101
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Nucleated red blood cells impact DNA methylation and expression analyses of cord blood hematopoietic cells. Clin Epigenetics 2015; 7:95. [PMID: 26366232 PMCID: PMC4567832 DOI: 10.1186/s13148-015-0129-6] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2015] [Accepted: 08/31/2015] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Genome-wide DNA methylation (DNAm) studies have proven extremely useful to understand human hematopoiesis. Due to their active DNA content, nucleated red blood cells (nRBCs) contribute to epigenetic and transcriptomic studies derived from whole cord blood. Genomic studies of cord blood hematopoietic cells isolated by fluorescence-activated cell sorting (FACS) may be significantly altered by heterotopic interactions with nRBCs during conventional cell sorting. RESULTS We report that cord blood T cells, and to a lesser extent monocytes and B cells, physically engage with nRBCs during FACS. These heterotopic interactions resulted in significant cross-contamination of genome-wide epigenetic and transcriptomic data. Formal exclusion of erythroid lineage-specific markers yielded DNAm profiles (measured by the Illumina 450K array) of cord blood CD4 and CD8 T lymphocytes, B lymphocytes, natural killer (NK) cells, granulocytes, monocytes, and nRBCs that were more consistent with expected hematopoietic lineage relationships. Additionally, we identified eight highly differentially methylated CpG sites in nRBCs (false detection rate <5 %, |Δβ| >0.50) that can be used to detect nRBC contamination of purified hematopoietic cells or to assess the impact of nRBCs on whole cord blood DNAm profiles. Several of these erythroid markers are located in or near genes involved in erythropoiesis (ZFPM1, HDAC4) or immune function (MAP3K14, IFIT1B), reinforcing a possible immune regulatory role for nRBCs in early life. CONCLUSIONS Heterotopic interactions between erythroid cells and white blood cells can result in contaminated cell populations if not properly excluded during cell sorting. Cord blood nRBCs have a distinct DNAm profile that can significantly skew epigenetic studies. Our findings have major implications for the design and interpretation of genome-wide epigenetic and transcriptomic studies using human cord blood.
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102
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Suderman M, Pappas JJ, Borghol N, Buxton JL, McArdle WL, Ring SM, Hertzman C, Power C, Szyf M, Pembrey M. Lymphoblastoid cell lines reveal associations of adult DNA methylation with childhood and current adversity that are distinct from whole blood associations. Int J Epidemiol 2015; 44:1331-40. [PMID: 26351305 DOI: 10.1093/ije/dyv168] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/14/2015] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Some cohort studies bank lymphoblastoid cell lines (LCLs) as a renewable source of participant DNA. However, although LCL DNA has proved valuable for genetic studies, its utility in epigenetic epidemiology research is unknown. METHODS To assess whether LCL DNA can be used for life-course environmental epigenomics, we carried out a pilot methylomic study (using the Illumina Infinium Human Methylation 450 BeadChip) of nil-passage, Epstein-Barr virus (EBV)-transformed LCLs (n = 42) and 28 matched whole-blood (WB) samples. These were from adult male participants of the British 1958 birth cohort, selected for extremes of social economic position (SEP) in childhood and adulthood, with additional information available on childhood abuse and prenatal tobacco exposure. RESULTS We identified a small number of weak associations between these exposures and methylation levels of both individual CpG sites and genomic regions in WB and LCLs. However, only one of the regional, and none of the individual CpG site associations were common to both sample types. The lack of overlap between the associations detected in LCL compared with those found in WB could either be due to the EBV-transformation process, or to the fact that, unlike WB, LCLs are essentially a single (CD19+) cell type. We provide evidence that the latter is the more potent explanation, by showing that CpG sites known to be differentially methylated between different types of blood cell have significantly lower correlations (R = 0.11) than average (R = 0.2) between WB and LCLs in our datasets, whereas sites known to be affected by EBV-transformation have significantly higher correlations (R = 0.3). CONCLUSIONS This small pilot study suggests that the DNA methylation profile of LCLs is more closely related to that of B cells than WB and, additionally, that LCLs may nevertheless be useful for life-course environmental epigenomics.
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Affiliation(s)
- Matthew Suderman
- MRC Integrative Epidemiology Unit (IEU), School of Social and Community Medicine, University of Bristol, Bristol, UK,
| | - Jane J Pappas
- Department of Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada, Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| | - Nada Borghol
- Department of Biochemistry, Faculty of Sciences I, Lebanese University, Beirut, Lebanon
| | - Jessica L Buxton
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK
| | - Wendy L McArdle
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Susan M Ring
- MRC Integrative Epidemiology Unit (IEU), School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Clyde Hertzman
- Human Early Learning Partnership, University of British Columbia, British Columbia, Canada
| | - Chris Power
- Population, Policy and Practice, UCL Institute of Child Health, London, UK
| | - Moshe Szyf
- Department of Physiology, University of Toronto, Toronto, Ontario, Canada, Sackler Program for Epigenetics & Developmental Psychobiology, McGill University, Montreal, Quebec, Canada and
| | - Marcus Pembrey
- Genetics and Epigenetics in Health and Disease Section, UCL Institute of Child Health, UK
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103
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Zhang N, Zhao S, Zhang SH, Chen J, Lu D, Shen M, Li C. Intra-Monozygotic Twin Pair Discordance and Longitudinal Variation of Whole-Genome Scale DNA Methylation in Adults. PLoS One 2015; 10:e0135022. [PMID: 26248206 PMCID: PMC4527769 DOI: 10.1371/journal.pone.0135022] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2014] [Accepted: 07/16/2015] [Indexed: 02/04/2023] Open
Abstract
Monozygotic twins share identical genomic DNA and are indistinguishable using conventional genetic markers. Increasing evidence indicates that monozygotic twins are epigenetically distinct, suggesting that a comparison between DNA methylation patterns might be useful to approach this forensic problem. However, the extent of epigenetic discordance between healthy adult monozygotic twins and the stability of CpG loci within the same individual over a short time span at the whole-genome scale are not well understood. Here, we used Infinium HumanMethylation450 Beadchips to compare DNA methylation profiles using blood collected from 10 pairs of monozygotic twins and 8 individuals sampled at 0, 3, 6, and 9 months. Using an effective and unbiased method for calling differentially methylated (DM) CpG sites, we showed that 0.087%–1.530% of the CpG sites exhibit differential methylation in monozygotic twin pairs. We further demonstrated that, on whole-genome level, there has been no significant epigenetic drift within the same individuals for up to 9 months, including one monozygotic twin pair. However, we did identify a subset of CpG sites that vary in DNA methylation over the 9-month period. The magnitude of the intra-pair or longitudinal methylation discordance of the CpG sites inside the CpG islands is greater than those outside the CpG islands. The CpG sites located on shores appear to be more suitable for distinguishing between MZ twins.
