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Li X, Lyu C, Luo Z, Zhao J, Wang Z, Yang C, Dai Q, Li H, Zhou Y, Li Z, Chen F, Gao Y. The roles of IGF2 and DNMT methylation and elongase6 related fatty acids in metabolic syndrome. Food Funct 2021; 12:10253-10262. [PMID: 34549217 DOI: 10.1039/d1fo00502b] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Background: The prevalence of metabolic syndrome (MetS) has increased along with rapid socio-economic development in China in recent decades, aggravating the burden of the health care system. Both plasma levels of fatty acids (FAs) and aberrant DNA methylation profiles are associated with MetS risk. However, studies exploring the role of DNA methylation and FAs simultaneously in MetS etiology are sparse. Objective: We aimed to explore the association between the gene methylation levels of insulin-like growth factor II (IGF2), H19, DNA methyltransferases 1 (DNMT1), DNA methyltransferases 3a (DNMT3a), and DNA methyltransferases 3b (DNMT3b) and MetS risk, and the etiological role of elongation of very-long-chain fatty acid elongase 6 (ELOVL6) related fatty acids. Method: Plasma levels of FAs were measured using a Gas Chromatography-Flame Ionization Detector (GC-FID) after organic extraction, and gene methylation was quantified using a real-time Quantitative Polymerase Chain Reaction (Q-PCR) detecting system after bisulfite treatment. The C18/C16 ratio was used as the indicator of ELOVL6 activity. Odds Ratio (OR) and 95% Confidence Interval (CI) were estimated with logistic regression. Results: Methylation levels in IGF2 and DNMT3a were not significantly associated with MetS risk. However, when stratified by C18/C16 ratio (high vs. low), positive associations were observed between the risk of MetS and methylation levels (>median) of IGF2a3 (OR = 3.1, 95% CI = 1.3-7.5) and DNMT3a (OR = 2.5, 95% CI = 1.1-5.8) genes, in individuals with lower C18/C16 ratios, while no significant associations were observed in subjects with high C18/C16 ratios. Conclusion: Methylation levels in IGF2 and DNMT3a genes may affect the risk of MetS in an ELOVL6 activity-dependent way among Chinese adults. Further studies in other populations are needed to validate this finding.
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Affiliation(s)
- Xiang Li
- CAS Key Laboratory of Nutrition Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
- School of Life Sciences, Shanghai University, Shanghai, China
| | - Chen Lyu
- Department of Epidemiology and Biostatistics, School of Public Health-Bloomington, Indiana University, Bloomington, USA
| | - ZhongCheng Luo
- Lunenfeld-Tanenbaum Research Institute, Obstetrics and Gynecology, Mount Sinai Hospital, University of Toronto, Toronto, Canada
| | - Jing Zhao
- CAS Key Laboratory of Nutrition Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
| | - Zhongli Wang
- Department of Rehabilitation Medicine, The Second Affiliated Hospital of Jiaxing University, The Second Hospital of Jiaxing, Jiaxing, China
| | - Chun Yang
- School of Public Health, Capital Medical University, Beijing, China
| | - Qi Dai
- CAS Key Laboratory of Nutrition Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
| | - Hui Li
- Department of Nutrition and Food Hygiene, School of Public Health, Peking University, Beijing, China
| | - Yunhua Zhou
- CAS Key Laboratory of Nutrition Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
| | - Zi Li
- CAS Key Laboratory of Nutrition Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
| | - Fuxue Chen
- School of Life Sciences, Shanghai University, Shanghai, China
| | - Ying Gao
- CAS Key Laboratory of Nutrition Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
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Wei S, Tao J, Xu J, Chen X, Wang Z, Zhang N, Zuo L, Jia Z, Chen H, Sun H, Yan Y, Zhang M, Lv H, Kong F, Duan L, Ma Y, Liao M, Xu L, Feng R, Liu G, Project TEWAS, Jiang Y. Ten Years of EWAS. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2021; 8:e2100727. [PMID: 34382344 PMCID: PMC8529436 DOI: 10.1002/advs.202100727] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 05/11/2021] [Indexed: 06/13/2023]
Abstract
Epigenome-wide association study (EWAS) has been applied to analyze DNA methylation variation in complex diseases for a decade, and epigenome as a research target has gradually become a hot topic of current studies. The DNA methylation microarrays, next-generation, and third-generation sequencing technologies have prepared a high-quality platform for EWAS. Here, the progress of EWAS research is reviewed, its contributions to clinical applications, and mainly describe the achievements of four typical diseases. Finally, the challenges encountered by EWAS and make bold predictions for its future development are presented.
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Affiliation(s)
- Siyu Wei
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
- The EWAS ProjectHarbinChina
| | - Junxian Tao
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
- The EWAS ProjectHarbinChina
| | - Jing Xu
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
- The EWAS ProjectHarbinChina
| | - Xingyu Chen
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Zhaoyang Wang
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Nan Zhang
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Lijiao Zuo
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Zhe Jia
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Haiyan Chen
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Hongmei Sun
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Yubo Yan
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Mingming Zhang
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Hongchao Lv
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Fanwu Kong
- The EWAS ProjectHarbinChina
- Department of NephrologyThe Second Affiliated HospitalHarbin Medical UniversityHarbin150001China
| | - Lian Duan
- The EWAS ProjectHarbinChina
- The First Affiliated Hospital of Wenzhou Medical UniversityWenzhou325000China
| | - Ye Ma
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
- The EWAS ProjectHarbinChina
| | - Mingzhi Liao
- The EWAS ProjectHarbinChina
- College of Life SciencesNorthwest A&F UniversityYanglingShanxi712100China
| | - Liangde Xu
- The EWAS ProjectHarbinChina
- School of Biomedical EngineeringWenzhou Medical UniversityWenzhou325035China
| | - Rennan Feng
- The EWAS ProjectHarbinChina
- Department of Nutrition and Food HygienePublic Health CollegeHarbin Medical UniversityHarbin150081China
| | - Guiyou Liu
- The EWAS ProjectHarbinChina
- Beijing Institute for Brain DisordersCapital Medical UniversityBeijing100069China
| | | | - Yongshuai Jiang
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
- The EWAS ProjectHarbinChina
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3
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Joo JE, Clendenning M, Wong EM, Rosty C, Mahmood K, Georgeson P, Winship IM, Preston SG, Win AK, Dugué PA, Jayasekara H, English D, Macrae FA, Hopper JL, Jenkins MA, Milne RL, Giles GG, Southey MC, Buchanan DD. DNA Methylation Signatures and the Contribution of Age-Associated Methylomic Drift to Carcinogenesis in Early-Onset Colorectal Cancer. Cancers (Basel) 2021; 13:cancers13112589. [PMID: 34070516 PMCID: PMC8199056 DOI: 10.3390/cancers13112589] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 05/14/2021] [Accepted: 05/19/2021] [Indexed: 12/12/2022] Open
Abstract
Simple Summary The role of DNA methylation in the carcinogenesis of colorectal cancer (CRC) diagnosed <50 years of age (early-onset CRC or EOCRC) is currently unknown. In this study, we investigated the genome-wide DNA methylation of 97 tumour and 54 normal colonic mucosa samples from people with EOCRC with the aim of identifying unique DNA methylation signatures and determining the role of ageing-related DNA methylation drift and age-acceleration in EOCRC aetiology. We found extensive DNA methylation alterations associated with EOCRC carcinogenesis, including a unique signature comprising 234 loci compared with CRCs from people >50 years of age. CpGs that undergo ageing-related methylation drift were significantly altered in EOCRC, and accelerated ageing was also evident in normal mucosa from people with EOCRC. Our study is the first study to identify unique DNA methylation changes in EOCRC, contributing novel information that may aid future efforts towards EOCRC prevention. Abstract We investigated aberrant DNA methylation (DNAm) changes and the contribution of ageing-associated methylomic drift and age acceleration to early-onset colorectal cancer (EOCRC) carcinogenesis. Genome-wide DNAm profiling using the Infinium HM450K on 97 EOCRC tumour and 54 normal colonic mucosa samples was compared with: (1) intermediate-onset CRC (IOCRC; diagnosed between 50–70 years; 343 tumour and 35 normal); and (2) late-onset CRC (LOCRC; >70 years; 318 tumour and 40 normal). CpGs associated with age-related methylation drift were identified using a public dataset of 231 normal mucosa samples from people without CRC. DNAm-age was estimated using epiTOC2. Common to all three age-of-onset groups, 88,385 (20% of all CpGs) CpGs were differentially methylated between tumour and normal mucosa. We identified 234 differentially methylated genes that were unique to the EOCRC group; 13 of these DMRs/genes were replicated in EOCRC compared with LOCRCs from TCGA. In normal mucosa from people without CRC, we identified 28,154 CpGs that undergo ageing-related DNAm drift, and of those, 65% were aberrantly methylated in EOCRC tumours. Based on the mitotic-based DNAm clock epiTOC2, we identified age acceleration in normal mucosa of people with EOCRC compared with normal mucosa from the IOCRC, LOCRC groups (p = 3.7 × 10−16) and young people without CRC (p = 5.8 × 10−6). EOCRC acquires unique DNAm alterations at 234 loci. CpGs associated with ageing-associated drift were widely affected in EOCRC without needing the decades-long accrual of DNAm drift as commonly seen in intermediate- and late-onset CRCs. Accelerated ageing in normal mucosa from people with EOCRC potentially underlies the earlier age of diagnosis in CRC carcinogenesis.
