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Parchwani D, Singh R, Patel D. Biological and translational attributes of mitochondrial DNA copy number: Laboratory perspective to clinical relevance. World J Methodol 2025; 15:102709. [DOI: 10.5662/wjm.v15.i3.102709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2024] [Revised: 01/21/2025] [Accepted: 02/08/2025] [Indexed: 03/06/2025] Open
Abstract
The mitochondrial DNA copy number (mtDNAcn) plays a vital role in cellular energy metabolism and mitochondrial health. As mitochondria are responsible for adenosine triphosphate production through oxidative phosphorylation, maintaining an appropriate mtDNAcn level is vital for the overall cellular function. Alterations in mtDNAcn have been linked to various diseases, including neurodegenerative disorders, metabolic conditions, and cancers, making it an important biomarker for understanding the disease pathogenesis. The accurate estimation of mtDNAcn is essential for clinical applications. Quantitative polymerase chain reaction and next-generation sequencing are commonly employed techniques with distinct advantages and limitations. Clinically, mtDNAcn serves as a valuable indicator for early diagnosis, disease progression, and treatment response. For instance, in oncology, elevated mtDNAcn levels in blood samples are associated with tumor aggressiveness and can aid in monitoring treatment efficacy. In neurodegenerative diseases such as Alzheimer’s and Parkinson’s, altered mtDNAcn patterns provide insights into disease mechanisms and progression. Understanding and estimating mtDNAcn are critical for advancing diagnostic and therapeutic strategies in various medical fields. As research continues to uncover the implications of mtDNAcn alterations, its potential as a clinical biomarker is likely to expand, thereby enhancing our ability to diagnose and manage complex diseases.
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Affiliation(s)
- Deepak Parchwani
- Department of Biochemistry, All India Institute of Medical Sciences, Rajkot 360001, India
| | - Ragini Singh
- Department of Biochemistry, All India Institute of Medical Sciences, Rajkot 360001, India
| | - Digisha Patel
- Department of Physiology, Shantabaa Medical College and General Hospital Amreli, Amreli 365601, Gujarāt, India
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Wu CY, Chang CC, Lin TT, Liu CS, Chen PS. Exploring the interplay between mitochondrial dysfunction, early life adversity and bipolar disorder. Int J Psychiatry Clin Pract 2025:1-7. [PMID: 40083249 DOI: 10.1080/13651501.2025.2476505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2024] [Revised: 02/24/2025] [Accepted: 03/03/2025] [Indexed: 03/16/2025]
Abstract
OBJECTIVE Mitochondria are essential for energy production and reactive oxygen species (ROS) generation, with changes in ROS levels or energy demands affecting mitochondrial DNA (mtDNA) copy numbers, indicating mitochondrial function. Early life adversity (ELA) affects mitochondrial dynamics, influencing long-term health. Both ELA and mitochondrial abnormalities have been independently associated with bipolar disorder (BD). This study aims to explore the complex interplay between mitochondrial dysfunction, ELA, and BD. METHODS The study included 60 participants diagnosed with BD and 66 healthy controls (HCs). Data were collected using the Childhood Trauma Questionnaire (CTQ), and leukocyte mtDNA copy number (MCN) was determined from blood samples. RESULTS The results indicated the CTQ sum scores were significantly higher in the BD group, reflecting greater exposure to ELA. In HCs, a marginally significant nonlinear relationship between the square of the CTQ sum score and MCN was found. Further analysis demonstrated a significant interaction between ELA and BD on MCN (p = 0.023), highlighting a critical connection between ELA and mitochondrial dysfunction in BD and reinforcing its biological underpinnings. CONCLUSIONS Future treatments for BD might target mitochondrial dysfunctions related to chronic stress, with potential pharmaceuticals designed to address these issues and mitigate the negative effects of chronic stress.
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Affiliation(s)
- Cheng Ying Wu
- Department of Psychiatry, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Cheng-Chen Chang
- School of Medicine, Chung Shan Medical University, Taichung, Taiwan
- Department of Psychiatry, Chung Shan Medical University Hospital, Taichung, Taiwan
| | - Ta-Tsung Lin
- Vascular and Genomic Center, Institute of ATP, Changhua Christian Hospital, Changhua, Taiwan
| | - Chin-San Liu
- Vascular and Genomic Center, Institute of ATP, Changhua Christian Hospital, Changhua, Taiwan
- Department of Neurology, Changhua Christian Hospital, Changhua, Taiwan
- Graduate Institute of Integrated Medicine, China Medical University, Taichung, Taiwan
- Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung, Taiwan
| | - Po See Chen
- Department of Psychiatry, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
- Institute of Behavioral Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan
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3
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Fu Y, Land M, Kavlashvili T, Cui R, Kim M, DeBitetto E, Lieber T, Ryu KW, Choi E, Masilionis I, Saha R, Takizawa M, Baker D, Tigano M, Lareau CA, Reznik E, Sharma R, Chaligne R, Thompson CB, Pe'er D, Sfeir A. Engineering mtDNA deletions by reconstituting end joining in human mitochondria. Cell 2025:S0092-8674(25)00194-1. [PMID: 40068680 DOI: 10.1016/j.cell.2025.02.009] [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: 08/27/2024] [Revised: 01/22/2025] [Accepted: 02/13/2025] [Indexed: 03/19/2025]
Abstract
Recent breakthroughs in the genetic manipulation of mitochondrial DNA (mtDNA) have enabled precise base substitutions and the efficient elimination of genomes carrying pathogenic mutations. However, reconstituting mtDNA deletions linked to mitochondrial myopathies remains challenging. Here, we engineered mtDNA deletions in human cells by co-expressing end-joining (EJ) machinery and targeted endonucleases. Using mitochondrial EJ (mito-EJ) and mito-ScaI, we generated a panel of clonal cell lines harboring a ∼3.5 kb mtDNA deletion across the full spectrum of heteroplasmy. Investigating these cells revealed a critical threshold of ∼75% deleted genomes, beyond which oxidative phosphorylation (OXPHOS) protein depletion, metabolic disruption, and impaired growth in galactose-containing media were observed. Single-cell multiomic profiling identified two distinct nuclear gene deregulation responses: one triggered at the deletion threshold and another progressively responding to heteroplasmy. Ultimately, we show that our method enables the modeling of disease-associated mtDNA deletions across cell types and could inform the development of targeted therapies.