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Affiliation(s)
- Na Zhang
- Shanghai Key Laboratory of Forensic Medicine, Institute of Forensic Sciences, Ministry of Justice, P.R. China, Shanghai, 200063, P.R. China
- State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Sciences, Fudan University, Shanghai, 200433, P.R. China
| | - Shumin Zhao
- Shanghai Key Laboratory of Forensic Medicine, Institute of Forensic Sciences, Ministry of Justice, P.R. China, Shanghai, 200063, P.R. China
| | - Su-Hua Zhang
- Shanghai Key Laboratory of Forensic Medicine, Institute of Forensic Sciences, Ministry of Justice, P.R. China, Shanghai, 200063, P.R. China
- State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Sciences, Fudan University, Shanghai, 200433, P.R. China
| | - Jinzhong Chen
- State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Sciences, Fudan University, Shanghai, 200433, P.R. China
| | - Daru Lu
- State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Sciences, Fudan University, Shanghai, 200433, P.R. China
| | - Min Shen
- Shanghai Key Laboratory of Forensic Medicine, Institute of Forensic Sciences, Ministry of Justice, P.R. China, Shanghai, 200063, P.R. China
| | - Chengtao Li
- Shanghai Key Laboratory of Forensic Medicine, Institute of Forensic Sciences, Ministry of Justice, P.R. China, Shanghai, 200063, P.R. China
- * E-mail:
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104
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Bauer M, Linsel G, Fink B, Offenberg K, Hahn AM, Sack U, Knaack H, Eszlinger M, Herberth G. A varying T cell subtype explains apparent tobacco smoking induced single CpG hypomethylation in whole blood. Clin Epigenetics 2015; 7:81. [PMID: 26246861 PMCID: PMC4526203 DOI: 10.1186/s13148-015-0113-1] [Citation(s) in RCA: 66] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2015] [Accepted: 07/13/2015] [Indexed: 12/23/2022] Open
Abstract
Background Many recent epigenetic studies report that cigarette smoking reduces DNA methylation in whole blood at the single CpG site cg19859270 within the GPR15 gene. Results Within two independent cohorts, we confirmed the differentially expression of the GPR15 gene when smokers and non-smokers subjects are compared. By validating the GPR15 protein expression at the cellular level, we found that the observed decreased methylation at this site in white blood cells (WBC) of smokers is mainly caused by the high proportion of CD3+GPR15+ expressing T cells in peripheral blood. In current smokers, the percentage of GPR15+ cells among CD3+ T cells in peripheral blood is significantly higher (15.5 ± 7.2 %, mean ± standard deviation) compared to non-smokers (3.7 ± 1.6 %). Treatment of peripheral blood mononuclear cell (PBMC) cultures with aqueous cigarette smoke extract did not induce a higher proportion of this T cell subtype. Conclusions Our results underline that DNA hypomethylation at cg19859270 site, observed in WBCs of smokers, did not arise by direct effect of tobacco smoking compounds on methylation of DNA but rather by the enrichment of a tobacco-smoking-induced lymphocyte population in the peripheral blood. Electronic supplementary material The online version of this article (doi:10.1186/s13148-015-0113-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Mario Bauer
- Department of Environmental Immunology, Helmholtz Centre for Environmental Research-UFZ, Leipzig, 04318 Germany
| | - Gunter Linsel
- Federal Institute for Occupational Safety and Health, Berlin, 10317 Germany
| | - Beate Fink
- Department of Environmental Immunology, Helmholtz Centre for Environmental Research-UFZ, Leipzig, 04318 Germany
| | - Kirsten Offenberg
- Department of Environmental Immunology, Helmholtz Centre for Environmental Research-UFZ, Leipzig, 04318 Germany
| | - Anne Maria Hahn
- Nikolaus-Fiebiger-Zentrum for Molecular Medicine, Institute of Genetics, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, 91054 Germany
| | - Ulrich Sack
- Institute of Clinical Immunology, Medical Faculty, University of Leipzig, Leipzig, 04103 Germany
| | - Heike Knaack
- Institute of Clinical Immunology, Medical Faculty, University of Leipzig, Leipzig, 04103 Germany
| | - Markus Eszlinger
- Division of Endocrinology and Nephrology, University of Leipzig, Leipzig, 04103 Germany
| | - Gunda Herberth
- Department of Environmental Immunology, Helmholtz Centre for Environmental Research-UFZ, Leipzig, 04318 Germany
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105
