taylor KD, Wang P, Tin A, Coresh J, Pankow JS, Fornage M, Guallar E, O'Rourke B, Pankratz N, Liu C, Levy D, Sotoodehnia N, Boerwinkle E, Arking DE. Mitochondrial DNA copy number can influence mortality and cardiovascular disease via methylation of nuclear DNA CpGs. Genome Med 2020; 12:84. [PMID: 32988399 PMCID: PMC7523322 DOI: 10.1186/s13073-020-00778-7] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Accepted: 09/04/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Mitochondrial DNA copy number (mtDNA-CN) has been associated with a variety of aging-related diseases, including all-cause mortality. However, the mechanism by which mtDNA-CN influences disease is not currently understood. One such mechanism may be through regulation of nuclear gene expression via the modification of nuclear DNA (nDNA) methylation. METHODS To investigate this hypothesis, we assessed the relationship between mtDNA-CN and nDNA methylation in 2507 African American (AA) and European American (EA) participants from the Atherosclerosis Risk in Communities (ARIC) study. To validate our findings, we assayed an additional 2528 participants from the Cardiovascular Health Study (CHS) (N = 533) and Framingham Heart Study (FHS) (N = 1995). We further assessed the effect of experimental modification of mtDNA-CN through knockout of TFAM, a regulator of mtDNA replication, via CRISPR-Cas9. RESULTS Thirty-four independent CpGs were associated with mtDNA-CN at genome-wide significance (P < 5 × 10- 8). Meta-analysis across all cohorts identified six mtDNA-CN-associated CpGs at genome-wide significance (P < 5 × 10- 8). Additionally, over half of these CpGs were associated with phenotypes known to be associated with mtDNA-CN, including coronary heart disease, cardiovascular disease, and mortality. Experimental modification of mtDNA-CN demonstrated that modulation of mtDNA-CN results in changes in nDNA methylation and gene expression of specific CpGs and nearby transcripts. Strikingly, the "neuroactive ligand receptor interaction" KEGG pathway was found to be highly overrepresented in the ARIC cohort (P = 5.24 × 10- 12), as well as the TFAM knockout methylation (P = 4.41 × 10- 4) and expression (P = 4.30 × 10- 4) studies. CONCLUSIONS These results demonstrate that changes in mtDNA-CN influence nDNA methylation at specific loci and result in differential expression of specific genes that may impact human health and disease via altered cell signaling.
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Affiliation(s)
- Christina A Castellani
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ryan J Longchamps
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jason A Sumpter
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Charles E Newcomb
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - John A Lane
- Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, MN, USA
| | - Megan L Grove
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jan Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - James S Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Penglong Wang
- Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Adrienne Tin
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Josef Coresh
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - James S Pankow
- Division of Epidemiology & Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Myriam Fornage
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Eliseo Guallar
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Brian O'Rourke
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, MN, USA
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Daniel Levy
- Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Dan E Arking
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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7
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Zhao D, Bartz TM, Sotoodehnia N, Post WS, Heckbert SR, Alonso A, Longchamps RJ, Castellani CA, Hong YS, Rotter JI, Lin HJ, O'Rourke B, Pankratz N, Lane JA, Yang SY, Guallar E, Arking DE. Mitochondrial DNA copy number and incident atrial fibrillation. BMC Med 2020; 18:246. [PMID: 32933497 PMCID: PMC7493408 DOI: 10.1186/s12916-020-01715-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Accepted: 07/21/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Mechanistic studies suggest that mitochondria DNA (mtDNA) dysfunction may be associated with increased risk of atrial fibrillation (AF). The association between mtDNA copy number (mtDNA-CN) and incident AF in the general population, however, remains unknown. METHODS We conducted prospective analyses of 19,709 participants from the Atherosclerosis Risk in Communities Study (ARIC), the Multi-Ethnic Study of Atherosclerosis (MESA), and the Cardiovascular Health Study (CHS). mtDNA-CN from the peripheral blood was calculated from probe intensities on the Affymetrix Genome-Wide Human single nucleotide polymorphisms (SNP) Array 6.0 in ARIC and MESA and from multiplexed real-time quantitative polymerase chain reaction (qPCR) in CHS. Incident AF cases were identified through electrocardiograms, review of hospital discharge codes, Medicare claims, and death certificates. RESULTS The median follow-up time was 21.4 years in ARIC, 12.9 years in MESA, and 11.0 years in CHS, during which 4021 participants developed incident atrial fibrillation (1761 in ARIC, 790 in MESA, and 1470 in CHS). In fully adjusted models, participants with the lowest quintile of mitochondria DNA copy number had an overall 13% increased risk (95% CI 1 to 27%) of incident atrial fibrillation compared to those with the highest quintile. Dose-response spline analysis also showed an inverse association between mitochondria DNA copy number and hazard for atrial fibrillation for all three cohorts. These associations were consistent across subgroups. CONCLUSIONS Mitochondria DNA copy number was inversely associated with the risk of AF independent of traditional cardiovascular risk factors. These findings implicate mitochondria DNA copy number as a novel risk factor for atrial fibrillation. Further research is warranted to understand the underlying mechanisms and to evaluate the role of mitochondria DNA copy number in the management of atrial fibrillation risk.