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Affiliation(s)
- Yi Fu
- Molecular Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Max Land
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Tamar Kavlashvili
- Molecular Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ruobing Cui
- Cancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Minsoo Kim
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Emily DeBitetto
- Molecular Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Toby Lieber
- Molecular Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Keun Woo Ryu
- Cancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Elim Choi
- Molecular Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ignas Masilionis
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Rahul Saha
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Meril Takizawa
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Daphne Baker
- Cancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Marco Tigano
- Department of Pathology and Genomic Medicine, Thomas Jefferson University, Philadelphia, PA, USA
| | - Caleb A Lareau
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ed Reznik
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Roshan Sharma
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ronan Chaligne
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Craig B Thompson
- Cancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Dana Pe'er
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Howard Hughes Medical Institute, New York, NY, USA
| | - Agnel Sfeir
- Molecular Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
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Jo S, Oh JH, Lee EJ, Choi M, Lee J, Lee S, Kim TW, Sung CO, Chung SJ. Mitochondrial DNA Copy Number as a Potential Biomarker for the Severity of Motor Symptoms and Prognosis in Parkinson's Disease. Mov Disord 2025; 40:502-510. [PMID: 39760477 DOI: 10.1002/mds.30098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2024] [Revised: 11/24/2024] [Accepted: 12/11/2024] [Indexed: 01/07/2025] Open
Abstract
BACKGROUND Mitochondrial function influences Parkinson's disease (PD) through the accumulation of pathogenic alpha-synuclein, oxidative stress, impaired autophagy, and neuroinflammation. The mitochondrial DNA copy number (mtDNA-CN), representing the number of mitochondrial DNA copies within a cell, serves as an easily assessable proxy for mitochondrial function. OBJECTIVE This study aimed to assess the diagnostic and prognostic capabilities of mtDNA-CN in PD. METHODS We assessed mtDNA-CN in blood samples using whole genome sequencing from 405 patients with PD and 200 healthy controls (HC). We examined the relationship between mtDNA-CN levels and motor symptom severity in PD, as well as their association with dementia development in patients with early-PD (within 3 years of diagnosis). RESULTS mtDNA-CN levels were significantly lower in patients with PD compared with HC (P = 1.1 × 10-5). A negative correlation was discovered between mtDNA-CN level and motor severity in PD (correlation coefficient = -0.20; P = 0.008). Among 210 patients with early-PD, Cox regression analysis demonstrated an association between lower mtDNA-CN levels and a higher risk of developing dementia (hazard ratio [HR] = 0.41, 95% confidence interval: 0.20-0.86, P = 0.02), even after adjusting for age and blood cell count (HR = 0.41, 95% confidence interval: 0.18-0.92, P = 0.03). However, mtDNA-CN levels did not significantly correlate with motor progression in PD. CONCLUSION Our findings suggest that blood mtDNA-CN may function as a diagnostic biomarker for PD and a prognostic marker for dementia in patients with PD. © 2025 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Sungyang Jo
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Ji-Hye Oh
- Bioinformatics Core Laboratory, Convergence Medicine Research Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Republic of Korea
| | - Eun-Jae Lee
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Moongwan Choi
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Jihyun Lee
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Sangjin Lee
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
- Department of Neurology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Republic of Korea
| | - Tae Won Kim
- Department of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Chang Ohk Sung
- Bioinformatics Core Laboratory, Convergence Medicine Research Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Republic of Korea
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Sun Ju Chung
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
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Tong T, Zhu C, Farrell JJ, Khurshid Z, Martin ER, Pericak-Vance MA, Wang LS, Bush WS, Schellenberg GD, Haines JL, Qiu WQ, Lunetta KL, Farrer LA, Zhang X. Blood-derived mitochondrial DNA copy number is associated with Alzheimer disease, Alzheimer-related biomarkers and serum metabolites. Alzheimers Res Ther 2024; 16:234. [PMID: 39444005 PMCID: PMC11515778 DOI: 10.1186/s13195-024-01601-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2024] [Accepted: 10/10/2024] [Indexed: 10/25/2024]
Abstract
