401
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Demanelis K, Virani S, Colacino JA, Basu N, Nishijo M, Ruangyuttikarn W, Swaddiwudhipong W, Nambunmee K, Rozek LS. Cadmium exposure and age-associated DNA methylation changes in non-smoking women from northern Thailand. ENVIRONMENTAL EPIGENETICS 2017; 3:dvx006. [PMID: 29492308 PMCID: PMC5804546 DOI: 10.1093/eep/dvx006] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2017] [Revised: 05/08/2017] [Accepted: 06/12/2017] [Indexed: 05/19/2023]
Abstract
DNA methylation changes with age, and may serve as a biomarker of aging. Cadmium (Cd) modifies cellular processes that promote aging and disrupts methylation globally. Whether Cd modifies aging processes by influencing establishment of age-associated methylation marks is currently unknown. In this pilot study, we characterized methylation profiles in > 450 000 CpG sites in 40 non-smoking women (age 40-80) differentially exposed to environmental Cd from Thailand. Based on specific gravity adjusted urinary Cd, we classified them as high (HE) and low (LE) exposed and age-matched within 5 years. Urinary Cd was defined as below 2 µg/l in the LE group. We predicted epigenetic age (DNAm-age) using two published methods by Horvath and Hannum and examined the difference between epigenetic age and chronologic age (Δage). We assessed differences by Cd exposure using linear mixed models adjusted for estimated white blood cell proportions, BMI, and urinary creatinine. We identified 213 age-associated CpG sites in our population (P < 10-4). Counterintuitively, the mean Δage was smaller in HE vs. LE (Hannum: 3.6 vs. 7.6 years, P = 0.0093; Horvath: 2.4 vs. 4.5 years, P = 0.1308). The Cd exposed group was associated with changes in methylation (P < 0.05) at 12, 8, and 20 age-associated sites identified in our population, Hannum, and Horvath. From the results of this pilot study, elevated Cd exposure is associated with methylation changes at age-associated sites and smaller differences between DNAm-age and chronologic age, in contrast to expected age-accelerating effects. Cd may modify epigenetic aging, and biomarkers of aging warrant further investigation when examining Cd and its relationship with chronic disease and mortality.
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Affiliation(s)
- Kathryn Demanelis
- Department of Environmental Health Sciences, University of Michigan, Ann Arbor, MI 48104, USA
| | - Shama Virani
- Department of Environmental Health Sciences, University of Michigan, Ann Arbor, MI 48104, USA
| | - Justin A. Colacino
- Department of Environmental Health Sciences, University of Michigan, Ann Arbor, MI 48104, USA
| | - Niladri Basu
- Faculty of Agricultural and Environmental Sciences, McGill University, Montreal, QC, H9X3V9, Canada
| | - Muneko Nishijo
- Department of Public Health, Kanazawa Medical University Hospital, Uchinada, 920-0293, Ishikawa, Japan
| | - Werawan Ruangyuttikarn
- Department of Forensic Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand
| | - Witaya Swaddiwudhipong
- Department of Community and Social Science, Mae Sot General Hospital, Mae Sot District, Tak Province 63110, Thailand
| | - Kowit Nambunmee
- School of Health Science, Mae Fah Luang University, Chiang Rai 57100, Thailand
| | - Laura S. Rozek
- Department of Environmental Health Sciences, University of Michigan, Ann Arbor, MI 48104, USA
- Correspondence address. Department of Environmental Health Sciences, Office of Global Public Health, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI 48109-2200, USA. Tel: 734-615-9816; E-mail:
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402
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McEwen LM, Morin AM, Edgar RD, MacIsaac JL, Jones MJ, Dow WH, Rosero-Bixby L, Kobor MS, Rehkopf DH. Differential DNA methylation and lymphocyte proportions in a Costa Rican high longevity region. Epigenetics Chromatin 2017; 10:21. [PMID: 28465725 PMCID: PMC5408416 DOI: 10.1186/s13072-017-0128-2] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2017] [Accepted: 04/13/2017] [Indexed: 01/01/2023] Open
Abstract
