1
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Elliott HR, Bennett CL, Caramaschi D, English S. Negative association between higher maternal pre-pregnancy body mass index and breastfeeding outcomes is not mediated by DNA methylation. Sci Rep 2024; 14:14675. [PMID: 38918574 PMCID: PMC11199553 DOI: 10.1038/s41598-024-65605-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 06/21/2024] [Indexed: 06/27/2024] Open
Abstract
The benefits of breastfeeding for the health and wellbeing of both infants and mothers are well documented, yet global breastfeeding rates are low. One factor associated with low breast feeding is maternal body mass index (BMI), which is used as a measure of obesity. The negative relationship between maternal obesity and breastfeeding is likely caused by a variety of social, psychological, and physiological factors. Maternal obesity may also have a direct biological association with breastfeeding through changes in maternal DNA methylation. Here, we investigate this potential biological association using data from a UK-based cohort study, the Avon Longitudinal Study of Parents and Children (ALSPAC). We find that pre-pregnancy body mass index (BMI) is associated with lower initiation to breastfeed and shorter breastfeeding duration. We conduct epigenome-wide association studies (EWAS) of pre-pregnancy BMI and breastfeeding outcomes, and run candidate-gene analysis of methylation sites associated with BMI identified via previous meta-EWAS. We find that DNA methylation at cg11453712, annotated to PHTP1, is associated with pre-pregnancy BMI. From our results, neither this association nor those at candidate-gene sites are likely to mediate the link between pre-pregnancy BMI and breastfeeding.
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Affiliation(s)
- Hannah R Elliott
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Chloe L Bennett
- School of Biological Sciences, University of Bristol, Bristol, UK
| | - Doretta Caramaschi
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Faculty of Health and Life Sciences, Department of Psychology, University of Exeter, Exeter, UK
| | - Sinead English
- School of Biological Sciences, University of Bristol, Bristol, UK.
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2
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Keller M, Svensson SIA, Rohde-Zimmermann K, Kovacs P, Böttcher Y. Genetics and Epigenetics in Obesity: What Do We Know so Far? Curr Obes Rep 2023; 12:482-501. [PMID: 37819541 DOI: 10.1007/s13679-023-00526-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/07/2023] [Indexed: 10/13/2023]
Abstract
PURPOSE OF REVIEW Enormous progress has been made in understanding the genetic architecture of obesity and the correlation of epigenetic marks with obesity and related traits. This review highlights current research and its challenges in genetics and epigenetics of obesity. RECENT FINDINGS Recent progress in genetics of polygenic traits, particularly represented by genome-wide association studies, led to the discovery of hundreds of genetic variants associated with obesity, which allows constructing polygenic risk scores (PGS). In addition, epigenome-wide association studies helped identifying novel targets and methylation sites being important in the pathophysiology of obesity and which are essential for the generation of methylation risk scores (MRS). Despite their great potential for predicting the individual risk for obesity, the use of PGS and MRS remains challenging. Future research will likely discover more loci being involved in obesity, which will contribute to better understanding of the complex etiology of human obesity. The ultimate goal from a clinical perspective will be generating highly robust and accurate prediction scores allowing clinicians to predict obesity as well as individual responses to body weight loss-specific life-style interventions.
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Affiliation(s)
- Maria Keller
- Medical Department III-Endocrinology, Nephrology, Rheumatology, Medical Center, University of Leipzig, 04103, Leipzig, Germany
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich at the University of Leipzig, University Hospital Leipzig, 04103, Leipzig, Germany
| | - Stina Ingrid Alice Svensson
- EpiGen, Department of Clinical Molecular Biology, Institute of Clinical Medicine, University of Oslo, 0316, Oslo, Norway
| | - Kerstin Rohde-Zimmermann
- Medical Department III-Endocrinology, Nephrology, Rheumatology, Medical Center, University of Leipzig, 04103, Leipzig, Germany
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich at the University of Leipzig, University Hospital Leipzig, 04103, Leipzig, Germany
| | - Peter Kovacs
- Medical Department III-Endocrinology, Nephrology, Rheumatology, Medical Center, University of Leipzig, 04103, Leipzig, Germany
| | - Yvonne Böttcher
- EpiGen, Department of Clinical Molecular Biology, Institute of Clinical Medicine, University of Oslo, 0316, Oslo, Norway.
- EpiGen, Medical Division, Akershus University Hospital, 1478, Lørenskog, Norway.
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3
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Wulfridge P, Davidovich A, Salvador AC, Manno GC, Tryggvadottir R, Idrizi A, Huda MN, Bennett BJ, Adams LG, Hansen KD, Threadgill DW, Feinberg AP. Precision pharmacological reversal of strain-specific diet-induced metabolic syndrome in mice informed by epigenetic and transcriptional regulation. PLoS Genet 2023; 19:e1010997. [PMID: 37871105 PMCID: PMC10621921 DOI: 10.1371/journal.pgen.1010997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 11/02/2023] [Accepted: 09/25/2023] [Indexed: 10/25/2023] Open
Abstract
Diet-related metabolic syndrome is the largest contributor to adverse health in the United States. However, the study of gene-environment interactions and their epigenomic and transcriptomic integration is complicated by the lack of environmental and genetic control in humans that is possible in mouse models. Here we exposed three mouse strains, C57BL/6J (BL6), A/J, and NOD/ShiLtJ (NOD), to a high-fat, high-carbohydrate diet, leading to varying degrees of metabolic syndrome. We then performed transcriptomic and genome-wide DNA methylation analyses for each strain and found overlapping but also highly divergent changes in gene expression and methylation upstream of the discordant metabolic phenotypes. Strain-specific pathway analysis of dietary effects revealed a dysregulation of cholesterol biosynthesis common to all three strains but distinct regulatory networks driving this dysregulation. This suggests a strategy for strain-specific targeted pharmacologic intervention of these upstream regulators informed by epigenetic and transcriptional regulation. As a pilot study, we administered the drug GW4064 to target one of these genotype-dependent networks, the farnesoid X receptor pathway, and found that GW4064 exerts strain-specific protection against dietary effects in BL6, as predicted by our transcriptomic analysis. Furthermore, GW4064 treatment induced inflammatory-related gene expression changes in NOD, indicating a strain-specific effect in its associated toxicities as well as its therapeutic efficacy. This pilot study demonstrates the potential efficacy of precision therapeutics for genotype-informed dietary metabolic intervention and a mouse platform for guiding this approach.
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Affiliation(s)
- Phillip Wulfridge
- Center for Epigenetics, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Adam Davidovich
- Center for Epigenetics, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Anna C. Salvador
- Department of Cell Biology and Genetics, Texas A&M Health Science Center, College Station, Texas, United States of America
- Department of Nutrition, Texas A&M University, College Station, Texas, United States of America
| | - Gabrielle C. Manno
- Department of Cell Biology and Genetics, Texas A&M Health Science Center, College Station, Texas, United States of America
| | - Rakel Tryggvadottir
- Center for Epigenetics, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Adrian Idrizi
- Center for Epigenetics, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - M. Nazmul Huda
- Department of Nutrition, University of California, Davis, California, United States of America
- Obesity and Metabolism Research Unit, USDA, ARS, Western Human Nutrition Research Center, Davis, California, United States of America
| | - Brian J. Bennett
- Department of Nutrition, University of California, Davis, California, United States of America
- Obesity and Metabolism Research Unit, USDA, ARS, Western Human Nutrition Research Center, Davis, California, United States of America
| | - L. Garry Adams
- Department of Veterinary Pathobiology, Texas A&M University, College Station, Texas, United States of America
| | - Kasper D. Hansen
- Center for Epigenetics, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
- Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - David W. Threadgill
- Department of Cell Biology and Genetics, Texas A&M Health Science Center, College Station, Texas, United States of America
- Department of Nutrition, Texas A&M University, College Station, Texas, United States of America
- Department of Biochemistry & Biophysics, Texas A&M University, College Station, Texas, United States of America
| | - Andrew P. Feinberg
- Center for Epigenetics, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
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4
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Issarapu P, Arumalla M, Elliott HR, Nongmaithem SS, Sankareswaran A, Betts M, Sajjadi S, Kessler NJ, Bayyana S, Mansuri SR, Derakhshan M, Krishnaveni GV, Shrestha S, Kumaran K, Di Gravio C, Sahariah SA, Sanderson E, Relton CL, Ward KA, Moore SE, Prentice AM, Lillycrop KA, Fall CHD, Silver MJ, Chandak GR. DNA methylation at the suppressor of cytokine signaling 3 (SOCS3) gene influences height in childhood. Nat Commun 2023; 14:5200. [PMID: 37626025 PMCID: PMC10457295 DOI: 10.1038/s41467-023-40607-0] [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: 01/14/2023] [Accepted: 08/01/2023] [Indexed: 08/27/2023] Open
Abstract
Human height is strongly influenced by genetics but the contribution of modifiable epigenetic factors is under-explored, particularly in low and middle-income countries (LMIC). We investigate links between blood DNA methylation and child height in four LMIC cohorts (n = 1927) and identify a robust association at three CpGs in the suppressor of cytokine signaling 3 (SOCS3) gene which replicates in a high-income country cohort (n = 879). SOCS3 methylation (SOCS3m)-height associations are independent of genetic effects. Mendelian randomization analysis confirms a causal effect of SOCS3m on height. In longitudinal analysis, SOCS3m explains a maximum 9.5% of height variance in mid-childhood while the variance explained by height polygenic risk score increases from birth to 21 years. Children's SOCS3m is associated with prenatal maternal folate and socio-economic status. In-vitro characterization confirms a regulatory effect of SOCS3m on gene expression. Our findings suggest epigenetic modifications may play an important role in driving child height in LMIC.
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Affiliation(s)
- Prachand Issarapu
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, India
- MRC Unit The Gambia at The London School of Hygiene and Tropical Medicine (LSHTM), London, UK
| | - Manisha Arumalla
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, India
| | - Hannah R Elliott
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Suraj S Nongmaithem
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, India
| | - Alagu Sankareswaran
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, India
- Academy of Scientific and Innovative Research, AcSIR, Ghaziabad, India
| | - Modupeh Betts
- MRC Unit The Gambia at The London School of Hygiene and Tropical Medicine (LSHTM), London, UK
| | - Sara Sajjadi
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, India
- Academy of Scientific and Innovative Research, AcSIR, Ghaziabad, India
| | - Noah J Kessler
- Department of Genetics, University of Cambridge, Cambridge, UK
| | - Swati Bayyana
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, India
- Academy of Scientific and Innovative Research, AcSIR, Ghaziabad, India
| | - Sohail R Mansuri
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, India
- Academy of Scientific and Innovative Research, AcSIR, Ghaziabad, India
| | - Maria Derakhshan
- MRC Unit The Gambia at The London School of Hygiene and Tropical Medicine (LSHTM), London, UK
| | - G V Krishnaveni
- Epidemiology Research Unit, CSI Holdsworth Memorial Hospital, Mysore, Karnataka, India
| | - Smeeta Shrestha
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, India
| | - Kalyanaraman Kumaran
- Epidemiology Research Unit, CSI Holdsworth Memorial Hospital, Mysore, Karnataka, India
- MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK
| | - Chiara Di Gravio
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Eleanor Sanderson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Kate A Ward
- MRC Unit The Gambia at The London School of Hygiene and Tropical Medicine (LSHTM), London, UK
- Department of Women & Children's Health, King's College London, London, UK
| | - Sophie E Moore
- MRC Unit The Gambia at The London School of Hygiene and Tropical Medicine (LSHTM), London, UK
- Department of Women & Children's Health, King's College London, London, UK
| | - Andrew M Prentice
- MRC Unit The Gambia at The London School of Hygiene and Tropical Medicine (LSHTM), London, UK
| | - Karen A Lillycrop
- School of Medicine, University of Southampton, Southampton, UK
- Biological Sciences, University of Southampton, Southampton, UK
| | - Caroline H D Fall
- MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK
| | - Matt J Silver
- MRC Unit The Gambia at The London School of Hygiene and Tropical Medicine (LSHTM), London, UK.
| | - Giriraj R Chandak
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, India.
- Academy of Scientific and Innovative Research, AcSIR, Ghaziabad, India.