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Affiliation(s)
- Di Zhao
- Departments of Epidemiology and Medicine, and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health, 2024 E. Monument Street, Room 2-645, Baltimore, MD, 21205, USA
| | - Traci M Bartz
- Departments of Biostatistics and Medicine, University of Washington, Seattle, WA, USA
| | - Nona Sotoodehnia
- Departments of Biostatistics and Medicine, University of Washington, Seattle, WA, USA
| | - Wendy S Post
- Departments of Epidemiology and Medicine, and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health, 2024 E. Monument Street, Room 2-645, Baltimore, MD, 21205, USA.,Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Susan R Heckbert
- Department of Epidemiology, University of Washington School of Public Health, Seattle, WA, USA
| | - Alvaro Alonso
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Ryan J Longchamps
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, 733 N. Broadway, Miller Research Building, Room 459, Baltimore, MD, 21205, USA
| | - Christina A Castellani
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, 733 N. Broadway, Miller Research Building, Room 459, Baltimore, MD, 21205, USA
| | - Yun Soo Hong
- Departments of Epidemiology and Medicine, and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health, 2024 E. Monument Street, Room 2-645, Baltimore, MD, 21205, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Henry J Lin
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Brian O'Rourke
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, USA
| | - John A Lane
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, USA
| | - Stephanie Y Yang
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, 733 N. Broadway, Miller Research Building, Room 459, Baltimore, MD, 21205, USA
| | - Eliseo Guallar
- Departments of Epidemiology and Medicine, and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health, 2024 E. Monument Street, Room 2-645, Baltimore, MD, 21205, USA.
| | - Dan E Arking
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, 733 N. Broadway, Miller Research Building, Room 459, Baltimore, MD, 21205, USA.
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8
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DeBarmore B, Longchamps RJ, Zhang Y, Kalyani RR, Guallar E, Arking DE, Selvin E, Young JH. Mitochondrial DNA copy number and diabetes: the Atherosclerosis Risk in Communities (ARIC) study. BMJ Open Diabetes Res Care 2020; 8:8/1/e001204. [PMID: 32801120 PMCID: PMC7430458 DOI: 10.1136/bmjdrc-2020-001204] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Revised: 04/08/2020] [Accepted: 05/18/2020] [Indexed: 01/01/2023] Open
Abstract
INTRODUCTION Mitochondrial DNA copy number (mtDNA-CN) is a measure of mitochondrial dysfunction and is associated with diabetes in experimental models. To explore the temporality of mitochondrial dysfunction and diabetes, we estimated the prevalent and incident association of mtDNA-CN and diabetes. RESEARCH DESIGN AND METHODS We assessed the associations of mtDNA-CN measured from buffy coat with prevalent and incident diabetes, stratified by race, in 8954 white and 2444 black participants in the Atherosclerosis Risk in Communities (ARIC) study, an observational cohort study. Follow-up for incident analyses was complete through visit 6, 2016. RESULTS Mean age at mtDNA-CN measurement was 57 years and 59% were female. Prevalence of diabetes at time of mtDNA-CN measurement was higher in blacks (563/2444, 23%) than whites (855/8954, 10%). The fully adjusted odds of prevalent diabetes for the 10th vs 90th percentile of mtDNA-CN was 1.05 (95% CI 0.74 to 1.49) among black and 1.49 (95% CI 1.20 to 1.85) among white participants. Over a median follow-up time of 19 years (Q1, Q3: 11, 24 years), we observed 617 incident diabetes cases among 1744 black and 2121 cases among 7713 white participants free of diabetes at baseline. The fully adjusted hazard of incident diabetes for the 10th vs 90th percentile of mtDNA-CN was 1.07 (95% CI 0.84 to 1.38) among black and 0.97 (95% CI 0.86 to 1.10) among white participants. CONCLUSIONS Lower mtDNA-CN in buffy coat was associated with prevalent diabetes in white but not black ARIC participants. Lower mtDNA-CN was not associated with incident diabetes over 20 years of follow-up in whites or blacks.