Background The Nicoya Peninsula in Costa Rica has one of the highest old-age life expectancies in the world, but the underlying biological mechanisms of this longevity are not well understood. As DNA methylation is hypothesized to be a component of biological aging, we focused on this malleable epigenetic mark to determine its association with current residence in Nicoya versus elsewhere in Costa Rica. Examining a population’s unique DNA methylation pattern allows us to differentiate hallmarks of longevity from individual stochastic variation. These differences may be characteristic of a combination of social, biological, and environmental contexts. Methods In a cross-sectional subsample of the Costa Rican Longevity and Healthy Aging Study, we compared whole blood DNA methylation profiles of residents from Nicoya (n = 48) and non-Nicoya (other Costa Rican regions, n = 47) using the Infinium HumanMethylation450 microarray. Results We observed a number of differences that may be markers of delayed aging, such as bioinformatically derived differential CD8+ T cell proportions. Additionally, both site- and region-specific analyses revealed DNA methylation patterns unique to Nicoyans. We also observed lower overall variability in DNA methylation in the Nicoyan population, another hallmark of younger biological age. Conclusions Nicoyans represent an interesting group of individuals who may possess unique immune cell proportions as well as distinct differences in their epigenome, at the level of DNA methylation. Electronic supplementary material The online version of this article (doi:10.1186/s13072-017-0128-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Lisa M McEwen
- Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, University of British Columbia, 950 West 28th Ave, Vancouver, Canada
| | - Alexander M Morin
- Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, University of British Columbia, 950 West 28th Ave, Vancouver, Canada
| | - Rachel D Edgar
- Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, University of British Columbia, 950 West 28th Ave, Vancouver, Canada
| | - Julia L MacIsaac
- Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, University of British Columbia, 950 West 28th Ave, Vancouver, Canada
| | - Meaghan J Jones
- Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, University of British Columbia, 950 West 28th Ave, Vancouver, Canada
| | - William H Dow
- School of Public Health, University of California, Berkeley, Berkeley, CA USA
| | - Luis Rosero-Bixby
- Centro Centroamericano de Población, Universidad de Costa Rica, San José, Costa Rica
| | - Michael S Kobor
- Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, University of British Columbia, 950 West 28th Ave, Vancouver, Canada
| | - David H Rehkopf
- Division of General Medical Disciplines, Department of Medicine, School of Medicine, Stanford University, 1070 Arastradero Road, Suite 300, Palo Alto, CA 94304 USA
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403
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Freytag V, Carrillo-Roa T, Milnik A, Sämann PG, Vukojevic V, Coynel D, Demougin P, Egli T, Gschwind L, Jessen F, Loos E, Maier W, Riedel-Heller SG, Scherer M, Vogler C, Wagner M, Binder EB, de Quervain DJF, Papassotiropoulos A. A peripheral epigenetic signature of immune system genes is linked to neocortical thickness and memory. Nat Commun 2017; 8:15193. [PMID: 28443631 PMCID: PMC5414038 DOI: 10.1038/ncomms15193] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2016] [Accepted: 03/08/2017] [Indexed: 01/01/2023] Open
Abstract
Increasing age is tightly linked to decreased thickness of the human neocortex. The biological mechanisms that mediate this effect are hitherto unknown. The DNA methylome, as part of the epigenome, contributes significantly to age-related phenotypic changes. Here, we identify an epigenetic signature that is associated with cortical thickness (P=3.86 × 10−8) and memory performance in 533 healthy young adults. The epigenetic effect on cortical thickness was replicated in a sample comprising 596 participants with major depressive disorder and healthy controls. The epigenetic signature mediates partially the effect of age on cortical thickness (P<0.001). A multilocus genetic score reflecting genetic variability of this signature is associated with memory performance (P=0.0003) in 3,346 young and elderly healthy adults. The genomic location of the contributing methylation sites points to the involvement of specific immune system genes. The decomposition of blood methylome-wide patterns bears considerable potential for the study of brain-related traits. Cortical thickness has high heritability estimates and is known to be influenced by genetic factors. Here, Freytag and colleagues show that DNA methylation patterns of peripheral blood monocytes are also correlated with cortical thickness and memory performance in human.