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Hernandez-Vargas H, Castelino J, Silver MJ, Dominguez-Salas P, Cros MP, Durand G, Le Calvez-Kelm F, Prentice AM, Wild CP, Moore SE, Hennig BJ, Herceg Z, Gong YY, Routledge MN. Exposure to aflatoxin B1 in utero is associated with DNA methylation in white blood cells of infants in The Gambia. Int J Epidemiol 2015; 44:1238-48. [PMID: 25855716 PMCID: PMC4588861 DOI: 10.1093/ije/dyv027] [Citation(s) in RCA: 75] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/23/2015] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Exposure to environmental toxins during embryonic development may lead to epigenetic changes that influence disease risk in later life. Aflatoxin is a contaminant of staple foods in sub-Saharan Africa, is a known human liver carcinogen and has been associated with stunting in infants. METHODS We have measured aflatoxin exposure in 115 pregnant women in The Gambia and examined the DNA methylation status of white blood cells from their infants at 2-8 months old (mean 3.6 ± 0.9). Aflatoxin exposure in women was assessed using an ELISA method to measure aflatoxin albumin (AF-alb) adducts in plasma taken at 1-16 weeks of pregnancy. Genome-wide DNA methylation of infant white blood cells was measured using the Illumina Infinium HumanMethylation450beadchip. RESULTS AF-alb levels ranged from 3.9 to 458.4 pg/mg albumin. We found that aflatoxin exposure in the mothers was associated to DNA methylation in their infants for 71 CpG sites (false discovery rate < 0.05), with an average effect size of 1.7% change in methylation. Aflatoxin-associated differential methylation was observed in growth factor genes such as FGF12 and IGF1, and immune-related genes such as CCL28, TLR2 and TGFBI. Moreover, one aflatoxin-associated methylation region (corresponding to the miR-4520b locus) was identified. CONCLUSIONS This study shows that maternal exposure to aflatoxin during the early stages of pregnancy is associated with differential DNA methylation patterns of infants, including in genes related to growth and immune function. This reinforces the need for interventions to reduce aflatoxin exposure, especially during critical periods of fetal and infant development.
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Affiliation(s)
| | | | - Matt J Silver
- MRC International Nutrition Group at LSHTM, UK & MRC Keneba, MRC Unit, The Gambia
| | | | - Marie-Pierre Cros
- Epigenetics Group, International Agency for Research on Cancer (IARC), Lyon, France
| | | | | | - Andrew M Prentice
- MRC International Nutrition Group at LSHTM, UK & MRC Keneba, MRC Unit, The Gambia
| | | | - Sophie E Moore
- MRC International Nutrition Group at LSHTM, UK & MRC Keneba, MRC Unit, The Gambia, MRC Human Nutrition Research, Cambridge, UK and
| | - Branwen J Hennig
- MRC International Nutrition Group at LSHTM, UK & MRC Keneba, MRC Unit, The Gambia
| | - Zdenko Herceg
- Epigenetics Group, International Agency for Research on Cancer (IARC), Lyon, France
| | - Yun Yun Gong
- UK Institute of Global Food Security, Queen's University Belfast, Belfast, UK
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106
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Wiencke JK, Bracci PM, Hsuang G, Zheng S, Hansen H, Wrensch MR, Rice T, Eliot M, Kelsey KT. A comparison of DNA methylation specific droplet digital PCR (ddPCR) and real time qPCR with flow cytometry in characterizing human T cells in peripheral blood. Epigenetics 2015; 9:1360-5. [PMID: 25437051 DOI: 10.4161/15592294.2014.967589] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
Quantitating the copy number of demethylated CpG promoter sites of the CD3Z gene can be used to estimate the numbers and proportions of T cells in human blood and tissue. Quantitative methylation specific PCR (qPCR) is useful for studying T cells but requires extensive calibration and is imprecise at low copy numbers. Here we compared the performance of a new digital PCR platform (droplet digital PCR or ddPCR) to qPCR using bisulfite converted DNA from 157 blood specimens obtained from ambulatory care controls and patients with primary glioma. We compared both ddPCR and qPCR with conventional flow cytometry (FACS) evaluation of CD3 positive T cells. Repeated measures on the same blood sample revealed ddPCR to be less variable than qPCR. Both qPCR and ddPCR correlated significantly with FACS evaluation of peripheral blood CD3 counts and CD3/total leukocyte values. However, statistical measures of agreement showed that linear concordance was stronger for ddPCR than for qPCR and the absolute values were closer to FACS for ddPCR. Both qPCR and ddPCR could distinguish clinically significant differences in T cell proportions and performed similarly to FACS. Given the higher precision, greater accuracy, and technical simplicity of ddPCR, this approach appears to be a superior DNA methylation based method than conventional qPCR for the assessment of T cells.