BACKGROUND Blood-derived mitochondrial DNA copy number (mtDNA-CN) is a proxy measurement of mitochondrial function in the peripheral and central systems. Abnormal mtDNA-CN not only indicates impaired mtDNA replication and transcription machinery but also dysregulated biological processes such as energy and lipid metabolism. However, the relationship between mtDNA-CN and Alzheimer disease (AD) is unclear. METHODS We performed two-sample Mendelian randomization (MR) using publicly available summary statistics from GWAS for mtDNA-CN and AD to investigate the causal relationship between mtDNA-CN and AD. We estimated mtDNA-CN using whole-genome sequence data from blood and brain samples of 13,799 individuals from the Alzheimer's Disease Sequencing Project. Linear and Cox proportional hazards models adjusting for age, sex, and study phase were used to assess the association of mtDNA-CN with AD. The association of AD biomarkers and serum metabolites with mtDNA-CN in blood was evaluated in Alzheimer's Disease Neuroimaging Initiative using linear regression. We conducted a causal mediation analysis to test the natural indirect effects of mtDNA-CN change on AD risk through the significantly associated biomarkers and metabolites. RESULTS MR analysis suggested a causal relationship between decreased blood-derived mtDNA-CN and increased risk of AD (OR = 0.68; P = 0.013). Survival analysis showed that decreased mtDNA-CN was significantly associated with higher risk of conversion from mild cognitive impairment to AD (HR = 0.80; P = 0.002). We also identified significant associations of mtDNA-CN with brain FDG-PET (β = 0.103; P = 0.022), amyloid-PET (β = 0.117; P = 0.034), CSF amyloid-β (Aβ) 42/40 (β=-0.124; P = 0.017), CSF t-Tau (β = 0.128; P = 0.015), p-Tau (β = 0.140; P = 0.008), and plasma NFL (β=-0.124; P = 0.004) in females. Several lipid species, amino acids, biogenic amines in serum were also significantly associated with mtDNA-CN. Causal mediation analyses showed that about a third of the effect of mtDNA-CN on AD risk was mediated by plasma NFL (P = 0.009), and this effect was more significant in females (P < 0.005). CONCLUSIONS Our study indicates that mtDNA-CN measured in blood is predictive of AD and is associated with AD biomarkers including plasma NFL particularly in females. Further, we illustrate that decreased mtDNA-CN possibly increases AD risk through dysregulation of mitochondrial lipid metabolism and inflammation.
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Affiliation(s)
- Tong Tong
- Bioinformatics Program, Boston University, Boston, MA, USA
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Congcong Zhu
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - John J Farrell
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Zainab Khurshid
- Bioinformatics Program, Boston University, Boston, MA, USA
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Eden R Martin
- Hussman Institute of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Margaret A Pericak-Vance
- Hussman Institute of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Li-San Wang
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - William S Bush
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Gerard D Schellenberg
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Jonathan L Haines
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Wei Qiao Qiu
- Alzheimer's Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Pharmacology, Physiology and Biophysics, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Lindsay A Farrer
- Bioinformatics Program, Boston University, Boston, MA, USA.
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
- Alzheimer's Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
- Departments of Neurology and Ophthalmology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA.
- Boston University Chobanian & Avedisian School of Medicine, Biomedical Genetics E223, 72 East Concord Street, 02118, Boston, MA, USA.
| | - Xiaoling Zhang
- Bioinformatics Program, Boston University, Boston, MA, USA.
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
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6
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Fu Y, Land M, Cui R, Kavlashvili T, Kim M, Lieber T, Ryu KW, DeBitetto E, Masilionis I, Saha R, Takizawa M, Baker D, Tigano M, Reznik E, Sharma R, Chaligne R, Thompson CB, Pe'er D, Sfeir A. Engineering mtDNA Deletions by Reconstituting End-Joining in Human Mitochondria. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.10.15.618543. [PMID: 39463974 PMCID: PMC11507875 DOI: 10.1101/2024.10.15.618543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/29/2024]
Abstract
Recent breakthroughs in the genetic manipulation of mitochondrial DNA (mtDNA) have enabled the precise introduction of base substitutions and the effective removal of genomes carrying harmful mutations. However, the reconstitution of mtDNA deletions responsible for severe mitochondrial myopathies and age-related diseases has not yet been achieved in human cells. Here, we developed a method to engineer specific mtDNA deletions in human cells by co-expressing end-joining (EJ) machinery and targeted endonucleases. As a proof-of-concept, we used mito-EJ and mito-ScaI to generate a panel of clonal cell lines harboring a ∼3.5 kb mtDNA deletion with the full spectrum of heteroplasmy. Investigating these isogenic cells revealed a critical threshold of ∼75% deleted genomes, beyond which cells exhibited depletion of OXPHOS proteins, severe metabolic disruption, and impaired growth in galactose-containing media. Single-cell multiomic analysis revealed two distinct patterns of nuclear gene deregulation in response to mtDNA deletion accumulation; one triggered at the deletion threshold and another progressively responding to increasing heteroplasmy. In summary, the co-expression of mito-EJ and programable nucleases provides a powerful tool to model disease-associated mtDNA deletions in different cell types. Establishing a panel of cell lines with a large-scale deletion at varying levels of heteroplasmy is a valuable resource for understanding the impact of mtDNA deletions on diseases and guiding the development of potential therapeutic strategies. Highlights Combining prokaryotic end-joining with targeted endonucleases generates specific mtDNA deletions in human cellsEngineering a panel of cell lines with a large-scale deletion that spans the full spectrum of heteroplasmy75% heteroplasmy is the threshold that triggers mitochondrial and cellular dysfunctionTwo distinct nuclear transcriptional programs in response to mtDNA deletions: threshold-triggered and heteroplasmy-sensing.