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Affiliation(s)
- Bailey DeBarmore
- Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Ryan J Longchamps
- Genetic Medicine, Johns Hopkins University McKusick-Nathans Institute of Genetic Medicine, Baltimore, Maryland, USA
| | - Yiyi Zhang
- Epidemiology, JHSPH Welch Center for Prevention Epidemiology and Clinical Research, Baltimore, Maryland, USA
| | - Rita R Kalyani
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Eliseo Guallar
- Epidemiology, JHSPH Welch Center for Prevention Epidemiology and Clinical Research, Baltimore, Maryland, USA
| | - Dan E Arking
- Genetic Medicine, Johns Hopkins University McKusick-Nathans Institute of Genetic Medicine, Baltimore, Maryland, USA
| | - Elizabeth Selvin
- Epidemiology, JHSPH Welch Center for Prevention Epidemiology and Clinical Research, Baltimore, Maryland, USA
| | - J Hunter Young
- Epidemiology, JHSPH Welch Center for Prevention Epidemiology and Clinical Research, Baltimore, Maryland, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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9
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Castellani CA, Longchamps RJ, Sun J, Guallar E, Arking DE. Thinking outside the nucleus: Mitochondrial DNA copy number in health and disease. Mitochondrion 2020; 53:214-223. [PMID: 32544465 DOI: 10.1016/j.mito.2020.06.004] [Citation(s) in RCA: 159] [Impact Index Per Article: 39.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2020] [Revised: 05/19/2020] [Accepted: 06/08/2020] [Indexed: 02/07/2023]
Abstract
Mitochondrial DNA copy number (mtDNA-CN) is a biomarker of mitochondrial function and levels of mtDNA-CN have been reproducibly associated with overall mortality and a number of age-related diseases, including cardiovascular disease, chronic kidney disease, and cancer. Recent advancements in techniques for estimating mtDNA-CN, in particular the use of DNA microarrays and next-generation sequencing data, have led to the comprehensive assessment of mtDNA-CN across these and other diseases and traits. The importance of mtDNA-CN measures to disease and these advancing technologies suggest the potential for mtDNA-CN to be a useful biomarker in the clinic. While the exact mechanism(s) underlying the association of mtDNA-CN with disease remain to be elucidated, we review the existing literature which supports roles for inflammatory dynamics, immune function and alterations to cell signaling as consequences of variation in mtDNA-CN. We propose that future studies should focus on characterizing longitudinal, cell-type and cross-tissue profiles of mtDNA-CN as well as improving methods for measuring mtDNA-CN which will expand the potential for its use as a clinical biomarker.