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Affiliation(s)
- John K Wiencke
- a Department of Neurological Surgery ; University of California, San Francisco ; San Francisco , CA USA
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107
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Beach SRH, Lei MK, Brody GH, Dogan MV, Philibert RA. Higher levels of protective parenting are associated with better young adult health: exploration of mediation through epigenetic influences on pro-inflammatory processes. Front Psychol 2015; 6:676. [PMID: 26074840 PMCID: PMC4446530 DOI: 10.3389/fpsyg.2015.00676] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2015] [Accepted: 05/08/2015] [Indexed: 01/29/2023] Open
Abstract
The current investigation was designed to examine the association of parenting during late childhood and early adolescence, a time of rapid physical development, with biological propensity for inflammation. Based on life course theory, it was hypothesized that parenting during this period of rapid growth and development would be associated with biological outcomes and self-reported health assessed in young adulthood. It was expected that association of parenting with health would be mediated either by effects on methylation of a key inflammatory factor, Tumor necrosis factor (TNF), or else by association with a pro-inflammatory shift in the distribution of mononuclear blood cells. Supporting expectations, in a sample of 398 African American youth residing in rural Georgia, followed from age 11 to age 19, parenting at ages 11-13 was associated with youth reports of better health at age 19. We found that parenting was associated with changes in TNF methylation as well as with changes in cell-type composition. However, whereas methylation of TNF was a significant mediator of the association of parenting with young adult health, variation in mononuclear white blood cell types was not a significant mediator of the association of parenting with young adult health. The current research suggests the potential value of examining the health-related effects of parenting in late childhood and early adolescence. Further examination of protection against pro-inflammatory tendencies conferred by parenting appears warranted.
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Affiliation(s)
- Steven R H Beach
- Center for Family Research, University of Georgia , Athens, GA, USA
| | - Man Kit Lei
- Center for Family Research, University of Georgia , Athens, GA, USA
| | - Gene H Brody
- Center for Family Research, University of Georgia , Athens, GA, USA
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108
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Abstract
The functional consequences of trait associated SNPs are often investigated using expression quantitative trait locus (eQTL) mapping. While trait-associated variants may operate in a cell-type specific manner, eQTL datasets for such cell-types may not always be available. We performed a genome-environment interaction (GxE) meta-analysis on data from 5,683 samples to infer the cell type specificity of whole blood cis-eQTLs. We demonstrate that this method is able to predict neutrophil and lymphocyte specific cis-eQTLs and replicate these predictions in independent cell-type specific datasets. Finally, we show that SNPs associated with Crohn’s disease preferentially affect gene expression within neutrophils, including the archetypal NOD2 locus. Many variants in the genome, including variants associated with disease, affect the expression of genes. These so-called expression quantitative trait loci (eQTL) can be used to gain insight in the downstream consequences of disease. While it has been shown that many disease-associated variants alter gene expression in a cell-type dependent manner, eQTL datasets for specific cell types may not always be available and their sample size is often limited. We present a method that is able to detect cell type specific effects within eQTL datasets that have been generated from whole tissues (which may be composed of many cell types), in our case whole blood. By combining numerous whole blood datasets through meta-analysis, we show that we are able to detect eQTL effects that are specific for neutrophils and lymphocytes (two blood cell types). Additionally, we show that the variants associated with some diseases may preferentially alter the gene expression in one of these cell types. We conclude that our method is an alternative method to detect cell type specific eQTL effects, that may complement generating cell type specific eQTL datasets and that may be applied on other cell types and tissues as well.
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109
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Cai N, Chang S, Li Y, Li Q, Hu J, Liang J, Song L, Kretzschmar W, Gan X, Nicod J, Rivera M, Deng H, Du B, Li K, Sang W, Gao J, Gao S, Ha B, Ho HY, Hu C, Hu J, Hu Z, Huang G, Jiang G, Jiang T, Jin W, Li G, Li K, Li Y, Li Y, Li Y, Lin YT, Liu L, Liu T, Liu Y, Liu Y, Lu Y, Lv L, Meng H, Qian P, Sang H, Shen J, Shi J, Sun J, Tao M, Wang G, Wang G, Wang J, Wang L, Wang X, Wang X, Yang H, Yang L, Yin Y, Zhang J, Zhang K, Sun N, Zhang W, Zhang X, Zhang Z, Zhong H, Breen G, Wang J, Marchini J, Chen Y, Xu Q, Xu X, Mott R, Huang GJ, Kendler K, Flint J. Molecular signatures of major depression. Curr Biol 2015; 25:1146-56. [PMID: 25913401 PMCID: PMC4425463 DOI: 10.1016/j.cub.2015.03.008] [Citation(s) in RCA: 193] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2015] [Revised: 03/03/2015] [Accepted: 03/06/2015] [Indexed: 02/05/2023]