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Lozano M, McEachan RRC, Wright J, Yang TC, Dow C, Kadawathagedara M, Lepeule J, Bustamante M, Maitre L, Vrijheid M, Brantsæter AL, Meltzer HM, Bempi V, Roumeliotaki T, Thomsen C, Nawrot T, Broberg K, Llop S. Early life exposure to mercury and relationships with telomere length and mitochondrial DNA content in European children. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 932:173014. [PMID: 38729362 DOI: 10.1016/j.scitotenv.2024.173014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 05/03/2024] [Accepted: 05/03/2024] [Indexed: 05/12/2024]
Abstract
BACKGROUND Telomere length (TL) and mitochondrial function expressed as mitochondrial DNA copy number (mtDNAcn) are biomarkers of aging and oxidative stress and inflammation, respectively. Methylmercury (MeHg), a common pollutant in fish, induces oxidative stress. We hypothesized that elevated oxidative stress from exposure to MeHg decreases mtDNAcn and shortens TL. METHODS Study participants are 6-11-year-old children from the HELIX multi-center birth cohort study, comprising six European countries. Prenatal and postnatal total mercury (THg) concentrations were measured in blood samples, TL and mtDNAcn were determined in child DNA. Covariates and confounders were obtained by questionnaires. Robust regression models were run, considering sociodemographic and lifestyle covariates, as well as fish consumption. Sex, ethnicity, and fish consumption interaction models were also run. RESULTS We found longer TL with higher pre- and postnatal THg blood concentrations, even at low-level THg exposure according to the RfD proposed by the US EPA. The prenatal association showed a significant linear relationship with a 3.46 % increase in TL for each unit increased THg. The postnatal association followed an inverted U-shaped marginal non-linear relationship with 1.38 % an increase in TL for each unit increased THg until reaching a cut-point at 0.96 μg/L blood THg, from which TL attrition was observed. Higher pre- and postnatal blood THg concentrations were consistently related to longer TL among cohorts and no modification effect of fish consumption nor children's sex was observed. No association between THg exposure and mtDNAcn was found. DISCUSSION We found evidence that THg is associated with TL but the associations seem to be time- and concentration-dependent. Further studies are needed to clarify the mechanism behind the telomere changes of THg and related health effects.
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Affiliation(s)
- Manuel Lozano
- Epidemiology and Environmental Health Joint Research Unit, FISABIO-Universitat Jaume I-Universitat de València, Valencia, Spain; Preventive Medicine and Public Health, Food Sciences, Toxicology and Forensic Medicine Department, Universitat de València, Valencia, Spain.
| | - Rosemary R C McEachan
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, United Kingdom
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, United Kingdom
| | - Tiffany C Yang
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, United Kingdom
| | - Courtney Dow
- Université Paris Cité and Université Sorbonne Paris Nord, INSERM, INRAE, CRESS, Paris, France
| | - Manik Kadawathagedara
- Université Paris Cité and Université Sorbonne Paris Nord, INSERM, INRAE, CRESS, Paris, France
| | - Johanna Lepeule
- Université Grenoble Alpes, INSERM, CNRS, Institute for Advanced Biosciences (IAB), Grenoble, France
| | - Mariona Bustamante
- ISGlobal, Universitat Pompeu Fabra (UPF); Barcelona, Spain; Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Lea Maitre
- ISGlobal, Universitat Pompeu Fabra (UPF); Barcelona, Spain; Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Martine Vrijheid
- ISGlobal, Universitat Pompeu Fabra (UPF); Barcelona, Spain; Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Anne Lise Brantsæter
- Division of Climate and Environmental Health and Centre for Sustainable Diets, Norwegian Institute of Public Health, Oslo, Norway
| | - Helle Margrete Meltzer
- Division of Climate and Environmental Health and Centre for Sustainable Diets, Norwegian Institute of Public Health, Oslo, Norway
| | - Vasiliki Bempi
- Department of Social Medicine, School of Medicine, University of Crete, Heraklion, Greece
| | - Theano Roumeliotaki
- Department of Social Medicine, School of Medicine, University of Crete, Heraklion, Greece
| | - Cathrine Thomsen
- Department of Food Safety, Norwegian Institute of Public Health (NIPH), Oslo, Norway
| | - Tim Nawrot
- Research Unit Environment and Health, KU Leuven Department of Public Health and Primary Care, University of Leuven, Leuven, Belgium
| | - Karin Broberg
- Division of Occupational and Environmental Medicine, Department of Laboratory Medicine, Lund University, Lund, Sweden; Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Sabrina Llop
- Epidemiology and Environmental Health Joint Research Unit, FISABIO-Universitat Jaume I-Universitat de València, Valencia, Spain; Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
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8