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Affiliation(s)
- Christina A Castellani
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Ryan J Longchamps
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Jing Sun
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Eliseo Guallar
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States; The Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Dan E Arking
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
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10
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Hong YS, Longchamps RJ, Zhao D, Castellani CA, Loehr LR, Chang PP, Matsushita K, Grove ML, Boerwinkle E, Arking DE, Guallar E. Mitochondrial DNA Copy Number and Incident Heart Failure: The Atherosclerosis Risk in Communities (ARIC) Study. Circulation 2020; 141:1823-1825. [PMID: 32479199 PMCID: PMC7295435 DOI: 10.1161/circulationaha.120.046001] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Yun Soo Hong
- Departments of Epidemiology and Medicine, and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health. Baltimore, Maryland, USA
| | - Ryan J. Longchamps
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Di Zhao
- Departments of Epidemiology and Medicine, and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health. Baltimore, Maryland, USA
| | - Christina A. Castellani
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Laura R. Loehr
- Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Patricia P. Chang
- Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Kunihiro Matsushita
- Departments of Epidemiology and Medicine, and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health. Baltimore, Maryland, USA
| | - Megan L. Grove
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Dan E. Arking
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Eliseo Guallar
- Departments of Epidemiology and Medicine, and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health. Baltimore, Maryland, USA
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11
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Longchamps RJ, Castellani CA, Yang SY, Newcomb CE, Sumpter JA, Lane J, Grove ML, Guallar E, Pankratz N, Taylor KD, Rotter JI, Boerwinkle E, Arking DE. Evaluation of mitochondrial DNA copy number estimation techniques. PLoS One 2020; 15:e0228166. [PMID: 32004343 PMCID: PMC6994099 DOI: 10.1371/journal.pone.0228166] [Citation(s) in RCA: 76] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Accepted: 01/08/2020] [Indexed: 12/16/2022] Open
Abstract
Mitochondrial DNA copy number (mtDNA-CN), a measure of the number of mitochondrial genomes per cell, is a minimally invasive proxy measure for mitochondrial function and has been associated with several aging-related diseases. Although quantitative real-time PCR (qPCR) is the current gold standard method for measuring mtDNA-CN, mtDNA-CN can also be measured from genotyping microarray probe intensities and DNA sequencing read counts. To conduct a comprehensive examination on the performance of these methods, we use known mtDNA-CN correlates (age, sex, white blood cell count, Duffy locus genotype, incident cardiovascular disease) to evaluate mtDNA-CN calculated from qPCR, two microarray platforms, as well as whole genome (WGS) and whole exome sequence (WES) data across 1,085 participants from the Atherosclerosis Risk in Communities (ARIC) study and 3,489 participants from the Multi-Ethnic Study of Atherosclerosis (MESA). We observe mtDNA-CN derived from WGS data is significantly more associated with known correlates compared to all other methods (p < 0.001). Additionally, mtDNA-CN measured from WGS is on average more significantly associated with traits by 5.6 orders of magnitude and has effect size estimates 5.8 times more extreme than the current gold standard of qPCR. We further investigated the role of DNA extraction method on mtDNA-CN estimate reproducibility and found mtDNA-CN estimated from cell lysate is significantly less variable than traditional phenol-chloroform-isoamyl alcohol (p = 5.44x10-4) and silica-based column selection (p = 2.82x10-7). In conclusion, we recommend the field moves towards more accurate methods for mtDNA-CN, as well as re-analyze trait associations as more WGS data becomes available from larger initiatives such as TOPMed.