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5
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Wulfridge P, Davidovich A, Salvador AC, Manno GC, Tryggvadottir R, Idrizi A, Huda MN, Bennett BJ, Adams LG, Hansen KD, Threadgill DW, Feinberg AP. Precision pharmacological reversal of genotype-specific diet-induced metabolic syndrome in mice informed by transcriptional regulation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.25.538156. [PMID: 37163127 PMCID: PMC10168252 DOI: 10.1101/2023.04.25.538156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Diet-related metabolic syndrome is the largest contributor to adverse health in the United States. However, the study of gene-environment interactions and their epigenomic and transcriptomic integration is complicated by the lack of environmental and genetic control in humans that is possible in mouse models. Here we exposed three mouse strains, C57BL/6J (BL6), A/J, and NOD/ShiLtJ (NOD), to a high-fat high-carbohydrate diet, leading to varying degrees of metabolic syndrome. We then performed transcriptomic and genomic DNA methylation analyses and found overlapping but also highly divergent changes in gene expression and methylation upstream of the discordant metabolic phenotypes. Strain-specific pathway analysis of dietary effects reveals a dysregulation of cholesterol biosynthesis common to all three strains but distinct regulatory networks driving this dysregulation. This suggests a strategy for strain-specific targeted pharmacologic intervention of these upstream regulators informed by transcriptional regulation. As a pilot study, we administered the drug GW4064 to target one of these genotype-dependent networks, the Farnesoid X receptor pathway, and found that GW4064 exerts genotype-specific protection against dietary effects in BL6, as predicted by our transcriptomic analysis, as well as increased inflammatory-related gene expression changes in NOD. This pilot study demonstrates the potential efficacy of precision therapeutics for genotype-informed dietary metabolic intervention, and a mouse platform for guiding this approach.
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6
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Abstract
Nowadays, obesity is one of the largest public health problems worldwide. In the last few decades, there has been a marked increase in the obesity epidemic and its related comorbidities. Worldwide, more than 2.2 billion people (33%) are affected by overweight or obesity (712 million, 10%) and its associated metabolic complications. Although a high heritability of obesity has been estimated, the genetic variants conducted from genetic association studies only partially explain the variation of body mass index. This has led to a growing interest in understanding the potential role of epigenetics as a key regulator of gene-environment interactions on the development of obesity and its associated complications. Rapid advances in epigenetic research methods and reduced costs of epigenome-wide association studies have led to a great expansion of population-based studies. The field of epigenetics and metabolic diseases such as obesity has advanced rapidly in a short period of time. The main epigenetic mechanisms include DNA methylation, histone modifications, microRNA (miRNA)-mediated regulation and so on. DNA methylation is the most investigated epigenetic mechanism. Preliminary evidence from animal and human studies supports the effect of epigenetics on obesity. Studies of epigenome-wide association studies and genome-wide histone modifications from different biological specimens such as blood samples (newborn, children, adolescent, youth, woman, man, twin, race, and meta-analysis), adipose tissues, skeletal muscle cells, placenta, and saliva have reported the differential expression status of multiple genes before and after obesity interventions and have identified multiple candidate genes and biological markers. These findings may improve the understanding of the complex etiology of obesity and its related comorbidities, and help to predict an individual's risk of obesity at a young age and open possibilities for introducing targeted prevention and treatment strategies.
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Affiliation(s)
- Feng-Yao Wu
- Department of Comprehensive Internal Medicine, Affiliated Infectious Disease Hospital of Nanning (The Fourth People’s Hospital of Nanning), Guangxi Medical University, No. 1 Erli, Changgang Road, Nanning, 530023 Guangxi People’s Republic of China
| | - Rui-Xing Yin
- Department of Comprehensive Internal Medicine, Affiliated Infectious Disease Hospital of Nanning (The Fourth People’s Hospital of Nanning), Guangxi Medical University, No. 1 Erli, Changgang Road, Nanning, 530023 Guangxi People’s Republic of China
- Department of Cardiology, Institute of Cardiovascular Diseases, The First Affiliated Hospital, Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021 Guangxi People’s Republic of China
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7
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Li Y, Liu X, Tu R, Hou J, Zhuang G. Mendelian Randomization Analysis of the Association of SOCS3 Methylation with Abdominal Obesity. Nutrients 2022; 14:nu14183824. [PMID: 36145200 PMCID: PMC9503364 DOI: 10.3390/nu14183824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 09/06/2022] [Accepted: 09/13/2022] [Indexed: 11/16/2022] Open
Abstract
This study was conducted to evaluate the potential causality association of SOCS3 methylation with abdominal obesity using Mendelian randomization. A case-control study, including 1064 participants, was carried out on Chinese subjects aged 18 to 79. MethylTargetTM was used to detect the methylation level for each CpG site of SOCS3, and SNPscan® was applied to measure the single-nucleotide polymorphism (SNP) genotyping. The logistic regression was used to assess the relationship of SOCS3 methylation level and SNP genotyping with abdominal obesity. Three types of Mendelian randomization methods were implemented to examine the potential causality between SOCS3 methylation and obesity based on the SNP of SOCS3 as instrumental variables. SOCS3 methylation levels were inversely associated with abdominal obesity in five CpG sites (effect estimates ranged from 0.786 (Chr17:76356054) to 0.851 (Chr17:76356084)), and demonstrated positively association in 18 CpG sites (effect estimates ranged from 1.243 (Chr17:76354990) to 1.325 (Chr17:76355061)). The causal relationship between SOCS3 methylation and abdominal obesity was found using the maximum-likelihood method and Mendelian randomization method of penalized inverse variance weighted (MR-IVW), and the β values (95% CI) were 5.342 (0.215, 10.469) and 4.911 (0.259, 9.564), respectively. The causality was found between the SOCS3 methylation level and abdominal obesity in the Chinese population.
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Affiliation(s)
- Yuqian Li
- Departmentof Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Centre, Xi’an 710061, China
- Department of Clinical Pharmacology, School of Pharmaceutical Science, Zhengzhou University, Zhengzhou 450052, China
| | - Xiaotian Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou 450052, China
| | - Runqi Tu
- Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou 450052, China
| | - Jian Hou
- Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou 450052, China
| | - Guihua Zhuang
- Departmentof Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Centre, Xi’an 710061, China
- Correspondence: ; Tel.: +86-29-826-551-03
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8
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Matrisome alterations in obesity – Adipose tissue transcriptome study on monozygotic weight-discordant twins. Matrix Biol 2022; 108:1-19. [DOI: 10.1016/j.matbio.2022.02.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 02/16/2022] [Accepted: 02/23/2022] [Indexed: 12/11/2022]
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9
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Lelièvre SA. Can the epigenome contribute to risk stratification for cancer onset? NAR Cancer 2021; 3:zcab043. [PMID: 34734185 PMCID: PMC8559165 DOI: 10.1093/narcan/zcab043] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 10/10/2021] [Accepted: 10/27/2021] [Indexed: 12/12/2022] Open
Abstract
The increasing burden of cancer requires identifying and protecting individuals at highest risk. The epigenome provides an indispensable complement to genetic alterations for a risk stratification approach for the following reasons: gene transcription necessary for cancer onset is directed by epigenetic modifications and many risk factors studied so far have been associated with alterations related to the epigenome. The risk level depends on the plasticity of the epigenome during phases of life particularly sensitive to environmental and dietary impacts. Modifications in the activity of DNA regulatory regions and altered chromatin compaction may accumulate, hence leading to the increase of cancer risk. Moreover, tissue architecture directs the unique organization of the epigenome for each tissue and cell type, which allows the epigenome to control cancer risk in specific organs. Investigations of epigenetic signatures of risk should help identify a continuum of alterations leading to a threshold beyond which the epigenome cannot maintain homeostasis. We propose that this threshold may be similar in the population for a given tissue, but the pace to reach this threshold will depend on the combination of germline inheritance and the risk and protective factors encountered, particularly during windows of epigenetic susceptibility, by individuals.
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Affiliation(s)
- Sophie A Lelièvre
- Institut de Cancérologie de l'Ouest (ICO)-Western Cancer Institute, Scientific Direction for Translational Research, Angers, France
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10
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Do WL, Gohar J, McCullough LE, Galaviz KI, Conneely KN, Narayan KMV. Examining the association between adiposity and DNA methylation: A systematic review and meta-analysis. Obes Rev 2021; 22:e13319. [PMID: 34278703 DOI: 10.1111/obr.13319] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 05/26/2021] [Accepted: 06/22/2021] [Indexed: 12/13/2022]
Abstract
Obesity is associated with widespread differential DNA methylation (DNAm) patterns, though there have been limited overlap in the obesity-associated cytosine-guanine nucleotide pair (CpG) sites that have been identified in the literature. We systematically searched four databases for studies published until January 2020. Eligible studies included cross-sectional, longitudinal, or intervention studies examining adiposity and genome-wide DNAm in non-pregnant adults aged 18-75 in all tissue types. Study design and results were extracted in the descriptive review. Blood-based DNAm results in body mass index (BMI) and waist circumference (WC) were meta-analyzed using weighted sum of Z-score meta-analysis. Of the 10,548 studies identified, 46 studies were included in the systematic review with 18 and nine studies included in the meta-analysis of BMI and WC, respectively. In the blood, 77 and four CpG sites were significant in three or more studies of BMI and WC, respectively. Using a genome-wide threshold for significance, 52 blood-based CpG sites were significantly associated with BMI. These sites have previously been associated with many obesity-related diseases including type 2 diabetes, cardiovascular disease, Crohn's disease, and depression. Our study shows that DNAm at 52 CpG sites represent potential mediators of obesity-associated chronic diseases and may be novel intervention or therapeutic targets to protect against obesity-associated chronic diseases.
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Affiliation(s)
- Whitney L Do
- Nutrition and Health Sciences Program, Laney Graduate School, Emory University, Atlanta, Georgia, USA
| | - Jazib Gohar
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Lauren E McCullough
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Karla I Galaviz
- Department of Applied Health Science, School of Public Health, Indiana University Bloomington, Bloomington, Indiana, USA
| | - Karen N Conneely
- Department of Human Genetics, School of Medicine, Emory University, Atlanta, Georgia, USA
| | - K M Venkat Narayan
- Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
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11
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Lucia RM, Huang WL, Alvarez A, Masunaka I, Ziogas A, Goodman D, Odegaard AO, Norden-Krichmar TM, Park HL. Association of mammographic density with blood DNA methylation. Epigenetics 2021; 17:531-546. [PMID: 34116608 PMCID: PMC9067527 DOI: 10.1080/15592294.2021.1928994] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Background: Altered DNA methylation may be an intermediate phenotype between breast cancer risk factors and disease. Mammographic density is a strong risk factor for breast cancer. However, no studies to date have identified an epigenetic signature of mammographic density. We performed an epigenome-wide association study of mammographic density. Methods: White blood cell DNA methylation was measured for 385 postmenopausal women using the Illumina Infinium MethylationEPIC BeadChip array. Differential methylation was assessed using genome-wide, probe-level, and regional analyses. We implemented a resampling-based approach to improve the stability of our findings. Results: On average, women with elevated mammographic density exhibited DNA hypermethylation within CpG islands and gene promoters compared to women with lower mammographic density. We identified 250 CpG sites for which DNA methylation was significantly associated with mammographic density. The top sites were located within genes associated with cancer, including HDLBP, TGFB2, CCT4, and PAX8, and were more likely to be located in regulatory regions of the genome. We also identified differential DNA methylation in 37 regions, including within the promoters of PAX8 and PF4, a gene involved in the regulation of angiogenesis. Overall, our results paint a picture of epigenetic dysregulation associated with mammographic density. Conclusion: Mammographic density is associated with differential DNA methylation throughout the genome, including within genes associated with cancer. Our results suggest the potential involvement of several genes in the biological mechanisms behind differences in breast density between women. Further studies are warranted to explore these potential mechanisms and potential links to breast cancer risk.
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Affiliation(s)
- Rachel M Lucia
- Department of Epidemiology, University of California, Irvine, USA
| | - Wei-Lin Huang
- Department of Epidemiology, University of California, Irvine, USA
| | - Andrea Alvarez
- Department of Medicine, University of California, Irvine, USA
| | - Irene Masunaka
- Department of Medicine, University of California, Irvine, USA
| | - Argyrios Ziogas
- Department of Medicine, University of California, Irvine, USA
| | - Deborah Goodman
- Department of Epidemiology, University of California, Irvine, USA
| | | | | | - Hannah Lui Park
- Department of Epidemiology, University of California, Irvine, USA.,Department of Pathology and Laboratory Medicine, University of California, Irvine, USA
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12
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Wang SC, Liao LM, Ansar M, Lin SY, Hsu WW, Su CM, Chung YM, Liu CC, Hung CS, Lin RK. Automatic Detection of the Circulating Cell-Free Methylated DNA Pattern of GCM2, ITPRIPL1 and CCDC181 for Detection of Early Breast Cancer and Surgical Treatment Response. Cancers (Basel) 2021; 13:cancers13061375. [PMID: 33803633 PMCID: PMC8002961 DOI: 10.3390/cancers13061375] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 03/12/2021] [Accepted: 03/16/2021] [Indexed: 12/31/2022] Open
Abstract
The early detection of cancer can reduce cancer-related mortality. There is no clinically useful noninvasive biomarker for early detection of breast cancer. The aim of this study was to develop accurate and precise early detection biomarkers and a dynamic monitoring system following treatment. We analyzed a genome-wide methylation array in Taiwanese and The Cancer Genome Atlas (TCGA) breast cancer (BC) patients. Most breast cancer-specific circulating methylated CCDC181, GCM2 and ITPRIPL1 biomarkers were found in the plasma. An automatic analysis process of methylated ccfDNA was established. A combined analysis of CCDC181, GCM2 and ITPRIPL1 (CGIm) was performed in R using Recursive Partitioning and Regression Trees to establish a new prediction model. Combined analysis of CCDC181, GCM2 and ITPRIPL1 (CGIm) was found to have a sensitivity level of 97% and an area under the curve (AUC) of 0.955 in the training set, and a sensitivity level of 100% and an AUC of 0.961 in the test set. The circulating methylated CCDC181, GCM2 and ITPRIPL1 was also significantly decreased after surgery (all p < 0.001). The aberrant methylation patterns of the CCDC181, GCM2 and ITPRIPL1 genes means that they are potential biomarkers for the detection of early BC and can be combined with breast imaging data to achieve higher accuracy, sensitivity and specificity, facilitating breast cancer detection. They may also be applied to monitor the surgical treatment response.