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Affiliation(s)
- Jihoon E. Joo
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Melbourne 3010, Australia; (J.E.J.); (M.C.); (C.R.); (K.M.); (P.G.); (S.G.P.); (H.J.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Melbourne 3000, Australia
| | - Mark Clendenning
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Melbourne 3010, Australia; (J.E.J.); (M.C.); (C.R.); (K.M.); (P.G.); (S.G.P.); (H.J.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Melbourne 3000, Australia
| | - Ee Ming Wong
- Precision Medicine, Monash Health, Monash University, Clayton, Melbourne 3800, Australia; (E.M.W.); (P.-A.D.); (R.L.M.); (G.G.G.); (M.C.S.)
| | - Christophe Rosty
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Melbourne 3010, Australia; (J.E.J.); (M.C.); (C.R.); (K.M.); (P.G.); (S.G.P.); (H.J.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Melbourne 3000, Australia
- School of Medicine, University of Queensland, Herston, Brisbane 4006, Australia
- Envoi Pathology, Brisbane 4059, Australia
| | - Khalid Mahmood
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Melbourne 3010, Australia; (J.E.J.); (M.C.); (C.R.); (K.M.); (P.G.); (S.G.P.); (H.J.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Melbourne 3000, Australia
- Melbourne Bioinformatics, The University of Melbourne, Parkville, Melbourne 3010, Australia
| | - Peter Georgeson
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Melbourne 3010, Australia; (J.E.J.); (M.C.); (C.R.); (K.M.); (P.G.); (S.G.P.); (H.J.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Melbourne 3000, Australia
| | - Ingrid M. Winship
- Department of Medicine, The Royal Melbourne Hospital, University of Melbourne, Parkville, Melbourne 3050, Australia; (I.M.W.); (F.A.M.)
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Melbourne 3050, Australia
| | - Susan G. Preston
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Melbourne 3010, Australia; (J.E.J.); (M.C.); (C.R.); (K.M.); (P.G.); (S.G.P.); (H.J.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Melbourne 3000, Australia
| | - Aung Ko Win
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne 3010, Australia; (A.K.W.); (D.E.); (J.L.H.); (M.A.J.)
| | - Pierre-Antoine Dugué
- Precision Medicine, Monash Health, Monash University, Clayton, Melbourne 3800, Australia; (E.M.W.); (P.-A.D.); (R.L.M.); (G.G.G.); (M.C.S.)
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne 3010, Australia; (A.K.W.); (D.E.); (J.L.H.); (M.A.J.)
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne 3004, Australia
| | - Harindra Jayasekara
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Melbourne 3010, Australia; (J.E.J.); (M.C.); (C.R.); (K.M.); (P.G.); (S.G.P.); (H.J.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Melbourne 3000, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne 3004, Australia
| | - Dallas English
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne 3010, Australia; (A.K.W.); (D.E.); (J.L.H.); (M.A.J.)
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne 3004, Australia
| | - Finlay A. Macrae
- Department of Medicine, The Royal Melbourne Hospital, University of Melbourne, Parkville, Melbourne 3050, Australia; (I.M.W.); (F.A.M.)
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Melbourne 3050, Australia
- Colorectal Medicine and Genetics, The Royal Melbourne Hospital, Parkville, Melbourne 3050, Australia
| | - John L. Hopper
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne 3010, Australia; (A.K.W.); (D.E.); (J.L.H.); (M.A.J.)
| | - Mark A. Jenkins
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne 3010, Australia; (A.K.W.); (D.E.); (J.L.H.); (M.A.J.)
| | - Roger L. Milne
- Precision Medicine, Monash Health, Monash University, Clayton, Melbourne 3800, Australia; (E.M.W.); (P.-A.D.); (R.L.M.); (G.G.G.); (M.C.S.)
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne 3010, Australia; (A.K.W.); (D.E.); (J.L.H.); (M.A.J.)
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne 3004, Australia
| | - Graham G. Giles
- Precision Medicine, Monash Health, Monash University, Clayton, Melbourne 3800, Australia; (E.M.W.); (P.-A.D.); (R.L.M.); (G.G.G.); (M.C.S.)
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne 3010, Australia; (A.K.W.); (D.E.); (J.L.H.); (M.A.J.)
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne 3004, Australia
| | - Melissa C. Southey
- Precision Medicine, Monash Health, Monash University, Clayton, Melbourne 3800, Australia; (E.M.W.); (P.-A.D.); (R.L.M.); (G.G.G.); (M.C.S.)
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne 3004, Australia
- Department of Clinical Pathology, The University of Melbourne, Parkville, Melbourne 3010, Australia
| | - Daniel D. Buchanan
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Melbourne 3010, Australia; (J.E.J.); (M.C.); (C.R.); (K.M.); (P.G.); (S.G.P.); (H.J.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Melbourne 3000, Australia
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Melbourne 3050, Australia
- Correspondence: ; Tel.: +61-3-8559-7004
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4
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Gu Y, Liu X, Liao L, Gao Y, Shi Y, Ni J, He G. Relationship between lipid metabolism and Hedgehog signaling pathway. J Steroid Biochem Mol Biol 2021; 209:105825. [PMID: 33529733 DOI: 10.1016/j.jsbmb.2021.105825] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2020] [Revised: 10/28/2020] [Accepted: 01/13/2021] [Indexed: 02/08/2023]
Abstract
The Hedgehog (Hh) signaling pathway is highly conserved signaling pathway in cells. Steroids was found to play a vital role in Hh signaling pathway and aberrant Hh signaling was found to lead a series of disease correlate with abnormal lipid metabolism. This paper aimed to elucidate the relationship between lipid metabolism and Hedgehog signaling pathway.
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Affiliation(s)
- Yuan Gu
- Department of Orthopedics, The Second Xiangya Hospital, Central South University, Hunan 410011, PR China
| | - Xiaochen Liu
- University of Toledo Medical Center 3000 Arlington Ave. Toledo, OH 43614, USA
| | - Lele Liao
- Department of Orthopedics, The Second Xiangya Hospital, Central South University, Hunan 410011, PR China
| | - Yongquan Gao
- Department of Orthopedics, The Second Xiangya Hospital, Central South University, Hunan 410011, PR China
| | - Yu Shi
- West China School of Stomatology, Sichuan University, Chengdu 610041, PR China; State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, PR China
| | - Jiangdong Ni
- Department of Orthopedics, The Second Xiangya Hospital, Central South University, Hunan 410011, PR China
| | - Guangxu He
- Department of Orthopedics, The Second Xiangya Hospital, Central South University, Hunan 410011, PR China.