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Häkkinen I, Yazgeldi Gunaydin G, Pyöriä L, Kojima S, Parrish N, Perdomo MF, Wedenoja J, Hedman K, Heinonen S, Kajantie E, Laivuori H, Kere J, Katayama S, Wedenoja S. Fetal cord plasma herpesviruses and preeclampsia: an observational cohort study. Sci Rep 2024; 14:14605. [PMID: 38918446 PMCID: PMC11199493 DOI: 10.1038/s41598-024-65386-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2024] [Accepted: 06/19/2024] [Indexed: 06/27/2024] Open
Abstract
A previous study suggested that fetal inheritance of chromosomally integrated human herpesvirus 6 (ici-HHV6) is associated with the hypertensive pregnancy disorder preeclampsia (PE). We aimed to study this question utilizing cord plasma samples (n = 1276) of the Finnish Genetics of Preeclampsia Consortium (FINNPEC) cohort: 539 from a pregnancy with PE and 737 without. We studied these samples and 30 placentas from PE pregnancies by a multiplex qPCR for the DNAs of all nine human herpesviruses. To assess the population prevalence of iciHHV-6, we studied whole-genome sequencing data from blood-derived DNA of 3421 biobank subjects. Any herpes viral DNA was detected in only two (0.37%) PE and one (0.14%) control sample (OR 2.74, 95% CI 0.25-30.4). One PE sample contained iciHHV-6B and another HHV-7 DNA. The control's DNA was of iciHHV-6B; the fetus having growth restriction and preterm birth without PE diagnosis. Placentas showed no herpesviruses. In the biobank data, 3 of 3421 subjects (0.08%) had low level HHV-6B but no iciHHV-6. While iciHHV-6 proved extremely rare, both fetuses with iciHHV-6B were growth-restricted, preterm, and from a pregnancy with maternal hypertension. Our findings suggest that human herpesviruses are not a significant cause of PE, whereas iciHHV-6 may pose some fetal risk.
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Affiliation(s)
- Inka Häkkinen
- Stem Cells and Metabolism Research Program, University of Helsinki, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
| | - Gamze Yazgeldi Gunaydin
- Stem Cells and Metabolism Research Program, University of Helsinki, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
| | - Lari Pyöriä
- Department of Virology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Shohei Kojima
- Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences and RIKEN Cluster for Pioneering Research, Yokohama, Japan
| | - Nicholas Parrish
- Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences and RIKEN Cluster for Pioneering Research, Yokohama, Japan
| | - Maria F Perdomo
- Department of Virology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Juho Wedenoja
- Department of Ophthalmology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Klaus Hedman
- Department of Virology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Seppo Heinonen
- Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Eero Kajantie
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki and Oulu, Finland
- PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Hannele Laivuori
- Department of Obstetrics and Gynecology, Tampere University Hospital, Wellbeing Services County of Pirkanmaa, Tampere, Finland
- Faculty of Medicine and Health Technology, Center for Child, Adolescent and Maternal Health Research, Tampere University, Tampere, Finland
- Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Juha Kere
- Folkhälsan Research Center, Helsinki, Finland
- Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden
| | - Shintaro Katayama
- Stem Cells and Metabolism Research Program, University of Helsinki, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
| | - Satu Wedenoja
- Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
- Information Services Department, Finnish Institute for Health and Welfare, Helsinki, Finland.
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9
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Venkatesan D, Iyer M, Narayanasamy A, Gopalakrishnan AV, Vellingiri B. Plausible Role of Mitochondrial DNA Copy Number in Neurodegeneration-a Need for Therapeutic Approach in Parkinson's Disease (PD). Mol Neurobiol 2023; 60:6992-7008. [PMID: 37523043 DOI: 10.1007/s12035-023-03500-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 07/11/2023] [Indexed: 08/01/2023]
Abstract
Parkinson's disease (PD) is an advancing age-associated progressive brain disorder which has various diverse factors, among them mitochondrial dysfunction involves in dopaminergic (DA) degeneration. Aging causes a rise in mitochondrial abnormalities which leads to structural and functional modifications in neuronal activity and cell death in PD. This ends in deterioration of mitochondrial function, mitochondrial alterations, mitochondrial DNA copy number (mtDNA CN) and oxidative phosphorylation (OXPHOS) capacity. mtDNA levels or mtDNA CN in PD have reported that mtDNA depletion would be a predisposing factor in PD pathogenesis. To maintain the mtDNA levels, therapeutic approaches have been focused on mitochondrial biogenesis in PD. The depletion of mtDNA levels in PD can be influenced by autophagic dysregulation, apoptosis, neuroinflammation, oxidative stress, sirtuins, and calcium homeostasis. The current review describes the regulation of mtDNA levels and discusses the plausible molecular pathways in mtDNA CN depletion in PD pathogenesis. We conclude by suggesting further research on mtDNA depletion which might show a promising effect in predicting and diagnosing PD.