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Affiliation(s)
- Sheng-Chao Wang
- Ph.D. Program in Drug Discovery and Development Industry, College of Pharmacy, Taipei Medical University, No. 250, Wuxing Street, Taipei 110, Taiwan;
| | - Li-Min Liao
- Division of General Surgery, Department of Surgery, Taipei Medical University Shuang Ho Hospital, No.291, Zhongzheng Rd., Zhonghe District, New Taipei City 23561, Taiwan; (L.-M.L.); (C.-M.S.)
| | - Muhamad Ansar
- Ph.D. Program in the Clinical Drug Development of Herbal Medicine, Taipei Medical University, 250 Wu-Hsing Street, Taipei 110, Taiwan;
| | - Shih-Yun Lin
- Graduate Institute of Pharmacognosy, Taipei Medical University, 250 Wu-Hsing Street, Taipei 110, Taiwan;
| | - Wei-Wen Hsu
- Department of Statistics, College of Arts and Sciences, Kansas State University, 101 Dickens Hall, 1116 Mid-Campus Drive N, Manhattan, KS 66506-0802, USA;
| | - Chih-Ming Su
- Division of General Surgery, Department of Surgery, Taipei Medical University Shuang Ho Hospital, No.291, Zhongzheng Rd., Zhonghe District, New Taipei City 23561, Taiwan; (L.-M.L.); (C.-M.S.)
- Department of Surgery, School of Medicine, College of Medicine, Taipei Medical University, No. 250, Wuxing Street, Taipei 110, Taiwan
| | - Yu-Mei Chung
- Master Program for Clinical Pharmacogenomics and Pharmacoproteomics, Taipei Medical University, 250 Wu-Hsing Street, Taipei 110, Taiwan;
| | - Cai-Cing Liu
- School of Medical Laboratory Science and Biotechnology, College of Medical Science and Technology, Taipei Medical University, 250 Wu-Hsing Street, Taipei 110, Taiwan;
| | - Chin-Sheng Hung
- Division of General Surgery, Department of Surgery, Taipei Medical University Shuang Ho Hospital, No.291, Zhongzheng Rd., Zhonghe District, New Taipei City 23561, Taiwan; (L.-M.L.); (C.-M.S.)
- Department of Surgery, School of Medicine, College of Medicine, Taipei Medical University, No. 250, Wuxing Street, Taipei 110, Taiwan
- Correspondence: (C.-S.H.); (R.-K.L.); Tel.: +886-970-405-127 (C.-S.H.); +886-2-2736-1661 (ext. 6162) (R.-K.L.)
| | - Ruo-Kai Lin
- Ph.D. Program in Drug Discovery and Development Industry, College of Pharmacy, Taipei Medical University, No. 250, Wuxing Street, Taipei 110, Taiwan;
- Ph.D. Program in the Clinical Drug Development of Herbal Medicine, Taipei Medical University, 250 Wu-Hsing Street, Taipei 110, Taiwan;
- Graduate Institute of Pharmacognosy, Taipei Medical University, 250 Wu-Hsing Street, Taipei 110, Taiwan;
- Master Program for Clinical Pharmacogenomics and Pharmacoproteomics, Taipei Medical University, 250 Wu-Hsing Street, Taipei 110, Taiwan;
- Clinical trial center, Taipei Medical University Hospital, 252 Wu-Hsing Street, Taipei 110, Taiwan
- Correspondence: (C.-S.H.); (R.-K.L.); Tel.: +886-970-405-127 (C.-S.H.); +886-2-2736-1661 (ext. 6162) (R.-K.L.)
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13
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Choi YJ, Lee YA, Hong YC, Cho J, Lee KS, Shin CH, Kim BN, Kim JI, Park SJ, Bisgaard H, Bønnelykke K, Lim YH. Effect of prenatal bisphenol A exposure on early childhood body mass index through epigenetic influence on the insulin-like growth factor 2 receptor (IGF2R) gene. ENVIRONMENT INTERNATIONAL 2020; 143:105929. [PMID: 32645488 DOI: 10.1016/j.envint.2020.105929] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 06/22/2020] [Accepted: 06/23/2020] [Indexed: 06/11/2023]
Abstract
OBJECTIVES Epigenetic mechanisms have been suggested to play a role in the link between in utero exposure to bisphenol A (BPA) and pediatric obesity; however, there is little evidence regarding this mechanism in humans. We obtained data on obesity-associated CpG sites from a previous epigenome-wide association study, and then examined whether methylation at those CpG sites was influenced by prenatal BPA exposure. We then evaluated the relationship between CpG methylation status and body mass index (BMI) in a prospective children's cohort at ages 2, 4, 6, and 8 years. METHODS Methylation profiles of 59 children were longitudinally analyzed at ages 2 and 6 years using the Infinium Human Methylation BeadChip. A total of 594 CpG sites known to be BMI or obesity-associated sites were tested for an association with prenatal BPA levels, categorized into low and high exposure groups based on the 80th percentile of maternal BPA levels (2.68 μg/g creatinine), followed by an analysis of the association between DNA methylation and BMI from ages 2-8. RESULTS There was a significant increase in the methylation levels of cg19196862 (IGF2R) in the high BPA group at age 2 years (p = 0.00030, false discovery rate corrected p < 0.10) but not at age 6. With one standard deviation increase of methylation at cg19196862 (IGF2R) at age 2 years, the linear mixed model analysis revealed that BMI during ages 2-8 years significantly increased by 0.49 (95% confidence interval; 0.08, 0.90) in girls, but not in boys. The indirect effect of prenatal BPA exposure on early childhood BMI through methylation at cg19196862 (IGF2R) at age 2 years was marginally significant. CONCLUSIONS Prenatal exposure to BPA may influence differential methylation of IGF2R at age 2. This result indicates that a possible sensitive period of DNA methylation occurs earlier during development, which may affect BMI until later childhood in a sex-specific manner.
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Affiliation(s)
- Yoon-Jung Choi
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul 03080, Republic of Korea; Environmental Health Center, Seoul National University College of Medicine, Seoul 03080, Republic of Korea
| | - Young Ah Lee
- Department of Pediatrics, Seoul National University College of Medicine, Seoul 03080, Republic of Korea
| | - Yun-Chul Hong
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul 03080, Republic of Korea; Environmental Health Center, Seoul National University College of Medicine, Seoul 03080, Republic of Korea; Institute of Environmental Medicine, Seoul National University Medical Research Center, Seoul 03080, Republic of Korea
| | - Jinwoo Cho
- Institute of Environmental Medicine, Seoul National University Medical Research Center, Seoul 03080, Republic of Korea
| | - Kyung-Shin Lee
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul 03080, Republic of Korea; Environmental Health Center, Seoul National University College of Medicine, Seoul 03080, Republic of Korea
| | - Choong Ho Shin
- Department of Pediatrics, Seoul National University College of Medicine, Seoul 03080, Republic of Korea
| | - Bung-Nyun Kim
- Division of Children and Adolescent Psychiatry, Department of Psychiatry, Seoul National University Hospital, Seoul 03080, Republic of Korea
| | - Johanna Inhyang Kim
- Department of Psychiatry, Hanyang University Medical Center, Seoul 04763, Republic of Korea
| | - Soo Jin Park
- Department of Surgery, Wonkwang University Sanbon Hospital, Gunpo 15865, Republic of Korea
| | - Hans Bisgaard
- COPSAC (Copenhagen Prospective Studies on Asthma in Childhood), Herlev and Gentofte Hospital, University of Copenhagen, 2820, Gentofte, Copenhagen, Denmark
| | - Klaus Bønnelykke
- COPSAC (Copenhagen Prospective Studies on Asthma in Childhood), Herlev and Gentofte Hospital, University of Copenhagen, 2820, Gentofte, Copenhagen, Denmark
| | - Youn-Hee Lim
- Institute of Environmental Medicine, Seoul National University Medical Research Center, Seoul 03080, Republic of Korea; Section of Environmental Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen 1014, Denmark.
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14
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Li W, Baumbach J, Larsen MJ, Mohammadnejad A, Lund J, Christensen K, Christiansen L, Tan Q. Differential long noncoding RNA profiling of BMI in twins. Epigenomics 2020; 12:1531-1541. [PMID: 32901529 DOI: 10.2217/epi-2020-0033] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aim: Many efforts have been deployed to identify genetic variants associated with BMI. Alternatively, we explore epigenetic contribution to BMI variation by focusing on long noncoding RNAs (lncRNAs) which represents a key layer of epigenetic control. Materials & methods: We analyzed lncRNA expression in whole blood of 229 monozygotic twin pairs in association with BMI using generalized estimating equations. Results & conclusion: Six lncRNA probes were identified as significant (false discovery rate <0.05), with BMI showing causal effects on the expression of the significant lncRNAs. Functional annotation of differential profiles identified Gene ontology biological processes including kidney development, regulations of lipid biosynthetic process, circadian rhythm, notch signaling, etc. Whole blood lncRNAs are significantly expressed in response to BMI variation.
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Affiliation(s)
- Weilong Li
- Unit of Epidemiology, Biostatistics & Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Jan Baumbach
- Computational BioMedicine, Department of Mathematics & Computer Science, University of Southern Denmark, Odense, Denmark.,Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
| | - Martin J Larsen
- Department of Clinical Genetics, Odense University Hospital, Odense, Denmark.,Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Afsaneh Mohammadnejad
- Unit of Epidemiology, Biostatistics & Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Jesper Lund
- Unit of Epidemiology, Biostatistics & Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Kaare Christensen
- Unit of Epidemiology, Biostatistics & Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark.,Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Lene Christiansen
- Unit of Epidemiology, Biostatistics & Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark.,Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Qihua Tan
- Unit of Epidemiology, Biostatistics & Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark.,Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
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15
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Justice AE, Chittoor G, Gondalia R, Melton PE, Lim E, Grove ML, Whitsel EA, Liu CT, Cupples LA, Fernandez-Rhodes L, Guan W, Bressler J, Fornage M, Boerwinkle E, Li Y, Demerath E, Heard-Costa N, Levy D, Stewart JD, Baccarelli A, Hou L, Conneely K, Mori TA, Beilin LJ, Huang RC, Gordon-Larsen P, Howard AG, North KE. Methylome-wide association study of central adiposity implicates genes involved in immune and endocrine systems. Epigenomics 2020; 12:1483-1499. [PMID: 32901515 PMCID: PMC7923253 DOI: 10.2217/epi-2019-0276] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Accepted: 05/22/2020] [Indexed: 12/14/2022] Open
Abstract
Aim: We conducted a methylome-wide association study to examine associations between DNA methylation in whole blood and central adiposity and body fat distribution, measured as waist circumference, waist-to-hip ratio and waist-to-height ratio adjusted for body mass index, in 2684 African-American adults in the Atherosclerosis Risk in Communities study. Materials & methods: We validated significantly associated cytosine-phosphate-guanine methylation sites (CpGs) among adults using the Women's Health Initiative and Framingham Heart Study participants (combined n = 5743) and generalized associations in adolescents from The Raine Study (n = 820). Results & conclusion: We identified 11 CpGs that were robustly associated with one or more central adiposity trait in adults and two in adolescents, including CpG site associations near TXNIP, ADCY7, SREBF1 and RAP1GAP2 that had not previously been associated with obesity-related traits.
