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Liu D, Aziz NA, Landstra EN, Breteler MMB. The lipidomic correlates of epigenetic aging across the adult lifespan: A population-based study. Aging Cell 2023; 22:e13934. [PMID: 37496173 PMCID: PMC10497837 DOI: 10.1111/acel.13934] [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: 04/03/2023] [Revised: 07/05/2023] [Accepted: 07/07/2023] [Indexed: 07/28/2023] Open
Abstract
Lipid signaling is involved in longevity regulation, but which specific lipid molecular species affect human biological aging remains largely unknown. We investigated the relation between complex lipids and DNA methylation-based metrics of biological aging among 4181 participants (mean age 55.1 years (range 30.0-95.0)) from the Rhineland Study, an ongoing population-based cohort study in Bonn, Germany. The absolute concentration of 14 lipid classes, covering 964 molecular species and 267 fatty acid composites, was measured by Metabolon Complex Lipid Panel. DNA methylation-based metrics of biological aging (AgeAccelPheno and AgeAccelGrim) were calculated based on published algorithms. Epigenome-wide association analyses (EWAS) of biological aging-associated lipids and pathway analysis were performed to gain biological insights into the mechanisms underlying the effects of lipidomics on biological aging. We found that higher levels of molecular species belonging to neutral lipids, phosphatidylethanolamines, phosphatidylinositols, and dihydroceramides were associated with faster biological aging, whereas higher levels of lysophosphatidylcholine, hexosylceramide, and lactosylceramide species were associated with slower biological aging. Ceramide, phosphatidylcholine, and lysophosphatidylethanolamine species with odd-numbered fatty acid tail lengths were associated with slower biological aging, whereas those with even-numbered chain lengths were associated with faster biological aging. EWAS combined with functional pathway analysis revealed several complex lipids associated with biological aging as important regulators of known longevity and aging-related pathways.
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Affiliation(s)
- Dan Liu
- Population Health SciencesGerman Center for Neurodegenerative Diseases (DZNE)BonnGermany
| | - N. Ahmad Aziz
- Population Health SciencesGerman Center for Neurodegenerative Diseases (DZNE)BonnGermany
- Department of Neurology, Faculty of MedicineUniversity of BonnBonnGermany
| | - Elvire Nadieh Landstra
- Population Health SciencesGerman Center for Neurodegenerative Diseases (DZNE)BonnGermany
| | - Monique M. B. Breteler
- Population Health SciencesGerman Center for Neurodegenerative Diseases (DZNE)BonnGermany
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of MedicineUniversity of BonnBonnGermany
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Mu C, Zhao Q, Zhao Q, Yang L, Pang X, Liu T, Li X, Wang B, Fung SY, Cao H. Multi-omics in Crohn's disease: New insights from inside. Comput Struct Biotechnol J 2023; 21:3054-3072. [PMID: 37273853 PMCID: PMC10238466 DOI: 10.1016/j.csbj.2023.05.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 05/10/2023] [Accepted: 05/11/2023] [Indexed: 06/06/2023] Open
Abstract
Crohn's disease (CD) is an inflammatory bowel disease (IBD) with complex clinical manifestations such as chronic diarrhea, weight loss and hematochezia. Despite the increasing incidence worldwide, cure of CD remains extremely difficult. The rapid development of high-throughput sequencing technology with integrated-omics analyses in recent years has provided a new means for exploring the pathogenesis, mining the biomarkers and designing targeted personalized therapeutics of CD. Host genomics and epigenomics unveil heredity-related mechanisms of susceptible individuals, while microbiome and metabolomics map host-microbe interactions in CD patients. Proteomics shows great potential in searching for promising biomarkers. Nonetheless, single omics technology cannot holistically connect the mechanisms with heterogeneity of pathological behavior in CD. The rise of multi-omics analysis integrates genetic/epigenetic profiles with protein/microbial metabolite functionality, providing new hope for comprehensive and in-depth exploration of CD. Herein, we emphasized the different omics features and applications of CD and discussed the current research and limitations of multi-omics in CD. This review will update and deepen our understanding of CD from integration of broad omics spectra and will provide new evidence for targeted individualized therapeutics.
