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Guay SP, Paquette M, Taschereau A, Desgagné V, Bouchard L, Bernard S, Baass A. DNA methylation levels may contribute to severe hypertriglyceridemia in multifactorial chylomicronemia syndrome. Clin Biochem 2025; 135:110873. [PMID: 39756670 DOI: 10.1016/j.clinbiochem.2025.110873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2024] [Revised: 01/01/2025] [Accepted: 01/02/2025] [Indexed: 01/07/2025]
Abstract
BACKGROUND AND AIMS Familial chylomicronemia syndrome (FCS) and multifactorial chylomicronemia syndrome (MCS) are the two main causes of severe hypertriglyceridemia (sHTG). FCS is a rare autosomal recessive form of sHTG, whereas MCS is mainly polygenic in nature with both common and rare variants accumulating and leading to sHTG. However, 30 to 50% of MCS patients have no identified genetic cause of sHTG. DNA methylation (DNAm) is a non-traditional heritable factor known to be associated with triglyceride (TG) levels. The aim of this study is to determine if DNAm level at three candidate genes for hypertriglyceridemia (ABCG1, CPT1A and SREBF1) could contribute to sHTG in MCS patients. METHODS A total of 114 MCS and 20 FCS patients were included in this retrospective study. DNAm levels were measured at ABCG1 (cg06500161), CPT1A (cg00574958), and SREBF1 (cg11024682) gene loci using pyrosequencing of bisulfite-treated DNA. RESULTS DNAm levels at ABCG1, CPT1A and SREBF1 were significantly associated with TG levels or minimal TG levels in MCS patients. Prevalence of patients with at least 2 loci with DNAm levels into the top tertile of DNAm associated with hypertriglyceridemia was significantly higher in MCS patients with genetically undefined sHTG compared to MCS patients with polygenic sHTG and FCS patients (57 % vs. 24 % vs. 0 %, respectively; p < 0.0001). CONCLUSION This study suggests for the first time that DNAm could contribute to sHTG in MCS patients. It suggests that further studies of epivariations may contribute to better understand the clinical heterogeneity seen in MCS patients.
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Affiliation(s)
- Simon-Pierre Guay
- Genetic Dyslipidemias Clinic of the Montreal Clinical Research Institute, Montréal, Québec, Canada; Department of Pediatric, Division of Medical Genetics, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | - Martine Paquette
- Genetic Dyslipidemias Clinic of the Montreal Clinical Research Institute, Montréal, Québec, Canada
| | - Amélie Taschereau
- Department of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | - Véronique Desgagné
- Department of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Québec, Canada; Clinical Department of Laboratory Medicine, Centre intégré universitaire de santé et de services sociaux (CIUSSS) du Saguenay-Lac-Saint-Jean - Hôpital de Chicoutimi, Saguenay, Québec, Canada
| | - Luigi Bouchard
- Department of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Québec, Canada; Clinical Department of Laboratory Medicine, Centre intégré universitaire de santé et de services sociaux (CIUSSS) du Saguenay-Lac-Saint-Jean - Hôpital de Chicoutimi, Saguenay, Québec, Canada
| | - Sophie Bernard
- Genetic Dyslipidemias Clinic of the Montreal Clinical Research Institute, Montréal, Québec, Canada
| | - Alexis Baass
- Genetic Dyslipidemias Clinic of the Montreal Clinical Research Institute, Montréal, Québec, Canada; Department of Medicine, Divisions of Experimental Medicine and Medical Biochemistry, McGill University, Montréal, Québec, Canada.
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Dawangpa A, Chitta P, Rodrigues GDS, Iadsee N, Noronha NY, Nonino CB, Bueno Júnior CR, Sae-Lee C. Impact of combined exercise on blood DNA methylation and physical health in older women with obesity. PLoS One 2024; 19:e0315250. [PMID: 39680552 DOI: 10.1371/journal.pone.0315250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2024] [Accepted: 11/21/2024] [Indexed: 12/18/2024] Open
Abstract
This study examined the effects of a 14-week combined exercise program on blood DNA methylation (DNAm) and its potential biological pathways in normal-weight, overweight, and obese older women. A total of 41 participants were assessed at baseline, 7 weeks, and 14 weeks into the training. Their whole-blood DNAm profiles were measured using the Infinitum MethylationEPIC BeadChip, alongside physical and biochemical health evaluations. The results showed notable health improvements, with decreases in blood pressure and cholesterol levels in the overweight and obese groups. Blood triglycerides were reduced only in the overweight group. Physical performance also improved across all groups. At 14 weeks, 1,043 differentially methylated positions (DMPs) were identified, affecting 744 genes. The genes were linked to biological processes, such as cellular metabolism, with significant pathway enrichment related to oxidative phosphorylation and chemical carcinogenesis. Additionally, the overweight group experienced significant reductions in methylation levels at eight lipogenesis-related genes. Protein EpiScore analysis revealed decreased levels of CCL11, VEGFA, and NTRK3 proteins at 14 weeks compared to baseline. Despite these significant molecular changes, there was no observable difference in DNAm age after the intervention. This study highlights how combined exercise can modify DNAm patterns in older women, particularly in lipogenesis-related genes, but suggests that further research is needed to understand the full implications for biological ageing.
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Affiliation(s)
- Atchara Dawangpa
- Research Division, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand
- Department of Clinical Pathology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Pitaksin Chitta
- Research Division, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand
- Department of Clinical Pathology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | | | - Nutta Iadsee
- Research Division, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand
- Department of Clinical Pathology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Natália Y Noronha
- Department of Internal Medicine, Ribeirão Preto Medical School, University of São Paulo, São Paulo, Brazil
| | - Carla B Nonino
- Health Sciences Department, Ribeirão Preto Medical School, University of São Paulo, São Paulo, Brazil
| | - Carlos R Bueno Júnior
- School of Physical Education and Sport of Ribeirão Preto, University of Sao Paulo, Sao Paulo, Brazil
| | - Chanachai Sae-Lee
- Research Division, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand
- Department of Clinical Pathology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
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Ciantar J, Marttila S, Rajić S, Kostiniuk D, Mishra PP, Lyytikäinen LP, Mononen N, Kleber ME, März W, Kähönen M, Raitakari O, Lehtimäki T, Raitoharju E. Identification and functional characterisation of DNA methylation differences between East- and West-originating Finns. Epigenetics 2024; 19:2397297. [PMID: 39217505 PMCID: PMC11382697 DOI: 10.1080/15592294.2024.2397297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 08/14/2024] [Accepted: 08/22/2024] [Indexed: 09/04/2024] Open
Abstract
Eastern and Western Finns show a striking difference in coronary heart disease-related mortality; genetics is a known contributor for this discrepancy. Here, we discuss the potential role of DNA methylation in mediating the discrepancy in cardiometabolic disease-risk phenotypes between the sub-populations. We used data from the Young Finns Study (n = 969) to compare the genome-wide DNA methylation levels of East- and West-originating Finns. We identified 21 differentially methylated loci (FDR < 0.05; Δβ >2.5%) and 7 regions (smoothed FDR < 0.05; CpGs ≥ 5). Methylation at all loci and regions associates with genetic variants (p < 5 × 10-8). Independently of genetics, methylation at 11 loci and 4 regions associates with transcript expression, including genes encoding zinc finger proteins. Similarly, methylation at 5 loci and 4 regions associates with cardiometabolic disease-risk phenotypes including triglycerides, glucose, cholesterol, as well as insulin treatment. This analysis was also performed in LURIC (n = 2371), a German cardiovascular patient cohort, and results replicated for the association of methylation at cg26740318 and DMR_11p15 with diabetes-related phenotypes and methylation at DMR_22q13 with triglyceride levels. Our results indicate that DNA methylation differences between East and West Finns may have a functional role in mediating the cardiometabolic disease discrepancy between the sub-populations.
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Affiliation(s)
- Joanna Ciantar
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Saara Marttila
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Gerontology Research Center, Tampere University, Tampere, Finland
- Tays Research Services, Wellbeing Services County of Pirkanmaa, Tampere University Hospital, Tampere, Finland
| | - Sonja Rajić
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Daria Kostiniuk
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Tays Research Services, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Tays Research Services, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Nina Mononen
- Department of Clinical Chemistry, Tays Research Services, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Marcus E Kleber
- Vth Department of Medicine (Nephrology, Hypertensiology, Endocrinology, Diabetology, Rheumatology), Medical Faculty of Mannheim, Heidelberg University, Mannheim, Germany
- SYNLAB MVZ Humangenetik Mannheim, Mannheim, Germany
| | - Winfried März
- Vth Department of Medicine (Nephrology, Hypertensiology, Endocrinology, Diabetology, Rheumatology), Medical Faculty of Mannheim, Heidelberg University, Mannheim, Germany
- Synlab Academy, SYNLAB Holding Deutschland GmbH, Mannheim, Germany
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital and Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Tays Research Services, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Emma Raitoharju
- Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Fimlab Laboratories, Tampere, Finland
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Małodobra-Mazur M, Ołdakowska M, Dobosz T. Exploring PPAR Gamma and PPAR Alpha's Regulation Role in Metabolism via Epigenetics Mechanism. Biomolecules 2024; 14:1445. [PMID: 39595621 PMCID: PMC11591816 DOI: 10.3390/biom14111445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2024] [Revised: 10/18/2024] [Accepted: 11/12/2024] [Indexed: 11/28/2024] Open
Abstract
Peroxisome proliferator-activated receptors (PPARs) belong to a family of nuclear receptors. To date, three types of PPARs, namely PPARα, PPARδ, and PPARγ, have been identified, demonstrating co-expression across numerous tissues. PPARγ is primarily distributed in adipose tissue, the colon, the immune system, and the retina, while PPARα is predominantly expressed in metabolic tissues such as brown adipose tissue, the liver, and the kidneys. Both PPARγ and PPARα play crucial roles in various cellular processes. Recent data suggest that the PPAR family, among other mechanisms, might also be regulated by epigenetic mechanisms. Our recent studies, alongside numerous others, have highlighted the pivotal roles of DNA methylation and histone modifications in the regulation of PPARγ and PPARα, implicating them in the deterioration of metabolic disorders via epigenetic mechanisms. This still not fully understood mechanism of regulation in the nuclear receptors family has been summarized and described in the present paper. The present review summarizes the available data on PPARγ and PPARα regulation via epigenetic mechanisms, elucidating the link between the development of metabolic disorders and the dysregulation of PPARγ and PPARα resulting from these mechanisms.
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Affiliation(s)
- Małgorzata Małodobra-Mazur
- Department of Forensic Science, Division of Molecular Techniques, Wroclaw Medical University, Sklodowskiej-Curie 52, 51-367 Wroclaw, Poland; (M.O.); (T.D.)
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Šket R, Slapnik B, Kotnik P, Črepinšek K, Čugalj Kern B, Tesovnik T, Jenko Bizjan B, Vrhovšek B, Remec ŽI, Debeljak M, Battelino T, Kovač J. Integrating Genetic Insights, Technological Advancements, Screening, and Personalized Pharmacological Interventions in Childhood Obesity. Adv Ther 2024:10.1007/s12325-024-03057-8. [PMID: 39535684 DOI: 10.1007/s12325-024-03057-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2024] [Accepted: 10/25/2024] [Indexed: 11/16/2024]
Abstract
Childhood obesity is a significant global health challenge with rising prevalence over the past 50 years, affecting both immediate and long-term health outcomes. The increase in prevalence from 0.7% to 5.6% in girls and 0.9% to 7.8% in boys highlights the urgency of addressing this epidemic. By 2025, it is estimated that 206 million children and adolescents aged 5-19 years will be living with obesity. This review explores the complex interplay of genomics and genetics in pediatric obesity, transitioning from monogenic and polygenic obesity to epigenetics, and incorporating advancements in omics technologies. The evolutionary purpose of adiposity, systemic evaluation of hyperphagia, and the role of various genetic factors are discussed. Technological advancements in genotyping offer new insights and interventions. The integration of genetic screening into clinical practice for early identification and personalized treatment strategies is emphasized.
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Affiliation(s)
- Robert Šket
- University Children's Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Barbara Slapnik
- University Children's Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Primož Kotnik
- University Children's Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Klementina Črepinšek
- University Children's Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Barbara Čugalj Kern
- University Children's Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Tine Tesovnik
- University Children's Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Barbara Jenko Bizjan
- University Children's Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Blaž Vrhovšek
- University Children's Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
| | - Žiga I Remec
- University Children's Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
| | - Maruša Debeljak
- University Children's Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Tadej Battelino
- University Children's Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Jernej Kovač
- University Children's Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia.
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
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6
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Carper D, Lac M, Coue M, Labour A, Märtens A, Banda JAA, Mazeyrie L, Mechta M, Ingerslev LR, Elhadad M, Petit JV, Maslo C, Monbrun L, Del Carmine P, Sainte-Marie Y, Bourlier V, Laurens C, Mithieux G, Joanisse DR, Coudray C, Feillet-Coudray C, Montastier E, Viguerie N, Tavernier G, Waldenberger M, Peters A, Wang-Sattler R, Adamski J, Suhre K, Gieger C, Kastenmüller G, Illig T, Lichtinghagen R, Seissler J, Mounier R, Hiller K, Jordan J, Barrès R, Kuhn M, Pesta D, Moro C. Loss of atrial natriuretic peptide signaling causes insulin resistance, mitochondrial dysfunction, and low endurance capacity. SCIENCE ADVANCES 2024; 10:eadl4374. [PMID: 39383215 PMCID: PMC11463261 DOI: 10.1126/sciadv.adl4374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 09/06/2024] [Indexed: 10/11/2024]
Abstract
Type 2 diabetes (T2D) and obesity are strongly associated with low natriuretic peptide (NP) plasma levels and a down-regulation of NP guanylyl cyclase receptor-A (GCA) in skeletal muscle and adipose tissue. However, no study has so far provided evidence for a causal link between atrial NP (ANP)/GCA deficiency and T2D pathogenesis. Here, we show that both systemic and skeletal muscle ANP/GCA deficiencies in mice promote metabolic disturbances and prediabetes. Skeletal muscle insulin resistance is further associated with altered mitochondrial function and impaired endurance running capacity. ANP/GCA-deficient mice exhibit increased proton leak and reduced content of mitochondrial oxidative phosphorylation proteins. We further show that GCA is related to several metabolic traits in T2D and positively correlates with markers of oxidative capacity in human skeletal muscle. Together, these results indicate that ANP/GCA signaling controls muscle mitochondrial integrity and oxidative capacity in vivo and plays a causal role in the development of prediabetes.