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Affiliation(s)
- Anne E Justice
- Department of Population Health Sciences, Geisinger, Danville, PA 17822, USA
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Geetha Chittoor
- Department of Population Health Sciences, Geisinger, Danville, PA 17822, USA
| | - Rahul Gondalia
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Phillip E Melton
- School of Biomedical Science, Faculty of Health & Medical Sciences, The University of Western Australia, Perth, WA 6000, Australia
- School of Pharmacy & Biomedical Sciences, Faculty of Health Sciences, Curtin University, MRF Building, Perth, WA 6000, Australia
- Menzies Institute for Medical Research, College of Health & Medicine, University of Tasmania, Hobart, TA, 7000 Australia
| | - Elise Lim
- Department of Biostatistics, Boston University, Boston, MA 02118, USA
| | - Megan L Grove
- Human Genetics Center, Department of Epidemiology, Human Genetics & Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University, Boston, MA 02118, USA
| | - L Adrienne Cupples
- Department of Biostatistics, Boston University, Boston, MA 02118, USA
- Framingham Heart Study, Framingham, MA, 01701, USA
| | - Lindsay Fernandez-Rhodes
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biobehavioral Health, Pennsylvania State University, University Park, PA 16802, USA
| | - Weihua Guan
- Division of Biostatistics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Jan Bressler
- Human Genetics Center, Department of Epidemiology, Human Genetics & Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Myriam Fornage
- Center for Human Genetics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston McGovern Medical School, Houston, TX 77030, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics & Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Yun Li
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, NC 27599, USA
| | - Ellen Demerath
- Division of Epidemiology & Community Health, University of Minnesota, Minneapolis, MN 55455, USA
| | - Nancy Heard-Costa
- Framingham Heart Study, Framingham, MA, 01701, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Dan Levy
- Population sciences branch, NHLBI Framingham Heart Study, Framingham, MA 01702, USA
- Department of Medicine, Boston University, Boston, MA 02118, USA
| | - James D Stewart
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Andrea Baccarelli
- Laboratory of Environmental Epigenetics, Departments of Environmental Health Sciences & Epidemiology, Columbia University Mailman School of Public Health, New York, NY 10032, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University Chicago, Evanston, IL, USA
| | - Karen Conneely
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Trevor A Mori
- Medical School, University of Western Australia, Perth, Australia
| | | | - Rae-Chi Huang
- Telethon Kids Institute, University of Western Australia, Perth, Australia
| | - Penny Gordon-Larsen
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, NC 27599, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, NC 27516, USA
| | - Annie Green Howard
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, NC 27516, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, NC 27516, USA
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16
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Shrestha D, Ouidir M, Workalemahu T, Zeng X, Tekola-Ayele F. Placental DNA methylation changes associated with maternal prepregnancy BMI and gestational weight gain. Int J Obes (Lond) 2020; 44:1406-1416. [PMID: 32071425 PMCID: PMC7261634 DOI: 10.1038/s41366-020-0546-2] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Revised: 01/14/2020] [Accepted: 02/06/2020] [Indexed: 12/15/2022]
Abstract
BACKGROUND Maternal obesity prior to or during pregnancy influences fetal growth, predisposing the offspring to increased risk for obesity across the life course. Placental epigenetic mechanisms may underlie these associations. We conducted an epigenome-wide association study to identify placental DNA methylation changes associated with maternal prepregnancy body mass index (BMI) and rate of gestational weight gain at first (GWG1), second (GWG2), and third trimester (GWG3). METHOD Participants of the NICHD Fetal Growth Studies with genome-wide placental DNA methylation (n = 301) and gene expression (n = 75) data were included. Multivariable-adjusted regression models were used to test the associations of 1 kg/m2 increase in prepregnancy BMI or 1 kg/week increase in GWG with DNA methylation levels. Genes harboring top differentially methylated CpGs (FDR P < 0.05) were evaluated for placental gene expression. We assessed whether DNA methylation sites known to be associated with BMI in child or adult tissues, were also associated with maternal prepregnancy BMI in placenta. RESULTS Prepregnancy BMI was associated with DNA methylation at cg14568196[EGFL7], cg15339142[VETZ], and cg02301019[AC092377.1] (FDR P < 0.05, P ranging from 1.4 × 10-10 to 1.7 × 10-9). GWG1 or GWG2 was associated with DNA methylation at cg17918270[MYT1L], cg20735365[DLX5], and cg17451688[SLC35F3] (FDR P < 0.05, P ranging from 6.4 × 10-10 to 1.2 × 10-8). Both prepregnancy BMI and DNA methylation at cg1456819 [EGFL7] were negatively correlated with EGFL7 expression in placenta (P < 0.05). Several CpGs previously implicated in obesity traits in children and adults were associated with prepregnancy BMI in placenta. Functional annotations revealed that EGFL7 is highly expressed in placenta and the differentially methylated CpG sites near EGFL7 and VEZT were cis-meQTL targets in blood. CONCLUSIONS We identified placental DNA methylation changes at novel loci associated with prepregnancy BMI and GWG. The overlap between CpGs associated with obesity traits in placenta and other tissues in children and adults suggests that epigenetic mechanisms in placenta may give insights to early origins of obesity.
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Affiliation(s)
- Deepika Shrestha
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Marion Ouidir
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Tsegaselassie Workalemahu
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Xuehuo Zeng
- Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Fasil Tekola-Ayele
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.
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17
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Ratna MG, Nugrahaningsih DAA, Sholikhah EN, Dwianingsih EK, Malueka RG. The association between PON1 and GSTM1 genetic variation with methylation of p16 gene promoter among Javanese farmers exposed to pesticides at Magelang Regency, Central Java, Indonesia. Heliyon 2020; 6:e03993. [PMID: 32478190 PMCID: PMC7248662 DOI: 10.1016/j.heliyon.2020.e03993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Revised: 12/11/2019] [Accepted: 05/12/2020] [Indexed: 12/08/2022] Open
Abstract
Occupational exposure to pesticides leads to the development of cancer. Aberrant DNA methylation plays a crucial role in cancer. The manifestation of the carcinogenic effect of pesticides could be determined by the variation of genes encoding enzyme, including PON1 Q192R and GSTM1. The goal of this study was to find out polymorphism of PON1 Q192R and methylation of p16 gene promoter, and their correlation on Javanese farmers in the agricultural area of Ngablak Subdistrict, Magelang Regency, Central Java. Seventy-eight pesticide-exposed farmers enrolled in the study. Polymorphism of PON Q192R was determined using PCR-RFLP and variation of GSTM1 was examined using conventional PCR. The methylation of the p16 gene promoter was determined using methylation-specific PCR. The result revealed 94.9% polymorphism of PON1 Q192R, which was higher in the R/R (Arg/Arg) genotypes than Q/R (Gln/Arg) and lowest in Q/Q (Gln/Gln) genotypes. We also found 82.1% GSTM1 null genotype among the farmers enrolled in the study. As many as 26.9% methylations of p16 gene promoter were found among farmers. Genetic variation of PON1 Q192R and GSTM1 were not found to be correlated to the methylation status of p16 gene promoter in the Javanese population.
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Affiliation(s)
- Maya G Ratna
- Master of Biomedical Science Program, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Dwi A A Nugrahaningsih
- Department of Pharmacology and Therapy, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia.,Genetics Working Group, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Indonesia
| | - Eti N Sholikhah
- Department of Pharmacology and Therapy, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Ery K Dwianingsih
- Department of Anatomical Pathology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia.,Genetics Working Group, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Indonesia
| | - Rusdy G Malueka
- Department of Neurology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia.,Genetics Working Group, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Indonesia
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18
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Khamis A, Boutry R, Canouil M, Mathew S, Lobbens S, Crouch H, Andrew T, Abderrahmani A, Tamanini F, Froguel P. Histone deacetylase 9 promoter hypomethylation associated with adipocyte dysfunction is a statin-related metabolic effect. Clin Epigenetics 2020; 12:68. [PMID: 32410704 PMCID: PMC7222462 DOI: 10.1186/s13148-020-00858-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Accepted: 04/28/2020] [Indexed: 12/14/2022] Open
Abstract
Background Adipogenesis, the process whereby preadipocytes differentiate into mature adipocytes, is crucial for maintaining metabolic homeostasis. Cholesterol-lowering statins increase type 2 diabetes (T2D) risk possibly by affecting adipogenesis and insulin resistance but the (epi)genetic mechanisms involved are unknown. Here, we characterised the effects of statin treatment on adipocyte differentiation using in vitro human preadipocyte cell model to identify putative effective genes. Results Statin treatment during adipocyte differentiation caused a reduction in key genes involved in adipogenesis, such as ADIPOQ, GLUT4 and ABCG1. Using Illumina’s Infinium ‘850K’ Methylation EPIC array, we found a significant hypomethylation of cg14566882, located in the promoter of the histone deacetylase 9 (HDAC9) gene, in response to two types of statins (atorvastatin and mevastatin), which correlates with an increased HDAC9 mRNA expression. We confirmed that HDAC9 is a transcriptional repressor of the cholesterol efflux ABCG1 gene expression, which is epigenetically modified in obesity and prediabetic states. Thus, we assessed the putative impact of ABCG1 knockdown in mimicking the effect of statin in adipogenesis. ABCG1 KD reduced the expression of key genes involved in adipocyte differentiation and decreased insulin signalling and glucose uptake. In human blood cells from two cohorts, ABCG1 expression was impaired in response to statins, confirming that ABCG1 is targeted in vivo by these drugs. Conclusions We identified an epigenetic link between adipogenesis and adipose tissue insulin resistance in the context of T2D risk associated with statin use, which has important implications as HDAC9 and ABCG1 are considered potential therapeutic targets for obesity and metabolic diseases.
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Affiliation(s)
- Amna Khamis
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.,Université de Lille, Inserm UMR1283, CNRS-UMR 8199 - EGID, Lille, Lille University Hospital, F-59000, Lille, France
| | - Raphael Boutry
- Université de Lille, Inserm UMR1283, CNRS-UMR 8199 - EGID, Lille, Lille University Hospital, F-59000, Lille, France
| | - Mickaël Canouil
- Université de Lille, Inserm UMR1283, CNRS-UMR 8199 - EGID, Lille, Lille University Hospital, F-59000, Lille, France
| | - Sumi Mathew
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Stephane Lobbens
- Université de Lille, Inserm UMR1283, CNRS-UMR 8199 - EGID, Lille, Lille University Hospital, F-59000, Lille, France
| | - Hutokshi Crouch
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Toby Andrew
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Amar Abderrahmani
- Université de Lille, Inserm UMR1283, CNRS-UMR 8199 - EGID, Lille, Lille University Hospital, F-59000, Lille, France
| | - Filippo Tamanini
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Philippe Froguel
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK. .,Université de Lille, Inserm UMR1283, CNRS-UMR 8199 - EGID, Lille, Lille University Hospital, F-59000, Lille, France.
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19
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Giri AK, Prasad G, Bandesh K, Parekatt V, Mahajan A, Banerjee P, Kauser Y, Chakraborty S, Rajashekar D, Sharma A, Mathur SK, Basu A, McCarthy MI, Tandon N, Bharadwaj D. Multifaceted genome-wide study identifies novel regulatory loci in SLC22A11 and ZNF45 for body mass index in Indians. Mol Genet Genomics 2020; 295:1013-1026. [PMID: 32363570 DOI: 10.1007/s00438-020-01678-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2019] [Accepted: 04/11/2020] [Indexed: 12/22/2022]
Abstract
Obesity, a risk factor for multiple diseases (e.g. diabetes, hypertension, cancers) originates through complex interactions between genes and prevailing environment (food habit and lifestyle) that varies across populations. Indians exhibit a unique obesity phenotype with high abdominal adiposity for a given body weight compared to matched white populations suggesting presence of population-specific genetic and environmental factors influencing obesity. However, Indian population-specific genetic contributors for obesity have not been explored yet. Therefore, to identify potential genetic contributors, we performed a two-staged genome-wide association study (GWAS) for body mass index (BMI), a common measure to evaluate obesity in 5973 Indian adults and the lead findings were further replicated in 1286 Indian adolescents. Our study revealed novel association of variants-rs6913677 in BAI3 gene (p = 1.08 × 10-8) and rs2078267 in SLC22A11 gene (p = 4.62 × 10-8) at GWAS significance, and of rs8100011 in ZNF45 gene (p = 1.04 × 10-7) with near GWAS significance. As genetic loci may dictate the phenotype through modulation of epigenetic processes, we overlapped genetic data of identified signals with their DNA methylation patterns in 236 Indian individuals and performed methylation quantitative trait loci (meth-QTL) analysis. Further, functional roles of discovered variants and underlying genes were speculated using publicly available gene regulatory databases (ENCODE, JASPAR, GeneHancer, GTEx). The identified variants in BAI3 and SLC22A11 genes were found to dictate methylation patterns at unique CpGs harboring critical cis-regulatory elements. Further, BAI3, SLC22A11 and ZNF45 variants were located in repressive chromatin, active enhancer, and active chromatin regions, respectively, in human subcutaneous adipose tissue in ENCODE database. Additionally, these genomic regions represented potential binding sites for key transcription factors implicated in obesity and/or metabolic disorders. Interestingly, GTEx portal identify rs8100011 as a robust cis-expression quantitative trait locus (cis-eQTL) in subcutaneous adipose tissue (p = 1.6 × 10-7), and ZNF45 gene expression in skeletal muscle of Indian subjects showed an inverse correlation with BMI indicating its possible role in obesity. In conclusion, our study discovered 3 novel population-specific functional genetic variants (rs6913677, rs2078267, rs8100011) in 2 novel (SLC22A11 and ZNF45) and 1 earlier reported gene (BAI3) for BMI in Indians. Our study decodes key genomic loci underlying obesity phenotype in Indians that may serve as prospective drug targets in future.