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Affiliation(s)
- Chenlu Mu
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Qianjing Zhao
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Qing Zhao
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Lijiao Yang
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Xiaoqi Pang
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Tianyu Liu
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Xiaomeng Li
- Department of Immunology, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Science, Tianjin Medical University, Tianjin, China
| | - Bangmao Wang
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Shan-Yu Fung
- Department of Immunology, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Science, Tianjin Medical University, Tianjin, China
| | - Hailong Cao
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
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Nie X, Mu G, Guo Y, Yang S, Wang X, Ye Z, Tan Q, Wang M, Zhou M, Ma J, Chen W. Associations of selenium exposure with blood lipids: Exploring mediating DNA methylation sites in general Chinese urban non-smokers. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 869:161815. [PMID: 36708841 DOI: 10.1016/j.scitotenv.2023.161815] [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: 10/31/2022] [Revised: 01/17/2023] [Accepted: 01/20/2023] [Indexed: 06/18/2023]
Abstract
Selenium (Se) is widely distributed in the total environment and people are commonly exposed to Se, while the potential effects and mechanisms of Se exposure on blood lipids have not been well established. This study aimed to assess the associations of urinary Se (SeU) with blood lipids and explore the potential mediating DNA methylation sites. We included 2844 non-smoke participants from the second follow-up (2017-2018) of the Wuhan-Zhuhai cohort (WHZH) in this study. SeU and blood lipids [i.e., total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL), and high-density lipoprotein cholesterol (HDL)] for all participants were determined. The associations of SeU with blood lipids were analyzed by generalized linear models. Then, we conducted the blood lipids related epigenome-wide association studies (EWAS) among 221 never smokers, and the mediation analysis was conducted to explore the potential mediating cytosine-phosphoguanine (CpG) sites in the above associations. In this study, the SeU concentration of the participants in this study was 1.40 (0.94, 2.08) μg/mmol Cr. The SeU was positively associated with TC and LDL, and not associated with TG and HDL. We found 131, 3, and 1 new CpG sites related to TC, HDL, and LDL, respectively. Mediation analyses found that the methylation of cg06964030 (within MIR1306) and cg15824094 (within PLCH2) significantly mediated the positive association between SeU and TC. In conclusion, high levels of Se exposure were associated with increased TC and LDL among non-smokers, and the methylation of MIR1306 and PLCH2 partly mediated Se-associated TC increase. These findings provide new insights into the effects and mechanisms of Se exposure on lipids metabolism and highlight the importance of controlling Se exposure and intake for preventing high blood lipids.
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Affiliation(s)
- Xiuquan Nie
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Ge Mu
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Yanjun Guo
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Shijie Yang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Xing Wang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Zi Ye
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Qiyou Tan
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Mengyi Wang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Min Zhou
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Jixuan Ma
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Weihong Chen
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
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Wu Z, Chen L, Hong X, Si J, Cao W, Yu C, Huang T, Sun D, Liao C, Pang Y, Pang Z, Cong L, Wang H, Wu X, Liu Y, Guo Y, Chen Z, Lv J, Gao W, Li L. Temporal associations between leukocytes DNA methylation and blood lipids: a longitudinal study. Clin Epigenetics 2022; 14:132. [PMID: 36274151 PMCID: PMC9588246 DOI: 10.1186/s13148-022-01356-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 10/13/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND The associations between blood lipids and DNA methylation have been investigated in epigenome-wide association studies mainly among European ancestry populations. Several studies have explored the direction of the association using cross-sectional data, while evidence of longitudinal data is still lacking. RESULTS We tested the associations between peripheral blood leukocytes DNA methylation and four lipid measures from Illumina 450 K or EPIC arrays in 1084 participants from the Chinese National Twin Registry and replicated the result in 988 participants from the China Kadoorie Biobank. A total of 23 associations of 19 CpG sites were identified, with 4 CpG sites located in or adjacent to 3 genes (TMEM49, SNX5/SNORD17 and CCDC7) being novel. Among the validated associations, we conducted a cross-lagged analysis to explore the temporal sequence and found temporal associations of methylation levels of 2 CpG sites with triglyceride and 2 CpG sites with high-density lipoprotein-cholesterol (HDL-C) in all twins. In addition, methylation levels of cg11024682 located in SREBF1 at baseline were temporally associated with triglyceride at follow-up in only monozygotic twins. We then performed a mediation analysis with the longitudinal data and the result showed that the association between body mass index and HDL-C was partially mediated by the methylation level of cg06500161 (ABCG1), with a mediation proportion of 10.1%. CONCLUSIONS Our study indicated that the DNA methylation levels of ABCG1, AKAP1 and SREBF1 may be involved in lipid metabolism and provided evidence for elucidating the regulatory mechanism of lipid homeostasis.