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Affiliation(s)
- Dhivya Venkatesan
- Centre for Neuroscience, Department of Biotechnology, Karpagam Academy of Higher Education (Deemed to Be University), Coimbatore, 641021, India
| | - Mahalaxmi Iyer
- Centre for Neuroscience, Department of Biotechnology, Karpagam Academy of Higher Education (Deemed to Be University), Coimbatore, 641021, India
| | - Arul Narayanasamy
- Disease Proteomics Laboratory, Department of Zoology, Bharathiar University, Coimbatore, 641046, Tamil Nadu, India
| | - Abilash Valsala Gopalakrishnan
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Tamil Nadu, Vellore, 632014, India
| | - Balachandar Vellingiri
- Cytogenetics and Stem Cell Laboratory, Department of Zoology, School of Basic Sciences, Central University of Punjab, Bathinda, Punjab, 151401, India.
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10
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Jurrjens AW, Seldin MM, Giles C, Meikle PJ, Drew BG, Calkin AC. The potential of integrating human and mouse discovery platforms to advance our understanding of cardiometabolic diseases. eLife 2023; 12:e86139. [PMID: 37000167 PMCID: PMC10065800 DOI: 10.7554/elife.86139] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 03/15/2023] [Indexed: 04/01/2023] Open
Abstract
Cardiometabolic diseases encompass a range of interrelated conditions that arise from underlying metabolic perturbations precipitated by genetic, environmental, and lifestyle factors. While obesity, dyslipidaemia, smoking, and insulin resistance are major risk factors for cardiometabolic diseases, individuals still present in the absence of such traditional risk factors, making it difficult to determine those at greatest risk of disease. Thus, it is crucial to elucidate the genetic, environmental, and molecular underpinnings to better understand, diagnose, and treat cardiometabolic diseases. Much of this information can be garnered using systems genetics, which takes population-based approaches to investigate how genetic variance contributes to complex traits. Despite the important advances made by human genome-wide association studies (GWAS) in this space, corroboration of these findings has been hampered by limitations including the inability to control environmental influence, limited access to pertinent metabolic tissues, and often, poor classification of diseases or phenotypes. A complementary approach to human GWAS is the utilisation of model systems such as genetically diverse mouse panels to study natural genetic and phenotypic variation in a controlled environment. Here, we review mouse genetic reference panels and the opportunities they provide for the study of cardiometabolic diseases and related traits. We discuss how the post-GWAS era has prompted a shift in focus from discovery of novel genetic variants to understanding gene function. Finally, we highlight key advantages and challenges of integrating complementary genetic and multi-omics data from human and mouse populations to advance biological discovery.
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Affiliation(s)
- Aaron W Jurrjens
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
| | - Marcus M Seldin
- Department of Biological Chemistry and Center for Epigenetics and Metabolism, University of California, Irvine, Irvine, United States
| | - Corey Giles
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
- Baker Department of Cardiovascular Research Translation and Implementation, La Trobe University, Bundoora, Australia
| | - Peter J Meikle
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
- Baker Department of Cardiovascular Research Translation and Implementation, La Trobe University, Bundoora, Australia
| | - Brian G Drew
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
| | - Anna C Calkin
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
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11
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Przanowski P, Przanowska RK, Guertin MJ. ANKLE1 cleaves mitochondrial DNA and contributes to cancer risk by promoting apoptosis resistance and metabolic dysregulation. Commun Biol 2023; 6:231. [PMID: 36859531 PMCID: PMC9977882 DOI: 10.1038/s42003-023-04611-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 02/20/2023] [Indexed: 03/03/2023] Open
Abstract
Alleles within the chr19p13.1 locus are associated with increased risk of both ovarian and breast cancer and increased expression of the ANKLE1 gene. ANKLE1 is molecularly characterized as an endonuclease that efficiently cuts branched DNA and shuttles between the nucleus and cytoplasm. However, the role of ANKLE1 in mammalian development and homeostasis remains unknown. In normal development ANKLE1 expression is limited to the erythroblast lineage and we found that ANKLE1's role is to cleave the mitochondrial genome during erythropoiesis. We show that ectopic expression of ANKLE1 in breast epithelial-derived cells leads to genome instability and mitochondrial DNA (mtDNA) cleavage. mtDNA degradation then leads to mitophagy and causes a shift from oxidative phosphorylation to glycolysis (Warburg effect). Moreover, mtDNA degradation activates STAT1 and expression of epithelial-mesenchymal transition (EMT) genes. Reduction in mitochondrial content contributes to apoptosis resistance, which may allow precancerous cells to avoid apoptotic checkpoints and proliferate. These findings provide evidence that ANKLE1 is the causal cancer susceptibility gene in the chr19p13.1 locus and describe mechanisms by which higher ANKLE1 expression promotes cancer risk.
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Affiliation(s)
- Piotr Przanowski
- Department of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, Charlottesville, VA, USA.