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Affiliation(s)
- Virginie Freytag
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055 Basel, Switzerland.,Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055 Basel, Switzerland
| | - Tania Carrillo-Roa
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, D-80804 Munich, Germany
| | - Annette Milnik
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055 Basel, Switzerland.,Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055 Basel, Switzerland.,Psychiatric University Clinics, University of Basel, CH-4055 Basel, Switzerland
| | - Philipp G Sämann
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, D-80804 Munich, Germany
| | - Vanja Vukojevic
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055 Basel, Switzerland.,Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055 Basel, Switzerland.,Department Biozentrum, Life Sciences Training Facility, University of Basel, CH-4056 Basel, Switzerland
| | - David Coynel
- Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055 Basel, Switzerland.,Division of Cognitive Neuroscience, Department of Psychology, University of Basel, CH-4055 Basel, Switzerland
| | - Philippe Demougin
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055 Basel, Switzerland.,Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055 Basel, Switzerland.,Department Biozentrum, Life Sciences Training Facility, University of Basel, CH-4056 Basel, Switzerland
| | - Tobias Egli
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055 Basel, Switzerland.,Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055 Basel, Switzerland
| | - Leo Gschwind
- Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055 Basel, Switzerland.,Division of Cognitive Neuroscience, Department of Psychology, University of Basel, CH-4055 Basel, Switzerland
| | - Frank Jessen
- German Center for Neurodegenerative Diseases (DZNE), D-53175 Bonn, Germany.,Department of Psychiatry, University of Cologne, Medical Faculty, D-50924 Cologne, Germany
| | - Eva Loos
- Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055 Basel, Switzerland.,Division of Cognitive Neuroscience, Department of Psychology, University of Basel, CH-4055 Basel, Switzerland
| | - Wolfgang Maier
- German Center for Neurodegenerative Diseases (DZNE), D-53175 Bonn, Germany.,Department of Psychiatry, University of Bonn, D-53105 Bonn, Germany
| | - Steffi G Riedel-Heller
- Institute of Social Medicine, Occupational Health and Public Health, University of Leipzig, D-04103 Leipzig, Germany
| | - Martin Scherer
- Center for Psychosocial Medicine, Department of Primary Medical Care, University Medical Center Hamburg-Eppendorf, D-20246 Hamburg, Germany
| | - Christian Vogler
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055 Basel, Switzerland.,Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055 Basel, Switzerland.,Psychiatric University Clinics, University of Basel, CH-4055 Basel, Switzerland
| | - Michael Wagner
- German Center for Neurodegenerative Diseases (DZNE), D-53175 Bonn, Germany.,Department of Psychiatry, University of Bonn, D-53105 Bonn, Germany
| | - Elisabeth B Binder
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, D-80804 Munich, Germany.,Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia 30322, USA
| | - Dominique J-F de Quervain
- Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055 Basel, Switzerland.,Psychiatric University Clinics, University of Basel, CH-4055 Basel, Switzerland.,Division of Cognitive Neuroscience, Department of Psychology, University of Basel, CH-4055 Basel, Switzerland
| | - Andreas Papassotiropoulos
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055 Basel, Switzerland.,Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055 Basel, Switzerland.,Psychiatric University Clinics, University of Basel, CH-4055 Basel, Switzerland.,Department Biozentrum, Life Sciences Training Facility, University of Basel, CH-4056 Basel, Switzerland
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404
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de Goede OM, Lavoie PM, Robinson WP. Cord blood hematopoietic cells from preterm infants display altered DNA methylation patterns. Clin Epigenetics 2017; 9:39. [PMID: 28428831 PMCID: PMC5397745 DOI: 10.1186/s13148-017-0339-1] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2016] [Accepted: 04/08/2017] [Indexed: 12/18/2022] Open
Abstract