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Affiliation(s)
- Zhiyu Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Lu Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Xuanming Hong
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Jiahui Si
- National Institute of Health Data Science at Peking University, Peking University, Beijing, 100191, China
| | - Weihua Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, 100191, China
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Chunxiao Liao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Zengchang Pang
- Qingdao Center for Disease Control and Prevention, Qingdao, 266033, China
| | - Liming Cong
- Zhejiang Center for Disease Control and Prevention, Hangzhou, 310051, China
| | - Hua Wang
- Jiangsu Center for Disease Control and Prevention, Nanjing, 210008, China
| | - Xianping Wu
- Sichuan Center for Disease Control and Prevention, Chengdu, 610041, China
| | - Yu Liu
- Heilongjiang Center for Disease Control and Prevention, Harbin, 150090, China
| | - Yu Guo
- Fuwai hospital Chinese Academy of Medical Sciences, Beijing, 100037, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, 100191, China
- Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing, 100191, China
| | - Wenjing Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, 100191, China.
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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: 5.3] [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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Fragoso-Bargas N, Opsahl JO, Kiryushchenko N, Böttcher Y, Lee-Ødegård S, Qvigstad E, Richardsen KR, Waage CW, Sletner L, Jenum AK, Prasad RB, Groop LC, Moen GH, Birkeland KI, Sommer C. Cohort profile: Epigenetics in Pregnancy (EPIPREG) - population-based sample of European and South Asian pregnant women with epigenome-wide DNA methylation (850k) in peripheral blood leukocytes. PLoS One 2021; 16:e0256158. [PMID: 34388220 PMCID: PMC8362992 DOI: 10.1371/journal.pone.0256158] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 08/01/2021] [Indexed: 11/26/2022] Open
Abstract
Pregnancy is a valuable model to study the association between DNA methylation and several cardiometabolic traits, due to its direct potential to influence mother's and child's health. Epigenetics in Pregnancy (EPIPREG) is a population-based sample with the aim to study associations between DNA-methylation in pregnancy and cardiometabolic traits in South Asian and European pregnant women and their offspring. This cohort profile paper aims to present our sample with genetic and epigenetic data and invite researchers with similar cohorts to collaborative projects, such as replication of ours or their results and meta-analysis. In EPIPREG we have quantified epigenome-wide DNA methylation in maternal peripheral blood leukocytes in gestational week 28±1 in Europeans (n = 312) and South Asians (n = 168) that participated in the population-based cohort STORK Groruddalen, in Norway. DNA methylation was measured with Infinium MethylationEPIC BeadChip (850k sites), with technical validation of four CpG sites using bisulphite pyrosequencing in a subset (n = 30). The sample is well characterized with few missing data on e.g. genotype, universal screening for gestational diabetes, objectively measured physical activity, bioelectrical impedance, anthropometrics, biochemical measurements, and a biobank with maternal serum and plasma, urine, placenta tissue. In the offspring, we have repeated ultrasounds during pregnancy, cord blood, and anthropometrics up to 4 years of age. We have quantified DNA methylation in peripheral blood leukocytes in nearly all eligible women from the STORK Groruddalen study, to minimize the risk of selection bias. Genetic principal components distinctly separated Europeans and South Asian women, which fully corresponded with the self-reported ethnicity. Technical validation of 4 CpG sites from the methylation bead chip showed good agreement with bisulfite pyrosequencing. We plan to study associations between DNA methylation and cardiometabolic traits and outcomes.