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5
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Epigenetic pacemaker: closed form algebraic solutions. BMC Genomics 2020; 21:257. [PMID: 32299339 PMCID: PMC7161103 DOI: 10.1186/s12864-020-6606-0] [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] [Indexed: 12/04/2022] Open
Abstract
Background DNA methylation is widely used as a biomarker in crucial medical applications as well as for human age prediction of very high accuracy. This biomarker is based on the methylation status of several hundred CpG sites. In a recent line of publications we have adapted a versatile concept from evolutionary biology - the Universal Pacemaker (UPM) - to the setting of epigenetic aging and denoted it the Epigenetic PaceMaker (EPM). The EPM, as opposed to other epigenetic clocks, is not confined to specific pattern of aging, and the epigenetic age of the individual is inferred independently of other individuals. This allows an explicit modeling of aging trends, in particular non linear relationship between chronological and epigenetic age. In one of these recent works, we have presented an algorithmic improvement based on a two-step conditional expectation maximization (CEM) algorithm to arrive at a critical point on the likelihood surface. The algorithm alternates between a time step and a site step while advancing on the likelihood surface. Results Here we introduce non trivial improvements to these steps that are essential for analyzing data sets of realistic magnitude in a manageable time and space. These structural improvements are based on insights from linear algebra and symbolic algebra tools, providing us greater understanding of the degeneracy of the complex problem space. This understanding in turn, leads to the complete elimination of the bottleneck of cumbersome matrix multiplication and inversion, yielding a fast closed form solution in both steps of the CEM.In the experimental results part, we compare the CEM algorithm over several data sets and demonstrate the speedup obtained by the closed form solutions. Our results support the theoretical analysis of this improvement. Conclusions These improvements enable us to increase substantially the scale of inputs analyzed by the method, allowing us to apply the new approach to data sets that could not be analyzed before.
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6
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Johnson ND, Huang L, Li R, Li Y, Yang Y, Kim HR, Grant C, Wu H, Whitsel EA, Kiel DP, Baccarelli AA, Jin P, Murabito JM, Conneely KN. Age-related DNA hydroxymethylation is enriched for gene expression and immune system processes in human peripheral blood. Epigenetics 2019; 15:294-306. [PMID: 31506003 DOI: 10.1080/15592294.2019.1666651] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
DNA methylation (DNAm) has a well-established association with age in many tissues, including peripheral blood mononuclear cells (PBMCs). Compared to DNAm, the closely related epigenetic modification known as DNA hydroxymethylation (DNAhm) was much more recently discovered in mammals. Preliminary investigations have observed a positive correlation between gene body DNAhm and cis-gene expression. While some of these studies have observed an association between age and global DNAhm, none have investigated region-specific age-related DNAhm in human blood samples. In this study, we investigated DNAhm and gene expression in PBMCs of 10 young and 10 old, healthy female volunteers. Thousands of regions were differentially hydroxymethylated in the old vs. young individuals in gene bodies, exonic regions, enhancers, and promoters. Consistent with previous work, we observed directional consistency between age-related differences in DNAhm and gene expression. Further, age-related DNAhm and genes with high levels of DNAhm were enriched for immune system processes which may support a role of age-related DNAhm in immunosenescence.
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Affiliation(s)
- Nicholas D Johnson
- Department of Human Genetics, Emory University, Atlanta, GA, USA.,Population Biology, Ecology, and Evolution Program, Emory University, Atlanta, GA, USA
| | - Luoxiu Huang
- Department of Human Genetics, Emory University, Atlanta, GA, USA
| | - Ronghua Li
- Department of Human Genetics, Emory University, Atlanta, GA, USA
| | - Yun Li
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.,Department of Biostatistics, Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA
| | - Yuchen Yang
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Hye Rim Kim
- Department of Human Genetics, Emory University, Atlanta, GA, USA.,Cancer Biology Graduate Program, Emory University, Atlanta, GA, USA
| | - Crystal Grant
- Department of Human Genetics, Emory University, Atlanta, GA, USA.,Genetics and Molecular Biology Graduate Program, Emory University, Atlanta, GA, USA
| | - Hao Wu
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.,Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Douglas P Kiel
- Hebrew SeniorLife, Department of Medicine Beth Israel Deaconess Medical Center and Harvard Medical School, Hinda and Arthur Marcus Institute for Aging Research, Boston, MA, USA
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Peng Jin
- Department of Human Genetics, Emory University, Atlanta, GA, USA
| | - Joanne M Murabito
- National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA.,Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Karen N Conneely
- Department of Human Genetics, Emory University, Atlanta, GA, USA.,Population Biology, Ecology, and Evolution Program, Emory University, Atlanta, GA, USA
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7
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Snir S, Farrell C, Pellegrini M. Human epigenetic ageing is logarithmic with time across the entire lifespan. Epigenetics 2019; 14:912-926. [PMID: 31138013 DOI: 10.1080/15592294.2019.1623634] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Epigenetic changes during ageing have been characterized by multiple epigenetic clocks that allow the prediction of chronological age based on methylation status. Despite their accuracy and utility, epigenetic age biomarkers leave many questions about epigenetic ageing unanswered. Specifically, they do not permit the unbiased characterization of non-linear epigenetic ageing trends across entire life spans, a critical question underlying this field of research. Here we provide an integrated framework to address this question. Our model, inspired from evolutionary models, is able to account for acceleration/deceleration in epigenetic changes by fitting an individual's model age, the epigenetic age, which is related to chronological age in a non-linear fashion. Application of this model to DNA methylation data measured across broad age ranges, from before birth to old age, and from two tissue types, suggests a universal logarithmic trend characterizes epigenetic ageing across entire lifespans.
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Affiliation(s)
- Sagi Snir
- a Department of Evolutionary Biology, University of Haifa , Haifa , Israel
| | - Colin Farrell
- b Department of Molecular, Cell and Developmental Biology, University of California , Los Angeles , CA , USA
| | - Matteo Pellegrini
- b Department of Molecular, Cell and Developmental Biology, University of California , Los Angeles , CA , USA
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8
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Kennedy DW, White NM, Benton MC, Fox A, Scott RJ, Griffiths LR, Mengersen K, Lea RA. Critical evaluation of linear regression models for cell-subtype specific methylation signal from mixed blood cell DNA. PLoS One 2018; 13:e0208915. [PMID: 30571772 PMCID: PMC6301777 DOI: 10.1371/journal.pone.0208915] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Accepted: 11/26/2018] [Indexed: 01/12/2023] Open
Abstract
Epigenome-wide association studies seek to identify DNA methylation sites associated with clinical outcomes. Difference in observed methylation between specific cell-subtypes is often of interest; however, available samples often comprise a mixture of cells. To date, cell-subtype estimates have been obtained from mixed-cell DNA data using linear regression models, but the accuracy of such estimates has not been critically assessed. We evaluated linear regression performance for cell-subtype specific methylation estimation using a 450K methylation array dataset of both mixed-cell and cell-subtype sorted samples from six healthy males. CpGs associated with each cell-subtype were first identified using t-tests between groups of cell-subtype sorted samples. Subsequent reduced panels of reliably accurate CpGs were identified from mixed-cell samples using an accuracy heuristic (D). Performance was assessed by comparing cell-subtype specific estimates from mixed-cells with corresponding cell-sorted mean using the mean absolute error (MAE) and the Coefficient of Determination (R2). At the cell-subtype level, methylation levels at 3272 CpGs could be estimated to within a MAE of 5% of the expected value. The cell-subtypes with the highest accuracy were CD56+ NK (R2 = 0.56) and CD8+T (R2 = 0.48), where 23% of sites were accurately estimated. Hierarchical clustering and pathways enrichment analysis confirmed the biological relevance of the panels. Our results suggest that linear regression for cell-subtype specific methylation estimation is accurate only for some cell-subtypes at a small fraction of cell-associated sites but may be applicable to EWASs of disease traits with a blood-based pathology. Although sample size was a limitation in this study, we suggest that alternative statistical methods will provide the greatest performance improvements.