Background Premature infants are highly vulnerable to infection. This is partly attributable to the preterm immune system, which differs from that of the term neonate in cell composition and function. Multiple studies have found differential DNA methylation (DNAm) between preterm and term infants’ cord blood; however, interpretation of these studies is limited by the confounding factor of blood cell composition. This study evaluates the epigenetic impact of preterm birth in isolated hematopoietic cell populations, reducing the concern of cell composition differences. Methods Genome-wide DNAm was measured using the Illumina 450K array in T cells, monocytes, granulocytes, and nucleated red blood cells (nRBCs) isolated from cord blood of 5 term and 5 preterm (<31 weeks gestational age) newborns. DNAm of hematopoietic cells was compared globally across the 450K array and through site-specific linear modeling. Results Nucleated red blood cells (nRBCs) showed the most extensive changes in DNAm, with 9258 differentially methylated (DM) sites (FDR < 5%, |Δβ| > 0.10) discovered between preterm and term infants compared to the <1000 prematurity-DM sites identified in white blood cell populations. The direction of DNAm change with gestational age at these prematurity-DM sites followed known patterns of hematopoietic differentiation, suggesting that term hematopoietic cell populations are more epigenetically mature than their preterm counterparts. Consistent shifts in DNAm between preterm and term cells were observed at 25 CpG sites, with many of these sites located in genes involved in growth and proliferation, hematopoietic lineage commitment, and the cytoskeleton. DNAm in preterm and term hematopoietic cells conformed to previously identified DNAm signatures of fetal liver and bone marrow, respectively. Conclusions This study presents the first genome-wide mapping of epigenetic differences in hematopoietic cells across the late gestational period. DNAm differences in hematopoietic cells between term and <31 weeks were consistent with the hematopoietic origin of these cells during ontogeny, reflecting an important role of DNAm in their regulation. Due to the limited sample size and the high coincidence of prematurity and multiple births, the relationship between cause of preterm birth and DNAm could not be evaluated. These findings highlight gene regulatory mechanisms at both cell-specific and systemic levels that may be involved in fetal immune system maturation. Electronic supplementary material The online version of this article (doi:10.1186/s13148-017-0339-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Olivia M de Goede
- BC Children's Hospital Research Institute, Room 2082, 950W 28th Avenue, Vancouver, BC V5Z 4H4 Canada.,Department of Medical Genetics, University of British Columbia, Vancouver, BC V6T 1Z3 Canada
| | - Pascal M Lavoie
- BC Children's Hospital Research Institute, Room 2082, 950W 28th Avenue, Vancouver, BC V5Z 4H4 Canada.,Department of Pediatrics, University of British Columbia, Vancouver, BC V6T 1Z3 Canada
| | - Wendy P Robinson
- BC Children's Hospital Research Institute, Room 2082, 950W 28th Avenue, Vancouver, BC V5Z 4H4 Canada.,Department of Medical Genetics, University of British Columbia, Vancouver, BC V6T 1Z3 Canada
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405
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Sundar IK, Yin Q, Baier BS, Yan L, Mazur W, Li D, Susiarjo M, Rahman I. DNA methylation profiling in peripheral lung tissues of smokers and patients with COPD. Clin Epigenetics 2017; 9:38. [PMID: 28416970 PMCID: PMC5391602 DOI: 10.1186/s13148-017-0335-5] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Accepted: 03/29/2017] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Epigenetics changes have been shown to be affected by cigarette smoking. Cigarette smoke (CS)-mediated DNA methylation can potentially affect several cellular and pathophysiological processes, acute exacerbations, and comorbidity in the lungs of patients with chronic obstructive pulmonary disease (COPD). We sought to determine whether genome-wide lung DNA methylation profiles of smokers and patients with COPD were significantly different from non-smokers. We isolated DNA from parenchymal lung tissues of patients including eight lifelong non-smokers, eight current smokers, and eight patients with COPD and analyzed the samples using Illumina's Infinium HumanMethylation450 BeadChip. RESULTS Our data revealed that the differentially methylated genes were related to top canonical pathways (e.g., G beta gamma signaling, mechanisms of cancer, and nNOS signaling in neurons), disease and disorders (organismal injury and abnormalities, cancer, and respiratory disease), and molecular and cellular functions (cell death and survival, cellular assembly and organization, cellular function and maintenance) in patients with COPD. The genome-wide DNA methylation analysis identified suggestive genes, such as NOS1AP, TNFAIP2, BID, GABRB1, ATXN7, and THOC7 with DNA methylation changes in COPD lung tissues that were further validated by pyrosequencing. Pyrosequencing validation confirmed hyper-methylation in smokers and patients with COPD as compared to non-smokers. However, we did not detect significant differences in DNA methylation for TNFAIP2, ATXN7, and THOC7 genes in smokers and COPD groups despite the changes observed in the genome-wide analysis. CONCLUSIONS Our study suggests that DNA methylation in suggestive genes, such as NOS1AP, BID, and GABRB1 may be used as epigenetic signatures in smokers and patients with COPD if the same is validated in a larger cohort. Future studies are required to correlate DNA methylation status with transcriptomics of selective genes identified in this study and elucidate their role and involvement in the progression of COPD and its exacerbations.
