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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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2
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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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3
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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: 0] [Impact Index Per Article: 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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4
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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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5
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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 RF, 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: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [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
| | | | - 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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6
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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: 0.5] [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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7
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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: 52] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [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
- grid.214458.e0000000086837370Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109 USA
| | - Lap Sum Chan
- grid.214458.e0000000086837370Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109 USA
| | - Debraj Bose
- grid.214458.e0000000086837370Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109 USA
| | - Anne U. Jackson
- grid.214458.e0000000086837370Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109 USA
| | - Peter VandeHaar
- grid.214458.e0000000086837370Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109 USA
| | - Adam E. Locke
- grid.4367.60000 0001 2355 7002McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO 63108 USA
| | - Christian Fuchsberger
- grid.214458.e0000000086837370Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109 USA ,grid.511439.bInstitute for Biomedicine, Eurac Research, Bolzano, 39100 Italy
| | - Heather M. Stringham
- grid.214458.e0000000086837370Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109 USA
| | - Ryan Welch
- grid.214458.e0000000086837370Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109 USA
| | - Ketian Yu
- grid.214458.e0000000086837370Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109 USA
| | - Lilian Fernandes Silva
- grid.9668.10000 0001 0726 2490Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, 70210 Finland
| | - Susan K. Service
- grid.19006.3e0000 0000 9632 6718Center 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
- grid.214458.e0000000086837370Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109 USA ,grid.25879.310000 0004 1936 8972Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104 USA
| | - Emily C. Hector
- grid.40803.3f0000 0001 2173 6074Department of Statistics, North Carolina State University, Raleigh, NC 27695 USA
| | - Erica Young
- grid.4367.60000 0001 2355 7002McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO 63108 USA ,grid.4367.60000 0001 2355 7002Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St Louis, MO 63110 USA
| | - Liron Ganel
- grid.4367.60000 0001 2355 7002McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO 63108 USA
| | - Indraniel Das
- grid.4367.60000 0001 2355 7002McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO 63108 USA
| | - Haley Abel
- grid.4367.60000 0001 2355 7002Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110 USA
| | - Michael R. Erdos
- grid.94365.3d0000 0001 2297 5165Molecular Genetics Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892 USA
| | - Lori L. Bonnycastle
- grid.94365.3d0000 0001 2297 5165Molecular Genetics Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892 USA
| | - Johanna Kuusisto
- grid.9668.10000 0001 0726 2490Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, 70210 Finland ,grid.410705.70000 0004 0628 207XCenter for Medicine and Clinical Research, Kuopio University Hospital, Kuopio, 70210 Finland
| | - Nathan O. Stitziel
- grid.4367.60000 0001 2355 7002McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO 63108 USA ,grid.4367.60000 0001 2355 7002Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St Louis, MO 63110 USA ,grid.4367.60000 0001 2355 7002Department of Genetics, Washington University School of Medicine, St Louis, MO 63110 USA
| | - Ira M. Hall
- grid.47100.320000000419368710Center for Genomic Health, Department of Genetics, Yale University, New Haven, CT 06510 USA
| | - Gregory R. Wagner
- grid.429438.00000 0004 0402 1933Metabolon, Inc., Morrisville, NC 27560 USA
| | | | - Jian Kang
- grid.214458.e0000000086837370Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109 USA
| | - Jean Morrison
- grid.214458.e0000000086837370Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109 USA
| | - Charles F. Burant
- grid.214458.e0000000086837370Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109 USA
| | - Francis S. Collins
- grid.94365.3d0000 0001 2297 5165Molecular Genetics Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892 USA
| | - Samuli Ripatti
- grid.7737.40000 0004 0410 2071Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00290 Finland ,grid.7737.40000 0004 0410 2071Department of Public Health, University of Helsinki, Helsinki, 00014 Finland ,grid.66859.340000 0004 0546 1623Broad Institute of MIT & Harvard, Cambridge, MA 02142 USA
| | - Aarno Palotie
- grid.7737.40000 0004 0410 2071Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00290 Finland ,grid.7737.40000 0004 0410 2071Department of Public Health, University of Helsinki, Helsinki, 00014 Finland ,grid.32224.350000 0004 0386 9924Analytic and Translational Genetics Unit, Department of Medicine, Department of Neurology, and Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114 USA
| | - Nelson B. Freimer
- grid.19006.3e0000 0000 9632 6718Center 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
- grid.10698.360000000122483208Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA
| | - Laura J. Scott
- grid.214458.e0000000086837370Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109 USA
| | - Xiaoquan Wen
- grid.214458.e0000000086837370Department 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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