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Affiliation(s)
- Daniel W. Kennedy
- ARC Centre of Excellence for the Mathematical and Statistical Frontiers, Queensland University of Technology, Brisbane, Australia
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
| | - Nicole M. White
- ARC Centre of Excellence for the Mathematical and Statistical Frontiers, Queensland University of Technology, Brisbane, Australia
| | - Miles C. Benton
- Genomics Research Centre, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia
| | - Andrew Fox
- Florey Department of Neuroscience and Mental Health, Melbourne, Australia
| | - Rodney J. Scott
- Centre for Information-Based Medicine, Hunter Medical Research Institute, Newcastle, Australia
| | - Lyn R. Griffiths
- Genomics Research Centre, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia
| | - Kerrie Mengersen
- ARC Centre of Excellence for the Mathematical and Statistical Frontiers, Queensland University of Technology, Brisbane, Australia
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
| | - Rodney A. Lea
- Genomics Research Centre, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia
- Florey Department of Neuroscience and Mental Health, Melbourne, Australia
- * E-mail:
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9
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Castellano-Castillo D, Morcillo S, Clemente-Postigo M, Crujeiras AB, Fernandez-García JC, Torres E, Tinahones FJ, Macias-Gonzalez M. Adipose tissue inflammation and VDR expression and methylation in colorectal cancer. Clin Epigenetics 2018; 10:60. [PMID: 29719581 PMCID: PMC5921388 DOI: 10.1186/s13148-018-0493-0] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2017] [Accepted: 04/12/2018] [Indexed: 12/16/2022] Open
Abstract
Background Lack of vitamin D (VD) has been associated with colorectal cancer (CRC). VD has anti-inflammatory effects and regulates several cellular pathways by means of its receptor, including epigenetic modifications. Adipose tissue dysfunction has been related to low-grade inflammation, which is related to diseases like cancer. The aim of this study was to explore the relationship between serum 25-hydroxyvitamin D (25(OH)D), adipose tissue gene expression of VD receptor (VDR), pro-inflammatory markers, and the epigenetic factor DNA methyltransferase 3a (DNMT3A) as well as VDR promoter methylation in CRC. Methods Blood and visceral adipose tissue from 57 CRC and 50 healthy control subjects were collected. CRC subjects had lower serum 25(OH)D levels and higher VDR gene expression, and these were negatively correlated in the CRC group. Results Adipose tissue NFκB1, IL6, and IL1B gene expression were higher in the CRC subjects than in the control subjects. 25(OH)D correlated negatively with NFκB1 and CRP. In turn, CRP correlated positively with NFκB1, IL6, IL1B, and VDR gene expression as well as NFκB1 that correlated positively with IL6 and IL1B. DNMT3A mRNA was negatively correlated with serum 25(OH)D and positively correlated with VDR DNA methylation. VDR DNA methylation at position 4 had lower levels in the CRC group. Global NFκB1 methylation at dinucleotide 3 was lower in the CRC group. Conclusion Our results suggest that adipose tissue may be a key factor in CRC development. The low 25(OH)D levels and high adipose tissue VDR expression in CRC may, at least in part, mediate this relationship by modifying adipose tissue DNA methylation and promoting inflammation. Electronic supplementary material The online version of this article (10.1186/s13148-018-0493-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Daniel Castellano-Castillo
- 11Unidad de Gestión Clínica de Endocrinología y Nutrición del Hospital Virgen de la Victoria, Instituto de Investigación Biomédica de Málaga (IBIMA), Universidad de Málaga, Málaga, Spain
| | - Sonsoles Morcillo
- 2CIBER Fisiopatología de la Obesidad y Nutrición (CB06/03), Madrid, Spain
| | - Mercedes Clemente-Postigo
- 11Unidad de Gestión Clínica de Endocrinología y Nutrición del Hospital Virgen de la Victoria, Instituto de Investigación Biomédica de Málaga (IBIMA), Universidad de Málaga, Málaga, Spain.,2CIBER Fisiopatología de la Obesidad y Nutrición (CB06/03), Madrid, Spain
| | - Ana Belén Crujeiras
- 3Laboratory of Molecular and Cellular Endocrinology, Instituto de Investigación Sanitaria (IDIS), Complejo Hospitalario Universitario de Santiago (CHUS/SERGAS), Santiago de Compostela University (USC), Santiago de Compostela, Spain.,4CIBER Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Madrid, Spain
| | - Jose Carlos Fernandez-García
- 11Unidad de Gestión Clínica de Endocrinología y Nutrición del Hospital Virgen de la Victoria, Instituto de Investigación Biomédica de Málaga (IBIMA), Universidad de Málaga, Málaga, Spain.,2CIBER Fisiopatología de la Obesidad y Nutrición (CB06/03), Madrid, Spain
| | - Esperanza Torres
- 5Unidad de Gestión Clínica de Oncología Intercentros Hospital Universitario Virgen de la Victoria, Málaga, Spain
| | - Francisco José Tinahones
- 11Unidad de Gestión Clínica de Endocrinología y Nutrición del Hospital Virgen de la Victoria, Instituto de Investigación Biomédica de Málaga (IBIMA), Universidad de Málaga, Málaga, Spain.,2CIBER Fisiopatología de la Obesidad y Nutrición (CB06/03), Madrid, Spain
| | - Manuel Macias-Gonzalez
- 11Unidad de Gestión Clínica de Endocrinología y Nutrición del Hospital Virgen de la Victoria, Instituto de Investigación Biomédica de Málaga (IBIMA), Universidad de Málaga, Málaga, Spain.,2CIBER Fisiopatología de la Obesidad y Nutrición (CB06/03), Madrid, Spain
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10
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Matsumura H, Nakano Y, Ochi H, Onohara Y, Sairaku A, Tokuyama T, Tomomori S, Motoda C, Amioka M, Hironobe N, Toshishige M, Takahashi S, Imai K, Sueda T, Chayama K, Kihara Y. H558R, a common SCN5A polymorphism, modifies the clinical phenotype of Brugada syndrome by modulating DNA methylation of SCN5A promoters. J Biomed Sci 2017; 24:91. [PMID: 29202755 PMCID: PMC5713129 DOI: 10.1186/s12929-017-0397-x] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2017] [Accepted: 11/22/2017] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND A common SCN5A polymorphism H558R (c.1673 A > G, rs1805124) improves sodium channel activity in mutated channels and known to be a genetic modifier of Brugada syndrome patients (BrS). We investigated clinical manifestations and underlying mechanisms of H558R in BrS. METHODS AND RESULTS We genotyped H558R in 100 BrS (mean age 45 ± 14 years; 91 men) and 1875 controls (mean age 54 ± 18 years; 1546 men). We compared clinical parameters in BrS with and without H558R (H558R+ vs. H558R- group, N = 9 vs. 91). We also obtained right atrial sections from 30 patients during aortic aneurysm operations and compared SCN5A expression and methylation with or without H558R. H558R was less frequent in BrS than controls (9.0% vs. 19.2%, P = 0.028). The VF occurrence ratio was significantly lower (0% vs. 29.7%, P = 0.03) and spontaneous type 1 ECG was less observed in H558R+ than H558R- group (33.3% vs. 74.7%, P = 0.01). The SCN5A expression level was significantly higher and the methylation rate was significantly lower in sections with H558R (N = 10) than those without (0.98 ± 0.14 vs. 0.83 ± 0.19, P = 0.04; 0.7 ± 0.2% vs. 1.6 ± 0.1%, P = 0.004, respectively). In BrS with heterozygous H558R, the A allele mRNA expression was 1.38 fold higher than G allele expression. CONCLUSION The SCN5A polymorphism H558R may be a modifier that protects against VF occurrence in BrS. The H558R decreased the SCN5A promoter methylation and increased the expression level in cardiac tissue. An allelic expression imbalance in BrS with a heterozygous H558R may also contribute to the protective effects in heterozygous mutations.