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Affiliation(s)
- Ryan J. Longchamps
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
| | - Christina A. Castellani
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
| | - Stephanie Y. Yang
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
| | - Charles E. Newcomb
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
| | - Jason A. Sumpter
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
| | - John Lane
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States of America
| | - Megan L. Grove
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States of America
| | - Eliseo Guallar
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States of America
| | - Kent D. Taylor
- LABioMed and Department of Pediatrics, at Harbor-UCLA Medical Center, Institute for Translational Genomics and Population Sciences, Torrance, CA, United States of America
| | - Jerome I. Rotter
- LABioMed and Department of Pediatrics, at Harbor-UCLA Medical Center, Institute for Translational Genomics and Population Sciences, Torrance, CA, United States of America
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States of America
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, United States of America
| | - Dan E. Arking
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
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12
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Sun J, Longchamps RJ, Piggott DA, Castellani CA, Sumpter JA, Brown TT, Mehta SH, Arking DE, Kirk GD. Association Between HIV Infection and Mitochondrial DNA Copy Number in Peripheral Blood: A Population-Based, Prospective Cohort Study. J Infect Dis 2020; 219:1285-1293. [PMID: 30476184 DOI: 10.1093/infdis/jiy658] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Accepted: 11/09/2018] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Low mitochondrial DNA (mtDNA) copy number (CN) is a predictor of adverse aging outcomes, and its status may be altered in human immunodeficiency virus (HIV)-infected persons. This study evaluated the cross-sectional and longitudinal change of mtDNA CN by HIV markers. METHODS mtDNA CN was measured in the ALIVE (AIDS Linked to the Intravenous Experience) cohort of persons with a history of injecting drugs. Multivariable linear regression models controlling for demographic characteristics, behavior, and hepatitis C virus (HCV) seropositivity assessed the relationship of mtDNA CN to HIV markers (CD4+ T-cell counts, viral load, antiretroviral therapy [ART] use). Linear mixed models tested the association between HIV markers and age-related mtDNA CN trajectories. RESULTS Among 741 individuals at baseline, 436 (59%) were infected with HIV. HIV-infected individuals who had lower CD4+ T-cell counts (P = .01), had higher viral loads (P < .01), and were not receiving ART (P < .01) had significantly lower mtDNA CNs than uninfected persons; there was no difference between participants who were uninfected and HIV-infected individuals who had well-controlled HIV levels. In longitudinal follow-up of 507 participants, from age 50 years onward, mtDNA CN declined significantly faster among HIV-infected individuals than among HIV-uninfected persons (-0.03 units of change/year vs 0.006 units of change/year; P = .04), even among infected individuals with well-controlled HIV. CONCLUSION Before 50 years of age, mtDNA CN is similar between HIV-infected individuals with well-controlled HIV and uninfected persons, but from age 50 onward, mtDNA CN declines significantly faster among all infected individuals than among HIV-uninfected persons.
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Affiliation(s)
- Jing Sun
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland
| | - Ryan J Longchamps
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Damani A Piggott
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland.,Division of Infectious Disease, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Christina A Castellani
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Jason A Sumpter
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Todd T Brown
- Division of Endocrinology, Diabetes, and Metabolism, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Shruti H Mehta
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland
| | - Dan E Arking
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Gregory D Kirk
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland.,Division of Infectious Disease, Johns Hopkins School of Medicine, Baltimore, Maryland
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Ashar FN, Zhang Y, Longchamps RJ, Lane J, Moes A, Grove ML, Mychaleckyj JC, Taylor KD, Coresh J, Rotter JI, Boerwinkle E, Pankratz N, Guallar E, Arking DE. Association of Mitochondrial DNA Copy Number With Cardiovascular Disease. JAMA Cardiol 2019; 2:1247-1255. [PMID: 29049454 DOI: 10.1001/jamacardio.2017.3683] [Citation(s) in RCA: 164] [Impact Index Per Article: 32.