- Department of Biomedical Engineering, University of Virginia School of Medicine, Charlottesville, VA, USA.
| | - Róża K Przanowska
- Department of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, Charlottesville, VA, USA
- Department of Biomedical Engineering, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Michael J Guertin
- Center for Cell Analysis and Modeling, University of Connecticut, Farmington, CT, USA.
- Department of Genetics and Genome Sciences, University of Connecticut, Farmington, CT, USA.
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12
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Hanks SC, Forer L, Schönherr S, LeFaive J, Martins T, Welch R, Gagliano Taliun SA, Braff D, Johnsen JM, Kenny EE, Konkle BA, Laakso M, Loos RFJ, McCarroll S, Pato C, Pato MT, Smith AV, Boehnke M, Scott LJ, Fuchsberger C. Extent to which array genotyping and imputation with large reference panels approximate deep whole-genome sequencing. Am J Hum Genet 2022; 109:1653-1666. [PMID: 35981533 PMCID: PMC9502057 DOI: 10.1016/j.ajhg.2022.07.012] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Accepted: 07/20/2022] [Indexed: 01/02/2023] Open
Abstract
Understanding the genetic basis of human diseases and traits is dependent on the identification and accurate genotyping of genetic variants. Deep whole-genome sequencing (WGS), the gold standard technology for SNP and indel identification and genotyping, remains very expensive for most large studies. Here, we quantify the extent to which array genotyping followed by genotype imputation can approximate WGS in studies of individuals of African, Hispanic/Latino, and European ancestry in the US and of Finnish ancestry in Finland (a population isolate). For each study, we performed genotype imputation by using the genetic variants present on the Illumina Core, OmniExpress, MEGA, and Omni 2.5M arrays with the 1000G, HRC, and TOPMed imputation reference panels. Using the Omni 2.5M array and the TOPMed panel, ≥90% of bi-allelic single-nucleotide variants (SNVs) are well imputed (r2 > 0.8) down to minor-allele frequencies (MAFs) of 0.14% in African, 0.11% in Hispanic/Latino, 0.35% in European, and 0.85% in Finnish ancestries. There was little difference in TOPMed-based imputation quality among the arrays with >700k variants. Individual-level imputation quality varied widely between and within the three US studies. Imputation quality also varied across genomic regions, producing regions where even common (MAF > 5%) variants were consistently not well imputed across ancestries. The extent to which array genotyping and imputation can approximate WGS therefore depends on reference panel, genotype array, sample ancestry, and genomic location. Imputation quality by variant or genomic region can be queried with our new tool, RsqBrowser, now deployed on the Michigan Imputation Server.
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Affiliation(s)
- Sarah C Hanks
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Lukas Forer
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Sebastian Schönherr
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Jonathon LeFaive
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Taylor Martins
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Ryan Welch
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Sarah A Gagliano Taliun
- Department of Medicine and Department of Neurosciences, Université de Montréal, Montreal, QC, Canada; Research Centre, Montreal Heart Institute, Montreal, QC, Canada
| | - David Braff
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Jill M Johnsen
- Research Institute, Bloodworks, Seattle, WA, USA; Department of Medicine, University of Washington, Seattle, WA, USA
| | - Eimear E Kenny
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Barbara A Konkle
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Ruth F J Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Steven McCarroll
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Carlos Pato
- Departments of Psychiatry, Rutgers University, Robert Wood Johnson Medical School and New Jersey Medical School, New Brunswick, NJ, USA
| | - Michele T Pato
- Departments of Psychiatry, Rutgers University, Robert Wood Johnson Medical School and New Jersey Medical School, New Brunswick, NJ, USA
| | - Albert V Smith
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Laura J Scott
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Christian Fuchsberger
- Institute for Biomedicine (Affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy.
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13
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Sanglard LP, Kuehn LA, Snelling WM, Spangler ML. Influence of environmental factors and genetic variation on mitochondrial DNA copy number. J Anim Sci 2022; 100:6576804. [PMID: 35511236 PMCID: PMC9150079 DOI: 10.1093/jas/skac059] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 02/24/2022] [Indexed: 01/21/2023] Open
Abstract
Mitochondrial DNA copy number (mtDNA CN) has been shown to be highly heritable and associated with traits of interest in humans. However, studies are lacking in the literature for livestock species such as beef cattle. In this study, 2,371 individuals from a crossbred beef population comprising the Germplasm Evaluation program from the U.S. Meat Animal Research Center had samples of blood, leucocyte, or semen collected for low-pass sequencing (LPS) that resulted in both nuclear DNA (nuDNA) and mitochondrial DNA (mtDNA) sequence reads. Mitochondrial DNA CN was estimated based on the ratio of mtDNA to nuDNA coverages. Genetic parameters for mtDNA CN were estimated from an animal model based on a genomic relationship matrix (~87K SNP from the nuDNA). Different models were used to test the effects of tissue, sex, age at sample collection, heterosis, and breed composition. Maternal effects, assessed by fitting a maternal additive component and by fitting eleven SNP on the mtDNA, were also obtained. As previously reported, mtDNA haplotypes were used to classify individuals into Taurine haplogroups (T1, T2, T3/T4, and T5). Estimates of heritability when fitting fixed effects in addition to the intercept were moderate, ranging from 0.11 to 0.31 depending on the model. From a model ignoring contemporary group, semen samples had the lowest mtDNA CN, as expected, followed by blood and leucocyte samples (P ≤ 0.001). The effect of sex and the linear and quadratic effects of age were significant (P ≤ 0.02) depending on the model. When significant, females had greater mtDNA CN than males. The effects of heterosis and maternal heterosis were not significant (P ≥ 0.47). The estimates of maternal and mtDNA heritability were near zero (≤0.03). Most of the samples (98%) were classified as haplogroup T3. Variation was observed in the mtDNA within Taurine haplogroups, which enabled the identification of 24 haplotypes. These results suggest that mtDNA CN is under nuclear genetic control and would respond favorably to selection.