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Affiliation(s)
- Anil K Giri
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.,Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, India
| | - Gauri Prasad
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.,Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, India
| | - Khushdeep Bandesh
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.,Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, India
| | - Vaisak Parekatt
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India
| | - Anubha Mahajan
- Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Priyanka Banerjee
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India
| | - Yasmeen Kauser
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.,Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, India
| | - Shraddha Chakraborty
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.,Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, India
| | - Donaka Rajashekar
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India
| | | | - Abhay Sharma
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.,Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, India
| | - Sandeep Kumar Mathur
- Department of Endocrinology, Sawai Man Singh Medical College, Jaipur, Rajasthan, India
| | - Analabha Basu
- National Institute of Biomedical Genomics, Kalyani, West Bengal, India
| | - Mark I McCarthy
- Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Nikhil Tandon
- Department of Endocrinology and Metabolism, All India Institute of Medical Sciences, New Delhi, India.
| | - Dwaipayan Bharadwaj
- Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, India. .,Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, India.
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20
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Epigenetic Biomarkers for Environmental Exposures and Personalized Breast Cancer Prevention. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17041181. [PMID: 32069786 PMCID: PMC7068429 DOI: 10.3390/ijerph17041181] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Revised: 02/07/2020] [Accepted: 02/10/2020] [Indexed: 12/11/2022]
Abstract
Environmental and lifestyle factors are believed to account for >80% of breast cancers; however, it is not well understood how and when these factors affect risk and which exposed individuals will actually develop the disease. While alcohol consumption, obesity, and hormone therapy are some known risk factors for breast cancer, other exposures associated with breast cancer risk have not yet been identified or well characterized. In this paper, it is proposed that the identification of blood epigenetic markers for personal, in utero, and ancestral environmental exposures can help researchers better understand known and potential relationships between exposures and breast cancer risk and may enable personalized prevention strategies.
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21
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Delacrétaz A, Glatard A, Dubath C, Gholam-Rezaee M, Sanchez-Mut JV, Gräff J, von Gunten A, Conus P, Eap CB. Psychotropic drug-induced genetic-epigenetic modulation of CRTC1 gene is associated with early weight gain in a prospective study of psychiatric patients. Clin Epigenetics 2019; 11:198. [PMID: 31878957 PMCID: PMC6933694 DOI: 10.1186/s13148-019-0792-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2019] [Accepted: 12/02/2019] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Metabolic side effects induced by psychotropic drugs represent a major health issue in psychiatry. CREB-regulated transcription coactivator 1 (CRTC1) gene plays a major role in the regulation of energy homeostasis and epigenetic mechanisms may explain its association with obesity features previously described in psychiatric patients. This prospective study included 78 patients receiving psychotropic drugs that induce metabolic disturbances, with weight and other metabolic parameters monitored regularly. Methylation levels in 76 CRTC1 probes were assessed before and after 1 month of psychotropic treatment in blood samples. RESULTS Significant methylation changes were observed in three CRTC1 CpG sites (i.e., cg07015183, cg12034943, and cg 17006757) in patients with early and important weight gain (i.e., equal or higher than 5% after 1 month; FDR p value = 0.02). Multivariable models showed that methylation decrease in cg12034943 was more important in patients with early weight gain (≥ 5%) than in those who did not gain weight (p = 0.01). Further analyses combining genetic and methylation data showed that cg12034943 was significantly associated with early weight gain in patients carrying the G allele of rs4808844A>G (p = 0.03), a SNP associated with this methylation site (p = 0.03). CONCLUSIONS These findings give new insights on psychotropic-induced weight gain and underline the need of future larger prospective epigenetic studies to better understand the complex pathways involved in psychotropic-induced metabolic side effects.
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Affiliation(s)
- Aurélie Delacrétaz
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Centre for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland
| | - Anaïs Glatard
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Centre for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland
| | - Céline Dubath
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Centre for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland
| | - Mehdi Gholam-Rezaee
- Centre of Psychiatric Epidemiology and Psychopathology, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland
| | - Jose Vicente Sanchez-Mut
- Laboratory of Neuroepigenetics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Johannes Gräff
- Laboratory of Neuroepigenetics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Armin von Gunten
- Service of Old Age Psychiatry, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland
| | - Philippe Conus
- Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland
| | - Chin B Eap
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Centre for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland. .,Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland.
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22
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Kresovich JK, Xu Z, O'Brien KM, Weinberg CR, Sandler DP, Taylor JA. Epigenetic mortality predictors and incidence of breast cancer. Aging (Albany NY) 2019; 11:11975-11987. [PMID: 31848323 PMCID: PMC6949084 DOI: 10.18632/aging.102523] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Accepted: 11/18/2019] [Indexed: 12/12/2022]
Abstract
Measures derived using blood DNA methylation are increasingly under investigation as indicators of disease and mortality risk. Three existing epigenetic age measures or “epigenetic clocks” appear associated with breast cancer. Two newly-developed epigenetic mortality predictors may be related to all-cancer incidence, but associations with specific cancers have not been examined in large studies. Using HumanMethylation450 BeadChips to measure blood DNA methylation in 2,773 cancer-free women enrolled in the Sister Study, we calculated two epigenetic mortality predictors: ‘GrimAgeAccel’ and the ‘mortality score’ (MS). Using Cox proportional hazard models, neither GrimAgeAccel nor the MS were associated with overall breast cancer incidence (GrimAgeAccel hazard ratio [HR]: 1.06, 95% confidence interval [CI]: 0.98-1.14, P=0.17; MS HR: 0.99, 95% CI: 0.92-1.07, P=0.85); however, a weak, positive association was observed for GrimAgeAccel and invasive breast cancer (HR: 1.08, 95% CI: 0.99-1.17, P=0.08). Stratification of invasive cancers by menopause status at diagnoses revealed the association was predominantly observed for postmenopausal breast cancer (HR: 1.10, 95% CI: 1.01, 1.20, P=0.04). Although the MS was unrelated to breast cancer risk, we find evidence that GrimAgeAccel may be weakly associated with invasive breast cancer, particularly for women diagnosed after menopause.
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Affiliation(s)
- Jacob K Kresovich
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Durham, NC 27709, USA
| | - Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Durham, NC 27709, USA
| | - Katie M O'Brien
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Durham, NC 27709, USA
| | - Clarice R Weinberg
- Biostatistics and Computation Biology Branch, National Institute of Environmental Health Sciences, NIH, Durham, NC 27709, USA
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Durham, NC 27709, USA
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Durham, NC 27709, USA.,Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Durham, NC 27709, USA
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23
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Sun D, Zhang T, Su S, Hao G, Chen T, Li QZ, Bazzano L, He J, Wang X, Li S, Chen W. Body Mass Index Drives Changes in DNA Methylation: A Longitudinal Study. Circ Res 2019; 125:824-833. [PMID: 31510868 DOI: 10.1161/circresaha.119.315397] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
RATIONALE Previous EWASs (Epigenome-Wide Association Studies) suggest that obesity may be the cause, not a consequence, of changes in DNA methylation (DNAm). However, longitudinal observations are lacking. OBJECTIVE To identify 5'-cytosine-phosphate-guanine-3' in DNA (CpG) sites associated with body mass index (BMI) and examine the temporal relationship between dynamic changes in DNAm and BMI in a longitudinal cohort. METHODS AND RESULTS Race-specific EWASs were performed in 995 whites and 490 blacks from the Bogalusa Heart Study. Suggestive CpG sites were further replicated in 252 whites and 228 blacks from the Georgia Stress and Heart Study. Cross-lagged panel analysis was used to examine the temporal relationship between DNAm and BMI in 439 whites and 201 blacks who were examined twice 6.2 years apart. In discovery and replication samples, 349 CpG sites (266 novel) in whites and 36 (21 novel) in blacks were identified to be robustly associated with BMI, with 8 (1 novel) CpG sites overlapping between the 2 races. Cross-lagged panel analyses showed significant unidirectional paths (PFDR <0.05) from baseline BMI to follow-up DNAm at 18 CpG sites in whites and 7 in blacks; no CpG sites showed significant paths from DNAm at baseline to BMI at follow-up. Baseline BMI was associated with a DNAm score (calculated from DNAm levels at the associated CpG sites) at follow-up (P<0.001 both in blacks and in whites). CONCLUSIONS The findings provide strong evidence that obesity is the cause, not a consequence, of changes in DNAm over time.
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Affiliation(s)
- Dianjianyi Sun
- From the Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China (D.S.).,Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (D.S., T.Z., L.B., J.H., W.C.)
| | - Tao Zhang
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (D.S., T.Z., L.B., J.H., W.C.).,Department of Biostatistics, School of Public Health, Shandong University, Jinan, China (T.Z.)
| | - Shaoyong Su
- Georgia Prevention Institute, Department of Population Health Sciences, Medical College of Georgia, Augusta University (S.S., G.H., X.W)
| | - Guang Hao
- Georgia Prevention Institute, Department of Population Health Sciences, Medical College of Georgia, Augusta University (S.S., G.H., X.W)
| | - Tao Chen
- Microarray Core Facility, University of Texas Southwestern Medical Center, Dallas, TX (T.C., Z.L.)
| | - Quan-Zhen Li
- Microarray Core Facility, University of Texas Southwestern Medical Center, Dallas, TX (T.C., Z.L.)
| | - Lydia Bazzano
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (D.S., T.Z., L.B., J.H., W.C.)
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (D.S., T.Z., L.B., J.H., W.C.)
| | - Xiaoling Wang
- Georgia Prevention Institute, Department of Population Health Sciences, Medical College of Georgia, Augusta University (S.S., G.H., X.W)
| | - Shengxu Li
- Children's Minnesota Research Institute, Children's Hospitals and Clinics of Minnesota, Minneapolis (S.L.)
| | - Wei Chen
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (D.S., T.Z., L.B., J.H., W.C.)
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24
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Liu J, Carnero-Montoro E, van Dongen J, Lent S, Nedeljkovic I, Ligthart S, Tsai PC, Martin TC, Mandaviya PR, Jansen R, Peters MJ, Duijts L, Jaddoe VWV, Tiemeier H, Felix JF, Willemsen G, de Geus EJC, Chu AY, Levy D, Hwang SJ, Bressler J, Gondalia R, Salfati EL, Herder C, Hidalgo BA, Tanaka T, Moore AZ, Lemaitre RN, Jhun MA, Smith JA, Sotoodehnia N, Bandinelli S, Ferrucci L, Arnett DK, Grallert H, Assimes TL, Hou L, Baccarelli A, Whitsel EA, van Dijk KW, Amin N, Uitterlinden AG, Sijbrands EJG, Franco OH, Dehghan A, Spector TD, Dupuis J, Hivert MF, Rotter JI, Meigs JB, Pankow JS, van Meurs JBJ, Isaacs A, Boomsma DI, Bell JT, Demirkan A, van Duijn CM. An integrative cross-omics analysis of DNA methylation sites of glucose and insulin homeostasis. Nat Commun 2019; 10:2581. [PMID: 31197173 PMCID: PMC6565679 DOI: 10.1038/s41467-019-10487-4] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Accepted: 05/09/2019] [Indexed: 02/07/2023] Open
Abstract
Despite existing reports on differential DNA methylation in type 2 diabetes (T2D) and obesity, our understanding of its functional relevance remains limited. Here we show the effect of differential methylation in the early phases of T2D pathology by a blood-based epigenome-wide association study of 4808 non-diabetic Europeans in the discovery phase and 11,750 individuals in the replication. We identify CpGs in LETM1, RBM20, IRS2, MAN2A2 and the 1q25.3 region associated with fasting insulin, and in FCRL6, SLAMF1, APOBEC3H and the 15q26.1 region with fasting glucose. In silico cross-omics analyses highlight the role of differential methylation in the crosstalk between the adaptive immune system and glucose homeostasis. The differential methylation explains at least 16.9% of the association between obesity and insulin. Our study sheds light on the biological interactions between genetic variants driving differential methylation and gene expression in the early pathogenesis of T2D.