Abstract
Adversity, particularly in early life, can cause illness. Clues to the responsible mechanisms may lie with the discovery of molecular signatures of stress, some of which include alterations to an individual’s somatic genome. Here, using genome sequences from 11,670 women, we observed a highly significant association between a stress-related disease, major depression, and the amount of mtDNA (p = 9.00 × 10−42, odds ratio 1.33 [95% confidence interval [CI] = 1.29–1.37]) and telomere length (p = 2.84 × 10−14, odds ratio 0.85 [95% CI = 0.81–0.89]). While both telomere length and mtDNA amount were associated with adverse life events, conditional regression analyses showed the molecular changes were contingent on the depressed state. We tested this hypothesis with experiments in mice, demonstrating that stress causes both molecular changes, which are partly reversible and can be elicited by the administration of corticosterone. Together, these results demonstrate that changes in the amount of mtDNA and telomere length are consequences of stress and entering a depressed state. These findings identify increased amounts of mtDNA as a molecular marker of MD and have important implications for understanding how stress causes the disease. Amount of mtDNA is increased, and telomeric DNA is shortened in major depression Both changes can be induced with stress but are contingent on the depressed state Changes are tissue specific and in part due to glucocorticoid secretion Changes are in part reversible and represent switches in metabolic strategy
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Affiliation(s)
- Na Cai
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford, Oxfordshire OX3 7BN, UK
| | - Simon Chang
- Department and Graduate Institute of Biomedical Sciences, College of Medicine, Chang Gung University, Tao-Yuan 33302, Taiwan, ROC
| | - Yihan Li
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford, Oxfordshire OX3 7BN, UK
| | - Qibin Li
- BGI-Shenzhen, Floor 9 Complex Building, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong 518083, China
| | - Jingchu Hu
- BGI-Shenzhen, Floor 9 Complex Building, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong 518083, China
| | - Jieqin Liang
- BGI-Shenzhen, Floor 9 Complex Building, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong 518083, China
| | - Li Song
- BGI-Shenzhen, Floor 9 Complex Building, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong 518083, China
| | - Warren Kretzschmar
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford, Oxfordshire OX3 7BN, UK
| | - Xiangchao Gan
- Department of Comparative Developmental Genetics, Max Planck Institute for Plant Breeding Research, Carl-von-Linne-Weg 10, Cologne 50829, Germany
| | - Jerome Nicod
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford, Oxfordshire OX3 7BN, UK
| | - Margarita Rivera
- Centro de Investigacion Medica en Red de Salud Mental, CIBERSAM-University of Granada, Granada, Spain; MRC SGDP Centre, Institute of Psychiatry at King's College, De Crespigny Park, London SE5 8AF, UK; National Institute for Health Research, Biomedical Research Centre for Mental Health, Institute of Psychiatry at King's College, De Crespigny Park, London SE5 8AF, UK
| | - Hong Deng
- Mental Health Center of West China Hospital of Sichuan University, No. 28 South Dianxin Street, Wuhou District, Chengdu, Sichuan 610000, China
| | - Bo Du
- Hebei Mental Health Center, No. 572 Dongfeng Road, Baoding, Hebei 71000, China
| | - Keqing Li
- Hebei Mental Health Center, No. 572 Dongfeng Road, Baoding, Hebei 71000, China
| | - Wenhu Sang
- Hebei Mental Health Center, No. 572 Dongfeng Road, Baoding, Hebei 71000, China
| | - Jingfang Gao
- Zhejiang Traditional Chinese Medical Hospital, No. 54 Youdian Road, Hangzhou, Zhejiang 310000, China
| | - Shugui Gao
- Ningbo Kang Ning Hospital, No. 1 Zhuangyu Road, Zhenhai District, Ningbo, Zhejiang 315000, China
| | - Baowei Ha
- Liaocheng No. 4 Hospital, No. 47 North Huayuan Road, Liaocheng, Shandong 252000, China
| | - Hung-Yao Ho
- Department of Medical Biotechnology and Laboratory Science, College of Medicine, Chang Gung University, Tao-Yuan 33302, Taiwan, ROC
| | - Chunmei Hu
- No. 3 Hospital of Heilongjiang Province, No. 135 Jiaotong Road, Beian, Heilongjiang 164000, China
| | - Jian Hu
- Harbin Medical University, No. 23 Youzheng Street, Nangang District, Haerbin, Heilongjiang 150000, China
| | - Zhenfei Hu
- BGI-Shenzhen, Floor 9 Complex Building, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong 518083, China
| | - Guoping Huang
- Sichuan Mental Health Center, No. 190, East Jiannan Road, Mianyang, Sichuan 621000, China
| | - Guoqing Jiang
- Chongqing Mental Health Center, No. 102 Jinzishan, Jiangbei District, Chongqing, Chongqing 404100, China
| | - Tao Jiang
- BGI-Shenzhen, Floor 9 Complex Building, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong 518083, China
| | - Wei Jin
- BGI-Shenzhen, Floor 9 Complex Building, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong 518083, China
| | - Gongying Li
- Mental Health Institute of Jining Medical College, Dai Zhuang, Bei Jiao, Jining, Shandong 272000, China
| | - Kan Li
- Mental Hospital of Jiangxi Province, No. 43 Shangfang Road, Nanchang, Jiangxi 330000, China
| | - Yi Li
- Wuhan Mental Health Center, No. 70, Youyi Road, Wuhan, Hubei 430000, China
| | - Yingrui Li
- BGI-Shenzhen, Floor 9 Complex Building, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong 518083, China
| | - Youhui Li