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Affiliation(s)
- Leticia P Sanglard
- Department of Animal Science, University of Nebraska, Lincoln, NE 68583, USA
| | - Larry A Kuehn
- USDA, ARS, Roman L Hruska U.S. Meat Animal Research Center, Clay Center, NE 68933, USA
| | - Warren M Snelling
- USDA, ARS, Roman L Hruska U.S. Meat Animal Research Center, Clay Center, NE 68933, USA
| | - Matthew L Spangler
- Department of Animal Science, University of Nebraska, Lincoln, NE 68583, USA
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14
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Yin X, Chan LS, Bose D, Jackson AU, VandeHaar P, Locke AE, Fuchsberger C, Stringham HM, Welch R, Yu K, Fernandes Silva L, Service SK, Zhang D, Hector EC, Young E, Ganel L, Das I, Abel H, Erdos MR, Bonnycastle LL, Kuusisto J, Stitziel NO, Hall IM, Wagner GR, Kang J, Morrison J, Burant CF, Collins FS, Ripatti S, Palotie A, Freimer NB, Mohlke KL, Scott LJ, Wen X, Fauman EB, Laakso M, Boehnke M. Genome-wide association studies of metabolites in Finnish men identify disease-relevant loci. Nat Commun 2022; 13:1644. [PMID: 35347128 PMCID: PMC8960770 DOI: 10.1038/s41467-022-29143-5] [Citation(s) in RCA: 77] [Impact Index Per Article: 25.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 02/23/2022] [Indexed: 01/13/2023] Open
Abstract
Few studies have explored the impact of rare variants (minor allele frequency < 1%) on highly heritable plasma metabolites identified in metabolomic screens. The Finnish population provides an ideal opportunity for such explorations, given the multiple bottlenecks and expansions that have shaped its history, and the enrichment for many otherwise rare alleles that has resulted. Here, we report genetic associations for 1391 plasma metabolites in 6136 men from the late-settlement region of Finland. We identify 303 novel association signals, more than one third at variants rare or enriched in Finns. Many of these signals identify genes not previously implicated in metabolite genome-wide association studies and suggest mechanisms for diseases and disease-related traits.
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Affiliation(s)
- Xianyong Yin
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Lap Sum Chan
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Debraj Bose
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Anne U Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Peter VandeHaar
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Adam E Locke
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, 63108, USA
| | - Christian Fuchsberger
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
- Institute for Biomedicine, Eurac Research, Bolzano, 39100, Italy
| | - Heather M Stringham
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Ryan Welch
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Ketian Yu
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Lilian Fernandes Silva
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, 70210, Finland
| | - Susan K Service
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, 90024, USA
| | - Daiwei Zhang
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Emily C Hector
- Department of Statistics, North Carolina State University, Raleigh, NC, 27695, USA
| | - Erica Young
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, 63108, USA
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St Louis, MO, 63110, USA
| | - Liron Ganel
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, 63108, USA
| | - Indraniel Das
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, 63108, USA
| | - Haley Abel
- Department of Medicine, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Michael R Erdos
- Molecular Genetics Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Lori L Bonnycastle
- Molecular Genetics Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, 70210, Finland
- Center for Medicine and Clinical Research, Kuopio University Hospital, Kuopio, 70210, Finland
| | - Nathan O Stitziel
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, 63108, USA
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St Louis, MO, 63110, USA
- Department of Genetics, Washington University School of Medicine, St Louis, MO, 63110, USA
| | - Ira M Hall
- Center for Genomic Health, Department of Genetics, Yale University, New Haven, CT, 06510, USA
| | | | - Jian Kang
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Jean Morrison
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Charles F Burant
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Francis S Collins
- Molecular Genetics Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00290, Finland
- Department of Public Health, University of Helsinki, Helsinki, 00014, Finland
- Broad Institute of MIT & Harvard, Cambridge, MA, 02142, USA
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00290, Finland
- Department of Public Health, University of Helsinki, Helsinki, 00014, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Department of Neurology, and Department of Psychiatry, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Nelson B Freimer
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, 90024, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Laura J Scott
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Xiaoquan Wen
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Eric B Fauman
- Internal Medicine Research Unit, Pfizer Worldwide Research, Development and Medical, Cambridge, MA, 02139, USA.
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, 70210, Finland.
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA.
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