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Affiliation(s)
- Hiroya Matsumura
- Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, Japan
| | - Yukiko Nakano
- Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, Japan
- Laboratory for Digestive Diseases, Center for Genomic Medicine, RIKEN, Hiroshima, Japan
| | - Hidenori Ochi
- Laboratory for Digestive Diseases, Center for Genomic Medicine, RIKEN, Hiroshima, Japan
- Department of Gastroenterology and Metabolism, Division of Frontier Medical Science, Programs for Biomedical Research Graduate School of Biomedical Science, Hiroshima University, Hiroshima, Japan
| | - Yuko Onohara
- Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, Japan
| | - Akinori Sairaku
- Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, Japan
| | - Takehito Tokuyama
- Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, Japan
| | - Shunsuke Tomomori
- Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, Japan
| | - Chikaaki Motoda
- Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, Japan
| | - Michitaka Amioka
- Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, Japan
| | - Naoya Hironobe
- Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, Japan
| | - Masaaki Toshishige
- Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, Japan
| | - Shinya Takahashi
- Department of Cardiovascular Surgery, Hiroshima University Hospital, Hiroshima, Japan
| | - Katsuhiko Imai
- Department of Cardiovascular Surgery, Hiroshima University Hospital, Hiroshima, Japan
| | - Taijiro Sueda
- Department of Cardiovascular Surgery, Hiroshima University Hospital, Hiroshima, Japan
| | - Kazuaki Chayama
- Laboratory for Digestive Diseases, Center for Genomic Medicine, RIKEN, Hiroshima, Japan
- Department of Gastroenterology and Metabolism, Division of Frontier Medical Science, Programs for Biomedical Research Graduate School of Biomedical Science, Hiroshima University, Hiroshima, Japan
| | - Yasuki Kihara
- Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, Japan
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11
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Sayols-Baixeras S, Subirana I, Fernández-Sanlés A, Sentí M, Lluís-Ganella C, Marrugat J, Elosua R. DNA methylation and obesity traits: An epigenome-wide association study. The REGICOR study. Epigenetics 2017; 12:909-916. [PMID: 29099282 DOI: 10.1080/15592294.2017.1363951] [Citation(s) in RCA: 71] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022] Open
Abstract
Obesity is associated with increased risk of several diseases and has become epidemic. Obesity is highly heritable but the genetic variants identified by genome-wide association studies explain only limited variability. Epigenetics could contribute to explain the missing variability. The study aim was to discover differential methylation patterns related to obesity. We designed an epigenome-wide association study with a discovery phase in a subsample of 641 REGICOR study participants, validated by analysis of 2,515 participants in the Framingham Offspring Study. Blood DNA methylation was assessed using Illumina HumanMethylation450 BeadChip. Next, we meta-analyzed the data using the fixed effects method and performed a functional and pathway analysis using the Ingenuity Pathway Analysis software. We were able to validate 94 CpGs associated with body mass index (BMI) and 49 CpGs associated with waist circumference, located in 95 loci. In addition, we newly discovered 70 CpGs associated with BMI and 33 CpGs related to waist circumference. These CpGs explained 25.94% and 29.22% of the variability of BMI and waist circumference, respectively, in the REGICOR sample. We also evaluated 65 of the 95 validated loci in the GIANT genome-wide association data; 10 of them had Tag SNPs associated with BMI. The top-ranked diseases and functions identified in the functional and pathway analysis were neurologic, psychological, endocrine, and metabolic.
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Affiliation(s)
- Sergi Sayols-Baixeras
- a Cardiovascular Epidemiology and Genetics Research Group , IMIM (Hospital del Mar Medical Research Institute) , Barcelona , Catalonia , Spain.,b Universitat Pompeu Fabra (UPF) , Barcelona , Catalonia , Spain.,c CIBER Cardiovascular diseases (CIBERCV) , Barcelona , Catalonia , Spain
| | - Isaac Subirana
- a Cardiovascular Epidemiology and Genetics Research Group , IMIM (Hospital del Mar Medical Research Institute) , Barcelona , Catalonia , Spain.,d CIBER Epidemiology and Public Health (CIBERESP) , Barcelona , Catalonia , Spain
| | - Alba Fernández-Sanlés
- a Cardiovascular Epidemiology and Genetics Research Group , IMIM (Hospital del Mar Medical Research Institute) , Barcelona , Catalonia , Spain.,b Universitat Pompeu Fabra (UPF) , Barcelona , Catalonia , Spain
| | - Mariano Sentí
- b Universitat Pompeu Fabra (UPF) , Barcelona , Catalonia , Spain.,c CIBER Cardiovascular diseases (CIBERCV) , Barcelona , Catalonia , Spain
| | - Carla Lluís-Ganella
- a Cardiovascular Epidemiology and Genetics Research Group , IMIM (Hospital del Mar Medical Research Institute) , Barcelona , Catalonia , Spain
| | - Jaume Marrugat
- a Cardiovascular Epidemiology and Genetics Research Group , IMIM (Hospital del Mar Medical Research Institute) , Barcelona , Catalonia , Spain.,c CIBER Cardiovascular diseases (CIBERCV) , Barcelona , Catalonia , Spain
| | - Roberto Elosua
- a Cardiovascular Epidemiology and Genetics Research Group , IMIM (Hospital del Mar Medical Research Institute) , Barcelona , Catalonia , Spain.,c CIBER Cardiovascular diseases (CIBERCV) , Barcelona , Catalonia , Spain
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12
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Trends in DNA Methylation with Age Replicate Across Diverse Human Populations. Genetics 2017; 206:1659-1674. [PMID: 28533441 DOI: 10.1534/genetics.116.195594] [Citation(s) in RCA: 51] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2016] [Accepted: 05/09/2017] [Indexed: 01/31/2023] Open
Abstract
Aging is associated with widespread changes in genome-wide patterns of DNA methylation. Thousands of CpG sites whose tissue-specific methylation levels are strongly correlated with chronological age have been previously identified. However, the majority of these studies have focused primarily on cosmopolitan populations living in the developed world; it is not known if age-related patterns of DNA methylation at these loci are similar across a broad range of human genetic and ecological diversity. We investigated genome-wide methylation patterns using saliva- and whole blood-derived DNA from two traditionally hunting and gathering African populations: the Baka of the western Central African rain forest and the ≠Khomani San of the South African Kalahari Desert. We identified hundreds of CpG sites whose methylation levels are significantly associated with age, thousands that are significant in a meta-analysis, and replicate trends previously reported in populations of non-African descent. We confirmed that an age-associated site in the promoter of the gene ELOVL2 shows a remarkably congruent relationship with aging in humans, despite extensive genetic and environmental variation across populations. We also demonstrate that genotype state at methylation quantitative trait loci (meQTLs) can affect methylation trends at some age-associated CpG sites. Our study explores the relationship between CpG methylation and chronological age in populations of African hunter-gatherers, who rely on different diets across diverse ecologies. While many age-related CpG sites replicate across populations, we show that considering common genetic variation at meQTLs further improves our ability to detect previously identified age associations.
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13
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Johnson ND, Wiener HW, Smith AK, Nishitani S, Absher DM, Arnett DK, Aslibekyan S, Conneely KN. Non-linear patterns in age-related DNA methylation may reflect CD4 + T cell differentiation. Epigenetics 2017; 12:492-503. [PMID: 28387568 DOI: 10.1080/15592294.2017.1314419] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
DNA methylation (DNAm) is an important epigenetic process involved in the regulation of gene expression. While many studies have identified thousands of loci associated with age, few have differentiated between linear and non-linear DNAm trends with age. Non-linear trends could indicate early- or late-life gene regulatory processes. Using data from the Illumina 450K array on 336 human peripheral blood samples, we identified 21 CpG sites that associated with age (P<1.03E-7) and exhibited changing rates of DNAm change with age (P<1.94E-6). For 2 of these CpG sites (cg07955995 and cg22285878), DNAm increased with age at an increasing rate, indicating that differential DNAm was greatest among elderly individuals. We observed significant replication for both CpG sites (P<5.0E-8) in a second set of peripheral blood samples. In 8 of 9 additional data sets comprising samples of monocytes, T cell subtypes, and brain tissue, we observed a pattern directionally consistent with DNAm increasing with age at an increasing rate, which was nominally significant in the 3 largest data sets (4.3E-15<P<0.039). cg07955995 and cg22285878 reside in the promoter region of KLF14, which encodes a protein involved in immune cell differentiation via the repression of FOXP3. These findings may suggest a possible role for cg07955995 and cg22285878 in immunosenescence.
