Monica Del C Gomez-Alonso1,2, Anja Kretschmer1,2, Rory Wilson1,2, Liliane Pfeiffer1,2, Ville Karhunen3,4, Ilkka Seppälä5, Weihua Zhang3,6, Kirstin Mittelstraß1,2, Simone Wahl1,2, Pamela R Matias-Garcia1,2, Holger Prokisch7,8, Sacha Horn1,2, Thomas Meitinger7,8,9, Luis R Serrano-Garcia1,2,10, Sylvain Sebert4, Olli Raitakari11,12,13, Marie Loh3,14, Wolfgang Rathmann15,16, Martina Müller-Nurasyid17,18,19, Christian Herder16,20,21, Michael Roden16,20,21, Mikko Hurme22, Marjo-Riitta Jarvelin3,4,23,24, Mika Ala-Korpela4,25,26,27, Jaspal S Kooner6,28,29,30, Annette Peters2, Terho Lehtimäki5, John C Chambers3,6,14,29,30, Christian Gieger1,2, Johannes Kettunen4,26,27, Melanie Waldenberger31,32,33. 1. Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany. 2. Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany. 3. Department of Epidemiology and Biostatistics, Imperial College London, London, UK. 4. Center for Life Course Health Research, University of Oulu, Oulu University Hospital, Oulu, Finland. 5. Department of Clinical Chemistry, Pirkanmaa Hospital District, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland. 6. Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, London, Middlesex, UK. 7. Institute of Human Genetics, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany. 8. Institute of Human Genetics, School of Medicine, Technical University Munich, Munich, Germany. 9. German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany. 10. Chair of Microbiology, Technical University of Munich, Freising, Germany. 11. Centre for Population Health Research, University of Turku, Turku University Hospital, Turku, Finland. 12. Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland. 13. Department of Clinical Physiology and Nuclear Medicine, University of Turku, Turku University Hospital, Turku, Finland. 14. Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore. 15. Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany. 16. German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany. 17. Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany. 18. Institute of Genetic Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany. 19. Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55101, Mainz, Germany. 20. Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany. 21. Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany. 22. Department of Microbiology and Immunology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland. 23. UKMRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK. 24. Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK. 25. NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland. 26. Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland. 27. Biocenter Oulu, University of Oulu, Oulu, Finland. 28. National Heart and Lung Institute, Imperial College London, London, UK. 29. Imperial College Healthcare NHS Trust, London, UK. 30. MRC-PHE Centre for Environment and Health, Imperial College London, London, UK. 31. Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany. waldenberger@helmholtz-muenchen.de. 32. Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany. waldenberger@helmholtz-muenchen.de. 33. German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany. waldenberger@helmholtz-muenchen.de.
Abstract
BACKGROUND: The discovery of robust and trans-ethnically replicated DNA methylation markers of metabolic phenotypes, has hinted at a potential role of epigenetic mechanisms in lipid metabolism. However, DNA methylation and the lipid compositions and lipid concentrations of lipoprotein sizes have been scarcely studied. Here, we present an epigenome-wide association study (EWAS) (N = 5414 total) of mostly lipid-related metabolic measures, including a fine profiling of lipoproteins. As lipoproteins are the main players in the different stages of lipid metabolism, examination of epigenetic markers of detailed lipoprotein features might improve the diagnosis, prognosis, and treatment of metabolic disturbances. RESULTS: We conducted an EWAS of leukocyte DNA methylation and 226 metabolic measurements determined by nuclear magnetic resonance spectroscopy in the population-based KORA F4 study (N = 1662) and replicated the results in the LOLIPOP, NFBC1966, and YFS cohorts (N = 3752). Follow-up analyses in the discovery cohort included investigations into gene transcripts, metabolic-measure ratios for pathway analysis, and disease endpoints. We identified 161 associations (p value < 4.7 × 10-10), covering 16 CpG sites at 11 loci and 57 metabolic measures. Identified metabolic measures were primarily medium and small lipoproteins, and fatty acids. For apolipoprotein B-containing lipoproteins, the associations mainly involved triglyceride composition and concentrations of cholesterol esters, triglycerides, free cholesterol, and phospholipids. All associations for HDL lipoproteins involved triglyceride measures only. Associated metabolic measure ratios, proxies of enzymatic activity, highlight amino acid, glucose, and lipid pathways as being potentially epigenetically implicated. Five CpG sites in four genes were associated with differential expression of transcripts in blood or adipose tissue. CpG sites in ABCG1 and PHGDH showed associations with metabolic measures, gene transcription, and metabolic measure ratios and were additionally linked to obesity or previous myocardial infarction, extending previously reported observations. CONCLUSION: Our study provides evidence of a link between DNA methylation and the lipid compositions and lipid concentrations of different lipoprotein size subclasses, thus offering in-depth insights into well-known associations of DNA methylation with total serum lipids. The results support detailed profiling of lipid metabolism to improve the molecular understanding of dyslipidemia and related disease mechanisms.
BACKGROUND: The discovery of robust and trans-ethnically replicated DNA methylation markers of metabolic phenotypes, has hinted at a potential role of epigenetic mechanisms in lipid metabolism. However, DNA methylation and the lipid compositions and lipid concentrations of lipoprotein sizes have been scarcely studied. Here, we present an epigenome-wide association study (EWAS) (N = 5414 total) of mostly lipid-related metabolic measures, including a fine profiling of lipoproteins. As lipoproteins are the main players in the different stages of lipid metabolism, examination of epigenetic markers of detailed lipoprotein features might improve the diagnosis, prognosis, and treatment of metabolic disturbances. RESULTS: We conducted an EWAS of leukocyte DNA methylation and 226 metabolic measurements determined by nuclear magnetic resonance spectroscopy in the population-based KORA F4 study (N = 1662) and replicated the results in the LOLIPOP, NFBC1966, and YFS cohorts (N = 3752). Follow-up analyses in the discovery cohort included investigations into gene transcripts, metabolic-measure ratios for pathway analysis, and disease endpoints. We identified 161 associations (p value < 4.7 × 10-10), covering 16 CpG sites at 11 loci and 57 metabolic measures. Identified metabolic measures were primarily medium and small lipoproteins, and fatty acids. For apolipoprotein B-containing lipoproteins, the associations mainly involved triglyceride composition and concentrations of cholesterol esters, triglycerides, free cholesterol, and phospholipids. All associations for HDL lipoproteins involved triglyceride measures only. Associated metabolic measure ratios, proxies of enzymatic activity, highlight amino acid, glucose, and lipid pathways as being potentially epigenetically implicated. Five CpG sites in four genes were associated with differential expression of transcripts in blood or adipose tissue. CpG sites in ABCG1 and PHGDH showed associations with metabolic measures, gene transcription, and metabolic measure ratios and were additionally linked to obesity or previous myocardial infarction, extending previously reported observations. CONCLUSION: Our study provides evidence of a link between DNA methylation and the lipid compositions and lipid concentrations of different lipoprotein size subclasses, thus offering in-depth insights into well-known associations of DNA methylation with total serum lipids. The results support detailed profiling of lipid metabolism to improve the molecular understanding of dyslipidemia and related disease mechanisms.
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