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Affiliation(s)
- Nicolas Fragoso-Bargas
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Julia O. Opsahl
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Nadezhda Kiryushchenko
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
- Department of Bioscience, University of Oslo, Oslo, Norway
| | - Yvonne Böttcher
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Clinical Molecular Biology, Akershus University Hospital, Lørenskog, Norway
- Helmholtz-Institute for Metabolic, Adiposity and Vascular Research, Leipzig, Germany
| | | | - Elisabeth Qvigstad
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kåre Rønn Richardsen
- Faculty of Health Sciences, Department of Physiotherapy, Oslo Metropolitan University, Oslo, Norway
| | - Christin W. Waage
- Faculty of Health Sciences, Department of Physiotherapy, Oslo Metropolitan University, Oslo, Norway
- Department of General Practice, General Practice Research Unit (AFE), Institute of Health and Society, University of Oslo, Oslo, Norway
| | - Line Sletner
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Pediatric and Adolescents Medicine, Akershus University Hospital, Lørenskog, Norway
| | - Anne Karen Jenum
- Department of General Practice, General Practice Research Unit (AFE), Institute of Health and Society, University of Oslo, Oslo, Norway
| | | | | | - Gunn-Helen Moen
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, QLD, Australia
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Kåre I. Birkeland
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Christine Sommer
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
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Legrand A, Iftimovici A, Khayachi A, Chaumette B. Epigenetics in bipolar disorder: a critical review of the literature. Psychiatr Genet 2021; 31:1-12. [PMID: 33290382 DOI: 10.1097/ypg.0000000000000267] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
INTRODUCTION Bipolar disorder (BD) is a chronic, disabling disease characterised by alternate mood episodes, switching through depressive and manic/hypomanic phases. Mood stabilizers, in particular lithium salts, constitute the cornerstone of the treatment in the acute phase as well as for the prevention of recurrences. The pathophysiology of BD and the mechanisms of action of mood stabilizers remain largely unknown but several pieces of evidence point to gene x environment interactions. Epigenetics, defined as the regulation of gene expression without genetic changes, could be the molecular substrate of these interactions. In this literature review, we summarize the main epigenetic findings associated with BD and response to mood stabilizers. METHODS We searched PubMed, and Embase databases and classified the articles depending on the epigenetic mechanisms (DNA methylation, histone modifications and non-coding RNAs). RESULTS We present the different epigenetic modifications associated with BD or with mood-stabilizers. The major reported mechanisms were DNA methylation, histone methylation and acetylation, and non-coding RNAs. Overall, the assessments are poorly harmonized and the results are more limited than in other psychiatric disorders (e.g. schizophrenia). However, the nature of BD and its treatment offer excellent opportunities for epigenetic research: clear impact of environmental factors, clinical variation between manic or depressive episodes resulting in possible identification of state and traits biomarkers, documented impact of mood-stabilizers on the epigenome. CONCLUSION Epigenetic is a growing and promising field in BD that may shed light on its pathophysiology or be useful as biomarkers of response to mood-stabilizer.
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Affiliation(s)
- Adrien Legrand
- Université de Paris, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Paris
| | - Anton Iftimovici
- Université de Paris, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Paris
- Neurospin, CEA, Gif-sur-Yvette, France
| | - Anouar Khayachi
- Department of Neurology and Neurosurgery, Montreal Neurological Institute-Hospital, McGill University, Montreal, Canada
| | - Boris Chaumette
- Université de Paris, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Paris
- GHU Paris Psychiatrie et Neurosciences, Hôpital Sainte Anne, Paris, France
- Department of Psychiatry, McGill University, Montreal, Canada
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Abstract
Cardiovascular diseases are the leading cause of death worldwide. Complex diseases with highly heterogenous disease progression among patient populations, cardiovascular diseases feature multifactorial contributions from both genetic and environmental stressors. Despite significant effort utilizing multiple approaches from molecular biology to genome-wide association studies, the genetic landscape of cardiovascular diseases, particularly for the nonfamilial forms of heart failure, is still poorly understood. In the past decade, systems-level approaches based on omics technologies have become an important approach for the study of complex traits in large populations. These advances create opportunities to integrate genetic variation with other biological layers to identify and prioritize candidate genes, understand pathogenic pathways, and elucidate gene-gene and gene-environment interactions. In this review, we will highlight some of the recent progress made using systems genetics approaches to uncover novel mechanisms and molecular bases of cardiovascular pathophysiological manifestations. The key technology and data analysis platforms necessary to implement systems genetics will be described, and the current major challenges and future directions will also be discussed. For complex cardiovascular diseases, such as heart failure, systems genetics represents a powerful strategy to obtain mechanistic insights and to develop individualized diagnostic and therapeutic regiments, paving the way for precision cardiovascular medicine.