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Affiliation(s)
| | - Howard W Wiener
- b Department of Epidemiology , University of Alabama at Birmingham , Birmingham , AL , USA
| | - Alicia K Smith
- c Department of Gynecology and Obstetrics , Emory University , Atlanta , GA , USA.,d Department of Psychiatry and Behavioral Sciences , Emory University , Atlanta , GA , USA
| | - Shota Nishitani
- c Department of Gynecology and Obstetrics , Emory University , Atlanta , GA , USA.,d Department of Psychiatry and Behavioral Sciences , Emory University , Atlanta , GA , USA
| | - Devin M Absher
- e HudsonAlpha Institute for Biotechnology , Huntsville , AL , USA
| | - Donna K Arnett
- f College of Public Health , University of Kentucky , Lexington , KY , USA
| | - Stella Aslibekyan
- b Department of Epidemiology , University of Alabama at Birmingham , Birmingham , AL , USA
| | - Karen N Conneely
- a Department of Human Genetics , Emory University , Atlanta , GA , USA
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14
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Benton MC, Sutherland HG, Macartney-Coxson D, Haupt LM, Lea RA, Griffiths LR. Methylome-wide association study of whole blood DNA in the Norfolk Island isolate identifies robust loci associated with age. Aging (Albany NY) 2017; 9:753-768. [PMID: 28255110 PMCID: PMC5391229 DOI: 10.18632/aging.101187] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2016] [Accepted: 02/28/2017] [Indexed: 01/07/2023]
Abstract
Epigenetic regulation of various genomic functions, including gene expression, provide mechanisms whereby an organism can dynamically respond to changes in its environment and modify gene expression accordingly. One epigenetic mechanism implicated in human aging and age-related disorders is DNA methylation. Isolated populations such as Norfolk Island (NI) should be advantageous for the identification of epigenetic factors related to aging due to reduced genetic and environmental variation. Here we conducted a methylome-wide association study of age using whole blood DNA in 24 healthy female individuals from the NI genetic isolate (aged 24-47 years). We analysed 450K methylation array data using a machine learning approach (GLMnet) to identify age-associated CpGs. We identified 497 CpG sites, mapping to 422 genes, associated with age, with 11 sites previously associated with age. The strongest associations identified were for a single CpG site in MYOF and an extended region within the promoter of DDO. These hits were validated in curated public data from 2316 blood samples (MARMAL-AID). This study is the first to report robust age associations for MYOF and DDO, both of which have plausible functional roles in aging. This study also illustrates the value of genetic isolates to reveal new associations with epigenome-level data.
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Affiliation(s)
- Miles C Benton
- Genomics Research Centre, Institute of Health and Biomedical Innovation, School of Biomedical Sciences, Queensland University of Technology, Kelvin Grove, Queensland, 4059, Australia
| | - Heidi G Sutherland
- Genomics Research Centre, Institute of Health and Biomedical Innovation, School of Biomedical Sciences, Queensland University of Technology, Kelvin Grove, Queensland, 4059, Australia
| | - Donia Macartney-Coxson
- Kenepuru Science Centre, Institute of Environmental Science and Research, Wellington 5240, New Zealand
| | - Larisa M Haupt
- Genomics Research Centre, Institute of Health and Biomedical Innovation, School of Biomedical Sciences, Queensland University of Technology, Kelvin Grove, Queensland, 4059, Australia
| | - Rodney A Lea
- Genomics Research Centre, Institute of Health and Biomedical Innovation, School of Biomedical Sciences, Queensland University of Technology, Kelvin Grove, Queensland, 4059, Australia
| | - Lyn R Griffiths
- Genomics Research Centre, Institute of Health and Biomedical Innovation, School of Biomedical Sciences, Queensland University of Technology, Kelvin Grove, Queensland, 4059, Australia
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15
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Sommese L, Zullo A, Mancini FP, Fabbricini R, Soricelli A, Napoli C. Clinical relevance of epigenetics in the onset and management of type 2 diabetes mellitus. Epigenetics 2017; 12:401-415. [PMID: 28059593 DOI: 10.1080/15592294.2016.1278097] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Epigenetics is involved in the altered expression of gene networks that underlie insulin resistance and insufficiency. Major genes controlling β-cell differentiation and function, such as PAX4, PDX1, and GLP1 receptor, are epigenetically controlled. Epigenetics can cause insulin resistance through immunomediated pro-inflammatory actions related to several factors, such as NF-kB, osteopontin, and Toll-like receptors. Hereafter, we provide a critical and comprehensive summary on this topic with a particular emphasis on translational and clinical aspects. We discuss the effect of epigenetics on β-cell regeneration for cell replacement therapy, the emerging bioinformatics approaches for analyzing the epigenetic contribution to type 2 diabetes mellitus (T2DM), the epigenetic core of the transgenerational inheritance hypothesis in T2DM, and the epigenetic clinical trials on T2DM. Therefore, prevention or reversion of the epigenetic changes occurring during T2DM development may reduce the individual and societal burden of the disease.
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Affiliation(s)
- Linda Sommese
- a U.O.C. Clinical Immunology, Immunohematology, Transfusion Medicine and Transplant Immunology, Regional Reference Laboratory of Transplant Immunology , Department of Internal and Specialty Medicine , Azienda Ospedaliera Universitaria (AOU), Università degli Studi della Campania "Luigi Vanvitelli ," Italy.,b Department of Experimental Medicine , Second University of Naples , Italy
| | - Alberto Zullo
- c Department of Sciences and Technologies , University of Sannio , Benevento , Italy.,d CEINGE-Advanced Biotechnologies , Naples , Italy
| | | | - Rossella Fabbricini
- a U.O.C. Clinical Immunology, Immunohematology, Transfusion Medicine and Transplant Immunology, Regional Reference Laboratory of Transplant Immunology , Department of Internal and Specialty Medicine , Azienda Ospedaliera Universitaria (AOU), Università degli Studi della Campania "Luigi Vanvitelli ," Italy
| | - Andrea Soricelli
- e IRCCS Research Institute SDN , Naples , Italy.,f Department of Studies of Institutions and Territorial Systems , University of Naples Parthenope , Naples , Italy
| | - Claudio Napoli
- a U.O.C. Clinical Immunology, Immunohematology, Transfusion Medicine and Transplant Immunology, Regional Reference Laboratory of Transplant Immunology , Department of Internal and Specialty Medicine , Azienda Ospedaliera Universitaria (AOU), Università degli Studi della Campania "Luigi Vanvitelli ," Italy.,e IRCCS Research Institute SDN , Naples , Italy.,g Department of Medical, Surgical, Neurological, Metabolic and Geriatric Sciences , Second University of Naples , Italy
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16
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Lai CQ, Wojczynski MK, Parnell LD, Hidalgo BA, Irvin MR, Aslibekyan S, Province MA, Absher DM, Arnett DK, Ordovás JM. Epigenome-wide association study of triglyceride postprandial responses to a high-fat dietary challenge. J Lipid Res 2016; 57:2200-2207. [PMID: 27777315 PMCID: PMC5321216 DOI: 10.1194/jlr.m069948] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2016] [Revised: 10/16/2016] [Indexed: 12/18/2022] Open
Abstract
Postprandial lipemia (PPL), the increased plasma TG concentration after consuming a high-fat meal, is an independent risk factor for CVD. Individual responses to a meal high in fat vary greatly, depending on genetic and lifestyle factors. However, only a few loci have been associated with TG-PPL response. Heritable epigenomic changes may be significant contributors to the unexplained inter-individual PPL variability. We conducted an epigenome-wide association study on 979 subjects with DNA methylation measured from CD4+ T cells, who were challenged with a high-fat meal as a part of the Genetics of Lipid Lowering Drugs and Diet Network study. Eight methylation sites encompassing five genes, LPP, CPT1A, APOA5, SREBF1, and ABCG1, were significantly associated with PPL response at an epigenome-wide level (P < 1.1 × 10−7), but no methylation site reached epigenome-wide significance after adjusting for baseline TG levels. Higher methylation at LPP, APOA5, SREBF1, and ABCG1, and lower methylation at CPT1A methylation were correlated with an increased TG-PPL response. These PPL-associated methylation sites, also correlated with fasting TG, account for a substantially greater amount of phenotypic variance (14.9%) in PPL and fasting TG (16.3%) when compared with the genetic contribution of loci identified by our previous genome-wide association study (4.5%). In summary, the epigenome is a large contributor to the variation in PPL, and this has the potential to be used to modulate PPL and reduce CVD.