- No. 1 Hospital of Zhengzhou University, No. 1 East Jianshe Road, Zhengzhou, Henan 450000, China
| | - Yu-Ting Lin
- Graduate Institute of Biomedical Sciences, College of Medicine, Chang Gung University, Tao-Yuan 33302, Taiwan, ROC
| | - Lanfen Liu
- Shandong Mental Health Center, No. 49 East Wenhua Road, Jinan, Shandong 250000, China
| | - Tiebang Liu
- Shenzhen Key Lab for Psychological Healthcare, Kangning Hospital, No. 1080, Cuizhu Street, Luohu District, Shenzhen, Guangdong 518000, China
| | - Ying Liu
- The First Hospital of China Medical University, No. 155 North Nanjing Street, Heping District, Shenyang, Liaoning 110001, China
| | - Yuan Liu
- BGI-Shenzhen, Floor 9 Complex Building, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong 518083, China
| | - Yao Lu
- BGI-Shenzhen, Floor 9 Complex Building, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong 518083, China
| | - Luxian Lv
- Psychiatric Hospital of Henan Province, No. 388 Middle Jianshe Road, Xinxiang, Henan 453000, China
| | - Huaqing Meng
- No. 1 Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuanjiagang, Yuzhong District, Chongqing, Chongqing 400016, China
| | - Puyi Qian
- BGI-Shenzhen, Floor 9 Complex Building, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong 518083, China
| | - Hong Sang
- Changchun Mental Hospital, No. 4596 Beihuan Road, Changchun, Jilin 130000, China
| | - Jianhua Shen
- Tianjin Anding Hospital, No. 13 Liulin Road, Hexi District, Tianjin, Tianjin 300000, China
| | - Jianguo Shi
- Xian Mental Health Center, No. 15 Yanyin Road, New Qujiang District, Xian, Shaanxi 710000, China
| | - Jing Sun
- Brain Hospital of Nanjing Medical University, No. 264 Guangzhou Road, Nanjing, Jiangsu 210000, China
| | - Ming Tao
- Second Affiliated Hospital of Zhejiang Chinese Medical University, No. 318 Chaowang Road, Hangzhou, Zhejiang 310000, China
| | - Gang Wang
- Beijing Anding Hospital of Capital University of Medical Sciences, No. 5 Ankang Hutong, Deshengmen wai, Xicheng District, Beijing, Beijing 100000, China
| | - Guangbiao Wang
- BGI-Shenzhen, Floor 9 Complex Building, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong 518083, China
| | - Jian Wang
- BGI-Shenzhen, Floor 9 Complex Building, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong 518083, China
| | - Linmao Wang
- BGI-Shenzhen, Floor 9 Complex Building, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong 518083, China
| | - Xueyi Wang
- First Hospital of Hebei Medical University, No. 89 Donggang Road, Shijiazhuang, Hebei 50000, China
| | - Xumei Wang
- ShengJing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, Liaoning 110001, China
| | - Huanming Yang
- BGI-Shenzhen, Floor 9 Complex Building, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong 518083, China
| | - Lijun Yang
- Jilin Brain Hospital, No. 98 West Zhongyang Road, Siping, Jilin 136000, China
| | - Ye Yin
- BGI-Shenzhen, Floor 9 Complex Building, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong 518083, China
| | - Jinbei Zhang
- No. 3 Hospital of Sun Yat-sen University, No. 600 Tianhe Road, Tianhe District, Guangzhou, Guangdong 510000, China
| | - Kerang Zhang
- No. 1 Hospital of Shanxi Medical University, No. 85 South Jiefang Road, Taiyuan, Shanxi 30000, China
| | - Ning Sun
- No. 1 Hospital of Shanxi Medical University, No. 85 South Jiefang Road, Taiyuan, Shanxi 30000, China
| | - Wei Zhang
- Daqing No. 3 Hospital of Heilongjiang Province, No. 54 Xitai Road, Ranghulu District, Daqing, Heilongjiang 163000, China
| | - Xiuqing Zhang
- BGI-Shenzhen, Floor 9 Complex Building, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong 518083, China
| | - Zhen Zhang
- No. 4 Hospital of Jiangsu University, No. 246 Nanmen Street, Zhenjiang, Jiangsu 212000, China
| | - Hui Zhong
- Anhui Mental Health Center, No. 316 Huangshan Road, Hefei, Anhui 230000, China
| | - Gerome Breen
- MRC SGDP Centre, Institute of Psychiatry at King's College, De Crespigny Park, London SE5 8AF, UK; National Institute for Health Research, Biomedical Research Centre for Mental Health, Institute of Psychiatry at King's College, De Crespigny Park, London SE5 8AF, UK
| | - Jun Wang
- BGI-Shenzhen, Floor 9 Complex Building, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong 518083, China; Department of Biology, University of Copenhagen, Ole Maaloes Vej 5, Copenhagen 2200, Denmark; Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau 999078, China; Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Jonathan Marchini
- Department of Statistics, University of Oxford, Oxford, Oxfordshire OX1 3TG, UK; Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford, Oxfordshire OX3 7BN, UK
| | - Yiping Chen
- CTSU, University of Oxford, Richard Doll Building, Old Road Campus, Oxford, Oxfordshire OX3 7LF, UK
| | - Qi Xu
- National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences & Neuroscience Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 10005, China
| | - Xun Xu
- BGI-Shenzhen, Floor 9 Complex Building, Beishan Industrial Zone, Yantian District, Shenzhen, Guangdong 518083, China
| | - Richard Mott
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford, Oxfordshire OX3 7BN, UK
| | - Guo-Jen Huang
- Department and Graduate Institute of Biomedical Sciences, College of Medicine, Chang Gung University, Tao-Yuan 33302, Taiwan, ROC
| | - Kenneth Kendler
- Dept Psychiatry MCV, Virginia Commonwealth University, Richmond, VA 23298, USA
| | - Jonathan Flint
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford, Oxfordshire OX3 7BN, UK; East China Normal University, 3663 North Zhongshan Road, Shanghai 200062, China.