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Affiliation(s)
- Jun Liu
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands. .,Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7FL, UK.
| | - Elena Carnero-Montoro
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands.,Center for Genomics and Oncological Research, GENYO, Pfizer/University of Granada/Andalusian Government, PTS, Granada, 18007, Spain.,Department of Twin Research and Genetic Epidemiology, King's College London, London, WC2R 2LS, UK
| | - Jenny van Dongen
- Department of Biological Psychology, Amsterdam Public Health (APH) research institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, 1081BT, The Netherlands
| | - Samantha Lent
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Ivana Nedeljkovic
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands
| | - Symen Ligthart
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands
| | - Pei-Chien Tsai
- Department of Twin Research and Genetic Epidemiology, King's College London, London, WC2R 2LS, UK.,Department of Biomedical Sciences, Chang Gung University, Taoyuan, 333, Taiwan.,Division of Allergy, Asthma, and Rheumatology, Department of Pediatrics, Chang Gung Memorial Hospital, Linkou, 333, Taiwan
| | - Tiphaine C Martin
- Department of Twin Research and Genetic Epidemiology, King's College London, London, WC2R 2LS, UK.,Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.,The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Pooja R Mandaviya
- Department of Internal Medicine, Section of Pharmacology Vascular and Metabolic Diseases, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands
| | - Rick Jansen
- Department of Psychiatry and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, 1081BT, The Netherlands
| | - Marjolein J Peters
- Department of Internal Medicine, Section of Pharmacology Vascular and Metabolic Diseases, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands
| | - Liesbeth Duijts
- Division of Neonatology, Department of Pediatrics, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands.,Division of Respiratory Medicine, Department of Pediatrics, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands
| | - Vincent W V Jaddoe
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands.,Department of Pediatrics, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands.,Generation R Study Group, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands
| | - Henning Tiemeier
- Department of Child and Adolescent Psychiatry, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands.,Department of Social and Behavioral Science, Harvard TH Chan School of Public Health, Boston, MA, 02115, USA
| | - Janine F Felix
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands.,Department of Pediatrics, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands.,Generation R Study Group, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, Amsterdam Public Health (APH) research institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, 1081BT, The Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, Amsterdam Public Health (APH) research institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, 1081BT, The Netherlands
| | - Audrey Y Chu
- The Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20814, USA.,The Framingham Heart Study, National Heart, Lung and Blood Institute, National Institutes of Health, Framingham, MA, 01702, USA
| | - Daniel Levy
- The Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20814, USA.,The Framingham Heart Study, National Heart, Lung and Blood Institute, National Institutes of Health, Framingham, MA, 01702, USA
| | - Shih-Jen Hwang
- The Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20814, USA.,The Framingham Heart Study, National Heart, Lung and Blood Institute, National Institutes of Health, Framingham, MA, 01702, USA
| | - Jan Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Rahul Gondalia
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Elias L Salfati
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Christian Herder
- German Center for Diabetes Research (DZD), München-Neuherberg, 85764, Germany.,Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, 40225, Germany.,Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, 40225, Germany
| | - Bertha A Hidalgo
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, 35233, USA
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, 21224, USA
| | - Ann Zenobia Moore
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, 21224, USA
| | - Rozenn N Lemaitre
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, 98101, USA
| | - Min A Jhun
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, 98101, USA
| | | | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, 21224, USA
| | - Donna K Arnett
- School of Public Health, University of Kentucky, Lexington, KY, 40536, USA
| | - Harald Grallert
- German Center for Diabetes Research (DZD), München-Neuherberg, 85764, Germany.,Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Themistocles L Assimes
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Lifang Hou
- Center for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University Chicago, Evanston, IL, 60611, USA.,Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Andrea Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, 10032, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, 27599, USA.,Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina, NC, 27516, USA
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, 2333ZA, The Netherlands.,Department of Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, 2333ZA, The Netherlands
| | - Najaf Amin
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands.,Department of Internal Medicine, Section of Pharmacology Vascular and Metabolic Diseases, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands
| | - Eric J G Sijbrands
- Department of Internal Medicine, Section of Pharmacology Vascular and Metabolic Diseases, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands
| | - Oscar H Franco
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands.,Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, 3012, Switzerland
| | - Abbas Dehghan
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands.,Department of Epidemiology and Biostatistics, Imperial College London, London, SW7 2AZ, UK
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, WC2R 2LS, UK
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Marie-France Hivert
- Department of Medicine, Université de Sherbrooke, Sherbrooke, QC, J1K0A5, Canada.,Diabetes Unit, Massachusetts General Hospital, Boston, MA, 02114, USA.,Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences and Departments of Pediatrics and Medicine, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - James B Meigs
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA.,Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA.,Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - James S Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Joyce B J van Meurs
- CARIM School for Cardiovascular Diseases, Maastricht Centre for Systems Biology (MaCSBio), and Departments of Biochemistry and Physiology, Maastricht University, Maastricht, 6211LK, The Netherlands
| | - Aaron Isaacs
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands.,CARIM School for Cardiovascular Diseases, Maastricht Centre for Systems Biology (MaCSBio), and Departments of Biochemistry and Physiology, Maastricht University, Maastricht, 6211LK, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Amsterdam Public Health (APH) research institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, 1081BT, The Netherlands
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, WC2R 2LS, UK
| | - Ayşe Demirkan
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands. .,Department of Genetics, University Medical Center Groningen, Groningen, 9713GZ, The Netherlands. .,Section of Statistical Multi-Omics, Department of Experimental and Clinical Research, School of Bioscience and Medicine, Univeristy of Surrey, Guildford, GU2 7XH, UK.
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, 3015GD, The Netherlands. .,Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7FL, UK. .,Leiden Academic Center for Drug Research, Leiden University, Leiden, 2311EZ, The Netherlands.
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25
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Li W, Zhang D, Wang W, Wu Y, Mohammadnejad A, Lund J, Baumbach J, Christiansen L, Tan Q. DNA methylome profiling in identical twin pairs discordant for body mass index. Int J Obes (Lond) 2019; 43:2491-2499. [PMID: 31152155 DOI: 10.1038/s41366-019-0382-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Revised: 04/01/2019] [Accepted: 04/05/2019] [Indexed: 02/07/2023]
Abstract
OBJECTIVE Body mass index (BMI) serves as an important measurement of obesity and adiposity, which are highly correlated with cardiometabolic diseases. Although high heritability has been estimated, the identified genetic variants by genetic association studies only explain a small proportion of BMI variation. As an active effort for further exploring the molecular basis of BMI variation, large-scale epigenome-wide association studies have been conducted but with limited number of loci reported, perhaps due to poorly controlled confounding factors, including genetic factors. Being genetically identical, monozygotic twins discordant for BMI are ideal subjects for analyzing the epigenetic association between DNA methylation and BMI, providing perfect control on their genetic makeups largely responsible for BMI variation. SUBJECTS We performed an epigenome-wide association study on BMI using 30 identical twin pairs (15 male and 15 female pairs) with age ranging from 39 to 72 years and degree of BMI discordance ranging from 3-7.5 kg/m2. Methylation data from whole blood samples were collected using the reduced representation bisulfite sequencing technique. RESULTS After adjusting for blood cell composition and clinical variables, we identified 136 CpGs with p-value < 1e-4, 30 CpGs with p < 1e-05 but no CpGs reached genome-wide significance. Genomic region-based analysis found 11 differentially methylated regions harboring coding and non-coding genes some of which were validated by gene expression analysis on independent samples. CONCLUSIONS Our DNA methylation sequencing analysis on identical twins provides new references for the epigenetic regulation on BMI and obesity.
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Affiliation(s)
- Weilong Li
- Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Dongfeng Zhang
- Division of Epidemiology and Health Statistics, Qingdao University Medical College, Qingdao, China
| | - Weijing Wang
- Division of Epidemiology and Health Statistics, Qingdao University Medical College, Qingdao, China
| | - Yili Wu
- Division of Epidemiology and Health Statistics, Qingdao University Medical College, Qingdao, China
| | - Afsaneh Mohammadnejad
- Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Jesper Lund
- Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Jan Baumbach
- Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany.,Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark
| | - Lene Christiansen
- Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, Odense, Denmark.,Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Qihua Tan
- Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, Odense, Denmark. .,Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
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26
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Arpón A, Milagro FI, Ramos-Lopez O, Mansego ML, Santos JL, Riezu-Boj JI, Martínez JA. Epigenome-wide association study in peripheral white blood cells involving insulin resistance. Sci Rep 2019; 9:2445. [PMID: 30792424 PMCID: PMC6385280 DOI: 10.1038/s41598-019-38980-2] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Accepted: 01/11/2019] [Indexed: 02/06/2023] Open
Abstract
Insulin resistance (IR) is a hallmark of type 2 diabetes, metabolic syndrome and cardiometabolic risk. An epigenetic phenomena such as DNA methylation might be involved in the onset and development of systemic IR. The aim of this study was to explore the genetic DNA methylation levels in peripheral white blood cells with the objective of identifying epigenetic signatures associated with IR measured by the Homeostatic Model Assessment of IR (HOMA-IR) following an epigenome-wide association study approach. DNA methylation levels were assessed using Infinium Methylation Assay (Illumina), and were associated with HOMA-IR values of participants from the Methyl Epigenome Network Association (MENA) project, finding statistical associations for at least 798 CpGs. A stringent statistical analysis revealed that 478 of them showed a differential methylation pattern between individuals with HOMA-IR ≤ 3 and > 3. ROC curves of top four CpGs out of 478 allowed differentiating individuals between both groups (AUC≈0.88). This study demonstrated the association between DNA methylation in some specific CpGs and HOMA-IR values that will help to the understanding and in the development of new strategies for personalized approaches to predict and prevent IR-associated diseases.
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Affiliation(s)
- Ana Arpón
- University of Navarra, Department of Nutrition, Food Sciences and Physiology & Centre for Nutrition Research, Pamplona, Spain
| | - Fermín I Milagro
- University of Navarra, Department of Nutrition, Food Sciences and Physiology & Centre for Nutrition Research, Pamplona, Spain.,Spanish Biomedical Research Centre in Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain
| | - Omar Ramos-Lopez
- University of Navarra, Department of Nutrition, Food Sciences and Physiology & Centre for Nutrition Research, Pamplona, Spain
| | - M Luisa Mansego
- University of Navarra, Department of Nutrition, Food Sciences and Physiology & Centre for Nutrition Research, Pamplona, Spain
| | - José Luis Santos
- Department of Nutrition, Diabetes and Metabolism, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - José-Ignacio Riezu-Boj
- University of Navarra, Department of Nutrition, Food Sciences and Physiology & Centre for Nutrition Research, Pamplona, Spain. .,Navarra Institute for Health Research (IdiSNa), Pamplona, Spain.
| | - J Alfredo Martínez
- University of Navarra, Department of Nutrition, Food Sciences and Physiology & Centre for Nutrition Research, Pamplona, Spain.,Spanish Biomedical Research Centre in Physiopathology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain.,Navarra Institute for Health Research (IdiSNa), Pamplona, Spain.,Madrid Institute for Advanced Studies (IMDEA), IMDEA Food, Madrid, Spain
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27
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O’Brien KM, Sandler DP, Xu Z, Kinyamu HK, Taylor JA, Weinberg CR. Vitamin D, DNA methylation, and breast cancer. Breast Cancer Res 2018; 20:70. [PMID: 29996894 PMCID: PMC6042268 DOI: 10.1186/s13058-018-0994-y] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2018] [Accepted: 05/25/2018] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Vitamin D has anticarcinogenic and immune-related properties and may protect against some diseases, including breast cancer. Vitamin D affects gene transcription and may influence DNA methylation. METHODS We studied the relationships between serum vitamin D, DNA methylation, and breast cancer using a case-cohort sample (1070 cases, 1277 in subcohort) of non-Hispanic white women. For our primary analysis, we used robust linear regression to examine the association between serum 25-hydroxyvitamin D (25(OH)D) and methylation within a random sample of the cohort ("subcohort"). We focused on 198 CpGs in or near seven vitamin D-related genes. For these 198 candidate CpG loci, we also examined how multiplicative interactions between methylation and 25(OH)D were associated with breast cancer risk. This was done using Cox proportional hazards models and the full case-cohort sample. We additionally conducted an exploratory epigenome-wide association study (EWAS) of the association between 25(OH)D and DNA methylation in the subcohort. RESULTS Of the CpGs in vitamin D-related genes, cg21201924 (RXRA) had the lowest p value for association with 25(OH)D (p = 0.0004). Twenty-two other candidate CpGs were associated with 25(OH)D (p < 0.05; RXRA, NADSYN1/DHCR7, GC, or CYP27B1). We observed an interaction between 25(OH)D and methylation at cg21201924 in relation to breast cancer risk (ratio of hazard ratios = 1.22, 95% confidence interval 1.10-1.34; p = 7 × 10-5), indicating a larger methylation-breast cancer hazard ratio in those with high serum 25(OH)D concentrations. We also observed statistically significant (p < 0.05) interactions for six other RXRA CpGs and CpGs in CYP24A1, CYP27B1, NADSYN1/DHCR7, and VDR. In the EWAS of the subcohort, 25(OH)D was associated (q < 0.05) with methylation at cg24350360 (EPHX1; p = 3.4 × 10-8), cg06177555 (SPN; p = 9.8 × 10-8), and cg13243168 (SMARCD2; p = 2.9 × 10-7). CONCLUSIONS 25(OH)D concentrations were associated with DNA methylation of CpGs in several vitamin D-related genes, with potential links to immune function-related genes. Methylation of CpGs in vitamin D-related genes may interact with 25(OH)D to affect the risk of breast cancer.