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Affiliation(s)
- Deborah Carper
- Institute of Metabolic and Cardiovascular Diseases, INSERM/Paul Sabatier University, UMR1297, Team MetaDiab, Toulouse, France
| | - Marlène Lac
- Institute of Metabolic and Cardiovascular Diseases, INSERM/Paul Sabatier University, UMR1297, Team MetaDiab, Toulouse, France
| | - Marine Coue
- Institute of Metabolic and Cardiovascular Diseases, INSERM/Paul Sabatier University, UMR1297, Team MetaDiab, Toulouse, France
| | - Axel Labour
- Institute of Metabolic and Cardiovascular Diseases, INSERM/Paul Sabatier University, UMR1297, Team MetaDiab, Toulouse, France
| | - Andre Märtens
- Department of Bioinformatics and Biochemistry, Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig and Physikalisch-Technische Bundesanstalt, Brunswick, Germany
| | - Jorge Alberto Ayala Banda
- Institute of Metabolic and Cardiovascular Diseases, INSERM/Paul Sabatier University, UMR1297, Team MetaDiab, Toulouse, France
| | - Laurène Mazeyrie
- Institute of Metabolic and Cardiovascular Diseases, INSERM/Paul Sabatier University, UMR1297, Team MetaDiab, Toulouse, France
| | - Mie Mechta
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Lars Roed Ingerslev
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Mohamed Elhadad
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | | | - Claire Maslo
- Institute of Metabolic and Cardiovascular Diseases, INSERM/Paul Sabatier University, UMR1297, Team MetaDiab, Toulouse, France
| | - Laurent Monbrun
- Institute of Metabolic and Cardiovascular Diseases, INSERM/Paul Sabatier University, UMR1297, Team MetaDiab, Toulouse, France
| | - Peggy Del Carmine
- Institut NeuroMyoGène, Université Claude Bernard Lyon 1, INSERM U1315, CNRS UMR, 5261 Lyon, France
| | - Yannis Sainte-Marie
- Institute of Metabolic and Cardiovascular Diseases, INSERM/Paul Sabatier University, UMR1297, Team MetaDiab, Toulouse, France
| | - Virginie Bourlier
- Institute of Metabolic and Cardiovascular Diseases, INSERM/Paul Sabatier University, UMR1297, Team MetaDiab, Toulouse, France
| | - Claire Laurens
- Institute of Metabolic and Cardiovascular Diseases, INSERM/Paul Sabatier University, UMR1297, Team MetaDiab, Toulouse, France
| | | | - Denis R. Joanisse
- Department of Kinesiology, Centre de Recherche de l’Institut Universitaire de Cardiologie et de Pneumologie de Québec, Université Laval, Québec, Canada
| | - Charles Coudray
- Dynamique Musculaire Et Métabolisme, INRAE, UMR866, Université Montpellier, Montpellier, France
| | | | - Emilie Montastier
- Institute of Metabolic and Cardiovascular Diseases, INSERM/Paul Sabatier University, UMR1297, Team MetaDiab, Toulouse, France
| | - Nathalie Viguerie
- Institute of Metabolic and Cardiovascular Diseases, INSERM/Paul Sabatier University, UMR1297, Team MetaDiab, Toulouse, France
| | - Geneviève Tavernier
- Institute of Metabolic and Cardiovascular Diseases, INSERM/Paul Sabatier University, UMR1297, Team MetaDiab, Toulouse, France
| | - Melanie Waldenberger
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Rui Wang-Sattler
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Jerzy Adamski
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore
- Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Vrazov trg 2, 1000 Ljubljana, Slovenia
| | - Karsten Suhre
- Bioinformatics Core, Weill Cornell Medicine-Qatar, Doha, Qatar
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Gabi Kastenmüller
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Thomas Illig
- Hannover Unified Biobank, Hannover Medical School, Hanover, Germany
| | - Ralf Lichtinghagen
- Department of Clinical Chemistry, Hannover Medical School, Hannover, Germany
| | - Jochen Seissler
- Diabetes Zentrum, Medizinische Klinik und Poliklinik IV, Klinikum der Universität München, LMU, München, Germany
| | - Remy Mounier
- Institut NeuroMyoGène, Université Claude Bernard Lyon 1, INSERM U1315, CNRS UMR, 5261 Lyon, France
| | - Karsten Hiller
- Department of Bioinformatics and Biochemistry, Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig and Physikalisch-Technische Bundesanstalt, Brunswick, Germany
| | - Jens Jordan
- Institute of Aerospace Medicine, German Aerospace Center, Cologne, Germany
- Medical Faculty, University of Cologne, Cologne, Germany
| | - Romain Barrès
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Michaela Kuhn
- Institute of Physiology, University of Würzburg, Würzburg, Germany
| | - Dominik Pesta
- Institute of Aerospace Medicine, German Aerospace Center, Cologne, Germany
- Medical Faculty, University of Cologne, Cologne, Germany
- Center for Endocrinology, Diabetes, and Preventive Medicine (CEDP), University Hospital Cologne, Cologne, Germany
- Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Cedric Moro
- Institute of Metabolic and Cardiovascular Diseases, INSERM/Paul Sabatier University, UMR1297, Team MetaDiab, Toulouse, France
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7
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Si J, Ma Y, Yu C, Sun D, Pang Y, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Zheng X, Avery D, Chen J, Chen Z, Liang L, Li L, Lv J. DNA Methylation Age Mediates Effect of Metabolic Profile on Cardiovascular and General Aging. Circ Res 2024; 135:954-966. [PMID: 39308399 DOI: 10.1161/circresaha.124.325066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 09/02/2024] [Accepted: 09/09/2024] [Indexed: 10/12/2024]
Abstract
BACKGROUND Alterations in lipid metabolism and DNA methylation are 2 hallmarks of aging. Connecting metabolomic, epigenomic, and aging outcomes help unravel the complex mechanisms underlying aging. We aimed to assess whether DNA methylation clocks mediate the association of circulating metabolites with incident atherosclerotic cardiovascular disease (ASCVD) and frailty. METHODS The China Kadoorie Biobank is a prospective cohort study with a baseline survey from 2004 to 2008 and a follow-up period until December 31, 2018. We used the Infinium Methylation EPIC BeadChip to measure the methylation levels of 988 participants' baseline blood leukocyte DNA. Metabolite profiles, including lipoprotein particles, lipid constituents, and various circulating metabolites, were measured using quantitative nuclear magnetic resonance. The pace of DNA methylation age acceleration (AA) was calculated using 5 widely used epigenetic clocks (the first generation: Horvath, Hannum, and Li; the second generation: Grim and Pheno). Incident ASCVD was ascertained through linkage with local death and disease registries and national health insurance databases, supplemented by active follow-up. The frailty index was constructed using medical conditions, symptoms, signs, and physical measurements collected at baseline. RESULTS A total of 508 incident cases of ASCVD were documented during a median follow-up of 9.5 years. The first generation of epigenetic clocks was associated with the risk of ASCVD (P<0.05). For each SD increment in LiAA, HorvathAA, and HannumAA, the corresponding hazard ratios for ASCVD risk were 1.16 (1.05-1.28), 1.10 (1.00-1.22), and 1.17 (1.04-1.31), respectively. Only LiAA mediated the association of various metabolites (lipids, fatty acids, histidine, and inflammatory biomarkers) with ASCVD, with the mediating proportion reaching up to 15% for the diameter of low-density lipoprotein (P=1.2×10-2). Regarding general aging, a 1-SD increase in GrimAA was associated with an average increase of 0.10 in the frailty index (P=2.0×10-3), and a 33% and 63% increased risk of prefrailty and frailty at baseline (P=1.5×10-2 and 5.8×10-2), respectively; this association was not observed with other clocks. GrimAA mediated the effect of various lipids, fatty acids, glucose, lactate, and inflammatory biomarkers on the frailty index, with the mediating proportion reaching up to 22% for triglycerides in very small-sized very low-density lipoprotein (P=6.0×10-3). CONCLUSIONS These findings suggest that epigenomic mechanisms may play a role in the associations between circulating metabolites and the aging process. Different mechanisms underlie the first and second generations of DNA methylation age in cardiovascular and general aging.
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Affiliation(s)
- Jiahui Si
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China (J.S.)
| | - Yu Ma
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China (Y.M., C.Y., D.S., Y.P., L. Li, J.L.)
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China (Y.M., C.Y., D.S., Y.P., L. Li, J.L.)
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China (C.Y., D.S., Y.P., P.P., L. Li, J.L.)
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China (C.Y., D.S., Y.P., L. Li, J.L.)
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China (Y.M., C.Y., D.S., Y.P., L. Li, J.L.)
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China (C.Y., D.S., Y.P., P.P., L. Li, J.L.)
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China (C.Y., D.S., Y.P., L. Li, J.L.)
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China (Y.M., C.Y., D.S., Y.P., L. Li, J.L.)
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China (C.Y., D.S., Y.P., P.P., L. Li, J.L.)
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China (C.Y., D.S., Y.P., L. Li, J.L.)
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China (C.Y., D.S., Y.P., P.P., L. Li, J.L.)
| | - Ling Yang
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom (L.Y., I.Y.M., R.G.W., Y.C., H.D., D.A., Z.C.)
| | - Iona Y Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom (L.Y., I.Y.M., R.G.W., Y.C., H.D., D.A., Z.C.)
| | - Robin G Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom (L.Y., I.Y.M., R.G.W., Y.C., H.D., D.A., Z.C.)
| | - Yiping Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom (L.Y., I.Y.M., R.G.W., Y.C., H.D., D.A., Z.C.)
| | - Huaidong Du
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom (L.Y., I.Y.M., R.G.W., Y.C., H.D., D.A., Z.C.)
| | - Xiaoyan Zheng
- NCDs Prevention and Control Department, Licang CDC (X.Z.)
| | - Daniel Avery
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom (L.Y., I.Y.M., R.G.W., Y.C., H.D., D.A., Z.C.)
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China (J.C.)
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom (L.Y., I.Y.M., R.G.W., Y.C., H.D., D.A., Z.C.)
| | - Liming Liang
- Departments of Epidemiology and Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA (L. Liang)
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China (Y.M., C.Y., D.S., Y.P., L. Li, J.L.)
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China (C.Y., D.S., Y.P., P.P., L. Li, J.L.)
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China (C.Y., D.S., Y.P., L. Li, J.L.)
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China (Y.M., C.Y., D.S., Y.P., L. Li, J.L.)
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China (C.Y., D.S., Y.P., P.P., L. Li, J.L.)
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China (C.Y., D.S., Y.P., L. Li, J.L.)
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China (J.L.). The members of steering committee and collaborative group are listed in the online-only supplemental material
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8
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Bizzarri D, Reinders MJT, Kuiper L, Beekman M, Deelen J, van Meurs JBJ, van Dongen J, Pool R, Boomsma DI, Ghanbari M, Franke L, Slagboom PE, van den Akker EB. NMR metabolomics-guided DNA methylation mortality predictors. EBioMedicine 2024; 107:105279. [PMID: 39154540 PMCID: PMC11378104 DOI: 10.1016/j.ebiom.2024.105279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 07/25/2024] [Accepted: 07/29/2024] [Indexed: 08/20/2024] Open
Abstract
BACKGROUND 1H-NMR metabolomics and DNA methylation in blood are widely known biomarkers predicting age-related physiological decline and mortality yet exert mutually independent mortality and frailty signals. METHODS Leveraging multi-omics data in four Dutch population studies (N = 5238, ∼40% of which male) we investigated whether the mortality signal captured by 1H-NMR metabolomics could guide the construction of DNA methylation-based mortality predictors. FINDINGS We trained DNA methylation-based surrogates for 64 metabolomic analytes and found that analytes marking inflammation, fluid balance, or HDL/VLDL metabolism could be accurately reconstructed using DNA-methylation assays. Interestingly, a previously reported multi-analyte score indicating mortality risk (MetaboHealth) could also be accurately reconstructed. Sixteen of our derived surrogates, including the MetaboHealth surrogate, showed significant associations with mortality, independent of relevant covariates. INTERPRETATION The addition of our metabolic analyte-derived surrogates to the well-established epigenetic clock GrimAge demonstrates that our surrogates potentially represent valuable mortality signal. FUNDING BBMRI-NL, X-omics, VOILA, Medical Delta, NWO, ERC.
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Affiliation(s)
- Daniele Bizzarri
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Leiden Computational Biology Center, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Delft Bioinformatics Lab, TU Delft, Delft, the Netherlands
| | - Marcel J T Reinders
- Leiden Computational Biology Center, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Delft Bioinformatics Lab, TU Delft, Delft, the Netherlands
| | - Lieke Kuiper
- Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands; Center for Nutrition, Prevention and Health Services, National Institute for Public Health and Environment (RIVM), Bilthoven, the Netherlands
| | - Marian Beekman
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Joris Deelen
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Max Planck Institute for the Biology of Ageing, Cologne, Germany; Cologne Excellence Cluster on Cellular Stress Responses in Aging Associated Diseases, University of Cologne, Cologne, Germany
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands; Department of Orthopaedics & Sports, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, the Netherlands; Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - René Pool
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, the Netherlands; Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC, Rotterdam, the Netherlands
| | - Lude Franke
- Department of Genetics, University Medical Center Groningen, Groningen, the Netherlands
| | - Pieternella E Slagboom
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Max Planck Institute for the Biology of Ageing, Cologne, Germany
| | - Erik B van den Akker
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Leiden Computational Biology Center, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Delft Bioinformatics Lab, TU Delft, Delft, the Netherlands.
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9
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Ademowo OS, Wenk MR, Maier AB. Advances in clinical application of lipidomics in healthy ageing and healthy longevity medicine. Ageing Res Rev 2024; 100:102432. [PMID: 39029802 DOI: 10.1016/j.arr.2024.102432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 07/11/2024] [Accepted: 07/16/2024] [Indexed: 07/21/2024]
Abstract
It is imperative to optimise health and healthspan across the lifespan. The accumulation of reactive oxygen species (ROS) has been implicated in the hallmarks of ageing and inhibiting ROS production can potentially delay ageing whilst increasing healthy longevity. Lipids and lipid mediators (derivatives of lipids) are becoming increasingly recognized as central molecule in tissue and cellular function and are susceptible to peroxidation; hence linked with ageing. Lipid classes implicated in the ageing process include sterols, glycerophospholipids, sphingolipids and the oxidation products of polyunsaturated fatty acids but these are not yet translated into the clinic. Further mechanistic studies are required for the understanding of lipid classes in the ageing process. Lipidomics, the system level characterisation of lipid species with respect to metabolism and function, might provide a significant and useful biological age profiling tool through longitudinal studies. Lipid profiles in different ages among healthy individuals could be harnessed as lipid biomarkers of healthy ageing with potential integration for the development of lipid-based ageing clock (lipid clock). The potential of a lipid clock includes the prediction of future morbidity or mortality, which will promote precision and healthy longevity medicine.
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Affiliation(s)
- Opeyemi Stella Ademowo
- Healthy Ageing and Mental Wellbeing Research Centre, Biomedical and Clinical Sciences, University of Derby, UK
| | - Markus R Wenk
- Singapore Lipidomics Incubator (SLING), Life Sciences Institute, National University of Singapore, Singapore; Precision Medicine Translational Research Programme and Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore; College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
| | - Andrea B Maier
- Healthy Longevity Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Centre for Healthy Longevity, @AgeSingapore, National University Health System, Singapore; Department of Human Movement Sciences, @AgeAmsterdam, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Amsterdam, the Netherlands.
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10
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Fu H, Pickering H, Rubbi L, Ross TM, Zhou W, Reed EF, Pellegrini M. The response to influenza vaccination is associated with DNA methylation-driven regulation of T cell innate antiviral pathways. Clin Epigenetics 2024; 16:114. [PMID: 39169387 PMCID: PMC11340180 DOI: 10.1186/s13148-024-01730-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: 04/25/2024] [Accepted: 08/12/2024] [Indexed: 08/23/2024] Open
Abstract
BACKGROUND The effect of vaccination on the epigenome remains poorly characterized. In previous research, we identified an association between seroprotection against influenza and DNA methylation at sites associated with the RIG-1 signaling pathway, which recognizes viral double-stranded RNA and leads to a type I interferon response. However, these studies did not fully account for confounding factors including age, gender, and BMI, along with changes in cell-type composition. RESULTS Here, we studied the influenza vaccine response in a longitudinal cohort vaccinated over two consecutive years (2019-2020 and 2020-2021), using peripheral blood mononuclear cells and a targeted DNA methylation approach. To address the effects of multiple factors on the epigenome, we designed a multivariate multiple regression model that included seroprotection levels as quantified by the hemagglutination-inhibition (HAI) assay test. CONCLUSIONS Our findings indicate that 179 methylation sites can be combined as potential signatures to predict seroprotection. These sites were not only enriched for genes involved in the regulation of the RIG-I signaling pathway, as found previously, but also enriched for other genes associated with innate immunity to viruses and the transcription factor binding sites of BRD4, which is known to impact T cell memory. We propose a model to suggest that the RIG-I pathway and BRD4 could potentially be modulated to improve immunization strategies.