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Importance Mitochondrial dysfunction is a core component of the aging process and may play a key role in atherosclerotic cardiovascular disease. Mitochondrial DNA copy number (mtDNA-CN), which represents the number of mitochondria per cell and number of mitochondrial genomes per mitochondrion, is an indirect biomarker of mitochondrial function. Objective To determine whether mtDNA-CN, measured in an easily accessible tissue (buffy coat/circulating leukocytes), can improve risk classification for cardiovascular disease (CVD) and help guide initiation of statin therapy for primary prevention of CVD. Design, Setting, and Participants Prospective, population-based cohort analysis including 21 870 participants (20 163 free from CVD at baseline) from 3 studies: Cardiovascular Health Study (CHS), Atherosclerosis Risk in Communities Study (ARIC), and Multiethnic Study of Atherosclerosis (MESA). The mean follow-up was 13.5 years. The study included 11 153 participants from ARIC, 4830 from CHS, and 5887 from MESA. Analysis of the data was conducted from March 10, 2014, to January 29, 2017. Exposures Mitochondrial DNA-CN measured from buffy coat/circulating leukocytes. Main Outcomes and Measures Incident CVD, which combines coronary heart disease, defined as the first incident myocardial infarction or death owing to coronary heart disease, and stroke, defined as the first nonfatal stroke or death owing to stroke. Results Of the 21 870 participants, the mean age was 62.4 years (ARIC, 57.9 years; MESA, 62.4 years; and CHS, 72.5 years), and 54.7% of participants were women. The hazard ratios for incident coronary heart disease, stroke, and CVD associated with a 1-SD decrease in mtDNA-CN were 1.29 (95% CI, 1.24-1.33), 1.11 (95% CI, 1.06-1.16), and 1.23 (95% CI, 1.19-1.26). The associations persisted after adjustment for traditional CVD risk factors. Addition of mtDNA-CN to the 2013 American College of Cardiology/American Heart Association Pooled Cohorts Equations for estimating 10-year hard atherosclerosis CVD risk was associated with improved risk classification (continuous net reclassification index, 0.194; 95% CI, 0.130-0.258; P < .001). Mitochondrial DNA-CN further improved sensitivity and specificity for the 2013 American College of Cardiology/American Heart Association recommendations on initiating statin therapy for primary prevention of ASCVD (net 221 individuals appropriately downclassified and net 15 individuals appropriately upclassified). Conclusions and Relevance Mitochondrial DNA-CN was independently associated with incident CVD in 3 large prospective studies and may have potential clinical utility in improving CVD risk classification.
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Affiliation(s)
- Foram N Ashar
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Yiyi Zhang
- Departments of Epidemiology and Medicine, and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland
| | - Ryan J Longchamps
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - John Lane
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis
| | - Anna Moes
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Megan L Grove
- School of Public Health, Human Genetics Center, The University of Texas Health Science Center at Houston
| | | | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor, University of California, Los Angeles Medical Center, Torrance
| | - Josef Coresh
- Departments of Epidemiology and Medicine, and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor, University of California, Los Angeles Medical Center, Torrance.,Division of Genomic Outcomes, Departments of Pediatrics and Medicine, Harbor, University of California, Los Angeles Medical Center, Torrance
| | - Eric Boerwinkle
- School of Public Health, Human Genetics Center, The University of Texas Health Science Center at Houston
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis
| | - Eliseo Guallar
- Departments of Epidemiology and Medicine, and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland
| | - Dan E Arking
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
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14
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Zhang Y, Guallar E, Ashar FN, Longchamps RJ, Castellani CA, Lane J, Grove ML, Coresh J, Sotoodehnia N, Ilkhanoff L, Boerwinkle E, Pankratz N, Arking DE. Association between mitochondrial DNA copy number and sudden cardiac death: findings from the Atherosclerosis Risk in Communities study (ARIC). Eur Heart J 2018; 38:3443-3448. [PMID: 29020391 DOI: 10.1093/eurheartj/ehx354] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2017] [Accepted: 06/02/2017] [Indexed: 12/25/2022] Open
Abstract
Aims Sudden cardiac death (SCD) is a major public health burden. Mitochondrial dysfunction has been implicated in a wide range of cardiovascular diseases including cardiomyopathy, heart failure, and arrhythmias, but it is unknown if it also contributes to SCD risk. We sought to examine the prospective association between mtDNA copy number (mtDNA-CN), a surrogate marker of mitochondrial function, and SCD risk. Methods and results We measured baseline mtDNA-CN in 11 093 participants from the Atherosclerosis Risk in Communities (ARIC) study. mtDNA copy number was calculated from probe intensities of mitochondrial single nucleotide polymorphisms (SNP) on the Affymetrix Genome-Wide Human SNP Array 6.0. Sudden cardiac death was defined as a sudden pulseless condition presumed due to a ventricular tachyarrhythmia in a previously stable individual without evidence of a non-cardiac cause of cardiac arrest. Sudden cardiac death cases were reviewed and adjudicated by an expert committee. During a median follow-up of 20.4 years, we observed 361 SCD cases. After adjusting for age, race, sex, and centre, the hazard ratio for SCD comparing the 1st to the 5th quintiles of mtDNA-CN was 2.24 (95% confidence interval 1.58-3.19; P-trend <0.001). When further adjusting for traditional cardiovascular disease risk factors, prevalent coronary heart disease, heart rate, QT interval, and QRS duration, the association remained statistically significant. Spline regression models showed that the association was approximately linear over the range of mtDNA-CN values. No apparent interaction by race or by sex was detected. Conclusion In this community-based prospective study, mtDNA-CN in peripheral blood was inversely associated with the risk of SCD.