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Affiliation(s)
- Chao-Qiang Lai
- USDA Agricultural Research Service, Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA
| | - Mary K Wojczynski
- Department of Genetics, Washington University School of Medicine, St. Louis, MO
| | - Laurence D Parnell
- USDA Agricultural Research Service, Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA
| | - Bertha A Hidalgo
- Department of Epidemiology, School of Public Health, University of Alabama, Birmingham, AL
| | - Marguerite Ryan Irvin
- Department of Epidemiology, School of Public Health, University of Alabama, Birmingham, AL
| | - Stella Aslibekyan
- Department of Epidemiology, School of Public Health, University of Alabama, Birmingham, AL
| | - Michael A Province
- Department of Genetics, Washington University School of Medicine, St. Louis, MO
| | - Devin M Absher
- Hudson Alpha Institute for Biotechnology, Huntsville, AL
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY
| | - José M Ordovás
- Nutrition and Genomics Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA
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17
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Sayols-Baixeras S, Subirana I, Lluis-Ganella C, Civeira F, Roquer J, Do AN, Absher D, Cenarro A, Muñoz D, Soriano-Tárraga C, Jiménez-Conde J, Ordovas JM, Senti M, Aslibekyan S, Marrugat J, Arnett DK, Elosua R. Identification and validation of seven new loci showing differential DNA methylation related to serum lipid profile: an epigenome-wide approach. The REGICOR study. Hum Mol Genet 2016; 25:4556-4565. [PMID: 28173150 PMCID: PMC6284258 DOI: 10.1093/hmg/ddw285] [Citation(s) in RCA: 62] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2016] [Revised: 07/13/2016] [Accepted: 08/19/2016] [Indexed: 11/13/2022] Open
Abstract
Lipid traits (total, low-density and high-density lipoprotein cholesterol, and triglycerides) are risk factors for cardiovascular disease. DNA methylation is not only an inherited but also modifiable epigenetic mark that has been related to cardiovascular risk factors. Our aim was to identify loci showing differential DNA methylation related to serum lipid levels. Blood DNA methylation was assessed using the Illumina Human Methylation 450 BeadChip. A two-stage epigenome-wide association study was performed, with a discovery sample in the REGICOR study (n = 645) and validation in the Framingham Offspring Study (n = 2,542). Fourteen CpG sites located in nine genes (SREBF1, SREBF2, PHOSPHO1, SYNGAP1, ABCG1, CPT1A, MYLIP, TXNIP and SLC7A11) and 2 intergenic regions showed differential methylation in association with lipid traits. Six of these genes and 1 intergenic region were new discoveries showing differential methylation related to total cholesterol (SREBF2), HDL-cholesterol (PHOSPHO1, SYNGAP1 and an intergenic region in chromosome 2) and triglycerides (MYLIP, TXNIP and SLC7A11). These CpGs explained 0.7%, 9.5% and 18.9% of the variability of total cholesterol, HDL cholesterol and triglycerides in the Framingham Offspring Study, respectively. The expression of the genes SREBF2 and SREBF1 was inversely associated with methylation of their corresponding CpGs (P-value = 0.0042 and 0.0045, respectively) in participants of the GOLDN study (n = 98). In turn, SREBF1 expression was directly associated with HDL cholesterol (P-value = 0.0429). Genetic variants in SREBF1, PHOSPHO1, ABCG1 and CPT1A were also associated with lipid profile. Further research is warranted to functionally validate these new loci and assess the causality of new and established associations between these differentially methylated loci and lipid metabolism.
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Affiliation(s)
- S Sayols-Baixeras
- Cardiovascular Epidemiology and Genetics Research Group, IMIM (Hospital
del Mar Medical Research Institute), Barcelona, Catalonia, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain
| | - I Subirana
- Cardiovascular Epidemiology and Genetics Research Group, IMIM (Hospital
del Mar Medical Research Institute), Barcelona, Catalonia, Spain
- CIBER Epidemiology and Public Health, Barcelona, Catalonia, Spain
| | - C Lluis-Ganella
- Cardiovascular Epidemiology and Genetics Research Group, IMIM (Hospital
del Mar Medical Research Institute), Barcelona, Catalonia, Spain
| | - F Civeira
- Unidad Clínica y de Investigación en Lípidos y Arteriosclerosis,
Hospital Universitario Miguel Servet, Instituto de Investigación Sanitaria Aragón, Zaragoza,
Spain
| | - J Roquer
- Department of Neurology, Neurovascular Research Group, IMIM (Hospital
del Mar Medical Research Institute), Barcelona 08003, Catalonia, Spain
| | - AN Do
- Department of Epidemiology, University of Alabama at Birmingham,
Birmingham, AL, USA
| | - D Absher
- Hudson Alpha Institute for Biotechnology, Huntsville, AL, USA
| | - A Cenarro
- Unidad Clínica y de Investigación en Lípidos y Arteriosclerosis,
Hospital Universitario Miguel Servet, Instituto de Investigación Sanitaria Aragón, Zaragoza,
Spain
| | - D Muñoz
- Cardiovascular Risk and Nutrition Research Group, IMIM (Hospital del Mar
Medical Research Institute), Barcelona, Catalonia, Spain
| | - C Soriano-Tárraga
- Department of Neurology, Neurovascular Research Group, IMIM (Hospital
del Mar Medical Research Institute), Barcelona 08003, Catalonia, Spain
| | - J Jiménez-Conde
- Department of Neurology, Neurovascular Research Group, IMIM (Hospital
del Mar Medical Research Institute), Barcelona 08003, Catalonia, Spain
| | - J M Ordovas
- Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts
University, Boston, MA, USA
| | - M Senti
- Department of Experimental and Health Sciences, Pompeu Fabra
University, Barcelona, Catalonia, Spain
| | - S Aslibekyan
- Department of Epidemiology, University of Alabama at Birmingham,
Birmingham, AL, USA
| | - J Marrugat
- Cardiovascular Epidemiology and Genetics Research Group, IMIM (Hospital
del Mar Medical Research Institute), Barcelona, Catalonia, Spain
| | - D K Arnett
- Dean's Office, College of Public Health, University of Kentucky,
Lexington, KY, USA
| | - R Elosua
- Cardiovascular Epidemiology and Genetics Research Group, IMIM (Hospital
del Mar Medical Research Institute), Barcelona, Catalonia, Spain
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Ali O, Cerjak D, Kent JW, James R, Blangero J, Carless MA, Zhang Y. Methylation of SOCS3 is inversely associated with metabolic syndrome in an epigenome-wide association study of obesity. Epigenetics 2016; 11:699-707. [PMID: 27564309 PMCID: PMC5048720 DOI: 10.1080/15592294.2016.1216284] [Citation(s) in RCA: 51] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Epigenetic mechanisms, including DNA methylation, mediate the interaction between gene and environment and may play an important role in the obesity epidemic. We assessed the relationship between DNA methylation and obesity in peripheral blood mononuclear cells (PBMCs) at 485,000 CpG sites across the genome in family members (8-90 y of age) using a discovery cohort (192 individuals) and a validation cohort (1,052 individuals) of Northern European ancestry. After Bonferroni-correction (Pα=0.05 = 1.31 × 10−7) for genome-wide significance, we identified 3 loci, cg18181703 (SOCS3), cg04502490 (ZNF771), and cg02988947 (LIMD2), where methylation status was associated with body mass index percentile (BMI%), a clinical index for obesity in children, adolescents, and adults. These sites were also associated with multiple metabolic syndrome (MetS) traits, including central obesity, fat depots, insulin responsiveness, and plasma lipids. The SOCS3 methylation locus was also associated with the clinical definition of MetS. In the validation cohort, SOCS3 methylation status was found to be inversely associated with BMI% (P = 1.75 × 10−6), waist to height ratio (P = 4.18 × 10−7), triglycerides (P = 4.01 × 10−4), and MetS (P = 4.01 × 10−7), and positively correlated with HDL-c (P = 4.57 × 10−8). Functional analysis in a sub cohort (333 individuals) demonstrated SOCS3 methylation and gene expression in PBMCs were inversely correlated (P = 2.93 × 10−4) and expression of SOCS3 was positively correlated with status of MetS (P = 0.012). We conclude that epigenetic modulation of SOCS3, a gene involved in leptin and insulin signaling, may play an important role in obesity and MetS.