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Affiliation(s)
- Hongxiang Fu
- Department of Molecular Cell and Developmental Biology, University of California Los Angeles, Los Angeles, CA, USA
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Harry Pickering
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Liudmilla Rubbi
- Department of Molecular Cell and Developmental Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Ted M Ross
- Department of Infectious Diseases, University of Georgia, Athens, GA, USA
- Center for Vaccines and Immunology, University of Georgia, Athens, GA, USA
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Elaine F Reed
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Matteo Pellegrini
- Department of Molecular Cell and Developmental Biology, University of California Los Angeles, Los Angeles, CA, USA.
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11
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Wu J, Palasantzas V, Andreu-Sánchez S, Plösch T, Leonard S, Li S, Bonder MJ, Westra HJ, van Meurs J, Ghanbari M, Franke L, Zhernakova A, Fu J, Hoogerland JA, Zhernakova DV. Epigenome-wide association study on the plasma metabolome suggests self-regulation of the glycine and serine pathway through DNA methylation. Clin Epigenetics 2024; 16:104. [PMID: 39138531 PMCID: PMC11323446 DOI: 10.1186/s13148-024-01718-7] [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: 12/14/2023] [Accepted: 07/29/2024] [Indexed: 08/15/2024] Open
Abstract
BACKGROUND The plasma metabolome reflects the physiological state of various biological processes and can serve as a proxy for disease risk. Plasma metabolite variation, influenced by genetic and epigenetic mechanisms, can also affect the cellular microenvironment and blood cell epigenetics. The interplay between the plasma metabolome and the blood cell epigenome remains elusive. In this study, we performed an epigenome-wide association study (EWAS) of 1183 plasma metabolites in 693 participants from the LifeLines-DEEP cohort and investigated the causal relationships in DNA methylation-metabolite associations using bidirectional Mendelian randomization and mediation analysis. RESULTS After rigorously adjusting for potential confounders, including genetics, we identified five robust associations between two plasma metabolites (L-serine and glycine) and three CpG sites located in two independent genomic regions (cg14476101 and cg16246545 in PHGDH and cg02711608 in SLC1A5) at a false discovery rate of less than 0.05. Further analysis revealed a complex bidirectional relationship between plasma glycine/serine levels and DNA methylation. Moreover, we observed a strong mediating role of DNA methylation in the effect of glycine/serine on the expression of their metabolism/transport genes, with the proportion of the mediated effect ranging from 11.8 to 54.3%. This result was also replicated in an independent population-based cohort, the Rotterdam Study. To validate our findings, we conducted in vitro cell studies which confirmed the mediating role of DNA methylation in the regulation of PHGDH gene expression. CONCLUSIONS Our findings reveal a potential feedback mechanism in which glycine and serine regulate gene expression through DNA methylation.
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Affiliation(s)
- Jiafei Wu
- Department of Genetics, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands
| | - Victoria Palasantzas
- Department of Genetics, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands
- Department of Pediatrics, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands
| | - Sergio Andreu-Sánchez
- Department of Genetics, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands
- Department of Pediatrics, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands
| | - Torsten Plösch
- Department of Obstetrics and Gynecology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Perinatal Neurobiology Research Group, Department of Pediatrics, School of Medicine and Health Sciences, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
| | - Sam Leonard
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Shuang Li
- Department of Genetics, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands
| | - Marc Jan Bonder
- Department of Genetics, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands
| | - Harm-Jan Westra
- Department of Genetics, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands
| | - Joyce van Meurs
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Lude Franke
- Department of Genetics, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands
| | - Alexandra Zhernakova
- Department of Genetics, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands
| | - Jingyuan Fu
- Department of Genetics, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands
- Department of Pediatrics, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands
| | - Joanne A Hoogerland
- Department of Genetics, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands.
- Department of Pediatrics, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands.
| | - Daria V Zhernakova
- Department of Genetics, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands.
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12
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Ren Y, Huang P, Zhang L, Tang YF, Luo SL, She Z, Peng H, Chen YQ, Luo JW, Duan WX, Liu LJ, Liu LQ. Dual Regulation Mechanism of Obesity: DNA Methylation and Intestinal Flora. Biomedicines 2024; 12:1633. [PMID: 39200098 PMCID: PMC11351752 DOI: 10.3390/biomedicines12081633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 07/15/2024] [Accepted: 07/18/2024] [Indexed: 09/01/2024] Open
Abstract
Obesity is a multifactorial chronic inflammatory metabolic disorder, with pathogenesis influenced by genetic and non-genetic factors such as environment and diet. Intestinal microbes and their metabolites play significant roles in the occurrence and development of obesity by regulating energy metabolism, inducing chronic inflammation, and impacting intestinal hormone secretion. Epigenetics, which involves the regulation of host gene expression without changing the nucleotide sequence, provides an exact direction for us to understand how the environment, lifestyle factors, and other risk factors contribute to obesity. DNA methylation, as the most common epigenetic modification, is involved in the pathogenesis of various metabolic diseases. The epigenetic modification of the host is induced or regulated by the intestinal microbiota and their metabolites, linking the dynamic interaction between the microbiota and the host genome. In this review, we examined recent advancements in research, focusing on the involvement of intestinal microbiota and DNA methylation in the etiology and progression of obesity, as well as potential interactions between the two factors, providing novel perspectives and avenues for further elucidating the pathogenesis, prevention, and treatment of obesity.
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Affiliation(s)
- Yi Ren
- Department of Pediatrics, The Second Xiangya Hospital of Central South University, Changsha 410011, China; (Y.R.); (P.H.); (L.Z.); (Y.-F.T.); (S.-L.L.); (Z.S.); (H.P.); (Y.-Q.C.); (J.-W.L.); (W.-X.D.); (L.-J.L.)
- Children’s Brain Development and Brain Injury Research Office, The Second Xiangya Hospital of Central South University, Changsha 410011, China
- Department of Pediatrics, Haikou Hospital of the Maternal and Child Health, Haikou 570100, China
- Department of Children’s Healthcare, Hainan Modern Women and Children’s Medical, Haikou 570100, China
| | - Peng Huang
- Department of Pediatrics, The Second Xiangya Hospital of Central South University, Changsha 410011, China; (Y.R.); (P.H.); (L.Z.); (Y.-F.T.); (S.-L.L.); (Z.S.); (H.P.); (Y.-Q.C.); (J.-W.L.); (W.-X.D.); (L.-J.L.)
- Children’s Brain Development and Brain Injury Research Office, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Lu Zhang
- Department of Pediatrics, The Second Xiangya Hospital of Central South University, Changsha 410011, China; (Y.R.); (P.H.); (L.Z.); (Y.-F.T.); (S.-L.L.); (Z.S.); (H.P.); (Y.-Q.C.); (J.-W.L.); (W.-X.D.); (L.-J.L.)
- Children’s Brain Development and Brain Injury Research Office, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Yu-Fen Tang
- Department of Pediatrics, The Second Xiangya Hospital of Central South University, Changsha 410011, China; (Y.R.); (P.H.); (L.Z.); (Y.-F.T.); (S.-L.L.); (Z.S.); (H.P.); (Y.-Q.C.); (J.-W.L.); (W.-X.D.); (L.-J.L.)
- Children’s Brain Development and Brain Injury Research Office, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Sen-Lin Luo
- Department of Pediatrics, The Second Xiangya Hospital of Central South University, Changsha 410011, China; (Y.R.); (P.H.); (L.Z.); (Y.-F.T.); (S.-L.L.); (Z.S.); (H.P.); (Y.-Q.C.); (J.-W.L.); (W.-X.D.); (L.-J.L.)
- Children’s Brain Development and Brain Injury Research Office, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Zhou She
- Department of Pediatrics, The Second Xiangya Hospital of Central South University, Changsha 410011, China; (Y.R.); (P.H.); (L.Z.); (Y.-F.T.); (S.-L.L.); (Z.S.); (H.P.); (Y.-Q.C.); (J.-W.L.); (W.-X.D.); (L.-J.L.)
- Children’s Brain Development and Brain Injury Research Office, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Hong Peng
- Department of Pediatrics, The Second Xiangya Hospital of Central South University, Changsha 410011, China; (Y.R.); (P.H.); (L.Z.); (Y.-F.T.); (S.-L.L.); (Z.S.); (H.P.); (Y.-Q.C.); (J.-W.L.); (W.-X.D.); (L.-J.L.)
- Children’s Brain Development and Brain Injury Research Office, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Yu-Qiong Chen
- Department of Pediatrics, The Second Xiangya Hospital of Central South University, Changsha 410011, China; (Y.R.); (P.H.); (L.Z.); (Y.-F.T.); (S.-L.L.); (Z.S.); (H.P.); (Y.-Q.C.); (J.-W.L.); (W.-X.D.); (L.-J.L.)
- Children’s Brain Development and Brain Injury Research Office, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Jin-Wen Luo
- Department of Pediatrics, The Second Xiangya Hospital of Central South University, Changsha 410011, China; (Y.R.); (P.H.); (L.Z.); (Y.-F.T.); (S.-L.L.); (Z.S.); (H.P.); (Y.-Q.C.); (J.-W.L.); (W.-X.D.); (L.-J.L.)
- Children’s Brain Development and Brain Injury Research Office, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Wang-Xin Duan
- Department of Pediatrics, The Second Xiangya Hospital of Central South University, Changsha 410011, China; (Y.R.); (P.H.); (L.Z.); (Y.-F.T.); (S.-L.L.); (Z.S.); (H.P.); (Y.-Q.C.); (J.-W.L.); (W.-X.D.); (L.-J.L.)
- Children’s Brain Development and Brain Injury Research Office, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Ling-Juan Liu
- Department of Pediatrics, The Second Xiangya Hospital of Central South University, Changsha 410011, China; (Y.R.); (P.H.); (L.Z.); (Y.-F.T.); (S.-L.L.); (Z.S.); (H.P.); (Y.-Q.C.); (J.-W.L.); (W.-X.D.); (L.-J.L.)
- Children’s Brain Development and Brain Injury Research Office, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Li-Qun Liu
- Department of Pediatrics, The Second Xiangya Hospital of Central South University, Changsha 410011, China; (Y.R.); (P.H.); (L.Z.); (Y.-F.T.); (S.-L.L.); (Z.S.); (H.P.); (Y.-Q.C.); (J.-W.L.); (W.-X.D.); (L.-J.L.)
- Children’s Brain Development and Brain Injury Research Office, The Second Xiangya Hospital of Central South University, Changsha 410011, China
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13
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da Silva Rodrigues Marçal E, Borges JB, Bastos GM, Crespo Hirata TD, de Oliveira VF, Gonçalves RM, Faludi AA, Dias França JI, de Oliveira Silva DV, Malaquias VB, Luchessi AD, Silbiger VN, Nakazone MA, Carmo TS, Silva Souza DR, Sampaio MF, Crespo Hirata RD, Hirata MH. Methylation status of LDLR, PCSK9 and LDLRAP1 is associated with cardiovascular events in familial hypercholesterolemia. Epigenomics 2024; 16:809-820. [PMID: 38884343 PMCID: PMC11370914 DOI: 10.1080/17501911.2024.2351792] [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: 02/26/2024] [Accepted: 04/27/2024] [Indexed: 06/18/2024] Open
Abstract
Aim: Methylation of LDLR, PCSK9 and LDLRAP1 CpG sites was assessed in patients with familial hypercholesterolemia (FH). Methods: DNA methylation of was analyzed by pyrosequencing in 131 FH patients and 23 normolipidemic (NL) subjects.Results: LDLR, PCSK9 and LDLRP1 methylation was similar between FH patients positive (MD) and negative (non-MD) for pathogenic variants in FH-related genes. LDLR and PCSK9 methylation was higher in MD and non-MD groups than NL subjects (p < 0.05). LDLR, PCSK9 and LDLRAP1 methylation profiles were associated with clinical manifestations and cardiovascular events in FH patients (p < 0.05).Conclusion: Differential methylation of LDLR, PCSK9 and LDLRAP1 is associated with hypercholesterolemia and cardiovascular events. This methylation profile maybe useful as a biomarker and contribute to the management of FH.
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Affiliation(s)
- Elisangela da Silva Rodrigues Marçal
- Department of Clinical & Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo, Sao Paulo, 05508-000, Brazil
- Laboratory of Molecular Research in Cardiology, Institute of Cardiology Dante Pazzanese, Sao Paulo, 04012-909, Brazil
| | - Jéssica Bassani Borges
- Department of Research, Hospital Beneficiencia Portuguesa de Sao Paulo, Sao Paulo, 01323-001, Brazil
| | - Gisele Medeiros Bastos
- Department of Research, Hospital Beneficiencia Portuguesa de Sao Paulo, Sao Paulo, 01323-001, Brazil
| | - Thiago Dominguez Crespo Hirata
- Department of Clinical & Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo, Sao Paulo, 05508-000, Brazil
| | - Victor Fernandes de Oliveira
- Department of Clinical & Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo, Sao Paulo, 05508-000, Brazil
| | | | - Andre Arpad Faludi
- Medical Clinic Division, Institute of Cardiology Dante Pazzanese, Sao Paulo, 04012-909, Brazil
| | - João Italo Dias França
- Center for Clinical Trials & Pharmacovigilance, Butantan Institute, Sao Paulo, 05585-000, Brazil
| | - Daiana Vitor de Oliveira Silva
- Department of Clinical & Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo, Sao Paulo, 05508-000, Brazil
| | - Vanessa Barbosa Malaquias
- Department of Clinical & Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo, Sao Paulo, 05508-000, Brazil
| | - Andre Ducati Luchessi
- Department of Clinical & Toxicological Analyses, School of Pharmaceutical Sciences, Federal University of Rio Grande do Norte, Natal, 59012-570, Brazil
- Graduate Program in Pharmaceutical Sciences, Federal University of Rio Grande do Norte, Natal, 59012-570, Brazil
| | - Vivian Nogueira Silbiger
- Department of Clinical & Toxicological Analyses, School of Pharmaceutical Sciences, Federal University of Rio Grande do Norte, Natal, 59012-570, Brazil
- Graduate Program in Pharmaceutical Sciences, Federal University of Rio Grande do Norte, Natal, 59012-570, Brazil
| | - Marcelo Arruda Nakazone
- Department of Cardiology & Cardiovascular Surgery, Sao Jose do Rio Preto Medical School, Sao Jose do Rio Preto, 15090-000, Brazil
| | - Tayanne Silva Carmo
- Department of Biochemistry & Molecular Biology, Sao Jose do Rio Preto Medical School, Sao Jose do Rio Preto, 15090-000, Brazil
| | - Dorotéia Rossi Silva Souza
- Department of Biochemistry & Molecular Biology, Sao Jose do Rio Preto Medical School, Sao Jose do Rio Preto, 15090-000, Brazil
| | - Marcelo Ferraz Sampaio
- Department of Cardiology, Hospital Beneficencia Portuguesa de Sao Paulo, Sao Paulo, 01323-001, Brazil
| | - Rosario Dominguez Crespo Hirata
- Department of Clinical & Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo, Sao Paulo, 05508-000, Brazil
| | - Mario Hiroyuki Hirata
- Department of Clinical & Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo, Sao Paulo, 05508-000, Brazil
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14
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Chen C, Han P, Qing Y. Metabolic heterogeneity in tumor microenvironment - A novel landmark for immunotherapy. Autoimmun Rev 2024; 23:103579. [PMID: 39004158 DOI: 10.1016/j.autrev.2024.103579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 04/10/2024] [Accepted: 07/09/2024] [Indexed: 07/16/2024]
Abstract
The surrounding non-cancer cells and tumor cells that make up the tumor microenvironment (TME) have various metabolic rhythms. TME metabolic heterogeneity is influenced by the intricate network of metabolic control within and between cells. DNA, protein, transport, and microbial levels are important regulators of TME metabolic homeostasis. The effectiveness of immunotherapy is also closely correlated with alterations in TME metabolism. The response of a tumor patient to immunotherapy is influenced by a variety of variables, including intracellular metabolic reprogramming, metabolic interaction between cells, ecological changes within and between tumors, and general dietary preferences. Although immunotherapy and targeted therapy have made great strides, their use in the accurate identification and treatment of tumors still has several limitations. The function of TME metabolic heterogeneity in tumor immunotherapy is summarized in this article. It focuses on how metabolic heterogeneity develops and is regulated as a tumor progresses, the precise molecular mechanisms and potential clinical significance of imbalances in intracellular metabolic homeostasis and intercellular metabolic coupling and interaction, as well as the benefits and drawbacks of targeted metabolism used in conjunction with immunotherapy. This offers insightful knowledge and important implications for individualized tumor patient diagnosis and treatment plans in the future.