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Affiliation(s)
- Christoph D. Rau
- Departments of Anesthesiology, Medicine, Physiology
- Current address: Department of Genetics, University of North Carolina School of Medicine, Chapel Hill, NC 27599
| | - Aldons J. Lusis
- Department of Human Genetics and Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA 90095
| | - Yibin Wang
- Departments of Anesthesiology, Medicine, Physiology
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9
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Curtis SW, Gerkowicz SA, Cobb DO, Kilaru V, Terrell ML, Marder ME, Barr DB, Marsit CJ, Marcus M, Conneely KN, Smith AK. Sex-specific DNA methylation differences in people exposed to polybrominated biphenyl. Epigenomics 2020; 12:757-770. [PMID: 32496131 DOI: 10.2217/epi-2019-0179] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Aim: Michigan residents were exposed to polybrominated biphenyls (PBBs) when it was accidentally added to the food supply. Highly exposed individuals report sex-specific health problems, but the underlying biological mechanism behind these different health risks is not known. Materials and methods: DNA methylation in blood from 381 women and 277 men with PBB exposure was analyzed with the MethylationEPIC BeadChip. Results: 675 CpGs were associated with PBBs levels in males, while only 17 CpGs were associated in females (false discovery rate <0.05). No CpGs were associated in both sexes. These CpGs were enriched in different functional regions and transcription factor binding sites in each sex. Conclusion: Exposure to PBBs may have sex-specific effects on the epigenome that may underlie sex-specific adverse health outcomes.
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Affiliation(s)
- Sarah W Curtis
- Genetics & Molecular Biology Program, Laney Graduate School, Emory University School of Medicine, 101 Woodruff Circle NE, Ste 4217, Atlanta, GA 30322, USA
| | - Sabrina A Gerkowicz
- Department of Gynecology & Obstetrics, Emory University School of Medicine, 101 Woodruff Circle NE, Ste 4217, Atlanta, GA 30322, USA
| | - Dawayland O Cobb
- Department of Gynecology & Obstetrics, Emory University School of Medicine, 101 Woodruff Circle NE, Ste 4217, Atlanta, GA 30322, USA
| | - Varun Kilaru
- Department of Gynecology & Obstetrics, Emory University School of Medicine, 101 Woodruff Circle NE, Ste 4217, Atlanta, GA 30322, USA
| | - Metrecia L Terrell
- Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Rd, Atlanta, GA 30322, USA
| | - M Elizabeth Marder
- Department of Environmental Health, Emory University Rollins School of Public Health, 1518 Clifton Rd, Atlanta, GA 30322, USA
| | - Dana Boyd Barr
- Department of Environmental Health, Emory University Rollins School of Public Health, 1518 Clifton Rd, Atlanta, GA 30322, USA
| | - Carmen J Marsit
- Department of Environmental Health, Emory University Rollins School of Public Health, 1518 Clifton Rd, Atlanta, GA 30322, USA
| | - Michele Marcus
- Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Rd, Atlanta, GA 30322, USA.,Department of Pediatrics Emory University School of Medicine, 1518 Clifton Rd, Atlanta, GA 30322, USA
| | - Karen N Conneely
- Department of Human Genetics, Emory University School of Medicine, 615 Michael St, Atlanta, GA 30322, USA
| | - Alicia K Smith
- Department of Gynecology & Obstetrics, Emory University School of Medicine, 101 Woodruff Circle NE, Ste 4217, Atlanta, GA 30322, USA.,Department of Psychiatry & Behavioral Science, Emory University School of Medicine, 101 Woodruff Circle NE, Ste 4217, Atlanta, GA 30322, USA
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10
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Ouidir M, Zeng X, Workalemahu T, Shrestha D, Grantz KL, Mendola P, Zhang C, Tekola-Ayele F. Early pregnancy dyslipidemia is associated with placental DNA methylation at loci relevant for cardiometabolic diseases. Epigenomics 2020; 12:921-934. [PMID: 32677467 PMCID: PMC7466909 DOI: 10.2217/epi-2019-0293] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Accepted: 04/07/2020] [Indexed: 02/07/2023] Open
Abstract
Aim: To identify placental DNA methylation changes that are associated with early pregnancy maternal dyslipidemia. Materials & methods: We analyzed placental genome-wide DNA methylation (n = 262). Genes annotating differentially methylated CpGs were evaluated for gene expression in placenta (n = 64). Results: We found 11 novel significant differentially methylated CpGs associated with high total cholesterol, low-density lipoprotein cholesterol and triglycerides, and low high-density lipoprotein cholesterol. High triglycerides were associated with decreased methylation of cg02785814 (ALX4) and decreased expression of ALX4 in placenta. Genes annotating the differentially methylated CpGs play key roles in lipid metabolism and were enriched in dyslipidemia pathways. Functional annotation found cis-methylation quantitative trait loci for genetic loci in ALX4 and EXT2. Conclusion: Our findings lend novel insights into potential placental epigenetic mechanisms linked with maternal dyslipidemia. Trial Registration: ClinicalTrials.gov, NCT00912132.