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Affiliation(s)
- Omar Ali
- a Department of Pediatrics , Medical College of Wisconsin , Milwaukee , WI , USA
| | - Diana Cerjak
- b TOPS Obesity and Metabolic Research Center, Department of Medicine, Medical College of Wisconsin , Milwaukee , WI , USA.,c Human and Molecular Genetics Center, Medical College of Wisconsin , Milwaukee , WI , USA
| | - Jack W Kent
- d Department of Genetics , Texas Biomedical Research Institute , San Antonio , TX , USA
| | - Roland James
- b TOPS Obesity and Metabolic Research Center, Department of Medicine, Medical College of Wisconsin , Milwaukee , WI , USA.,c Human and Molecular Genetics Center, Medical College of Wisconsin , Milwaukee , WI , USA
| | - John Blangero
- e South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley , Brownsville , TX , USA
| | - Melanie A Carless
- d Department of Genetics , Texas Biomedical Research Institute , San Antonio , TX , USA
| | - Yi Zhang
- b TOPS Obesity and Metabolic Research Center, Department of Medicine, Medical College of Wisconsin , Milwaukee , WI , USA.,c Human and Molecular Genetics Center, Medical College of Wisconsin , Milwaukee , WI , USA
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19
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Kim S, Eliot M, Koestler DC, Houseman EA, Wetmur JG, Wiencke JK, Kelsey KT. Enlarged leukocyte referent libraries can explain additional variance in blood-based epigenome-wide association studies. Epigenomics 2016; 8:1185-92. [PMID: 27529193 DOI: 10.2217/epi-2016-0037] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
AIM We examined whether variation in blood-based epigenome-wide association studies could be more completely explained by augmenting existing reference DNA methylation libraries. MATERIALS & METHODS We compared existing and enhanced libraries in predicting variability in three publicly available 450K methylation datasets that collected whole-blood samples. Models were fit separately to each CpG site and used to estimate the additional variability when adjustments for cell composition were made with each library. RESULTS Calculation of the mean difference in the CpG-specific residual sums of squares error between models for an arthritis, aging and metabolic syndrome dataset, indicated that an enhanced library explained significantly more variation across all three datasets (p < 10(-3)). CONCLUSION Pathologically important immune cell subtypes can explain important variability in epigenome-wide association studies done in blood.
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Affiliation(s)
- Stephanie Kim
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912, USA.,Department of Environmental Health, Boston University School of Public Health, Boston, MA 02118, USA
| | - Melissa Eliot
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912, USA
| | - Devin C Koestler
- Department of Biostatistics, University of Kansas Medical Center, Kansas City, KA 66160, USA
| | - Eugene A Houseman
- Oregon State University College of Public Health & Human Sciences, Corvallis, OR 97331, USA
| | - James G Wetmur
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - John K Wiencke
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94158, USA
| | - Karl T Kelsey
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912, USA.,Department of Laboratory Medicine & Pathology, Brown University, Providence, RI 02912, USA
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20
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Sierra MI, Fernández AF, Fraga MF. Epigenetics of Aging. Curr Genomics 2016; 16:435-40. [PMID: 27019618 PMCID: PMC4765531 DOI: 10.2174/1389202916666150817203459] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2015] [Revised: 06/20/2015] [Accepted: 06/26/2015] [Indexed: 01/10/2023] Open
Abstract
The best-known phenomenon exemplifying epigenetic drift (the alteration of epigenetic patterns during aging) is the gradual decrease of global DNA methylation. Aging cells, different tissue types, as well as a variety of human diseases possess their own distinct DNA methylation profiles, although the functional impact of these is not always clear. DNA methylation appears to be a dynamic tool of transcriptional regulation, with an extra layer of complexity due to the recent discovery of the conversion of 5-methylcytosine into 5-hydroxymethylcytosine. This age-related DNA demethylation is associated with changes in histone modification patterns and, furthermore, we now know that ncRNAs have evolved in eukaryotes as epigenetic regulators of gene expression. In this review, we will discuss current knowledge on how all these epigenetic phenomena are implicated in human aging, and their links with external, internal and stochastic factors which can affect human age-related diseases onset.
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Affiliation(s)
- Marta I Sierra
- Cancer Epigenetics Laboratory, Institute of Oncology of Asturias (IUOPA), HUCA, Universidad de Oviedo and Nanomaterials and Nanotechnology Research Center (CINN-CSIC)-Universidad de Oviedo (UO) -Principado de Asturias, Spain
| | - Agustín F Fernández
- Cancer Epigenetics Laboratory, Institute of Oncology of Asturias (IUOPA), HUCA, Universidad de Oviedo and Nanomaterials and Nanotechnology Research Center (CINN-CSIC)-Universidad de Oviedo (UO) -Principado de Asturias, Spain
| | - Mario F Fraga
- Cancer Epigenetics Laboratory, Institute of Oncology of Asturias (IUOPA), HUCA, Universidad de Oviedo and Nanomaterials and Nanotechnology Research Center (CINN-CSIC)-Universidad de Oviedo (UO) -Principado de Asturias, Spain
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21
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Zhang Y, Ren J. Epigenetics and obesity cardiomyopathy: From pathophysiology to prevention and management. Pharmacol Ther 2016; 161:52-66. [PMID: 27013344 DOI: 10.1016/j.pharmthera.2016.03.005] [Citation(s) in RCA: 77] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Uncorrected obesity has been associated with cardiac hypertrophy and contractile dysfunction. Several mechanisms for this cardiomyopathy have been identified, including oxidative stress, autophagy, adrenergic and renin-angiotensin aldosterone overflow. Another process that may regulate effects of obesity is epigenetics, which refers to the heritable alterations in gene expression or cellular phenotype that are not encoded on the DNA sequence. Advances in epigenome profiling have greatly improved the understanding of the epigenome in obesity, where environmental exposures during early life result in an increased health risk later on in life. Several mechanisms, including histone modification, DNA methylation and non-coding RNAs, have been reported in obesity and can cause transcriptional suppression or activation, depending on the location within the gene, contributing to obesity-induced complications. Through epigenetic modifications, the fetus may be prone to detrimental insults, leading to cardiac sequelae later in life. Important links between epigenetics and obesity include nutrition, exercise, adiposity, inflammation, insulin sensitivity and hepatic steatosis. Genome-wide studies have identified altered DNA methylation patterns in pancreatic islets, skeletal muscle and adipose tissues from obese subjects compared with non-obese controls. In addition, aging and intrauterine environment are associated with differential DNA methylation. Given the intense research on the molecular mechanisms of the etiology of obesity and its complications, this review will provide insights into the current understanding of epigenetics and pharmacological and non-pharmacological (such as exercise) interventions targeting epigenetics as they relate to treatment of obesity and its complications. Particular focus will be on DNA methylation, histone modification and non-coding RNAs.
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Affiliation(s)
- Yingmei Zhang
- Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai 200032, China; Center for Cardiovascular Research and Alternative Medicine, University of Wyoming College of Health Sciences, Laramie, WY 82071, USA.
| | - Jun Ren
- Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai 200032, China; Center for Cardiovascular Research and Alternative Medicine, University of Wyoming College of Health Sciences, Laramie, WY 82071, USA.
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22
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Milagro FI, Riezu-Boj JI, Martinez JA. Epigenetic Determinants of Weight Management: Methylation Signatures. Curr Nutr Rep 2015. [DOI: 10.1007/s13668-015-0140-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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