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Ollikainen M, Ismail K, Gervin K, Kyllönen A, Hakkarainen A, Lundbom J, Järvinen EA, Harris JR, Lundbom N, Rissanen A, Lyle R, Pietiläinen KH, Kaprio J. Genome-wide blood DNA methylation alterations at regulatory elements and heterochromatic regions in monozygotic twins discordant for obesity and liver fat. Clin Epigenetics 2015; 7:39. [PMID: 25866590 PMCID: PMC4393626 DOI: 10.1186/s13148-015-0073-5] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2014] [Accepted: 03/11/2015] [Indexed: 12/16/2022] Open
Abstract
Background The current epidemic of obesity and associated diseases calls for swift actions to better understand the mechanisms by which genetics and environmental factors affect metabolic health in humans. Monozygotic (MZ) twin pairs showing discordance for obesity suggest that epigenetic influences represent one such mechanism. We studied genome-wide leukocyte DNA methylation variation in 30 clinically healthy young adult MZ twin pairs discordant for body mass index (BMI; average within-pair BMI difference: 5.4 ± 2.0 kg/m2). Results There were no differentially methylated cytosine-guanine (CpG) sites between the co-twins discordant for BMI. However, stratification of the twin pairs based on the level of liver fat accumulation revealed two epigenetically highly different groups. Significant DNA methylation differences (n = 1,236 CpG sites (CpGs)) between the co-twins were only observed if the heavier co-twins had excessive liver fat (n = 13 twin pairs). This unhealthy pattern of obesity was coupled with insulin resistance and low-grade inflammation. The differentially methylated CpGs included 23 genes known to be associated with obesity, liver fat, type 2 diabetes mellitus (T2DM) and metabolic syndrome, and potential novel metabolic genes. Differentially methylated CpG sites were overrepresented at promoters, insulators, and heterochromatic and repressed regions. Based on predictions by overlapping histone marks, repressed and weakly transcribed sites were significantly more often hypomethylated, whereas sites with strong enhancers and active promoters were hypermethylated. Further, significant clustering of differentially methylated genes in vitamin, amino acid, fatty acid, sulfur, and renin-angiotensin metabolism pathways was observed. Conclusions The methylome in leukocytes is altered in obesity associated with metabolic disturbances, and our findings indicate several novel candidate genes and pathways in obesity and obesity-related complications. Electronic supplementary material The online version of this article (doi:10.1186/s13148-015-0073-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Miina Ollikainen
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Khadeeja Ismail
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Kristina Gervin
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Anjuska Kyllönen
- Obesity Research Unit, Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
| | - Antti Hakkarainen
- Department of Radiology, HUS Medical Imaging Center, Helsinki University Central Hospital, University of Helsinki, Helsinki, Finland
| | - Jesper Lundbom
- Department of Radiology, HUS Medical Imaging Center, Helsinki University Central Hospital, University of Helsinki, Helsinki, Finland
| | - Elina A Järvinen
- Obesity Research Unit, Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
| | - Jennifer R Harris
- Division of Epidemiology, The Norwegian Institute of Public Health, Oslo, Norway
| | - Nina Lundbom
- Department of Radiology, HUS Medical Imaging Center, Helsinki University Central Hospital, University of Helsinki, Helsinki, Finland
| | - Aila Rissanen
- Department of Psychiatry, Helsinki University Central Hospital, Helsinki, Finland.,Endocrinology, Abdominal Center, Helsinki University Central Hospital, Helsinki, Finland
| | - Robert Lyle
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Kirsi H Pietiläinen
- Obesity Research Unit, Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland.,Endocrinology, Abdominal Center, Helsinki University Central Hospital, Helsinki, Finland.,Institute for Molecular Medicine FIMM, University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Department of Public Health, University of Helsinki, Helsinki, Finland.,Institute for Molecular Medicine FIMM, University of Helsinki, Helsinki, Finland.,Department of Mental Health and Substance Abuse Services, National Institute for Health and Welfare, Helsinki, Finland
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111
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Epigenetic control of myeloid cell differentiation, identity and function. Nat Rev Immunol 2015; 15:7-17. [PMID: 25534619 DOI: 10.1038/nri3777] [Citation(s) in RCA: 239] [Impact Index Per Article: 23.9] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Myeloid cells are crucial effectors of the innate immune response and important regulators of adaptive immunity. The differentiation and activation of myeloid cells requires the timely regulation of gene expression; this depends on the interplay of a variety of elements, including transcription factors and epigenetic mechanisms. Epigenetic control involves histone modifications and DNA methylation, and is coupled to lineage-specifying transcription factors, upstream signalling pathways and external factors released in the bone marrow, blood and tissue environments. In this Review, we highlight key epigenetic events controlling myeloid cell biology, focusing on those related to myeloid cell differentiation, the acquisition of myeloid identity and innate immune memory.
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113
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Jeschke J, Collignon E, Fuks F. DNA methylome profiling beyond promoters - taking an epigenetic snapshot of the breast tumor microenvironment. FEBS J 2014; 282:1801-14. [PMID: 25331982 DOI: 10.1111/febs.13125] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2014] [Revised: 10/06/2014] [Accepted: 10/19/2014] [Indexed: 12/22/2022]
Abstract
Breast cancer, one of the most common and deadliest malignancies in developed countries, is a remarkably heterogeneous disease, which is clinically reflected by patients who display similar pathological features but respond differently to treatments. In the search for mediators of responsiveness, the tumor microenvironment (TME), in particular tumor-associated immune cells, has been pushed into the spotlight as it has become clear that the TME is an active component of breast cancer disease that affects clinical outcomes. Thus, the characterization of the TME in terms of cell identities and their frequencies has generated a great deal of interest. The common methods currently used for this purpose are either limited in accuracy or application, and DNA methylation has recently been proposed as an alternative approach. The aim of this review is to discuss DNA methylation profiling beyond promoters as a potential clinical tool for TME characterization and cell typing within tumors. With respect to this, we review the role of DNA methylation in breast cancer and cell-lineage specification, as well as inform about the composition and clinical relevance of the TME.