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Affiliation(s)
- Katie M. O’Brien
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709 USA
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709 USA
| | - Dale P. Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709 USA
| | - Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709 USA
| | - H. Karimi Kinyamu
- Chromatin and Gene Expression Section, Epigenetics and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709 USA
| | - Jack A. Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709 USA
| | - Clarice R. Weinberg
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709 USA
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28
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Bauer M. Cell-type-specific disturbance of DNA methylation pattern: a chance to get more benefit from and to minimize cohorts for epigenome-wide association studies. Int J Epidemiol 2018; 47:917-927. [DOI: 10.1093/ije/dyy029] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/02/2023] Open
Affiliation(s)
- Mario Bauer
- Department of Environmental Immunology, Helmholtz Centre for Environmental Research, UFZ, Permoserst, 15, 04318 Leipzig, Germany
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29
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Li S, Wong EM, Bui M, Nguyen TL, Joo JHE, Stone J, Dite GS, Dugué PA, Milne RL, Giles GG, Saffery R, Southey MC, Hopper JL. Inference about causation between body mass index and DNA methylation in blood from a twin family study. Int J Obes (Lond) 2018; 43:243-252. [PMID: 29777239 DOI: 10.1038/s41366-018-0103-4] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2017] [Revised: 03/19/2018] [Accepted: 04/04/2018] [Indexed: 12/11/2022]
Abstract
BACKGROUND Several studies have reported DNA methylation in blood to be associated with body mass index (BMI), but few have investigated causal aspects of the association. We used a twin family design to assess this association at two life points and applied a novel analytical approach to appraise the evidence for causality. METHODS The methylation profile of DNA from peripheral blood was measured for 479 Australian women from 130 twin families. Linear regression was used to estimate the associations of DNA methylation at ~410,000 cytosine-guanine dinucleotides (CpGs), and of the average DNA methylation at ~20,000 genes, with current BMI, BMI at age 18-21 years, and the change between the two (BMI change). A novel regression-based methodology for twins, Inference about Causation through Examination of Familial Confounding (ICE FALCON), was used to assess causation. RESULTS At a 5% false discovery rate, nine, six and 12 CpGs at 24 loci were associated with current BMI, BMI at age 18-21 years and BMI change, respectively. The average DNA methylation of the BHLHE40 and SOCS3 loci was associated with current BMI, and of the PHGDH locus with BMI change. From the ICE FALCON analyses with BMI as the predictor and DNA methylation as the outcome, a woman's DNA methylation level was associated with her co-twin's BMI, and the association disappeared after conditioning on her own BMI, consistent with BMI causing DNA methylation. To the contrary, using DNA methylation as the predictor and BMI as the outcome, a woman's BMI was not associated with her co-twin's DNA methylation level, consistent with DNA methylation not causing BMI. CONCLUSION For middle-aged women, peripheral blood DNA methylation at several genomic locations is associated with current BMI, BMI at age 18-21 years and BMI change. Our study suggests that BMI has a causal effect on peripheral blood DNA methylation.
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Affiliation(s)
- Shuai Li
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - Ee Ming Wong
- Genetic Epidemiology Laboratory, Department of Clinical Pathology, University of Melbourne, Parkville, VIC, Australia.,Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia
| | - Minh Bui
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - Tuong L Nguyen
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - Ji-Hoon Eric Joo
- Genetic Epidemiology Laboratory, Department of Clinical Pathology, University of Melbourne, Parkville, VIC, Australia.,Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia
| | - Jennifer Stone
- Centre for Genetic Origins of Health and Disease, Curtin University and the University of Western Australia, Perth, WA, Australia
| | - Gillian S Dite
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - Pierre-Antoine Dugué
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia.,Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - Roger L Milne
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia.,Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - Graham G Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia.,Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - Richard Saffery
- Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, VIC, Australia.,Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
| | - Melissa C Southey
- Genetic Epidemiology Laboratory, Department of Clinical Pathology, University of Melbourne, Parkville, VIC, Australia.,Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia.
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30
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Lin C, Fesi BD, Marquis M, Bosak NP, Lysenko A, Koshnevisan MA, Duke FF, Theodorides ML, Nelson TM, McDaniel AH, Avigdor M, Arayata CJ, Shaw L, Bachmanov AA, Reed DR. Burly1 is a mouse QTL for lean body mass that maps to a 0.8-Mb region of chromosome 2. Mamm Genome 2018; 29:325-343. [PMID: 29737391 DOI: 10.1007/s00335-018-9746-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2018] [Accepted: 04/26/2018] [Indexed: 11/25/2022]
Abstract
To fine map a mouse QTL for lean body mass (Burly1), we used information from intercross, backcross, consomic, and congenic mice derived from the C57BL/6ByJ (host) and 129P3/J (donor) strains. The results from these mapping populations were concordant and showed that Burly1 is located between 151.9 and 152.7 Mb (rs33197365 to rs3700604) on mouse chromosome 2. The congenic region harboring Burly1 contains 26 protein-coding genes, 11 noncoding RNA elements (e.g., lncRNA), and 4 pseudogenes, with 1949 predicted functional variants. Of the protein-coding genes, 7 have missense variants, including genes that may contribute to lean body weight, such as Angpt41, Slc52c3, and Rem1. Lean body mass was increased by the B6-derived variant relative to the 129-derived allele. Burly1 influenced lean body weight at all ages but not food intake or locomotor activity. However, congenic mice with the B6 allele produced more heat per kilogram of lean body weight than did controls, pointing to a genotype effect on lean mass metabolism. These results show the value of integrating information from several mapping populations to refine the map location of body composition QTLs and to identify a short list of candidate genes.
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Affiliation(s)
- Cailu Lin
- Monell Chemical Senses Center, 3500 Market St, Philadelphia, PA, 19104, USA
| | - Brad D Fesi
- Monell Chemical Senses Center, 3500 Market St, Philadelphia, PA, 19104, USA
| | - Michael Marquis
- Monell Chemical Senses Center, 3500 Market St, Philadelphia, PA, 19104, USA
| | - Natalia P Bosak
- Monell Chemical Senses Center, 3500 Market St, Philadelphia, PA, 19104, USA
| | - Anna Lysenko
- Monell Chemical Senses Center, 3500 Market St, Philadelphia, PA, 19104, USA
| | | | - Fujiko F Duke
- Monell Chemical Senses Center, 3500 Market St, Philadelphia, PA, 19104, USA
| | | | - Theodore M Nelson
- Monell Chemical Senses Center, 3500 Market St, Philadelphia, PA, 19104, USA
| | - Amanda H McDaniel
- Monell Chemical Senses Center, 3500 Market St, Philadelphia, PA, 19104, USA
| | - Mauricio Avigdor
- Monell Chemical Senses Center, 3500 Market St, Philadelphia, PA, 19104, USA
| | - Charles J Arayata
- Monell Chemical Senses Center, 3500 Market St, Philadelphia, PA, 19104, USA
| | - Lauren Shaw
- Monell Chemical Senses Center, 3500 Market St, Philadelphia, PA, 19104, USA
| | | | - Danielle R Reed
- Monell Chemical Senses Center, 3500 Market St, Philadelphia, PA, 19104, USA.
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Abstract
PURPOSE OF REVIEW It is becoming increasingly evident that epigenetic mechanisms, particularly DNA methylation, play a role in the regulation of blood lipid levels and lipid metabolism-linked phenotypes and diseases. RECENT FINDINGS Recent genome-wide methylation and candidate gene studies of blood lipids have highlighted several robustly replicated methylation markers across different ethnicities. Furthermore, many of these lipid-related CpG sites associated with blood lipids are also linked to lipid-related phenotypes and diseases. Integrating epigenome-wide association studies (EWAS) data with other layers of molecular data such as genetics or the transcriptome, accompanied by relevant statistical methods (e.g. Mendelian randomization), provides evidence for causal relationships. Recent data suggest that epigenetic changes can be consequences rather than causes of dyslipidemia. There is sparse information on many lipid classes and disorders of lipid metabolism, and also on the interplay of DNA methylation with other epigenetic layers such as histone modifications and regulatory RNAs. SUMMARY The current review provides a literature overview of epigenetic modifications in lipid metabolism and other lipid-related phenotypes and diseases focusing on EWAS of DNA methylation from January 2016 to September 2017. Recent studies strongly support the importance of epigenetic modifications, such as DNA methylation, in lipid metabolism and related diseases for relevant biological insights, reliable biomarkers, and even future therapeutics.
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Affiliation(s)
- Kirstin Mittelstraß
- Research Unit of Molecular Epidemiology
- Institute of Epidemiology, Helmholtz Zentrum München, Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Neuherberg, Germany
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology
- Institute of Epidemiology, Helmholtz Zentrum München, Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Neuherberg, Germany
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32
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Titus AJ, Gallimore RM, Salas LA, Christensen BC. Cell-type deconvolution from DNA methylation: a review of recent applications. Hum Mol Genet 2018; 26:R216-R224. [PMID: 28977446 PMCID: PMC5886462 DOI: 10.1093/hmg/ddx275] [Citation(s) in RCA: 112] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2017] [Accepted: 07/11/2017] [Indexed: 02/07/2023] Open
Abstract
Recent advances in cell-type deconvolution approaches are adding to our understanding of the biology underlying disease development and progression. DNA methylation (DNAm) can be used as a biomarker of cell types, and through deconvolution approaches, to infer underlying cell type proportions. Cell-type deconvolution algorithms have two main categories: reference-based and reference-free. Reference-based algorithms are supervised methods that determine the underlying composition of cell types within a sample by leveraging differentially methylated regions (DMRs) specific to cell type, identified from DNAm measures of purified cell populations. Reference-free algorithms are unsupervised methods for use when cell-type specific DMRs are not available, allowing scientists to estimate putative cellular proportions or control for potential confounding from cell type. Reference-based deconvolution is typically applied to blood samples and has potentiated our understanding of the relation between immune profiles and disease by allowing estimation of immune cell proportions from archival DNA. Bioinformatic analyses using DNAm to infer immune cell proportions, part of a new field known as Immunomethylomics, provides a new direction for consideration in epigenome wide association studies (EWAS).
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Affiliation(s)
- Alexander J Titus
- Program in Quantitative Biomedical Sciences.,Department of Epidemiology
| | | | | | - Brock C Christensen
- Department of Epidemiology.,Department of Molecular and Systems Biology.,Department of Community and Family Medicine, Geisel School of Medicine at Dartmouth College, Hanover, NH 03755, USA
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Giuranna J, Diebels I, Hinney A. Polygene Varianten und Epigenetik bei Adipositas. MED GENET-BERLIN 2017. [DOI: 10.1007/s11825-017-0156-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Zusammenfassung
Hintergrund
Durch molekulargenetische Analysen wurde eine kleine Anzahl von Hauptgenen identifiziert, die Übergewicht (Body Mass Index, BMI ≥ 25 kg/m2) und Adipositas (BMI ≥ 30 kg/m2) bei Menschen mit bedingen können. Die zugrunde liegenden Mutationen sind selten. Die genetische Prädisposition zur Entwicklung einer Adipositas ist meist polygener Natur.
Ziel der Arbeit
Darstellung der polygenen Formen der Adipositas und epigenetischer Befunde.
Material und Methoden
Literaturübersicht.
Ergebnisse und Diskussion
Metaanalysen genomweiter Assoziationsstudien (GWAMA) haben bisher mehr als 100 Polygene oder polygene Loci identifiziert, die genomweit mit dem BMI assoziiert sind. Jedes einzelne Polygen leistet nur einen kleinen Beitrag zur Entwicklung einer Adipositas. Effektstärken liegen im Bereich von ca. 100 g bis 1,5 kg. Eine Reihe solcher prädisponierenden Genvarianten (Allele) findet sich bei adipösen Probanden. Allerdings tragen auch normalgewichtige und schlanke Individuen diese Allele, wenn auch in geringerer Frequenz. Diese Allele können durch statistische Analysen als Adipositas-Risikoallele identifiziert und validiert werden. Vor Kurzem haben sogenannte Cross-Disorder- und Cross-Phänotyp-Analysen zur Identifizierung von Genen geführt, die nicht allein durch Analysen der einzelnen Erkrankungen/Phänotypen nachgewiesen werden konnten. Funktionelle in-vitro- und in-vivo-Studien der GWAS-abgeleiteten Polygene könnten zu einem besseren Verständnis der molekulargenetischen Mechanismen der Körpergewichtsregulation führen. Erste genomweite Methylierungsmusteranalysen und Studien zu metastabilen Epiallelen tragen zudem zu einem besseren Verständnis der Pathomechanismen der Adipositas bei.