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Affiliation(s)
- Isaac K Sundar
- Department of Environmental Medicine, University of Rochester Medical Center, Box 850, 601 Elmwood Avenue, Rochester, 14642 NY USA
| | - Qiangzong Yin
- Department of Environmental Medicine, University of Rochester Medical Center, Box 850, 601 Elmwood Avenue, Rochester, 14642 NY USA
| | - Brian S Baier
- Department of Environmental Medicine, University of Rochester Medical Center, Box 850, 601 Elmwood Avenue, Rochester, 14642 NY USA
| | - Li Yan
- Department of Biostatistics and Bioinformatics, Roswell Park Cancer Institute, Buffalo, NY USA
| | - Witold Mazur
- Heart and Lung Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Dongmei Li
- Department of Clinical & Translational Research, University of Rochester Medical Center, Rochester, NY USA
| | - Martha Susiarjo
- Department of Environmental Medicine, University of Rochester Medical Center, Box 850, 601 Elmwood Avenue, Rochester, 14642 NY USA
| | - Irfan Rahman
- Department of Environmental Medicine, University of Rochester Medical Center, Box 850, 601 Elmwood Avenue, Rochester, 14642 NY USA
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406
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Chen L, Ge B, Casale FP, Vasquez L, Kwan T, Garrido-Martín D, Watt S, Yan Y, Kundu K, Ecker S, Datta A, Richardson D, Burden F, Mead D, Mann AL, Fernandez JM, Rowlston S, Wilder SP, Farrow S, Shao X, Lambourne JJ, Redensek A, Albers CA, Amstislavskiy V, Ashford S, Berentsen K, Bomba L, Bourque G, Bujold D, Busche S, Caron M, Chen SH, Cheung W, Delaneau O, Dermitzakis ET, Elding H, Colgiu I, Bagger FO, Flicek P, Habibi E, Iotchkova V, Janssen-Megens E, Kim B, Lehrach H, Lowy E, Mandoli A, Matarese F, Maurano MT, Morris JA, Pancaldi V, Pourfarzad F, Rehnstrom K, Rendon A, Risch T, Sharifi N, Simon MM, Sultan M, Valencia A, Walter K, Wang SY, Frontini M, Antonarakis SE, Clarke L, Yaspo ML, Beck S, Guigo R, Rico D, Martens JHA, Ouwehand WH, Kuijpers TW, Paul DS, Stunnenberg HG, Stegle O, Downes K, Pastinen T, Soranzo N. Genetic Drivers of Epigenetic and Transcriptional Variation in Human Immune Cells. Cell 2017; 167:1398-1414.e24. [PMID: 27863251 PMCID: PMC5119954 DOI: 10.1016/j.cell.2016.10.026] [Citation(s) in RCA: 419] [Impact Index Per Article: 59.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2016] [Revised: 08/19/2016] [Accepted: 10/14/2016] [Indexed: 12/20/2022]
Abstract
Characterizing the multifaceted contribution of genetic and epigenetic factors to disease phenotypes is a major challenge in human genetics and medicine. We carried out high-resolution genetic, epigenetic, and transcriptomic profiling in three major human immune cell types (CD14+ monocytes, CD16+ neutrophils, and naive CD4+ T cells) from up to 197 individuals. We assess, quantitatively, the relative contribution of cis-genetic and epigenetic factors to transcription and evaluate their impact as potential sources of confounding in epigenome-wide association studies. Further, we characterize highly coordinated genetic effects on gene expression, methylation, and histone variation through quantitative trait locus (QTL) mapping and allele-specific (AS) analyses. Finally, we demonstrate colocalization of molecular trait QTLs at 345 unique immune disease loci. This expansive, high-resolution atlas of multi-omics changes yields insights into cell-type-specific correlation between diverse genomic inputs, more generalizable correlations between these inputs, and defines molecular events that may underpin complex disease risk. Genome, transcriptome, and epigenome reference panel in three human immune cell types Identified 4,418 genes associated with epigenetic changes independent of genetics Described genome-epigenome coordination defining cell-type-specific regulatory events Functionally mapped disease mechanisms at 345 unique autoimmune disease loci
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Affiliation(s)
- Lu Chen
- Department of Human Genetics, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK; Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK
| | - Bing Ge
- Human Genetics, McGill University, 740 Dr. Penfield, Montreal, QC H3A 0G1, Canada
| | - Francesco Paolo Casale
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Louella Vasquez
- Department of Human Genetics, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK
| | - Tony Kwan
- Human Genetics, McGill University, 740 Dr. Penfield, Montreal, QC H3A 0G1, Canada
| | - Diego Garrido-Martín
- Bioinformatics and Genomics, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Carrer del Dr. Aiguader, 88, Barcelona 8003, Spain; Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), Plaça de la Mercè, 10- 12, Barcelona 8002, Spain
| | - Stephen Watt
- Department of Human Genetics, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK
| | - Ying Yan
- Department of Human Genetics, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK
| | - Kousik Kundu
- Department of Human Genetics, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK; Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK
| | - Simone Ecker
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernandez Almagro, 3, Madrid 28029, Spain; UCL Cancer Institute, University College London, 72 Huntley Street, London WC1E 6BT, UK