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Affiliation(s)
- Chen Chen
- The First Affiliated Hospital of Ningbo University, Ningbo 315211, Zhejiang, China
| | - Peng Han
- Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang, China.
| | - Yanping Qing
- The First Affiliated Hospital of Ningbo University, Ningbo 315211, Zhejiang, China.
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15
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Fu H, Pickering H, Rubbi L, Ross TM, Zhou W, Reed EF, Pellegrini M. The response to influenza vaccination is associated with DNA methylation-driven regulation of T cell innate antiviral pathways. RESEARCH SQUARE 2024:rs.3.rs-4324518. [PMID: 38826189 PMCID: PMC11142309 DOI: 10.21203/rs.3.rs-4324518/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Background The effect of vaccination on the epigenome remains poorly characterized. In previous research, we identified an association between seroprotection against influenza and DNA methylation at sites associated with the RIG-1 signaling pathway, which recognizes viral double-stranded RNA and leads to a type I interferon response. However, these studies did not fully account for confounding factors including age, gender, and BMI, along with changes in cell type composition. Results Here, we studied the influenza vaccine response in a longitudinal cohort vaccinated over two consecutive years (2019-2020 and 2020-2021), using peripheral blood mononuclear cells and a targeted DNA methylation approach. To address the effects of multiple factors on the epigenome, we designed a multivariate multiple regression model that included seroprotection levels as quantified by the hemagglutination-inhibition (HAI) assay test. Conclusions Our findings indicate that 179 methylation sites can be combined as potential signatures to predict seroprotection. These sites were not only enriched for genes involved in the regulation of the RIG-I signaling pathway, as found previously, but also enriched for other genes associated with innate immunity to viruses and the transcription factor binding sites of BRD4, which is known to impact T cell memory. We propose a model to suggest that the RIG-I pathway and BRD4 could potentially be modulated to improve immunization strategies.
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16
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Zhang K, Chen G, He J, Chen Z, Pan M, Tong J, Liu F, Xiang H. DNA methylation mediates the effects of PM 2.5 and O 3 on ceramide metabolism: A novel mechanistic link between air pollution and insulin resistance. JOURNAL OF HAZARDOUS MATERIALS 2024; 469:133864. [PMID: 38457969 DOI: 10.1016/j.jhazmat.2024.133864] [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: 11/30/2023] [Revised: 02/20/2024] [Accepted: 02/21/2024] [Indexed: 03/10/2024]
Abstract
Insulin resistance (IR), linked to air pollution, is an initial stage of early-onset Type 2 diabetes mellitus (T2DM). While ceramide metabolism plays an important role in IR pathogenesis, the effects of air pollution on this process and its mechanisms remain unclear. We recruited young adults aged 18-30 years to a panel study in Wuhan, China. Using personal portable devices and stationary monitoring stations, we tracked particulate matter with aerodynamic diameters≤ 2.5 µm (PM2.5) and Ozone (O3) levels. Liquid chromatography/mass spectrometry (LC-MS) based metabolomics quantified ceramide metabolism, and Illumina Infinium Human Methylation 850 kBeadChip assay measured deoxyribonucleic acid (DNA) methylation. Linear mixed-effects models assessed relationships of air pollution with i) IR indexes, ii) ceramide metabolism, and iii) DNA methylation. Mediation analysis was subsequently performed to evaluate the potential mediating effect of DNA methylation in the association between air pollution and ceramide metabolism. PM2.5 and O3 were associated with elevated IR. Specifically, each 10 μg/m3 increase in PM2.5 and O3 at lag0-12 h significantly increased triglyceride‑glucose index (TyG index) and TyG-BMI (TyG - Body mass index) by 0.88%, 0.89% and 0.26%, 0.26%, respectively. Furthermore, levels of eight ceramides were altered by air pollution exposure, and nine methylated CpG sites in inflammation genes mediated the effects of air pollution on ceramide metabolism. Our findings imply the existence of a novel mechanism connecting air pollution to IR.
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Affiliation(s)
- Ke Zhang
- Department of Global Health, School of Public Health, Wuhan University, Wuhan, China; Global Health Institute, School of Public Health, Wuhan University, Wuhan, China
| | - Gongbo Chen
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Jie He
- Department of Environmental Health Sciences, School of Public Health, University of Michigan-Ann Arbor, Ann Arbor, MI, USA
| | - Zhongyang Chen
- Department of Global Health, School of Public Health, Wuhan University, Wuhan, China; Global Health Institute, School of Public Health, Wuhan University, Wuhan, China
| | - Mengnan Pan
- Department of Global Health, School of Public Health, Wuhan University, Wuhan, China; Global Health Institute, School of Public Health, Wuhan University, Wuhan, China
| | - Jiahui Tong
- Department of Global Health, School of Public Health, Wuhan University, Wuhan, China; Global Health Institute, School of Public Health, Wuhan University, Wuhan, China
| | - Feifei Liu
- Department of Global Health, School of Public Health, Wuhan University, Wuhan, China; Global Health Institute, School of Public Health, Wuhan University, Wuhan, China.
| | - Hao Xiang
- Department of Global Health, School of Public Health, Wuhan University, Wuhan, China; Global Health Institute, School of Public Health, Wuhan University, Wuhan, China.
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17
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Lee HS, Kim B, Park T. Genome- and epigenome-wide association studies identify susceptibility of CpG sites and regions for metabolic syndrome in a Korean population. Clin Epigenetics 2024; 16:60. [PMID: 38685121 PMCID: PMC11059751 DOI: 10.1186/s13148-024-01671-5] [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: 11/14/2023] [Accepted: 04/13/2024] [Indexed: 05/02/2024] Open
Abstract
BACKGROUND While multiple studies have investigated the relationship between metabolic syndrome (MetS) and its related traits (fasting glucose, triglyceride, HDL cholesterol, blood pressure, waist circumference) and DNA methylation, our understanding of the epigenetic mechanisms in MetS remains limited. Therefore, we performed an epigenome-wide meta-analysis of blood DNA methylation to identify differentially methylated probes (DMPs) and differentially methylated regions (DMRs) associated with MetS and its components using two independent cohorts comprising a total of 2,334 participants. We also investigated the specific genetic effects on DNA methylation, identified methylation quantitative trait loci (meQTLs) through genome-wide association studies and further utilized Mendelian randomization (MR) to assess how these meQTLs subsequently influence MetS status. RESULTS We identified 40 DMPs and 27 DMRs that are significantly associated with MetS. In addition, we identified many novel DMPs and DMRs underlying inflammatory and steroid hormonal processes. The most significant associations were observed in 3 DMPs (cg19693031, cg26974062, cg02988288) and a DMR (chr1:145440444-145441553) at the TXNIP, which are involved in lipid metabolism. These CpG sites were identified as coregulators of DNA methylation in MetS, TG and FAG levels. We identified a total of 144 cis-meQTLs, out of which only 13 were found to be associated with DMPs for MetS. Among these, we confirmed the identified causal mediators of genetic effects at CpG sites cg01881899 at ABCG1 and cg00021659 at the TANK genes for MetS. CONCLUSIONS This study observed whether specific CpGs and methylated regions act independently or are influenced by genetic effects for MetS and its components in the Korean population. These associations between the identified DNA methylation and MetS, along with its individual components, may serve as promising targets for the development of preventive interventions for MetS.
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Affiliation(s)
- Ho-Sun Lee
- Forensic Toxicology Division, Daegu Institute, National Forensic Service, Chilgok-gun, 39872, Gyeongsangbuk-do, Korea.
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Korea.
| | - Boram Kim
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Korea
| | - Taesung Park
- Forensic Toxicology Division, Daegu Institute, National Forensic Service, Chilgok-gun, 39872, Gyeongsangbuk-do, Korea
- Department of Statistics, Seoul National University, Seoul, 08826, Korea
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18
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Hubers N, Hagenbeek FA, Pool R, Déjean S, Harms AC, Roetman PJ, van Beijsterveldt CEM, Fanos V, Ehli EA, Vermeiren RRJM, Bartels M, Hottenga JJ, Hankemeier T, van Dongen J, Boomsma DI. Integrative multi-omics analysis of genomic, epigenomic, and metabolomics data leads to new insights for Attention-Deficit/Hyperactivity Disorder. Am J Med Genet B Neuropsychiatr Genet 2024; 195:e32955. [PMID: 37534875 DOI: 10.1002/ajmg.b.32955] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 06/13/2023] [Accepted: 07/11/2023] [Indexed: 08/04/2023]
Abstract
The evolving field of multi-omics combines data and provides methods for simultaneous analysis across several omics levels. Here, we integrated genomics (transmitted and non-transmitted polygenic scores [PGSs]), epigenomics, and metabolomics data in a multi-omics framework to identify biomarkers for Attention-Deficit/Hyperactivity Disorder (ADHD) and investigated the connections among the three omics levels. We first trained single- and next multi-omics models to differentiate between cases and controls in 596 twins (cases = 14.8%) from the Netherlands Twin Register (NTR) demonstrating reasonable in-sample prediction through cross-validation. The multi-omics model selected 30 PGSs, 143 CpGs, and 90 metabolites. We confirmed previous associations of ADHD with glucocorticoid exposure and the transmembrane protein family TMEM, show that the DNA methylation of the MAD1L1 gene associated with ADHD has a relation with parental smoking behavior, and present novel findings including associations between indirect genetic effects and CpGs of the STAP2 gene. However, out-of-sample prediction in NTR participants (N = 258, cases = 14.3%) and in a clinical sample (N = 145, cases = 51%) did not perform well (range misclassification was [0.40, 0.57]). The results highlighted connections between omics levels, with the strongest connections between non-transmitted PGSs, CpGs, and amino acid levels and show that multi-omics designs considering interrelated omics levels can help unravel the complex biology underlying ADHD.
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Affiliation(s)
- Nikki Hubers
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Fiona A Hagenbeek
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - René Pool
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Sébastien Déjean
- Toulouse Mathematics Institute, UMR 5219, University of Toulouse, CNRS, Toulouse, France
| | - Amy C Harms
- Division of Analytical Biosciences, Leiden Academic Center for Drug Research, Leiden University, Leiden, the Netherlands
- The Netherlands Metabolomics Centre, Leiden, The Netherlands
| | - Peter J Roetman
- LUMC-Curium, Department of Child and Adolescent Psychiatry, Leiden University Medical Center, Leiden, the Netherlands
| | | | - Vassilios Fanos
- Department of Surgical Sciences, University of Cagliari and Neonatal Intensive Care Unit, Cagliari, Italy
| | - Erik A Ehli
- Avera Institute for Human Genetics, Sioux Falls, South Dakota, USA
| | - Robert R J M Vermeiren
- LUMC-Curium, Department of Child and Adolescent Psychiatry, Leiden University Medical Center, Leiden, the Netherlands
- Youz, Parnassia Group, the Netherlands
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Thomas Hankemeier
- Division of Analytical Biosciences, Leiden Academic Center for Drug Research, Leiden University, Leiden, the Netherlands
- The Netherlands Metabolomics Centre, Leiden, The Netherlands
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
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19
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Fu H, Pickering H, Rubbi L, Ross TM, Reed EF, Pellegrini M. Longitudinal analysis of influenza vaccination implicates regulation of RIG-I signaling by DNA methylation. Sci Rep 2024; 14:1455. [PMID: 38228690 PMCID: PMC10791625 DOI: 10.1038/s41598-024-51665-9] [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: 09/26/2023] [Accepted: 01/08/2024] [Indexed: 01/18/2024] Open
Abstract
Influenza virus infection alters the promoter DNA methylation of key immune response-related genes, including type-1 interferons and proinflammatory cytokines. However, less is known about the effect of the influenza vaccine on the epigenome. We utilized a targeted DNA methylation approach to study the longitudinal effects (day 0 pre-vaccination and day 28 post-vaccination) on influenza vaccination responses in peripheral blood mononuclear cells. We found that baseline, pre-vaccination methylation profiles are associated with pre-existing, protective serological immunity. Additionally, we identified 481 sites that were differentially methylated between baseline and day 28 post-vaccination. These were enriched for genes involved in the regulation of the RIG-I signaling pathway, an important regulator of viral responses. Our results suggest that DNA methylation changes to components of the RIG-I pathway are associated with vaccine effectiveness. Therefore, immunization strategies that target this pathway may improve serological responses to influenza vaccination.
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Affiliation(s)
- Hongxiang Fu
- Department of Molecular Cell and Developmental Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Harry Pickering
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Liudmilla Rubbi
- Department of Molecular Cell and Developmental Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Ted M Ross
- Department of Infectious Diseases, University of Georgia, Athens, GA, USA
- Center for Vaccines and Immunology, University of Georgia, Athens, GA, USA
| | - Elaine F Reed
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Matteo Pellegrini
- Department of Molecular Cell and Developmental Biology, University of California Los Angeles, Los Angeles, CA, USA.
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20
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Olichwier A, Sowka A, Balatskyi VV, Gan AM, Dziewulska A, Dobrzyn P. SCD1-related epigenetic modifications affect hormone-sensitive lipase (Lipe) gene expression in cardiomyocytes. BIOCHIMICA ET BIOPHYSICA ACTA. MOLECULAR CELL RESEARCH 2024; 1871:119608. [PMID: 37852324 DOI: 10.1016/j.bbamcr.2023.119608] [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: 05/31/2023] [Revised: 10/10/2023] [Accepted: 10/11/2023] [Indexed: 10/20/2023]
Abstract
Stearoyl-CoA desaturase 1 (SCD1) is an enzyme that is involved in the regulation of lipolysis in the heart. SCD1 also affects epigenetic mechanisms, such as DNA and histone modifications, in various tissues. Both epigenetic modifications and changes in lipid metabolism are involved in the heart's response to hypoxia. The present study tested the hypothesis that SCD1 and epigenetic modifications interact to control lipolysis in cardiomyocytes under normoxic and hypoxic conditions. We found that the inhibition of SCD1 activity and loss of SCD1 expression reduced global DNA methylation levels, DNA methyltransferase (DNMT) activity, and DNMT1 expression in HL-1 cardiomyocytes and the mouse heart. We also found that the inhibition of adipose triglyceride lipase is involved in the control of global DNA methylation levels in cardiomyocytes in an SCD1-independent manner. Additionally, SCD1 inhibition reduced expression of the hormone-sensitive lipase (Lipe) gene through an increase in methylation of the Lipe gene promoter. Under hypoxic conditions, SCD1 inhibition abolished hypoxia-inducible transcription factor 1α, likely through decreases in histone deacetylase, protein kinase A, and abhydrolase domain containing 5 protein levels, leading to the attenuation of DNA hypomethylation by DNMT1. Hypoxia led to demethylation of the Lipe promoter in cardiomyocytes with SCD1 inhibition, which increased Lipe expression. These results indicate that SCD1 is involved in the control of epigenetic mechanisms in the heart and may affect Lipe expression through changes in methylation in its promoter region. Therefore, SCD1 may be considered a key player in the epigenetic response to normoxia and hypoxia in cardiomyocytes.
