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Long P, Si J, Zhu Z, Jiang Y, Wang Y, Jiang Q, Li W, Xu X, You Y, Qu M, Wang H, Mo T, Liu K, Jiang J, Wang Q, Yu C, Guo Y, Millwood IY, Walters RG, He X, Yuan Y, Wang H, Zhang X, He M, Guo H, Chen Z, Li L, Lv J, Wang C, Wu T. Genome-wide DNA methylation profiling in blood reveals epigenetic signature of incident acute coronary syndrome. Nat Commun 2024; 15:7431. [PMID: 39198424 PMCID: PMC11358540 DOI: 10.1038/s41467-024-51751-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 08/14/2024] [Indexed: 09/01/2024] Open
Abstract
DNA methylation (DNAm) has been implicated in acute coronary syndrome (ACS), but the causality remains unclear in cross-sectional studies. Here, we conduct a prospective epigenome-wide association study of incident ACS in two Chinese cohorts (discovery: 751 nested case-control pairs; replication: 476 nested case-control pairs). We identified and validated 26 differentially methylated positions (DMPs, false discovery rate [FDR] <0.05), including three mapped to known cardiovascular disease genes (PRKCZ, PRDM16, EHBP1L1) and four with causal evidence from Mendelian randomization (PRKCZ, TRIM27, EMC2, EHBP1L1). Two hypomethylated DMPs were negatively correlated with the expression in blood of their mapped genes (PIGG and EHBP1L1), which were further found to overexpress in leukocytes and/or atheroma plaques. Finally, our DMPs could substantially improve the prediction of ACS over traditional risk factors and polygenic scores. These findings demonstrate the importance of DNAm in the pathogenesis of ACS and highlight DNAm as potential predictive biomarkers and treatment targets.
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Affiliation(s)
- Pinpin Long
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jiahui Si
- National Institute of Health Data Science at Peking University, Peking University, Beijing, China
| | - Ziwei Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yi Jiang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yufei Wang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Qin Jiang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Wending Li
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xuedan Xu
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yutong You
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Minghan Qu
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Huihui Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Tingting Mo
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Kang Liu
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jing Jiang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Qiuhong Wang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Yu Guo
- Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Iona Y Millwood
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Robin G Walters
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Ximiao He
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yu Yuan
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Hao Wang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiaomin Zhang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Meian He
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Huan Guo
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China.
| | - Chaolong Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
| | - Tangchun Wu
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
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Taschereau A, Thibeault K, Allard C, Juvinao-Quintero D, Perron P, Lutz SM, Bouchard L, Hivert MF. Maternal glycemia in pregnancy is longitudinally associated with blood DNAm variation at the FSD1L gene from birth to 5 years of age. Clin Epigenetics 2023; 15:107. [PMID: 37386647 PMCID: PMC10308691 DOI: 10.1186/s13148-023-01524-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 06/23/2023] [Indexed: 07/01/2023] Open
Abstract
BACKGROUND In utero exposure to maternal hyperglycemia has been associated with an increased risk for the development of chronic diseases in later life. These predispositions may be programmed by fetal DNA methylation (DNAm) changes that persist postnatally. However, although some studies have associated fetal exposure to gestational hyperglycemia with DNAm variations at birth, and metabolic phenotypes in childhood, no study has yet examined how maternal hyperglycemia during pregnancy may be associated with offspring DNAm from birth to five years of age. HYPOTHESIS Maternal hyperglycemia is associated with variation in offspring DNAm from birth to 5 years of age. METHODS We estimated maternal hyperglycemia using the area under the curve for glucose (AUCglu) following an oral glucose tolerance test conducted at 24-30 weeks of pregnancy. We quantified DNAm levels in cord blood (n = 440) and peripheral blood at five years of age (n = 293) using the Infinium MethylationEPIC BeadChip (Illumina). Our total sample included 539 unique dyads (mother-child) with 194 dyads having DNAm at both time-points. We first regressed DNAm M-values against the cell types and child age for each time-point separately to account for the difference by time of measurement for these variables. We then used a random intercept model from the linear mixed model (LMM) framework to assess the longitudinal association between maternal AUCglu and the repeated measures of residuals of DNAm. We adjusted for the following covariates as fixed effects in the random intercept model: maternal age, gravidity, smoking status, child sex, maternal body mass index (BMI) (measured at first trimester of pregnancy), and a binary variable for time-point. RESULTS In utero exposure to higher maternal AUCglu was associated with lower offspring blood DNAm levels at cg00967989 located in FSD1L gene (β = - 0.0267, P = 2.13 × 10-8) in adjusted linear regression mixed models. Our study also reports other CpG sites for which DNAm levels were suggestively associated (P < 1.0 × 10-5) with in utero exposure to gestational hyperglycemia. Two of these (cg12140144 and cg07946633) were found in the promotor region of PRDM16 gene (β: - 0.0251, P = 4.37 × 10-07 and β: - 0.0206, P = 2.24 × 10-06, respectively). CONCLUSION Maternal hyperglycemia is associated with offspring DNAm longitudinally assessed from birth to 5 years of age.