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Affiliation(s)
- Jana Jeschke
- Laboratory of Cancer Epigenetics, Université Libre de Bruxelles, Brussels, Belgium
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Carmona JJ, Sofer T, Hutchinson J, Cantone L, Coull B, Maity A, Vokonas P, Lin X, Schwartz J, Baccarelli AA. Short-term airborne particulate matter exposure alters the epigenetic landscape of human genes associated with the mitogen-activated protein kinase network: a cross-sectional study. Environ Health 2014; 13:94. [PMID: 25395096 PMCID: PMC4273424 DOI: 10.1186/1476-069x-13-94] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2014] [Accepted: 10/06/2014] [Indexed: 05/22/2023]
Abstract
BACKGROUND Exposure to air particulate matter is known to elevate blood biomarkers of inflammation and to increase cardiopulmonary morbidity and mortality. Major components of airborne particulate matter typically include black carbon from traffic and sulfates from coal-burning power plants. DNA methylation is thought to be sensitive to these environmental toxins and possibly mediate environmental effects on clinical outcomes via regulation of gene networks. The underlying mechanisms may include epigenetic modulation of major inflammatory pathways, yet the details remain unclear. METHODS We sought to elucidate how short-term exposure to air pollution components, singly and/or in combination, alter blood DNA methylation in certain inflammation-associated gene networks, MAPK and NF-κB, which may transmit the environmental signal(s) and influence the inflammatory pathway in vivo. To this end, we utilized a custom-integrated workflow-molecular processing, pollution surveillance, biostatical analysis, and bioinformatic visualization-to map novel human (epi)gene pathway-environment interactions. RESULTS Specifically, out of 84 MAPK pathway genes considered, we identified 11 whose DNA methylation status was highly associated with black carbon exposure, after adjusting for potential confounders-age, sulfate exposure, smoking, blood cell composition, and blood pressure. Moreover, after adjusting for these confounders, multi-pollutant analysis of synergistic DNA methylations significantly associated with sulfate and BC exposures yielded 14 MAPK genes. No associations were found with the NF-κB pathway. CONCLUSION Exposure to short-term air pollution components thus resulted in quantifiable epigenetic changes in the promoter areas of MAPK pathway genes. Bioinformatic mapping of single- vs. multi-exposure-associated epigenetic changes suggests that these alterations might affect biological pathways in nuanced ways that are not simply additive or fully predictable via individual-level exposure assessments.
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Affiliation(s)
- Juan Jose Carmona
- />Laboratory of Human Environmental Epigenetics, Department of Environmental Health, Harvard School of Public Health, Boston, MA USA
- />Exposure, Epidemiology, and Risk Program, Department of Environmental Health, Harvard School of Public Health, Boston, MA USA
- />Program in Quantitative Genomics, Department of Biostatistics, Harvard School of Public Health, Boston, MA USA
| | - Tamar Sofer
- />Program in Quantitative Genomics, Department of Biostatistics, Harvard School of Public Health, Boston, MA USA
| | - John Hutchinson
- />Center for Health Bioinformatics, Harvard School of Public Health, Boston, MA USA
| | - Laura Cantone
- />Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy
| | - Brent Coull
- />Program in Quantitative Genomics, Department of Biostatistics, Harvard School of Public Health, Boston, MA USA
| | - Arnab Maity
- />Department of Statistics, North Carolina State University, Raleigh, NC USA
| | - Pantel Vokonas
- />VA Normative Aging Study, Veterans Affairs Boston Healthcare System and the Department of Medicine, Boston University School of Medicine, Boston, Massachusetts USA
| | - Xihong Lin
- />Program in Quantitative Genomics, Department of Biostatistics, Harvard School of Public Health, Boston, MA USA
| | - Joel Schwartz
- />Laboratory of Human Environmental Epigenetics, Department of Environmental Health, Harvard School of Public Health, Boston, MA USA
- />Exposure, Epidemiology, and Risk Program, Department of Environmental Health, Harvard School of Public Health, Boston, MA USA
| | - Andrea A Baccarelli
- />Laboratory of Human Environmental Epigenetics, Department of Environmental Health, Harvard School of Public Health, Boston, MA USA
- />Exposure, Epidemiology, and Risk Program, Department of Environmental Health, Harvard School of Public Health, Boston, MA USA
- />Program in Quantitative Genomics, Department of Biostatistics, Harvard School of Public Health, Boston, MA USA
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DNA methylation biomarkers: cancer and beyond. Genes (Basel) 2014; 5:821-64. [PMID: 25229548 PMCID: PMC4198933 DOI: 10.3390/genes5030821] [Citation(s) in RCA: 190] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2014] [Revised: 08/17/2014] [Accepted: 09/01/2014] [Indexed: 12/23/2022] Open
Abstract
Biomarkers are naturally-occurring characteristics by which a particular pathological process or disease can be identified or monitored. They can reflect past environmental exposures, predict disease onset or course, or determine a patient's response to therapy. Epigenetic changes are such characteristics, with most epigenetic biomarkers discovered to date based on the epigenetic mark of DNA methylation. Many tissue types are suitable for the discovery of DNA methylation biomarkers including cell-based samples such as blood and tumor material and cell-free DNA samples such as plasma. DNA methylation biomarkers with diagnostic, prognostic and predictive power are already in clinical trials or in a clinical setting for cancer. Outside cancer, strong evidence that complex disease originates in early life is opening up exciting new avenues for the detection of DNA methylation biomarkers for adverse early life environment and for estimation of future disease risk. However, there are a number of limitations to overcome before such biomarkers reach the clinic. Nevertheless, DNA methylation biomarkers have great potential to contribute to personalized medicine throughout life. We review the current state of play for DNA methylation biomarkers, discuss the barriers that must be crossed on the way to implementation in a clinical setting, and predict their future use for human disease.
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