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Affiliation(s)
- Adam Olichwier
- Laboratory of Molecular Medical Biochemistry, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Adrian Sowka
- Laboratory of Molecular Medical Biochemistry, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Volodymyr V Balatskyi
- Laboratory of Molecular Medical Biochemistry, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Ana-Maria Gan
- Laboratory of Molecular Medical Biochemistry, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Anna Dziewulska
- Laboratory of Cell Signaling and Metabolic Disorders, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Pawel Dobrzyn
- Laboratory of Molecular Medical Biochemistry, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland.
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21
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Bey GS, Pike JR, Zannas AS, Xiao Q, Yu B, Shah AM, Palta P. The Relationship of Neighborhood Disadvantage, Biological Aging, and Psychosocial Risk and Resilience Factors in Heart Failure Incidence Among Black Persons: A Moderated Mediation Analysis. J Gerontol B Psychol Sci Soc Sci 2024; 79:gbad121. [PMID: 37591789 PMCID: PMC10745279 DOI: 10.1093/geronb/gbad121] [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: 04/07/2023] [Indexed: 08/19/2023] Open
Abstract
OBJECTIVES Deprived living environments contribute to greater heart failure (HF) risk among non-Hispanic Black persons, who disproportionately occupy disadvantaged neighborhoods. The mechanisms for these effects are not fully explicated, partially attributable to an insufficient understanding of the individual factors that contribute additional risk or resilience to the impact of neighborhood disadvantage on health. The objective of this study was, therefore, to clarify the complex pathways over which such exposures act to facilitate more targeted, effective interventions. Given the evidence for a mediating role of biological age and a moderating role of individual psychosocial characteristics in the neighborhood disadvantage-HF link, we tested a moderated mediation mechanism. METHODS Using multilevel causal moderated mediation models, we prospectively examined whether the association of neighborhood disadvantage with incident HF mediated through accelerated biological aging, captured by the GrimAge epigenetic clock, is moderated by hypothesized psychosocial risk (negative affect) and resilience (optimism) factors. RESULTS Among a sample of 1,448 Black participants in the shared Jackson Heart Study-Atherosclerosis Risk in Communities cohort (mean age 64.3 years), 334 adjudicated incident hospitalized HF events occurred over a median follow-up of 18 years. In models adjusted for age and sex, the indirect (GrimAge-mediated) effect of neighborhood disadvantage was moderated by psychosocial risk such that for every standard deviation increase in negative affect the hazards of HF was 1.18 (95% confidence interval = 1.05, 1.36). No moderated mediation effect was detected for optimism. DISCUSSION Findings support the necessity for multilevel interventions simultaneously addressing neighborhood and individual psychosocial risk in the reduction of HF among Black persons.
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Affiliation(s)
- Ganga S Bey
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - James R Pike
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA
| | - Anthony S Zannas
- Department of Psychiatry and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Qian Xiao
- University of Texas Health Sciences Center at Houston, Houston, Texas, USA
| | - Bing Yu
- School of Public Health, University of Texas Health Sciences Center at Houston, Houston, Texas, USA
| | - Amil M Shah
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Priya Palta
- Department of Neurology, University of North Carolina at Chapel Hill School of MedicineChapel Hill, North Carolina, USA
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22
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Bey G, Pike J, Palta P, Zannas A, Xiao Q, Love SA, Heiss G. Biological Age Mediates the Effects of Perceived Neighborhood Problems on Heart Failure Risk Among Black Persons. J Racial Ethn Health Disparities 2023; 10:3018-3030. [PMID: 36469285 PMCID: PMC10322228 DOI: 10.1007/s40615-022-01476-3] [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: 10/05/2022] [Revised: 11/18/2022] [Accepted: 11/21/2022] [Indexed: 12/09/2022]
Abstract
OBJECTIVE We assessed whether biological age, measured by the epigenetic clock GrimAge, mediates the association of objective and subjective neighborhood disadvantage with incident HF among Black persons. METHODS Participants were 1448 self-reported Black adults (mean age (standard deviation, SD) = 64.3 (5.5)) dually enrolled in two community-based cohorts in Jackson, Mississippi, the ARIC and JHS cohorts, who were free of HF as of January 1, 2000. Incident HF events leading to hospitalization through December 31, 2017, were classified using ICD-9 discharge codes of HF. Multilevel age- and sex-adjusted Cox causal mediation models were used to examine whether biological age (at the person and neighborhood level) mediated the effects of objective (the National Area Deprivation Index, ADI) and subjective (perceived neighborhood problems) neighborhood disadvantage on incident HF. RESULTS A total of 334 incident hospitalized HF events occurred over a median follow-up of 18.0 years. The total effect of the ADI and perceived neighborhood problems (SD units) on HF was hazard ration (HR) = 1.26 and 95% confidence interval (CI) 0.98-1.56 and HR = 1.26 and 95% CI 1.10-1.41, respectively. GrimAge mediated a majority of the effect of perceived neighborhood problems on HF (person-level indirect effect HR = 1.07; 95% CI 1.02-1.12 and neighborhood-level indirect effect HR = 1.18; 95% CI 1.03-1.34), with the combined indirect effect explaining 94.8% of the relationship. The combined indirect effect of ADI on incident HF was comparable but not statistically significant. CONCLUSIONS Subjective neighborhood disadvantage may confer an increased risk of HF among Black populations.
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Affiliation(s)
- Ganga Bey
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - James Pike
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Priya Palta
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Anthony Zannas
- Departments of Psychiatry and Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Qian Xiao
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Sciences Center at Houston, Houston, TX, USA
| | - Shelly-Ann Love
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Gerardo Heiss
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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23
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Maciejewski E, Horvath S, Ernst J. Cross-species and tissue imputation of species-level DNA methylation samples across mammalian species. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.26.568769. [PMID: 38076978 PMCID: PMC10705269 DOI: 10.1101/2023.11.26.568769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/24/2023]
Abstract
DNA methylation data offers valuable insights into various aspects of mammalian biology. The recent introduction and large-scale application of the mammalian methylation array has significantly expanded the availability of such data across conserved sites in many mammalian species. In our study, we consider 13,245 samples profiled on this array encompassing 348 species and 59 tissues from 746 species-tissue combinations. While having some coverage of many different species and tissue types, this data captures only 3.6% of potential species-tissue combinations. To address this gap, we developed CMImpute (Cross-species Methylation Imputation), a method based on a Conditional Variational Autoencoder, to impute DNA methylation for non-profiled species-tissue combinations. In cross-validation, we demonstrate that CMImpute achieves a strong correlation with actual observed values, surpassing several baseline methods. Using CMImpute we imputed methylation data for 19,786 new species-tissue combinations. We believe that both CMImpute and our imputed data resource will be useful for DNA methylation analyses across a wide range of mammalian species.
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Affiliation(s)
- Emily Maciejewski
- Computer Science Department, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Steve Horvath
- Dept. of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095 USA
- Dept. of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA 90095, US
- Altos Labs, Cambridge, UK, WA14 2DT
| | - Jason Ernst
- Computer Science Department, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research at University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
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24
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Costeira R, Evangelista L, Wilson R, Yan X, Hellbach F, Sinke L, Christiansen C, Villicaña S, Masachs OM, Tsai PC, Mangino M, Menni C, Berry SE, Beekman M, van Heemst D, Slagboom PE, Heijmans BT, Suhre K, Kastenmüller G, Gieger C, Peters A, Small KS, Linseisen J, Waldenberger M, Bell JT. Metabolomic biomarkers of habitual B vitamin intakes unveil novel differentially methylated positions in the human epigenome. Clin Epigenetics 2023; 15:166. [PMID: 37858220 PMCID: PMC10588110 DOI: 10.1186/s13148-023-01578-7] [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: 07/03/2023] [Accepted: 10/04/2023] [Indexed: 10/21/2023] Open
Abstract
BACKGROUND B vitamins such as folate (B9), B6, and B12 are key in one carbon metabolism, which generates methyl donors for DNA methylation. Several studies have linked differential methylation to self-reported intakes of folate and B12, but these estimates can be imprecise, while metabolomic biomarkers can offer an objective assessment of dietary intakes. We explored blood metabolomic biomarkers of folate and vitamins B6 and B12, to carry out epigenome-wide analyses across up to three European cohorts. Associations between self-reported habitual daily B vitamin intakes and 756 metabolites (Metabolon Inc.) were assessed in serum samples from 1064 UK participants from the TwinsUK cohort. The identified B vitamin metabolomic biomarkers were then used in epigenome-wide association tests with fasting blood DNA methylation levels at 430,768 sites from the Infinium HumanMethylation450 BeadChip in blood samples from 2182 European participants from the TwinsUK and KORA cohorts. Candidate signals were explored for metabolite associations with gene expression levels in a subset of the TwinsUK sample (n = 297). Metabolomic biomarker epigenetic associations were also compared with epigenetic associations of self-reported habitual B vitamin intakes in samples from 2294 European participants. RESULTS Eighteen metabolites were associated with B vitamin intakes after correction for multiple testing (Bonferroni-adj. p < 0.05), of which 7 metabolites were available in both cohorts and tested for epigenome-wide association. Three metabolites - pipecolate (metabolomic biomarker of B6 and folate intakes), pyridoxate (marker of B6 and folate) and docosahexaenoate (DHA, marker of B6) - were associated with 10, 3 and 1 differentially methylated positions (DMPs), respectively. The strongest association was observed between DHA and DMP cg03440556 in the SCD gene (effect = 0.093 ± 0.016, p = 4.07E-09). Pyridoxate, a catabolic product of vitamin B6, was inversely associated with CpG methylation near the SLC1A5 gene promoter region (cg02711608 and cg22304262) and with SLC7A11 (cg06690548), but not with corresponding changes in gene expression levels. The self-reported intake of folate and vitamin B6 had consistent but non-significant associations with the epigenetic signals. CONCLUSION Metabolomic biomarkers are a valuable approach to investigate the effects of dietary B vitamin intake on the human epigenome.
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Affiliation(s)
- Ricardo Costeira
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK.
| | - Laila Evangelista
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
| | - Rory Wilson
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Xinyu Yan
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
| | - Fabian Hellbach
- Epidemiology, Medical Faculty, University Augsburg, University Hospital Augsburg, 86156, Augsburg, Germany
| | - Lucy Sinke
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2333 ZC, Leiden, The Netherlands
| | - Colette Christiansen
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
| | - Sergio Villicaña
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
| | - Olatz M Masachs
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
| | - Pei-Chien Tsai
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
- Department of Biomedical Sciences, Chang Gung University, Taoyuan City, Taiwan
- Division of Pediatric Infectious Diseases, Department of Pediatrics, Chang Gung Memorial Hospital, Taoyuan City, Taiwan
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
| | - Cristina Menni
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
| | - Sarah E Berry
- Department of Nutritional Sciences, King's College London, London, SE1 9NH, UK
| | - Marian Beekman
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2333 ZC, Leiden, The Netherlands
| | - Diana van Heemst
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, 2300RC, Leiden, The Netherlands
| | - P Eline Slagboom
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2333 ZC, Leiden, The Netherlands
| | - Bastiaan T Heijmans
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2333 ZC, Leiden, The Netherlands
| | - Karsten Suhre
- Department of Biophysics and Physiology, Weill Cornell Medicine-Qatar, Doha, Qatar
| | - Gabi Kastenmüller
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
- German Research Center for Cardiovascular Disease (DZHK), Partner Site Munich Heart Alliance, 80802, Munich, Germany
| | - Annette Peters
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
- German Research Center for Cardiovascular Disease (DZHK), Partner Site Munich Heart Alliance, 80802, Munich, Germany
- Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Ludwig-Maximilians-Universität München, 81377, Munich, Germany
| | - Kerrin S Small
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK
| | - Jakob Linseisen
- Epidemiology, Medical Faculty, University Augsburg, University Hospital Augsburg, 86156, Augsburg, Germany
- Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Ludwig-Maximilians-Universität München, 81377, Munich, Germany
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
- German Research Center for Cardiovascular Disease (DZHK), Partner Site Munich Heart Alliance, 80802, Munich, Germany
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, SE1 7EH, UK.
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Sharma R, Diwan B. Lipids and the hallmarks of ageing: From pathology to interventions. Mech Ageing Dev 2023; 215:111858. [PMID: 37652278 DOI: 10.1016/j.mad.2023.111858] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 08/21/2023] [Accepted: 08/28/2023] [Indexed: 09/02/2023]
Abstract
Lipids are critical structural and functional architects of cellular homeostasis. Change in systemic lipid profile is a clinical indicator of underlying metabolic pathologies, and emerging evidence is now defining novel roles of lipids in modulating organismal ageing. Characteristic alterations in lipid metabolism correlate with age, and impaired systemic lipid profile can also accelerate the development of ageing phenotype. The present work provides a comprehensive review of the extent of lipids as regulators of the modern hallmarks of ageing viz., cellular senescence, chronic inflammation, gut dysbiosis, telomere attrition, genome instability, proteostasis and autophagy, epigenetic alterations, and stem cells dysfunctions. Current evidence on the modulation of each of these hallmarks has been discussed with emphasis on inherent age-dependent deficiencies in lipid metabolism as well as exogenous lipid changes. There appears to be sufficient evidence to consider impaired lipid metabolism as key driver of the ageing process although much of knowledge is yet fragmented. Considering dietary lipids, the type and quantity of lipids in the diet is a significant, but often overlooked determinant that governs the effects of lipids on ageing. Further research using integrative approaches amidst the known aging hallmarks is highly desirable for understanding the therapeutics of lipids associated with ageing.
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Affiliation(s)
- Rohit Sharma
- Nutrigerontology Laboratory, Faculty of Applied Sciences & Biotechnology, Shoolini University, Solan 173229, India.
| | - Bhawna Diwan
- Nutrigerontology Laboratory, Faculty of Applied Sciences & Biotechnology, Shoolini University, Solan 173229, India
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26
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Brown BC, Wang C, Kasela S, Aguet F, Nachun DC, Taylor KD, Tracy RP, Durda P, Liu Y, Johnson WC, Van Den Berg D, Gupta N, Gabriel S, Smith JD, Gerzsten R, Clish C, Wong Q, Papanicolau G, Blackwell TW, Rotter JI, Rich SS, Barr RG, Ardlie KG, Knowles DA, Lappalainen T. Multiset correlation and factor analysis enables exploration of multi-omics data. CELL GENOMICS 2023; 3:100359. [PMID: 37601969 PMCID: PMC10435377 DOI: 10.1016/j.xgen.2023.100359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 04/26/2023] [Accepted: 06/14/2023] [Indexed: 08/22/2023]
Abstract
Multi-omics datasets are becoming more common, necessitating better integration methods to realize their revolutionary potential. Here, we introduce multi-set correlation and factor analysis (MCFA), an unsupervised integration method tailored to the unique challenges of high-dimensional genomics data that enables fast inference of shared and private factors. We used MCFA to integrate methylation markers, protein expression, RNA expression, and metabolite levels in 614 diverse samples from the Trans-Omics for Precision Medicine/Multi-Ethnic Study of Atherosclerosis multi-omics pilot. Samples cluster strongly by ancestry in the shared space, even in the absence of genetic information, while private spaces frequently capture dataset-specific technical variation. Finally, we integrated genetic data by conducting a genome-wide association study (GWAS) of our inferred factors, observing that several factors are enriched for GWAS hits and trans-expression quantitative trait loci. Two of these factors appear to be related to metabolic disease. Our study provides a foundation and framework for further integrative analysis of ever larger multi-modal genomic datasets.