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Affiliation(s)
- Amélie Taschereau
- Department of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences (FMHS), Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Kathrine Thibeault
- Department of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences (FMHS), Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Catherine Allard
- Centre de Recherche du Centre hospitalier universitaire de Sherbrooke (CR-CHUS), Sherbrooke, QC, Canada
| | | | - Patrice Perron
- Centre de Recherche du Centre hospitalier universitaire de Sherbrooke (CR-CHUS), Sherbrooke, QC, Canada
- Department of Medicine, FMHS, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Sharon M Lutz
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Luigi Bouchard
- Department of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences (FMHS), Université de Sherbrooke, Sherbrooke, QC, Canada.
- Department of Medicine, FMHS, Université de Sherbrooke, Sherbrooke, QC, Canada.
- Clinical Department of Laboratory Medicine, Pavillon des Augustines, Centre intégré universitaire de santé et de services sociaux (CIUSSS) du Saguenay-Lac-Saint-Jean - Hôpital de Chicoutimi, 305 rue St-Vallier, Saguenay, QC, G7H 5H6, Canada.
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
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Lee HH, Chen CC, Ong JR, Lin YF, Lee FP, Hu CJ, Wang YH. Association of rs2651899 Polymorphism in the Positive Regulatory Domain 16 and Common Migraine Subtypes: A Meta-Analysis. Headache 2019; 60:71-80. [PMID: 31557325 DOI: 10.1111/head.13670] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/09/2019] [Indexed: 10/25/2022]
Abstract
BACKGROUND Migraine is a neurovascular disease with recurrent headache attacks. A polymorphism (rs2651899) of the PRDM16 gene, which is associated with migraine, was identified in recent genome-wide association studies. The potential role of the PRDM16 rs2651899 polymorphism in migraine is still unknown. Therefore, we conducted this systematic review and meta-analysis to examine this issue. METHODS We performed a comprehensive literature search of the PubMed, Embase, and Google Scholar databases to identify eligible studies published before October 2018. Individual odds ratio and 95% confidence interval was used to estimate the pooled strength of the association between the PRDM16 rs2651899 polymorphism and common migraine subtypes, including migraine with aura (MA) and migraine without aura (MO). RESULTS Six studies with 2853 cases and 9319 controls that fulfilled the inclusion and exclusion criteria were selected for this meta-analysis. Of the 6 included studies, 4 studies had available data for MWA and another 4 studies had data for MWoA. Overall, significant migraine risks of 1.257, 1.305, and 1.419 were found under allele model (C vs T), dominant model (C/C+T/C vs T/T), and recessive model (C/C vs T/C+T/T), respectively. In the recessive model, significantly increased risks of 1.454 and 1.546 were found for MA and MO, respectively. CONCLUSION Our major findings suggest that PRDM16 rs2651899 polymorphism is associated with the risk of migraine. Furthermore, we found that PRDM16 rs2651899 polymorphism is significantly related to common migraine subtypes (MA and MO).
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Affiliation(s)
- Hsun-Hua Lee
- Graduate Institute of Clinical Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.,Department of Neurology, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan.,Dizziness and Balance Disorder Center, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan
| | - Chih-Chung Chen
- Department of Neurology, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan.,Dizziness and Balance Disorder Center, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan.,Taipei Neuroscience Institute, Taipei Medical University, New Taipei City, Taiwan.,Department of Neurology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Jiann-Ruey Ong
- Department of Emergency Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan
| | - Yuan-Feng Lin
- Graduate Institute of Clinical Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Fei-Peng Lee
- Graduate Institute of Clinical Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.,Department of Otolaryngology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.,Department of Otolaryngology, Shuang Ho Hospital, Taipei Medical University, Taipei, Taiwan
| | - Chaur-Jong Hu
- Department of Neurology, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan.,Dizziness and Balance Disorder Center, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan.,Taipei Neuroscience Institute, Taipei Medical University, New Taipei City, Taiwan.,Department of Neurology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Yuan-Hung Wang
- Graduate Institute of Clinical Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.,Department of Medical Research, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan
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