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Affiliation(s)
- Yiyi Zhang
- Departments of Epidemiology and Medicine, and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health, 2024 E. Monument St.. Room 2-645, Baltimore, MD 21205, USA
| | - Eliseo Guallar
- Departments of Epidemiology and Medicine, and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health, 2024 E. Monument St.. Room 2-645, Baltimore, MD 21205, USA
| | - Foram N Ashar
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, 733 N. Broadway, Miller Research Building, Room 459, Baltimore, MD 21205, USA
| | - Ryan J Longchamps
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, 733 N. Broadway, Miller Research Building, Room 459, Baltimore, MD 21205, USA
| | - Christina A Castellani
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, 733 N. Broadway, Miller Research Building, Room 459, Baltimore, MD 21205, USA
| | - John Lane
- Department of Laboratory Medicine and Pathology, University of Minnesota, Room 1-156, Moos Tower, 515 Delaware Street SE, Minneapolis, MN 55455, USA
| | - Megan L Grove
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Josef Coresh
- Departments of Epidemiology and Medicine, and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health, 2024 E. Monument St.. Room 2-645, Baltimore, MD 21205, USA
| | - Nona Sotoodehnia
- Department of Medicine, Division of Cardiology, Cardiovascular Health Research Unit, University of Washington, 1730 Minor Ave, Suite 1360, Seattle, Washington 98101, USA
| | - Leonard Ilkhanoff
- Department of Medicine, Division of Cardiology, Electrophysiology Section, Northwestern University, 676 N. St. Clair, Suite 600, Chicago, Illinois, USA.,Inova Heart and Vascular Institute, 3300 Gallows Rd, Falls Church, VA 22042, USA
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.,Baylor College of Medicine, Human Genome Sequencing Center, One Baylor Plaza, Alkek N1419, MS: BCM226, Houston, TX 77030-3411, USA
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota, Room 1-156, Moos Tower, 515 Delaware Street SE, Minneapolis, MN 55455, USA
| | - Dan E Arking
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, 733 N. Broadway, Miller Research Building, Room 459, Baltimore, MD 21205, USA
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15
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Longchamps RJ, Abey SK, Martino AC, Henderson WA. Letter: gender-associated cell-free microRNA profiles in non-alcoholic fatty liver disease. Aliment Pharmacol Ther 2014; 39:997-8. [PMID: 24689349 PMCID: PMC4007279 DOI: 10.1111/apt.12649] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2013] [Revised: 01/13/2014] [Accepted: 01/14/2014] [Indexed: 12/12/2022]
Affiliation(s)
- Ryan J. Longchamps
- Digestive Disorder Unit, Biobehavioral Branch, Division of Intramural Research, National Institute of Nursing Research, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA
| | - Sarah K. Abey
- Digestive Disorder Unit, Biobehavioral Branch, Division of Intramural Research, National Institute of Nursing Research, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA
| | - Angela C. Martino
- Digestive Disorder Unit, Biobehavioral Branch, Division of Intramural Research, National Institute of Nursing Research, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA
| | - Wendy A. Henderson
- Digestive Disorder Unit, Biobehavioral Branch, Division of Intramural Research, National Institute of Nursing Research, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA
,Corresponding Author Digestive Disorder Unit, Biobehavioral Branch 10 Center Drive, 2-1341 Division of Intramural Research, NINR, NIH, DHHS Bethesda, MD 20892 Phone: 301-451-9534 Fax: 301-480-1413
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