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Affiliation(s)
- Brielin C. Brown
- New York Genome Center, New York, NY, USA
- Data Science Institute, Columbia University, New York, NY, USA
| | - Collin Wang
- New York Genome Center, New York, NY, USA
- Department of Computer Science, Columbia University, New York, NY, USA
| | - Silva Kasela
- New York Genome Center, New York, NY, USA
- Department of Systems Biology, Columbia University, New York, NY, USA
| | - François Aguet
- Illumina Incorporated, San Francisco, CA, USA
- The Broad Institute of MIT and Harvard, Boston, MA, USA
| | | | - Kent D. Taylor
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Russell P. Tracy
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA
| | - Peter Durda
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA
| | - Yongmei Liu
- Department of Medicine, Duke University Medical Center, Durham, NC, USA
| | - W. Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - David Van Den Berg
- Department of Clinical Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Namrata Gupta
- The Broad Institute of MIT and Harvard, Boston, MA, USA
| | - Stacy Gabriel
- The Broad Institute of MIT and Harvard, Boston, MA, USA
| | - Joshua D. Smith
- Northwest Genomics Center, University of Washington, Seattle, WA, USA
| | - Robert Gerzsten
- Beth Israel Deaconess Medical Center, Division of Cardiovascular Medicine, Boston, MA, USA
| | - Clary Clish
- The Broad Institute of MIT and Harvard, Boston, MA, USA
| | - Quenna Wong
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - George Papanicolau
- Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
| | - Thomas W. Blackwell
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Jerome I. Rotter
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - R. Graham Barr
- Mailman School of Public Health, Columbia University, New York, NY, USA
| | | | - David A. Knowles
- New York Genome Center, New York, NY, USA
- Data Science Institute, Columbia University, New York, NY, USA
- Department of Computer Science, Columbia University, New York, NY, USA
- Department of Systems Biology, Columbia University, New York, NY, USA
| | - Tuuli Lappalainen
- New York Genome Center, New York, NY, USA
- Department of Systems Biology, Columbia University, New York, NY, USA
- Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
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27
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Novelli G, Cassadonte C, Sbraccia P, Biancolella M. Genetics: A Starting Point for the Prevention and the Treatment of Obesity. Nutrients 2023; 15:2782. [PMID: 37375686 DOI: 10.3390/nu15122782] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 06/15/2023] [Accepted: 06/16/2023] [Indexed: 06/29/2023] Open
Abstract
Obesity is a common, serious, and costly disease. More than 1 billion people worldwide are obese-650 million adults, 340 million adolescents, and 39 million children. The WHO estimates that, by 2025, approximately 167 million people-adults and children-will become less healthy because they are overweight or obese. Obesity-related conditions include heart disease, stroke, type 2 diabetes, and certain types of cancer. These are among the leading causes of preventable, premature death. The estimated annual medical cost of obesity in the United States was nearly $173 billion in 2019 dollars. Obesity is considered the result of a complex interaction between genes and the environment. Both genes and the environment change in different populations. In fact, the prevalence changes as the result of eating habits, lifestyle, and expression of genes coding for factors involved in the regulation of body weight, food intake, and satiety. Expression of these genes involves different epigenetic processes, such as DNA methylation, histone modification, or non-coding micro-RNA synthesis, as well as variations in the gene sequence, which results in functional alterations. Evolutionary and non-evolutionary (i.e., genetic drift, migration, and founder's effect) factors have shaped the genetic predisposition or protection from obesity in modern human populations. Understanding and knowing the pathogenesis of obesity will lead to prevention and treatment strategies not only for obesity, but also for other related diseases.
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Affiliation(s)
- Giuseppe Novelli
- Department of Biomedicine and Prevention, Medical School, University of Rome Tor Vergata, Via Montpellier 1, 00133 Rome, Italy
- Italian Barometer Diabetes Observatory Foundation, IBDO, 00186 Rome, Italy
- Department of Pharmacology, School of Medicine, University of Nevada, Reno, NV 89557, USA
| | - Carmen Cassadonte
- Department of Biomedicine and Prevention, Medical School, University of Rome Tor Vergata, Via Montpellier 1, 00133 Rome, Italy
| | - Paolo Sbraccia
- Italian Barometer Diabetes Observatory Foundation, IBDO, 00186 Rome, Italy
- Department of Systems Medicine, Medical School, University of Rome Tor Vergata, Via Montpellier 1, 00133 Rome, Italy
| | - Michela Biancolella
- Department of Biology, Tor Vergata University of Rome, Via della Ricerca Scientifica 1, 00133 Rome, Italy
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28
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Uchehara B, Kwee LC, Regan J, Chatterjee R, Eckstrand J, Swope S, Gold G, Schaack T, Douglas P, Mettu P, Haddad F, Shore S, Hernandez A, Mahaffey KW, Pagidipati N, Shah SH. Accelerated Epigenetic Aging Is Associated With Multiple Cardiometabolic, Hematologic, and Renal Abnormalities: A Project Baseline Health Substudy. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2023; 16:216-223. [PMID: 37039013 PMCID: PMC10330131 DOI: 10.1161/circgen.122.003772] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 01/30/2023] [Indexed: 04/12/2023]
Abstract
BACKGROUND Epigenetic clocks estimate chronologic age using methylation levels at specific loci. We tested the hypothesis that accelerated epigenetic aging is associated with abnormal values in a range of clinical, imaging, and laboratory characteristics. METHODS The Project Baseline Health Study recruited 2502 participants, including 1661 with epigenetic age estimates from the Horvath pan-tissue clock. We classified individuals with extreme values as having epigenetic age acceleration (EAA) or epigenetic age deceleration. A subset of participants with longitudinal methylation profiling was categorized as accelerated versus nonaccelerated. Using principal components analysis, we created phenoclusters using 122 phenotypic variables and compared individuals with EAA versus epigenetic age deceleration, and at one year of follow-up, using logistic regression models adjusted for sex (false discovery rate [Q] <0.10); in secondary exploratory analyses, we tested individual clinical variables. RESULTS The EAA (n=188) and epigenetic age deceleration (n=195) groups were identified as having EAA estimates ≥5 years or ≤-5 years, respectively. In primary analyses, individuals with EAA had higher values for phenoclusters summarizing lung function and lipids, and lower values for a phenocluster representing physical function. In secondary analyses of individual variables, neutrophils, body mass index, and waist circumference were significantly higher in individuals with EAA (Q<0.10). No phenoclusters were significantly different between participants with accelerated (n=148) versus nonaccelerated (n=112) longitudinal aging. CONCLUSIONS We report multiple cardiometabolic, hematologic, and physical function features characterizing individuals with EAA. These highlight factors that may mediate the adverse effects of aging and identify potential targets for study of mitigation of these effects. REGISTRATION URL: https://www. CLINICALTRIALS gov; Unique identifier: NCT03154346.
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Affiliation(s)
| | | | - Jessica Regan
- Division of General Internal Medicine, Dept of Medicine
| | | | | | - Sue Swope
- Stanford Center for Clinical Research, Dept of Medicine, Stanford University School of Medicine, Stanford
| | - Gary Gold
- Stanford Center for Clinical Research, Dept of Medicine, Stanford University School of Medicine, Stanford
| | - Terry Schaack
- California Health & Longevity Institute, Westlake Village
| | | | - Prithu Mettu
- Division of Retinal Ophthalmology, Dept of Ophthalmology
| | - Francois Haddad
- Stanford Center for Clinical Research, Dept of Medicine, Stanford University School of Medicine, Stanford
| | | | - Adrian Hernandez
- Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC
| | - Kenneth W. Mahaffey
- Stanford Center for Clinical Research, Dept of Medicine, Stanford University School of Medicine, Stanford
| | | | - Svati H. Shah
- Duke Molecular Physiology Institute, Duke University
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Nikpay M. Genome-wide search identified DNA methylation sites that regulate the metabolome. Front Genet 2023; 14:1093882. [PMID: 37274792 PMCID: PMC10233745 DOI: 10.3389/fgene.2023.1093882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 05/09/2023] [Indexed: 06/07/2023] Open
Abstract
Background: Identifying DNA methylation sites that regulate the metabolome is important for several purposes. In this study, publicly available GWAS data were integrated to find methylation sites that impact metabolome through a discovery and replication scheme and by using Mendelian randomization. Results: The outcome of analyses revealed 107 methylation sites associated with 84 metabolites at the genome-wide significance level (p<5e-8) at both the discovery and replication stages. A large percentage of the observed associations (85%) were with lipids, significantly higher than expected (p = 0.0003). A number of CpG (methylation) sites showed specificity e.g., cg20133200 within PFKP was associated with glucose only and cg10760299 within GATM impacted the level of creatinine; in contrast, there were sites associated with numerous metabolites e.g., cg20102877 on the 2p23.3 region was associated with 39 metabolites. Integrating transcriptome data enabled identifying genes (N = 82) mediating the impact of methylation sites on the metabolome and cardiometabolic traits. For example, PABPC4 mediated the impact of cg15123755-HDL on type-2 diabetes. KCNK7 mediated the impact of cg21033440-lipids on hypertension. POC5, ILRUN, FDFT1, and NEIL2 mediated the impact of CpG sites on obesity through metabolic pathways. Conclusion: This study provides a catalog of DNA methylation sites that regulate the metabolome for downstream applications.
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30
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Moore JM, Bell EL, Hughes RO, Garfield AS. ABC transporters: human disease and pharmacotherapeutic potential. Trends Mol Med 2023; 29:152-172. [PMID: 36503994 DOI: 10.1016/j.molmed.2022.11.001] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 10/24/2022] [Accepted: 11/01/2022] [Indexed: 12/12/2022]
Abstract
Adenosine triphosphate (ATP)-binding cassette (ABC) transporters are a 48-member superfamily of membrane proteins that actively transport a variety of biological substrates across lipid membranes. Their functional diversity defines an expansive involvement in myriad aspects of human biology. At least 21 ABC transporters underlie rare monogenic disorders, with even more implicated in the predisposition to and symptomology of common and complex diseases. Such broad (patho)physiological relevance places this class of proteins at the intersection of disease causation and therapeutic potential, underlining them as promising targets for drug discovery, as exemplified by the transformative CFTR (ABCC7) modulator therapies for cystic fibrosis. This review will explore the growing relevance of ABC transporters to human disease and their potential as small-molecule drug targets.
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31
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Liu S, Li Y, Wei X, Adi D, Wang YT, Han M, Liu F, Chen BD, Li XM, Yang YN, Fu ZY, Ma YT. Genetic analysis of DNA methylation in dyslipidemia: a case-control study. PeerJ 2022; 10:e14590. [PMID: 36570009 PMCID: PMC9774006 DOI: 10.7717/peerj.14590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 11/28/2022] [Indexed: 12/23/2022] Open
Abstract
Background Coronary heart disease has become the leading cause of death in developed countries, and dyslipidemia is closely associated with the risk of cardiovascular disease. Dyslipidemia is caused by the abnormal regulation of several genes and signaling pathways, and dyslipidemia is influenced mainly by genetic variation. AMFR, FBXW7, INSIG1, INSIG2, and MBTPS1 genes are associated with lipid metabolism. In a recent GWAS study, the GRINA gene has been reported to be associated with dyslipidemia, but its molecular mechanism has not been thoroughly investigated. The correlation between the DNA methylation of these genes and lipid metabolism has not been studied. This study aimed to examine the relationship between the DNA methylation of these genes and the risk of dyslipidemia by comparing the methylation levels of dyslipidemia and control samples. Methods A case-control research method was used in this study. The patient's blood samples were collected at the Heart Center of the First Affiliated Hospital of Xinjiang Medical University. In the Xinjiang Han population, 100 cases of hyperlipidemia and 80 cases of the control group were selected. The two groups were age and gender-matched. Quantitative methylation analysis of CpG sites in the gene promoter regions of six genes was performed by Solexa high-throughput sequencing. Results The DNA methylation levels of 23 CpG sites in six genes were shown to be associated with hyperlipidemia, and a total of 20 DNA methylation haplotypes showed statistically significant differences between the two groups. When compared with the control group, the dyslipidemia group had significantly higher levels of methylation in the GRINA gene (2.68 vs 2.36, P = 0.04). Additionally, we also discovered a significant methylation haplotype of GRINA (P = 0.017). Conclusion The findings of this study reveal that the DNA methylation of GRINA increases the risk for dyslipidemia in humans.
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Affiliation(s)
- Shuai Liu
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Yang Li
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Xian Wei
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Dilare Adi
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Yong-Tao Wang
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Min Han
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Fen Liu
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Bang-Dang Chen
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Xiao-Mei Li
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Yi-Ning Yang
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Zhen-Yan Fu
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
| | - Yi-Tong Ma
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China,Xinjiang Key Laboratory of Cardiovascular Disease Research, Urumqi, China
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Fraszczyk E, Thio CHL, Wackers P, Dollé MET, Bloks VW, Hodemaekers H, Picavet HS, Stynenbosch M, Verschuren WMM, Snieder H, Spijkerman AMW, Luijten M. DNA methylation trajectories and accelerated epigenetic aging in incident type 2 diabetes. GeroScience 2022; 44:2671-2684. [PMID: 35947335 PMCID: PMC9768051 DOI: 10.1007/s11357-022-00626-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 07/19/2022] [Indexed: 01/07/2023] Open
Abstract
DNA methylation (DNAm) patterns across the genome changes during aging and development of complex diseases including type 2 diabetes (T2D). Our study aimed to estimate DNAm trajectories of CpG sites associated with T2D, epigenetic age (DNAmAge), and age acceleration based on four epigenetic clocks (GrimAge, Hannum, Horvath, phenoAge) in the period 10 years prior to and up to T2D onset. In this nested case-control study within Doetinchem Cohort Study, we included 132 incident T2D cases and 132 age- and sex-matched controls. DNAm was measured in blood using the Illumina Infinium Methylation EPIC array. From 107 CpG sites associated with T2D, 10 CpG sites (9%) showed different slopes of DNAm trajectories over time (p < 0.05) and an additional 8 CpG sites (8%) showed significant differences in DNAm levels (at least 1%, p-value per time point < 0.05) at all three time points with nearly parallel trajectories between incident T2D cases and controls. In controls, age acceleration levels were negative (slower epigenetic aging), while in incident T2D cases, levels were positive, suggesting accelerated aging in the case group. We showed that DNAm levels at specific CpG sites, up to 10 years before T2D onset, are different between incident T2D cases and healthy controls and distinct patterns of clinical traits over time may have an impact on those DNAm profiles. Up to 10 years before T2D diagnosis, cases manifested accelerated epigenetic aging. Markers of biological aging including age acceleration estimates based on Horvath need further investigation to assess their utility for predicting age-related diseases including T2D.
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Affiliation(s)
- Eliza Fraszczyk
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Chris H L Thio
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Paul Wackers
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Martijn E T Dollé
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Vincent W Bloks
- Department of Pediatrics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Hennie Hodemaekers
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - H Susan Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Marjolein Stynenbosch
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - W M Monique Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Harold Snieder
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Annemieke M W Spijkerman
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Mirjam Luijten
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.
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Qin X, Wang Y, Pedersen NL, Tang B, Hägg S. Dynamic patterns of blood lipids and DNA methylation in response to statin therapy. Clin Epigenetics 2022; 14:153. [PMID: 36443870 PMCID: PMC9706978 DOI: 10.1186/s13148-022-01375-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Accepted: 11/15/2022] [Indexed: 11/30/2022] Open
Abstract
INTRODUCTION Statins are lipid-lowering drugs and starting treatment has been associated with DNA methylation changes at genes related to lipid metabolism. However, the longitudinal pattern of how statins affect DNA methylation in relation to lipid levels has not been well investigated. METHODS We conducted an epigenetic association study in a longitudinal Swedish twin sample in previously reported lipid-related CpGs (cg10177197, cg17901584 and cg27243685). First, we applied a mixed-effect model to assess the association between blood lipids (total cholesterol (TC), low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), total triglyceride (TG)) and DNA methylation. Then, we performed a piecewise latent linear-linear growth curve model (LGCM) to explore the long-term changing pattern of lipids and methylation in response to statin treatment. Finally, we used a bivariate autoregressive latent trajectory model with structured residuals (ALT-SR) to analyze the cross-lagged effects in different lipid-CpG pairs in statin users and non-users. RESULTS We replicated the associations between TC, LDL, HDL and DNA methylation level in cg17901584 and cg27243685 (P values ranged from 4.70E-12 to 1.84E-04). From the piecewise LGCM, we showed that TC and LDL significantly decreased in statin users before treatment started and then remained stable. For non-statin users, we only found a slightly significant decreasing trend for TC and TG. We observed a similar dynamic pattern for methylation levels at cg27243685 and cg17901584. Before statin initiation, cg27243685 showed a significantly increasing trend and cg17901584 a decreasing trend, but post-treatment, there were no additional changes. From the ALT-SR model, we found TG levels to be significantly associated with the DNA methylation level of cg27243685 at the next measurement in statin users (estimate = 0.383, 95% CI: 0.173, 0.594, P value < 0.001). CONCLUSIONS Longitudinal blood lipid and DNA methylation levels change after statin treatment initiation, where the latter is mostly a response to alterations in lipid levels and not vice versa.