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Affiliation(s)
- Johanna Giuranna
- Aff1 0000 0001 2187 5445 grid.5718.b Klinik für Psychiatrie, Psychosomatik und Psychotherapie des Kindes- und Jugendalters, Universitätsklinikum Essen (AöR) Universität Duisburg-Essen Virchowstr. 171 45147 Essen Deutschland
| | - Inga Diebels
- Aff1 0000 0001 2187 5445 grid.5718.b Klinik für Psychiatrie, Psychosomatik und Psychotherapie des Kindes- und Jugendalters, Universitätsklinikum Essen (AöR) Universität Duisburg-Essen Virchowstr. 171 45147 Essen Deutschland
| | - Anke Hinney
- Aff1 0000 0001 2187 5445 grid.5718.b Klinik für Psychiatrie, Psychosomatik und Psychotherapie des Kindes- und Jugendalters, Universitätsklinikum Essen (AöR) Universität Duisburg-Essen Virchowstr. 171 45147 Essen Deutschland
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Cheng Z, Zheng L, Almeida FA. Epigenetic reprogramming in metabolic disorders: nutritional factors and beyond. J Nutr Biochem 2017; 54:1-10. [PMID: 29154162 DOI: 10.1016/j.jnutbio.2017.10.004] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2017] [Revised: 09/26/2017] [Accepted: 10/10/2017] [Indexed: 12/13/2022]
Abstract
Environmental factors (e.g., malnutrition and physical inactivity) contribute largely to metabolic disorders including obesity, type 2 diabetes, cardiometabolic disease and nonalcoholic fatty liver diseases. The abnormalities in metabolic activity and pathways have been increasingly associated with altered DNA methylation, histone modification and noncoding RNAs, whereas lifestyle interventions targeting diet and physical activity can reverse the epigenetic and metabolic changes. Here we review recent evidence primarily from human studies that links DNA methylation reprogramming to metabolic derangements or improvements, with a focus on cross-tissue (e.g., the liver, skeletal muscle, pancreas, adipose tissue and blood samples) epigenetic markers, mechanistic mediators of the epigenetic reprogramming, and the potential of using epigenetic traits to predict disease risk and intervention response. The challenges in epigenetic studies addressing the mechanisms of metabolic diseases and future directions are also discussed and prospected.
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Affiliation(s)
- Zhiyong Cheng
- Department of Human Nutrition, Foods, and Exercise, Fralin Translational Obesity Research Center, College of Agriculture and Life Science, Virginia Tech, Blacksburg, VA 24061, USA.
| | - Louise Zheng
- Department of Human Nutrition, Foods, and Exercise, Fralin Translational Obesity Research Center, College of Agriculture and Life Science, Virginia Tech, Blacksburg, VA 24061, USA
| | - Fabio A Almeida
- Department of Health Promotion, Social & Behavioral Health, College of Public Health, University of Nebraska Medical Center, Omaha, NE 68198, USA.
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Geurts YM, Dugué PA, Joo JE, Makalic E, Jung CH, Guan W, Nguyen S, Grove ML, Wong EM, Hodge AM, Bassett JK, FitzGerald LM, Tsimiklis H, Baglietto L, Severi G, Schmidt DF, Buchanan DD, MacInnis RJ, Hopper JL, Pankow JS, Demerath EW, Southey MC, Giles GG, English DR, Milne RL. Novel associations between blood DNA methylation and body mass index in middle-aged and older adults. Int J Obes (Lond) 2017; 42:887-896. [PMID: 29278407 DOI: 10.1038/ijo.2017.269] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2017] [Revised: 09/30/2017] [Accepted: 10/16/2017] [Indexed: 02/05/2023]
Abstract
BACKGROUND/OBJECTIVES There is increasing evidence of a relationship between blood DNA methylation and body mass index (BMI). We aimed to assess associations of BMI with individual methylation measures (CpGs) through a cross-sectional genome-wide DNA methylation association study and a longitudinal analysis of repeated measurements over time. SUBJECTS/METHODS Using the Illumina Infinium HumanMethylation450 BeadChip, DNA methylation measures were determined in baseline peripheral blood samples from 5361 adults recruited to the Melbourne Collaborative Cohort Study (MCCS) and selected for nested case-control studies, 2586 because they were subsequently diagnosed with cancer (cases) and 2775 as controls. For a subset of 1088 controls, these measures were repeated using blood samples collected at wave 2 follow-up, a median of 11 years later; weight was measured at both time points. Associations between BMI and blood DNA methylation were assessed using linear mixed-effects regression models adjusted for batch effects and potential confounders. These were applied to cases and controls separately, with results combined through fixed-effects meta-analysis. RESULTS Cross-sectional analysis identified 310 CpGs associated with BMI with P<1.0 × 10-7, 225 of which had not been reported previously. Of these 225 novel associations, 172 were replicated (P<0.05) using the Atherosclerosis Risk in Communities (ARIC) study. We also replicated using MCCS data (P<0.05) 335 of 392 associations previously reported with P<1.0 × 10-7, including 60 that had not been replicated before. Associations between change in BMI and change in methylation were observed for 34 of the 310 strongest signals in our cross-sectional analysis, including 7 that had not been replicated using the ARIC study. CONCLUSIONS Together, these findings suggest that BMI is associated with blood DNA methylation at a large number of CpGs across the genome, several of which are located in or near genes involved in ATP-binding cassette transportation, tumour necrosis factor signalling, insulin resistance and lipid metabolism.
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Affiliation(s)
- Y M Geurts
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - P-A Dugué
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - J E Joo
- Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, Parkville, VIC, Australia
| | - E Makalic
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - C-H Jung
- Melbourne Bioinformatics, University of Melbourne, Parkville, VIC, Australia
| | - W Guan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - S Nguyen
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - M L Grove
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - E M Wong
- Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, Parkville, VIC, Australia
| | - A M Hodge
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - J K Bassett
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - L M FitzGerald
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
| | - H Tsimiklis
- Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, Parkville, VIC, Australia
| | - L Baglietto
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - G Severi
- Human Genetics Foundation (HuGeF), Torino, Italy.,CESP (U1018 INSERM, Équipe Générations et Santé), Facultés de médecine Université Paris-Sud, UVSQ, Université Paris-Saclay, Villejuif, France
| | - D F Schmidt
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - D D Buchanan
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia.,Colorectal Oncogenomics Group, Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Parkville, VIC, Australia.,University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, VIC, Australia.,Genetic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, VIC, Australia
| | - R J MacInnis
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - J L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - J S Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - E W Demerath
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - M C Southey
- Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, Parkville, VIC, Australia
| | - G G Giles
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - D R English
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - R L Milne
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
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Critical Role of the Human ATP-Binding Cassette G1 Transporter in Cardiometabolic Diseases. Int J Mol Sci 2017; 18:ijms18091892. [PMID: 28869506 PMCID: PMC5618541 DOI: 10.3390/ijms18091892] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2017] [Revised: 08/30/2017] [Accepted: 08/30/2017] [Indexed: 12/15/2022] Open
Abstract
ATP-binding cassette G1 (ABCG1) is a member of the large family of ABC transporters which are involved in the active transport of many amphiphilic and lipophilic molecules including lipids, drugs or endogenous metabolites. It is now well established that ABCG1 promotes the export of lipids, including cholesterol, phospholipids, sphingomyelin and oxysterols, and plays a key role in the maintenance of tissue lipid homeostasis. Although ABCG1 was initially proposed to mediate cholesterol efflux from macrophages and then to protect against atherosclerosis and cardiovascular diseases (CVD), it becomes now clear that ABCG1 exerts a larger spectrum of actions which are of major importance in cardiometabolic diseases (CMD). Beyond a role in cellular lipid homeostasis, ABCG1 equally participates to glucose and lipid metabolism by controlling the secretion and activity of insulin and lipoprotein lipase. Moreover, there is now a growing body of evidence suggesting that modulation of ABCG1 expression might contribute to the development of diabetes and obesity, which are major risk factors of CVD. In order to provide the current understanding of the action of ABCG1 in CMD, we here reviewed major findings obtained from studies in mice together with data from the genetic and epigenetic analysis of ABCG1 in the context of CMD.
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Li L, Cui W, Zhang Y, Wang Y. Reduced CRHR-2 in placental tissues is associated with the high DNA methylation of CRHR-2 promoter in idiopathic preterm birth. INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL PATHOLOGY 2017; 10:9521-9526. [PMID: 31966828 PMCID: PMC6965987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 06/21/2017] [Accepted: 08/16/2017] [Indexed: 06/10/2023]
Abstract
The present study was to explore the expression of CRHR-1 and CRHR-2 in the placentas of idiopathic preterm birth (PTB-I), and to identify the CRHR-1 and CRHR-2 methylation with the deregulated CRHR-1 and CRHR-2. Immunohistochemical staining, real-time quantitative PCR and western blot analysis were performed to examine the expression of CRHR-1 and CRHR-2. The methylation in promoter regions of the CRHR-1 and CRHR-2 genes were specifically was analyzed using MethyLight method. Results demonstrated that the CRHR-2 expression was reduced in both mRNA and protein levels in PBT-I placental tissues, associating with a high level methylation of CRHR-2 gene in PTB-I placental specimens. in vitro experiments demonstrated that both CRHR-1 and CRHR-2 were downregulated, whereas the methylation of both CRHR-1 and CRHR-2 was upregulated in the hypoxia-treated human trophoblast-like JEG3 cells. In conclusion, CRHR-2 was downregulated in PTB-I in placenta tissues, in association with a high DNA methylation of CRHR-2 promoter. Methylation inhibitor might be a promising agent for PTB-I treatment.
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Affiliation(s)
- Lei Li
- Department of Obstetrics, The Affiliated Yantai Yuhuangding Hospital of Qingdao University Yantai, Shandong, China
| | - Wei Cui
- Department of Obstetrics, The Affiliated Yantai Yuhuangding Hospital of Qingdao University Yantai, Shandong, China
| | - Yan Zhang
- Department of Obstetrics, The Affiliated Yantai Yuhuangding Hospital of Qingdao University Yantai, Shandong, China
| | - Yuanli Wang
- Department of Obstetrics, The Affiliated Yantai Yuhuangding Hospital of Qingdao University Yantai, Shandong, China
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Zhang J, Han X, Sun S. IL-8 -251A/T and +781C/T polymorphisms were associated with risk of breast cancer in a Chinese population. INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL PATHOLOGY 2017; 10:7443-7450. [PMID: 31966587 PMCID: PMC6965227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 01/14/2017] [Accepted: 02/21/2017] [Indexed: 06/10/2023]
Abstract
Breast cancer is the leading cause of death of women in worldwide. The real mechanism of breast cancer is still unclear. IL-8 is a member of the chemokine superfamily, which plays an important role in regulating both inflammatory and immune processes. We performed a hospital-based case-control study to estimate the association between IL-8 -251A/T, -353A/T and +781C/T polymorphisms and risk of breast cancer in a Chinese population, and interaction between IL-8 polymorphism and environmental factors. During January 2014 and July 2016, a total of 442 patients with breast cancer and 447 normal control subjects were enrolled into our study. The IL-8 -251A/T, -353A/T and +781C/T polymorphisms were analyzed by the polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP). The TT genotype of IL-8 -251A/T was associated with higher risk of breast cancer as compared with the AA genotype (adjusted OR=1.96, 95% CI=1.26-3.05). Individuals carrying TT genotype of IL-8 -251A/T was correlated with an elevated risk of breast cancer in recessive model, when compared with the AA+AT genotype (adjusted OR=1.91, 95% CI=1.26-2.90). For the IL-8 +781C/T, the TT genotype showed lower association with risk of breast cancer in comparison to the CC genotype (adjusted OR=0.49, 95% CI=0.26-0.91); the TT genotype was also correlated with a decreased risk of breast cancer in recessive model (adjusted OR=0.46, 95% CI=0.25-0.84), as compared with the CC+CT genotype. In conclusion, our study suggests that IL-8 -251A/T and +781C/T could potentially be a biomarker for susceptibility to breast cancer risk.
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Affiliation(s)
- Jubiao Zhang
- Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan UniversityWuhan, Hubei Province, China
| | - Xiuhua Han
- Department of Breast Neoplasms Surgery, Inner Mongolia People’s HospitalHohhot, The Inner Mongolia Autonomous Region, China
| | - Shengrong Sun
- Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan UniversityWuhan, Hubei Province, China
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Johansson A, Flanagan JM. Epigenome-wide association studies for breast cancer risk and risk factors. TRENDS IN CANCER RESEARCH 2017; 12:19-28. [PMID: 28955137 PMCID: PMC5612397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
There have been six epigenome-wide association studies (EWAS) for breast cancer risk using blood DNA from prospective cohorts published thus far, and the only consistent finding is a global loss of methylation observed in breast cancer cases compared with controls, with no individual CpG sites passing validation across studies. In contrast, a more successful approach has been the identification of EWAS signatures of cancer risk factors such as smoking, body mass index, age and alcohol use with numerous validated CpG sites. These signatures may be used as a molecular test to quantify cancer risk associated with these factors. It is clear from the larger EWAS of risk exposures that similar-sized large collaborative studies may be needed to robustly identify DNA methylation signatures of breast cancer risk.
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Affiliation(s)
- Annelie Johansson
- Epigenetics Unit, Division of Cancer, Department of Surgery and Cancer, Imperial College London, UK
| | - James M. Flanagan
- Epigenetics Unit, Division of Cancer, Department of Surgery and Cancer, Imperial College London, UK
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