| | - Avik Datta
- Vertebrate Genomics, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - David Richardson
- Vertebrate Genomics, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Frances Burden
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK
| | - Daniel Mead
- Department of Human Genetics, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK
| | - Alice L Mann
- Department of Human Genetics, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK
| | - Jose Maria Fernandez
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernandez Almagro, 3, Madrid 28029, Spain
| | - Sophia Rowlston
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK
| | - Steven P Wilder
- Genome Analysis, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Samantha Farrow
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK
| | - Xiaojian Shao
- Human Genetics, McGill University, 740 Dr. Penfield, Montreal, QC H3A 0G1, Canada
| | - John J Lambourne
- Human Genetics, McGill University, 740 Dr. Penfield, Montreal, QC H3A 0G1, Canada; Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK
| | - Adriana Redensek
- Human Genetics, McGill University, 740 Dr. Penfield, Montreal, QC H3A 0G1, Canada
| | - Cornelis A Albers
- Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, P.O. Box 9101, Nijmegen 6500 HB, the Netherlands; Molecular Developmental Biology, Radboud Institute for Life Sciences, Radboud University, P.O. Box 9101, Nijmegen 6500 HB, the Netherlands
| | - Vyacheslav Amstislavskiy
- Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestr. 63/73, Berlin 14195, Germany
| | - Sofie Ashford
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK
| | - Kim Berentsen
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen 6525GA, the Netherlands
| | - Lorenzo Bomba
- Department of Human Genetics, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK
| | - Guillaume Bourque
- Human Genetics, McGill University, 740 Dr. Penfield, Montreal, QC H3A 0G1, Canada
| | - David Bujold
- Human Genetics, McGill University, 740 Dr. Penfield, Montreal, QC H3A 0G1, Canada
| | - Stephan Busche
- Human Genetics, McGill University, 740 Dr. Penfield, Montreal, QC H3A 0G1, Canada
| | - Maxime Caron
- Human Genetics, McGill University, 740 Dr. Penfield, Montreal, QC H3A 0G1, Canada
| | - Shu-Huang Chen
- Human Genetics, McGill University, 740 Dr. Penfield, Montreal, QC H3A 0G1, Canada
| | - Warren Cheung
- Human Genetics, McGill University, 740 Dr. Penfield, Montreal, QC H3A 0G1, Canada
| | - Oliver Delaneau
- Genetic Medicine and Development, University of Geneva Medical School-CMU, 1 Rue Michel-Servet, Geneva 1211, Switzerland
| | - Emmanouil T Dermitzakis
- Genetic Medicine and Development, University of Geneva Medical School-CMU, 1 Rue Michel-Servet, Geneva 1211, Switzerland
| | - Heather Elding
- Department of Human Genetics, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK
| | - Irina Colgiu
- Human Genetics Informatics, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK
| | - Frederik O Bagger
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK
| | - Paul Flicek
- Vertebrate Genomics, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Ehsan Habibi
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen 6525GA, the Netherlands
| | - Valentina Iotchkova
- Department of Human Genetics, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Eva Janssen-Megens
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen 6525GA, the Netherlands
| | - Bowon Kim
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen 6525GA, the Netherlands
| | - Hans Lehrach
- Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestr. 63/73, Berlin 14195, Germany
| | - Ernesto Lowy
- Vertebrate Genomics, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Amit Mandoli
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen 6525GA, the Netherlands
| | - Filomena Matarese
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen 6525GA, the Netherlands
| | - Matthew T Maurano
- Institute for Systems Genetics, New York University Langone Medical Center, ACLS West, Room 511, 430 East 29(th) Street, New York, NY 10016, USA
| | - John A Morris
- Human Genetics, McGill University, 740 Dr. Penfield, Montreal, QC H3A 0G1, Canada
| | - Vera Pancaldi
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernandez Almagro, 3, Madrid 28029, Spain
| | - Farzin Pourfarzad
- Blood Cell Research, Sanquin Research and Landsteiner Laboratory, Plesmanlaan 125, Amsterdam 1066CX, the Netherlands
| | - Karola Rehnstrom
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK
| | - Augusto Rendon
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; Bioinformatics, Genomics England, Charterhouse Square, London EC1M 6BQ, UK
| | - Thomas Risch
- Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestr. 63/73, Berlin 14195, Germany
| | - Nilofar Sharifi
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen 6525GA, the Netherlands
| | - Marie-Michelle Simon
- Human Genetics, McGill University, 740 Dr. Penfield, Montreal, QC H3A 0G1, Canada
| | - Marc Sultan
- Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestr. 63/73, Berlin 14195, Germany
| | - Alfonso Valencia
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernandez Almagro, 3, Madrid 28029, Spain