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Affiliation(s)
- Xueying Qin
- grid.11135.370000 0001 2256 9319Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38# Xueyuan Road, Beijing, 100191 China ,grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 17177 Stockholm, Sweden
| | - Yunzhang Wang
- grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 17177 Stockholm, Sweden
| | - Nancy L. Pedersen
- grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 17177 Stockholm, Sweden
| | - Bowen Tang
- grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 17177 Stockholm, Sweden
| | - Sara Hägg
- grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 17177 Stockholm, Sweden
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Yousefi PD, Suderman M, Langdon R, Whitehurst O, Davey Smith G, Relton CL. DNA methylation-based predictors of health: applications and statistical considerations. Nat Rev Genet 2022; 23:369-383. [PMID: 35304597 DOI: 10.1038/s41576-022-00465-w] [Citation(s) in RCA: 94] [Impact Index Per Article: 31.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/18/2022] [Indexed: 12/12/2022]
Abstract
DNA methylation data have become a valuable source of information for biomarker development, because, unlike static genetic risk estimates, DNA methylation varies dynamically in relation to diverse exogenous and endogenous factors, including environmental risk factors and complex disease pathology. Reliable methods for genome-wide measurement at scale have led to the proliferation of epigenome-wide association studies and subsequently to the development of DNA methylation-based predictors across a wide range of health-related applications, from the identification of risk factors or exposures, such as age and smoking, to early detection of disease or progression in cancer, cardiovascular and neurological disease. This Review evaluates the progress of existing DNA methylation-based predictors, including the contribution of machine learning techniques, and assesses the uptake of key statistical best practices needed to ensure their reliable performance, such as data-driven feature selection, elimination of data leakage in performance estimates and use of generalizable, adequately powered training samples.
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Affiliation(s)
- Paul D Yousefi
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Matthew Suderman
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Ryan Langdon
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Oliver Whitehurst
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Caroline L Relton
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK.
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Atherosclerosis Development and Progression: The Role of Atherogenic Small, Dense LDL. Medicina (B Aires) 2022; 58:medicina58020299. [PMID: 35208622 PMCID: PMC8877621 DOI: 10.3390/medicina58020299] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 02/10/2022] [Accepted: 02/14/2022] [Indexed: 12/16/2022] Open
Abstract
Atherosclerosis is responsible for large cardiovascular mortality in many countries globally. It has been shown over the last decades that the reduction of atherosclerotic progression is a critical factor for preventing future cardiovascular events. Low-density lipoproteins (LDL) have been successfully targeted, and their reduction is one of the key preventing measures in patients with atherosclerotic disease. LDL particles are pivotal for the formation and progression of atherosclerotic plaques; yet, they are quite heterogeneous, and smaller, denser LDL species are the most atherogenic. These particles have greater arterial entry and retention, higher susceptibility to oxidation, as well as reduced affinity for the LDL receptor. Increased proportion of small, dense LDL particles is an integral part of the atherogenic lipoprotein phenotype, the most common form of dyslipidemia associated with insulin resistance. Recent data suggest that both genetic and epigenetic factors might induce expression of this specific lipid pattern. In addition, a typical finding of increased small, dense LDL particles was confirmed in different categories of patients with elevated cardiovascular risk. Small, dense LDL is an independent risk factor for cardiovascular diseases, which emphasizes the clinical importance of both the quality and the quantity of LDL. An effective management of atherosclerotic disease should take into account the presence of small, dense LDL in order to prevent cardiovascular complications.
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Chang M, Kumar A, Kumar S, Huhn S, Timp W, Betenbaugh M, Du Z. Epigenetic Comparison of CHO Hosts and Clones Reveals Divergent Methylation and Transcription Patterns Across Lineages. Biotechnol Bioeng 2022; 119:1062-1076. [PMID: 35028935 DOI: 10.1002/bit.28036] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 12/08/2021] [Accepted: 12/26/2021] [Indexed: 11/11/2022]
Abstract
In this study, we examined DNA methylation and transcription profiles of recombinant clones derived from two different Chinese hamster ovary hosts. We found striking epigenetic differences between the clones, with global hypomethylation in the host 1 clones that produce bispecific antibody with higher productivity and complex assembly efficiency. Whereas the methylation patterns were found mostly inherited from the host, the host 1 clones exhibited continued demethylation reflected by the hypomethylation of newly emerged differential methylation regions (DMRs) even at the clone development stage. Several interconnected biological functions and pathways including cell adhesion, regulation of ion transport, and cholesterol biosynthesis were significantly altered between the clones at the RNA expression level and contained DMR in the promoter and/or gene-body of the transcripts, suggesting epigenetic regulation. Indeed, expression changes of epigenetic regulators were observed including writers (Dnmt1, Setdb1), readers (Mecp2), and erasers (Tet3, Kdm3a, Kdm1b/5c) involved in CpG methylation, histone methylation and heterochromatin maintenance. In addition, we identified putative transcription factors that may be readers or effectors of the epigenetic regulation in these clones. By combining transcriptomics with DNA methylation data, we identified potential processes and factors that may contribute to the variability in cell physiology between different production hosts. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Meiping Chang
- Process Cell Sciences, Biologics Process R&D, Merck & Co., Inc., Kenilworth, NJ, USA
| | - Amit Kumar
- Process Cell Sciences, Biologics Process R&D, Merck & Co., Inc., Kenilworth, NJ, USA
| | - Swetha Kumar
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University
| | - Steven Huhn
- Process Cell Sciences, Biologics Process R&D, Merck & Co., Inc., Kenilworth, NJ, USA
| | - Winston Timp
- Department of Biomedical Engineering, Johns Hopkins University
| | - Michael Betenbaugh
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University
| | - Zhimei Du
- Process Cell Sciences, Biologics Process R&D, Merck & Co., Inc., Kenilworth, NJ, USA
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Corella D. Why is it important to know DNA methylation patterns in people with hypertriglyceridaemia? CLINICA E INVESTIGACION EN ARTERIOSCLEROSIS : PUBLICACION OFICIAL DE LA SOCIEDAD ESPANOLA DE ARTERIOSCLEROSIS 2022; 34:33-35. [PMID: 35151430 DOI: 10.1016/j.arteri.2022.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Affiliation(s)
- Dolores Corella
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, Valencia, Spain; CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain.
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38
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Harville EW, Mishra PP, Kähönen M, Raitoharju E, Marttila S, Raitakari O, Lehtimäki T. Reproductive history and blood cell DNA methylation later in life: the Young Finns Study. Clin Epigenetics 2021; 13:227. [PMID: 34930449 PMCID: PMC8690999 DOI: 10.1186/s13148-021-01215-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 12/09/2021] [Indexed: 01/16/2023] Open
Abstract
Background Women with a history of complications of pregnancy, including hypertensive disorders, gestational diabetes or an infant fetal growth restriction or preterm birth, are at higher risk for cardiovascular disease later in life. We aimed to examine differences in maternal DNA methylation following pregnancy complications. Methods Data on women participating in the Young Finns study (n = 836) were linked to the national birth registry. DNA methylation in whole blood was assessed using the Infinium Methylation EPIC BeadChip. Epigenome-wide analysis was conducted on differential CpG methylation at 850 K sites. Reproductive history was also modeled as a predictor of four epigenetic age indices. Results Fourteen significant differentially methylated sites were found associated with both history of pre-eclampsia and overall hypertensive disorders of pregnancy. No associations were found between reproductive history and any epigenetic age acceleration measure. Conclusions Differences in epigenetic methylation profiles could represent pre-existing risk factors, or changes that occurred as a result of experiencing these complications. Supplementary Information The online version contains supplementary material available at 10.1186/s13148-021-01215-1.
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Affiliation(s)
- Emily W Harville
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, 70112, USA. .,Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, 33520, Tampere, Finland.
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, 33520, Tampere, Finland.,Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, 33521, Tampere, Finland.,Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, 33521, Tampere, Finland
| | - Emma Raitoharju
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, 33520, Tampere, Finland.,Department of Molecular Epidemiology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Saara Marttila
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, 33520, Tampere, Finland.,Department of Molecular Epidemiology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.,Gerontology Research Center, Tampere University, Tampere, Finland
| | - Olli Raitakari
- Research Center of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, 33520, Tampere, Finland.,Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, 33521, Tampere, Finland.,Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
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39
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Tin A, Schlosser P, Matias-Garcia PR, Thio CHL, Joehanes R, Liu H, Yu Z, Weihs A, Hoppmann A, Grundner-Culemann F, Min JL, Kuhns VLH, Adeyemo AA, Agyemang C, Ärnlöv J, Aziz NA, Baccarelli A, Bochud M, Brenner H, Bressler J, Breteler MMB, Carmeli C, Chaker L, Coresh J, Corre T, Correa A, Cox SR, Delgado GE, Eckardt KU, Ekici AB, Endlich K, Floyd JS, Fraszczyk E, Gao X, Gào X, Gelber AC, Ghanbari M, Ghasemi S, Gieger C, Greenland P, Grove ML, Harris SE, Hemani G, Henneman P, Herder C, Horvath S, Hou L, Hurme MA, Hwang SJ, Kardia SLR, Kasela S, Kleber ME, Koenig W, Kooner JS, Kronenberg F, Kühnel B, Ladd-Acosta C, Lehtimäki T, Lind L, Liu D, Lloyd-Jones DM, Lorkowski S, Lu AT, Marioni RE, März W, McCartney DL, Meeks KAC, Milani L, Mishra PP, Nauck M, Nowak C, Peters A, Prokisch H, Psaty BM, Raitakari OT, Ratliff SM, Reiner AP, Schöttker B, Schwartz J, Sedaghat S, Smith JA, Sotoodehnia N, Stocker HR, Stringhini S, Sundström J, Swenson BR, van Meurs JBJ, van Vliet-Ostaptchouk JV, Venema A, Völker U, Winkelmann J, Wolffenbuttel BHR, Zhao W, Zheng Y, Loh M, Snieder H, Waldenberger M, Levy D, Akilesh S, Woodward OM, Susztak K, Teumer A, Köttgen A. Epigenome-wide association study of serum urate reveals insights into urate co-regulation and the SLC2A9 locus. Nat Commun 2021; 12:7173. [PMID: 34887389 PMCID: PMC8660809 DOI: 10.1038/s41467-021-27198-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 11/08/2021] [Indexed: 12/25/2022] Open
Abstract
Elevated serum urate levels, a complex trait and major risk factor for incident gout, are correlated with cardiometabolic traits via incompletely understood mechanisms. DNA methylation in whole blood captures genetic and environmental influences and is assessed in transethnic meta-analysis of epigenome-wide association studies (EWAS) of serum urate (discovery, n = 12,474, replication, n = 5522). The 100 replicated, epigenome-wide significant (p < 1.1E-7) CpGs explain 11.6% of the serum urate variance. At SLC2A9, the serum urate locus with the largest effect in genome-wide association studies (GWAS), five CpGs are associated with SLC2A9 gene expression. Four CpGs at SLC2A9 have significant causal effects on serum urate levels and/or gout, and two of these partly mediate the effects of urate-associated GWAS variants. In other genes, including SLC7A11 and PHGDH, 17 urate-associated CpGs are associated with conditions defining metabolic syndrome, suggesting that these CpGs may represent a blood DNA methylation signature of cardiometabolic risk factors. This study demonstrates that EWAS can provide new insights into GWAS loci and the correlation of serum urate with other complex traits.
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Affiliation(s)
- Adrienne Tin
- Department of Medicine, University of Mississippi Medical Center, Jackson, 39216, MS, USA.