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Affiliation(s)
- Marion Ouidir
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Xuehuo Zeng
- Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Tsegaselassie Workalemahu
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Deepika Shrestha
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Katherine L. Grantz
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Pauline Mendola
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Cuilin Zhang
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Fasil Tekola-Ayele
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
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11
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Chen Z, Pang M, Zhao Z, Li S, Miao R, Zhang Y, Feng X, Feng X, Zhang Y, Duan M, Huang L, Zhou F. Feature selection may improve deep neural networks for the bioinformatics problems. Bioinformatics 2019; 36:1542-1552. [DOI: 10.1093/bioinformatics/btz763] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Revised: 09/03/2019] [Accepted: 10/02/2019] [Indexed: 12/22/2022] Open
Abstract
Abstract
Motivation
Deep neural network (DNN) algorithms were utilized in predicting various biomedical phenotypes recently, and demonstrated very good prediction performances without selecting features. This study proposed a hypothesis that the DNN models may be further improved by feature selection algorithms.
Results
A comprehensive comparative study was carried out by evaluating 11 feature selection algorithms on three conventional DNN algorithms, i.e. convolution neural network (CNN), deep belief network (DBN) and recurrent neural network (RNN), and three recent DNNs, i.e. MobilenetV2, ShufflenetV2 and Squeezenet. Five binary classification methylomic datasets were chosen to calculate the prediction performances of CNN/DBN/RNN models using feature selected by the 11 feature selection algorithms. Seventeen binary classification transcriptome and two multi-class transcriptome datasets were also utilized to evaluate how the hypothesis may generalize to different data types. The experimental data supported our hypothesis that feature selection algorithms may improve DNN models, and the DBN models using features selected by SVM-RFE usually achieved the best prediction accuracies on the five methylomic datasets.
Availability and implementation
All the algorithms were implemented and tested under the programming environment Python version 3.6.6.
Supplementary information
Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Zheng Chen
- BioKnow Health Informatics Lab, College of Computer Science and Technology
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, China
| | - Meng Pang
- BioKnow Health Informatics Lab, College of Computer Science and Technology
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, China
| | - Zixin Zhao
- BioKnow Health Informatics Lab, College of Computer Science and Technology
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, China
| | - Shuainan Li
- BioKnow Health Informatics Lab, College of Computer Science and Technology
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, China
| | - Rui Miao
- BioKnow Health Informatics Lab, College of Computer Science and Technology
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, China
| | - Yifan Zhang
- BioKnow Health Informatics Lab, College of Computer Science and Technology
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, China
| | - Xiaoyue Feng
- BioKnow Health Informatics Lab, College of Computer Science and Technology
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, China
| | - Xin Feng
- BioKnow Health Informatics Lab, College of Computer Science and Technology
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, China
| | - Yexian Zhang
- BioKnow Health Informatics Lab, College of Computer Science and Technology
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, China
| | - Meiyu Duan
- BioKnow Health Informatics Lab, College of Computer Science and Technology
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, China
| | - Lan Huang
- BioKnow Health Informatics Lab, College of Computer Science and Technology
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, China
| | - Fengfeng Zhou
- BioKnow Health Informatics Lab, College of Computer Science and Technology
- Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, China
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