| | - Klaudia Walter
- Department of Human Genetics, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK
| | - Shuang-Yin Wang
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen 6525GA, the Netherlands
| | - Mattia Frontini
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; British Heart Foundation Centre of Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Hills Road, Cambridge CB2 0QQ, UK
| | - Stylianos E Antonarakis
- Genetic Medicine and Development, University of Geneva Medical School-CMU, 1 Rue Michel-Servet, Geneva 1211, Switzerland
| | - Laura Clarke
- Vertebrate Genomics, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Marie-Laure Yaspo
- Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestr. 63/73, Berlin 14195, Germany
| | - Stephan Beck
- UCL Cancer Institute, University College London, 72 Huntley Street, London WC1E 6BT, UK
| | - Roderic Guigo
- Bioinformatics and Genomics, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Carrer del Dr. Aiguader, 88, Barcelona 8003, Spain; Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), Plaça de la Mercè, 10- 12, Barcelona 8002, Spain; Computational Genomics, Institut Hospital del Mar d'Investigacions Mediques (IMIM), Carrer del Dr. Aiguader, 88, Barcelona 8003, Spain
| | - Daniel Rico
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernandez Almagro, 3, Madrid 28029, Spain; Institute of Cellular Medicine, Newcastle University, Framlington Place, Newcastle upon Tyne NE2 4HH, UK
| | - Joost H A Martens
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen 6525GA, the Netherlands
| | - Willem H Ouwehand
- Department of Human Genetics, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK; Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; British Heart Foundation Centre of Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Hills Road, Cambridge CB2 0QQ, UK; The National Institute for Health Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics at the University of Cambridge, Strangeways Research Laboratory, University of Cambridge, Wort's Causeway, Cambridge CB1 8RN, UK
| | - Taco W Kuijpers
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; Blood Cell Research, Sanquin Research and Landsteiner Laboratory, Plesmanlaan 125, Amsterdam 1066CX, the Netherlands; Emma Children's Hospital, Academic Medical Center (AMC), University of Amsterdam, Location H7-230, Meibergdreef 9, Amsterdam 1105AZ, the Netherlands
| | - Dirk S Paul
- UCL Cancer Institute, University College London, 72 Huntley Street, London WC1E 6BT, UK; Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, Wort's Causeway, Cambridge CB1 8RN, UK
| | - Hendrik G Stunnenberg
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen 6525GA, the Netherlands
| | - Oliver Stegle
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Kate Downes
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK
| | - Tomi Pastinen
- Human Genetics, McGill University, 740 Dr. Penfield, Montreal, QC H3A 0G1, Canada.
| | - Nicole Soranzo
- Department of Human Genetics, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK; Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge CB2 0PT, UK; British Heart Foundation Centre of Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Hills Road, Cambridge CB2 0QQ, UK; The National Institute for Health Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics at the University of Cambridge, Strangeways Research Laboratory, University of Cambridge, Wort's Causeway, Cambridge CB1 8RN, UK.
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407
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Panopoulos AD, Smith EN, Arias AD, Shepard PJ, Hishida Y, Modesto V, Diffenderfer KE, Conner C, Biggs W, Sandoval E, D'Antonio-Chronowska A, Berggren WT, Izpisua Belmonte JC, Frazer KA. Aberrant DNA Methylation in Human iPSCs Associates with MYC-Binding Motifs in a Clone-Specific Manner Independent of Genetics. Cell Stem Cell 2017; 20:505-517.e6. [PMID: 28388429 PMCID: PMC5444384 DOI: 10.1016/j.stem.2017.03.010] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2016] [Revised: 01/06/2017] [Accepted: 03/15/2017] [Indexed: 01/24/2023]
Abstract
Induced pluripotent stem cells (iPSCs) show variable methylation patterns between lines, some of which reflect aberrant differences relative to embryonic stem cells (ESCs). To examine whether this aberrant methylation results from genetic variation or non-genetic mechanisms, we generated human iPSCs from monozygotic twins to investigate how genetic background, clone, and passage number contribute. We found that aberrantly methylated CpGs are enriched in regulatory regions associated with MYC protein motifs and affect gene expression. We classified differentially methylated CpGs as being associated with genetic and/or non-genetic factors (clone and passage), and we found that aberrant methylation preferentially occurs at CpGs associated with clone-specific effects. We further found that clone-specific effects play a strong role in recurrent aberrant methylation at specific CpG sites across different studies. Our results argue that a non-genetic biological mechanism underlies aberrant methylation in iPSCs and that it is likely based on a probabilistic process involving MYC that takes place during or shortly after reprogramming.