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
| | - Pascal Schlosser
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Pamela R Matias-Garcia
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, D-85764, Bavaria, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, D-85764, Bavaria, Germany
- TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Chris H L Thio
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Roby Joehanes
- Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Hongbo Liu
- Department of Medicine and Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, 19104, PA, USA
| | - Zhi Yu
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Antoine Weihs
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Anselm Hoppmann
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Franziska Grundner-Culemann
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Josine L Min
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | | | - Adebowale A Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Charles Agyemang
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, University of Amsterdam, 1105 AZ, Amsterdam, the Netherlands
| | - Johan Ärnlöv
- Department of Neurobiology, Care Sciences and Society (NVS), Family Medicine and Primary Care Unit, Karolinska Institutet, Huddinge, Sweden
- School of Health and Social Studies, Dalarna University, Falun, Sweden
| | - Nasir A Aziz
- Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Andrea Baccarelli
- Laboratory of Environmental Precision Health, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Murielle Bochud
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Hermann Brenner
- German Cancer Research Center (DKFZ), Division of Clinical Epidemiology and Aging Research, Heidelberg, Germany
- Network Aging Research, Heidelberg University, Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
- German Cancer Consortium, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jan Bressler
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, 77030, TX, USA
| | - Monique M B Breteler
- Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Cristian Carmeli
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
- Population Health Laboratory, University of Fribourg, Fribourg, Switzerland
| | - Layal Chaker
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Tanguy Corre
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, 39216, MS, USA
| | - Simon R Cox
- Lothian Birth Cohorts Group, Department of Psychology, The University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Graciela E Delgado
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University of Erlangen-Nürnberg, Erlangen, Germany
- Department of Nephrology and Medical Intensive Care, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Arif B Ekici
- Institute of Human Genetics, Friedrich-Alexander-UniversitätErlangen-Nürnberg, 91054, Erlangen, Germany
| | - Karlhans Endlich
- Department of Anatomy and Cell Biology, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
| | - James S Floyd
- Department of Medicine, University of Washington, Seattle, 98101, WA, USA
- Department of Epidemiology, University of Washington, Seattle, 98101, WA, USA
- Cardiovascular Health Research Unit, University of Washington, Seattle, 98101, WA, USA
| | - Eliza Fraszczyk
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Xu Gao
- Laboratory of Environmental Precision Health, Mailman School of Public Health, Columbia University, New York, NY, USA
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Xīn Gào
- German Cancer Research Center (DKFZ), Division of Clinical Epidemiology and Aging Research, Heidelberg, Germany
| | - Allan C Gelber
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Sahar Ghasemi
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, D-85764, Bavaria, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, D-85764, Bavaria, Germany
| | - Philip Greenland
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Megan L Grove
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, 77030, TX, USA
| | - Sarah E Harris
- Lothian Birth Cohorts Group, Department of Psychology, The University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Peter Henneman
- Department of Clinical Genetics, Amsterdam Reproduction & Development Research Institute, Amsterdam University Medical Centres, University of Amsterdam, Amsterdam, the Netherlands
| | - Christian Herder
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research, Munich-Neuherberg, Germany
- Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, 90095, CA, USA
- Biostatistics, Fielding School of Public Health, UCLA, Los Angeles, CA, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Mikko A Hurme
- Department of Microbiology and Immunology, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33014, Finland
| | - Shih-Jen Hwang
- Framingham Heart Study, Framingham, MA, USA
- Division of Intramural Research, Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, 48109, MI, USA
| | - Silva Kasela
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Marcus E Kleber
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- SYNLAB MVZ Humangenetik Mannheim, Mannheim, Germany
| | - Wolfgang Koenig
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
- DZHK (German Centre for Cardiovascular Research), Partner site Munich Heart Alliance, Munich, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Jaspal S Kooner
- National Heart and Lung Institute, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Southall, UK
- Imperial College Healthcare NHS Trust, London, UK
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Brigitte Kühnel
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, D-85764, Bavaria, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, D-85764, Bavaria, Germany
| | - Christine Ladd-Acosta
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Dan Liu
- Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Donald M Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Stefan Lorkowski
- Institute of Nutritional Sciences, Friedrich Schiller University Jena, Jena, Germany
- Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig, Jena, Germany
| | - Ake T Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, 90095, CA, USA
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig, Jena, Germany
- Synlab Academy, SYNLAB Holding Deutschland GmbH, Mannheim and Augsburg, Germany
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Karlijn A C Meeks
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, University of Amsterdam, 1105 AZ, Amsterdam, the Netherlands
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Matthias Nauck
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Christoph Nowak
- Department of Neurobiology, Care Sciences and Society (NVS), Family Medicine and Primary Care Unit, Karolinska Institutet, Huddinge, Sweden
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, D-85764, Bavaria, Germany
- Ludwig-Maximilians Universität München, Munich, Germany
| | - Holger Prokisch
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
- Department of Computational Health, Institute of Neurogenomics, Helmholtz Zentrum München, Munich, Germany
| | - Bruce M Psaty
- Department of Medicine, University of Washington, Seattle, 98101, WA, USA
- Department of Epidemiology, University of Washington, Seattle, 98101, WA, USA
- Cardiovascular Health Research Unit, University of Washington, Seattle, 98101, WA, USA
- Department of Health Services, University of Washington, Seattle, 98101, WA, USA
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Scott M Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, 48109, MI, USA
| | - Alex P Reiner
- Department of Epidemiology, University of Washington, Seattle, 98101, WA, USA
| | - Ben Schöttker
- German Cancer Research Center (DKFZ), Division of Clinical Epidemiology and Aging Research, Heidelberg, Germany
- Network Aging Research, Heidelberg University, Heidelberg, Germany
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Sanaz Sedaghat
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, 48109, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, University of Washington, Seattle, 98101, WA, USA
| | - Hannah R Stocker
- German Cancer Research Center (DKFZ), Division of Clinical Epidemiology and Aging Research, Heidelberg, Germany
- Network Aging Research, Heidelberg University, Heidelberg, Germany
| | - Silvia Stringhini
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Johan Sundström
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia
| | - Brenton R Swenson
- Cardiovascular Health Research Unit, University of Washington, Seattle, 98101, WA, USA
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Jana V van Vliet-Ostaptchouk
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Andrea Venema
- Department of Clinical Genetics, Amsterdam Reproduction & Development Research Institute, Amsterdam University Medical Centres, University of Amsterdam, Amsterdam, the Netherlands
| | - Uwe Völker
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Juliane Winkelmann
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
- Institute of Neurogenomics, Helmholtz Zentrum München, Munich, Germany
- Chair Neurogenetics, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Bruce H R Wolffenbuttel
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, 48109, MI, USA
| | - Yinan Zheng
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Marie Loh
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, D-85764, Bavaria, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, D-85764, Bavaria, Germany
- DZHK (German Centre for Cardiovascular Research), Partner site Munich Heart Alliance, Munich, Germany
| | - Daniel Levy
- Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Shreeram Akilesh
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Owen M Woodward
- Department of Physiology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Katalin Susztak
- Department of Medicine and Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, 19104, PA, USA
| | - Alexander Teumer
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland
| | - Anna Köttgen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
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40
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Martín-Campos JM. Genetic Determinants of Plasma Low-Density Lipoprotein Cholesterol Levels: Monogenicity, Polygenicity, and "Missing" Heritability. Biomedicines 2021; 9:biomedicines9111728. [PMID: 34829957 PMCID: PMC8615680 DOI: 10.3390/biomedicines9111728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 11/16/2021] [Accepted: 11/17/2021] [Indexed: 11/16/2022] Open
Abstract
Changes in plasma low-density lipoprotein cholesterol (LDL-c) levels relate to a high risk of developing some common and complex diseases. LDL-c, as a quantitative trait, is multifactorial and depends on both genetic and environmental factors. In the pregenomic age, targeted genes were used to detect genetic factors in both hyper- and hypolipidemias, but this approach only explained extreme cases in the population distribution. Subsequently, the genetic basis of the less severe and most common dyslipidemias remained unknown. In the genomic age, performing whole-exome sequencing in families with extreme plasma LDL-c values identified some new candidate genes, but it is unlikely that such genes can explain the majority of inexplicable cases. Genome-wide association studies (GWASs) have identified several single-nucleotide variants (SNVs) associated with plasma LDL-c, introducing the idea of a polygenic origin. Polygenic risk scores (PRSs), including LDL-c-raising alleles, were developed to measure the contribution of the accumulation of small-effect variants to plasma LDL-c. This paper discusses other possibilities for unexplained dyslipidemias associated with LDL-c, such as mosaicism, maternal effect, and induced epigenetic changes. Future studies should consider gene-gene and gene-environment interactions and the development of integrated information about disease-driving networks, including phenotypes, genotypes, transcription, proteins, metabolites, and epigenetics.
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Affiliation(s)
- Jesús Maria Martín-Campos
- Stroke Pharmacogenomics and Genetics Group, Institut de Recerca de l'Hospital de la Santa Creu i Sant Pau (IR-HSCSP)-Biomedical Research Institute Sant Pau (IIB-Sant Pau), C/Sant Quintí 77-79, 08041 Barcelona, Spain
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41
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Laaksonen J, Mishra PP, Seppälä I, Raitoharju E, Marttila S, Mononen N, Lyytikäinen LP, Kleber ME, Delgado GE, Lepistö M, Almusa H, Ellonen P, Lorkowski S, März W, Hutri-Kähönen N, Raitakari O, Kähönen M, Salonen JT, Lehtimäki T. Mitochondrial genome-wide analysis of nuclear DNA methylation quantitative trait loci. Hum Mol Genet 2021; 31:1720-1732. [PMID: 35077545 PMCID: PMC9122653 DOI: 10.1093/hmg/ddab339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Revised: 11/12/2021] [Accepted: 11/16/2021] [Indexed: 11/13/2022] Open
Abstract
Abstract
Mitochondria have a complex communication network with the surrounding cell and can alter nuclear DNA methylation (DNAm). Variation in the mitochondrial DNA (mtDNA) has also been linked to differential DNAm. Genome-wide association studies have identified numerous DNAm quantitative trait loci, but these studies have not examined the mitochondrial genome. Herein, we quantified nuclear DNAm from blood and conducted a mitochondrial genome-wide association study of DNAm, with an additional emphasis on sex- and prediabetes-specific heterogeneity. We used the Young Finns Study (n = 926) with sequenced mtDNA genotypes as a discovery sample and sought replication in the Ludwigshafen Risk and Cardiovascular Health study (n = 2317). We identified numerous significant associations in the discovery phase (P < 10−9), but they were not replicated when accounting for multiple testing. In total, 27 associations were nominally replicated with a P < 0.05. The replication analysis presented no evidence of sex- or prediabetes-specific heterogeneity. The 27 associations were included in a joint meta-analysis of the two cohorts, and 19 DNAm sites associated with mtDNA variants, while four other sites showed haplogroup associations. An expression quantitative trait methylation analysis was performed for the identified DNAm sites, pinpointing two statistically significant associations. This study provides evidence of a mitochondrial genetic control of nuclear DNAm with little evidence found for sex- and prediabetes-specific effects. The lack of a comparable mtDNA data set for replication is a limitation in our study and further studies are needed to validate our results.
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Affiliation(s)
- Jaakko Laaksonen
- To whom correspondence should be addressed at: Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, PO Box 100, Tampere FI-33014, Finland. Tel: +358 504080774; E-mail:
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Ilkka Seppälä
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Emma Raitoharju
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
- Molecular Epidemiology, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Saara Marttila
- Molecular Epidemiology, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
- Gerontology Research Center, Tampere University, Tampere 33520, Finland
| | - Nina Mononen
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Marcus E Kleber
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim 68167, Germany
| | - Graciela E Delgado
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim 68167, Germany
| | - Maija Lepistö
- Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki 00290, Finland
| | - Henrikki Almusa
- Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki 00290, Finland
| | - Pekka Ellonen
- Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki 00290, Finland
| | - Stefan Lorkowski
- Institute of Nutritional Sciences, Friedrich Schiller University Jena, Jena 07743, Germany
- Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig, Jena 07743, Germany
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim 68167, Germany
- Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig, Jena 07743, Germany
- SYNLAB Academy, SYNLAB Holding Deutschland GmbH, Augsburg 86156, Germany
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz 8010, Austria
| | - Nina Hutri-Kähönen
- Tampere Centre for Skills Training and Simulation, Tampere University, Tampere 33520, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku 20520, Finland
- Research Centre for Applied and Preventive Cardiovascular Medicine, University of Turku, Turku 20520, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku 20520, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere 33520, Finland
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Jukka T Salonen
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki 00014, Finland
- MAS-Metabolic Analytical Services Oy, Helsinki 00990, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
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Song MA, Seffernick AE, Archer KJ, Mori KM, Park SY, Chang L, Ernst T, Tiirikainen M, Peplowska K, Wilkens LR, Le Marchand L, Lim U. Race/ethnicity-associated blood DNA methylation differences between Japanese and European American women: an exploratory study. Clin Epigenetics 2021; 13:188. [PMID: 34635168 PMCID: PMC8507376 DOI: 10.1186/s13148-021-01171-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 08/25/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Racial/ethnic disparities in health reflect a combination of genetic and environmental causes, and DNA methylation may be an important mediator. We compared in an exploratory manner the blood DNA methylome of Japanese Americans (JPA) versus European Americans (EUA). METHODS Genome-wide buffy coat DNA methylation was profiled among healthy Multiethnic Cohort participant women who were Japanese (JPA; n = 30) or European (EUA; n = 28) Americans aged 60-65. Differentially methylated CpGs by race/ethnicity (DM-CpGs) were identified by linear regression (Bonferroni-corrected P < 0.1) and analyzed in relation to corresponding gene expression, a priori selected single nucleotide polymorphisms (SNPs), and blood biomarkers of inflammation and metabolism using Pearson or Spearman correlations (FDR < 0.1). RESULTS We identified 174 DM-CpGs with the majority of hypermethylated in JPA compared to EUA (n = 133), often in promoter regions (n = 48). Half (51%) of the genes corresponding to the DM-CpGs were involved in liver function and liver disease, and the methylation in nine genes was significantly correlated with gene expression for DM-CpGs. A total of 156 DM-CpGs were associated with rs7489665 (SH2B1). Methylation of DM-CpGs was correlated with blood levels of the cytokine MIP1B (n = 146). We confirmed some of the DM-CpGs in the TCGA adjacent non-tumor liver tissue of Asians versus EUA. CONCLUSION We found a number of differentially methylated CpGs in blood DNA between JPA and EUA women with a potential link to liver disease, specific SNPs, and systemic inflammation. These findings may support further research on the role of DNA methylation in mediating some of the higher risk of liver disease among JPA.
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Affiliation(s)
- Min-Ae Song
- Division of Environmental Health Science, College of Public Health, The Ohio State University, 404 Cunz Hall, 1841 Neil Ave., Columbus, OH, 43210, USA.
| | - Anna Eames Seffernick
- Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH, USA
| | - Kellie J Archer
- Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH, USA
| | - Kellie M Mori
- Division of Environmental Health Science, College of Public Health, The Ohio State University, 404 Cunz Hall, 1841 Neil Ave., Columbus, OH, 43210, USA
| | - Song-Yi Park
- Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Linda Chang
- School of Medicine, University of Maryland, Baltimore, MD, USA
| | - Thomas Ernst
- School of Medicine, University of Maryland, Baltimore, MD, USA
| | - Maarit Tiirikainen
- Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Karolina Peplowska
- Genomics and Bioinformatics Shared Resources, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Lynne R Wilkens
- Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Loïc Le Marchand
- Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Unhee Lim
- Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
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43
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Jones AC, Irvin MR, Claas SA, Arnett DK. Lipid Phenotypes and DNA Methylation: a Review of the Literature. Curr Atheroscler Rep 2021; 23:71. [PMID: 34468868 DOI: 10.1007/s11883-021-00965-w] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/11/2021] [Indexed: 12/17/2022]
Abstract
PURPOSE OF REVIEW Epigenetic modifications via DNA methylation have previously been linked to blood lipid levels, dyslipidemias, and atherosclerosis. The purpose of this review is to discuss current literature on the role of DNA methylation on lipid traits and their associated pathologies. RECENT FINDINGS Candidate gene and epigenome-wide approaches have identified differential methylation of genes associated with lipid traits (particularly CPT1A, ABCG1, SREBF1), and novel approaches are being implemented to further characterize these relationships. Moreover, studies on environmental factors have shown that methylation variations at lipid-related genes are associated with diet and pollution exposure. Further investigation is needed to elucidate the directionality of the associations between the environment, lipid traits, and epigenome. Future studies should also seek to increase the diversity of cohorts, as European and Asian ancestry populations are the predominant study populations in the current literature.
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Affiliation(s)
- Alana C Jones
- Medical Scientist Training Program, University of Alabama-Birmingham, Birmingham, AL, USA.,Department of Epidemiology, School of Public Health, University of Alabama-Birmingham, Birmingham, AL, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama-Birmingham, Birmingham, AL, USA
| | - Steven A Claas
- Department of Epidemiology, College of Public Health, University of Kentucky, 111 Washington Ave, Lexington, KY, 40508, USA
| | - Donna K Arnett
- Department of Epidemiology, College of Public Health, University of Kentucky, 111 Washington Ave, Lexington, KY, 40508, USA.
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Suhre K, Zaghlool S. Connecting the epigenome, metabolome and proteome for a deeper understanding of disease. J Intern Med 2021; 290:527-548. [PMID: 33904619 DOI: 10.1111/joim.13306] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 03/18/2021] [Accepted: 03/22/2021] [Indexed: 12/26/2022]
Abstract
Epigenome-wide association studies (EWAS) identify genes that are dysregulated by the studied clinical endpoints, thereby indicating potential new diagnostic biomarkers, drug targets and therapy options. Combining EWAS with deep molecular phenotyping, such as approaches enabled by metabolomics and proteomics, allows further probing of the underlying disease-associated pathways. For instance, methylation of the TXNIP gene is associated robustly with prevalent type 2 diabetes and further with metabolites that are short-term markers of glycaemic control. These associations reflect TXNIP's function as a glucose uptake regulator by interaction with the major glucose transporter GLUT1 and suggest that TXNIP methylation can be used as a read-out for the organism's exposure to glucose stress. Another case is the association between DNA methylation of the AHRR and F2RL3 genes with smoking and a protein that is involved in the reprogramming of the bronchial epithelium. These examples show that associations between DNA methylation and intermediate molecular traits can open new windows into how the body copes with physiological challenges. This knowledge, if carefully interpreted, may indicate novel therapy options and, together with monitoring of the methylation state of specific methylation sites, may in the future allow the early diagnosis of impending disease. It is essential for medical practitioners to recognize the potential that this field holds in translating basic research findings to clinical practice. In this review, we present recent advances in the field of EWAS with metabolomics and proteomics and discuss both the potential and the challenges of translating epigenetic associations, with deep molecular phenotypes, to biomedical applications.
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Affiliation(s)
- K Suhre
- From the, Bioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar.,Department of Biophysics and Physiology, Weill Cornell Medicine, New York, USA
| | - S Zaghlool
- From the, Bioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar.,Department of Biophysics and Physiology, Weill Cornell Medicine, New York, USA
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45
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The Therapeutic Potential of Epigenome-Modifying Drugs in Cardiometabolic Disease. CURRENT GENETIC MEDICINE REPORTS 2021. [DOI: 10.1007/s40142-021-00198-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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