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Affiliation(s)
- Athanasia D Panopoulos
- Gene Expression Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA; Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Erin N Smith
- Pediatrics and Rady Children's Hospital, University of California, San Diego, La Jolla, CA 92093, USA
| | - Angelo D Arias
- Pediatrics and Rady Children's Hospital, University of California, San Diego, La Jolla, CA 92093, USA
| | - Peter J Shepard
- Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093, USA; BioSpyder Technologies, Inc., Carlsbad, CA 92008, USA
| | - Yuriko Hishida
- Gene Expression Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Veronica Modesto
- Stem Cell Core, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | | | - Clay Conner
- Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA
| | | | | | | | - W Travis Berggren
- Stem Cell Core, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | | | - Kelly A Frazer
- Pediatrics and Rady Children's Hospital, University of California, San Diego, La Jolla, CA 92093, USA; Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093, USA; Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA 92093, USA; Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA 92093, USA.
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408
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FitzGerald LM, Naeem H, Makalic E, Schmidt DF, Dowty JG, Joo JE, Jung CH, Bassett JK, Dugue PA, Chung J, Lonie A, Milne RL, Wong EM, Hopper JL, English DR, Severi G, Baglietto L, Pedersen J, Giles GG, Southey MC. Genome-Wide Measures of Peripheral Blood Dna Methylation and Prostate Cancer Risk in a Prospective Nested Case-Control Study. Prostate 2017; 77:471-478. [PMID: 28116812 DOI: 10.1002/pros.23289] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Accepted: 11/11/2016] [Indexed: 12/15/2022]
Abstract
BACKGROUND Global measures of peripheral blood DNA methylation have been associated with risk of some malignancies, including breast, bladder, and gastric cancer. Here, we examined genome-wide measures of peripheral blood DNA methylation in prostate cancer and its non-aggressive and aggressive disease forms. METHODS We used a matched, case-control study of 687 incident prostate cancer samples, nested within a larger prospective cohort study. DNA methylation was measured in pre-diagnostic, peripheral blood samples using the Illumina Infinium HM450K BeadChip. Genome-wide measures of DNA methylation were computed as the median M-value of all CpG sites and according to CpG site location and regulatory function. We used conditional logistic regression to test for associations between genome-wide measures of DNA methylation and risk of prostate cancer and its subtypes, and by time between blood draw and diagnosis. RESULTS We observed no associations between the genome-wide measure of DNA methylation based on all CpG sites and risk of prostate cancer or aggressive disease. Risk of non-aggressive disease was associated with higher methylation of CpG islands (OR = 0.80; 95%CI = 0.68-0.94), promoter regions (OR = 0.79; 95%CI = 0.66-0.93), and high density CpG regions (OR = 0.80; 95%CI = 0.68-0.94). Additionally, higher methylation of all CpGs (OR = 0.66; 95%CI = 0.48-0.89), CpG shores (OR = 0.62; 95%CI = 0.45-0.84), and regulatory regions (OR = 0.68; 95% CI = 0.51-0.91) was associated with a reduced risk of overall prostate cancer within 5 years of blood draw but not thereafter. CONCLUSIONS A reduced risk of overall prostate cancer within 5 years of blood draw and non-aggressive prostate cancer was associated with higher genome-wide methylation of peripheral blood DNA. While these data have no immediate clinical utility, with further work they may provide insight into the early events of prostate carcinogenesis. Prostate 77:471-478, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Liesel M FitzGerald
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, VIC, Australia
- Cancer, Genetics, and Immunology, Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
| | - Haroon Naeem
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - Enes Makalic
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - Daniel F Schmidt
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - James G Dowty
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - Jihoon E Joo
- Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, Parkville, VIC, Australia
| | - Chol-Hee Jung
- VLSCI Life Sciences Computation Centre, University of Melbourne, Carlton, VIC, Australia
| | - Julie K Bassett
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, VIC, Australia
| | | | - Jessica Chung
- VLSCI Life Sciences Computation Centre, University of Melbourne, Carlton, VIC, Australia
| | - Andrew Lonie
- VLSCI Life Sciences Computation Centre, University of Melbourne, Carlton, VIC, Australia
| | - Roger L Milne
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, VIC, Australia
- 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 Pathology, University of Melbourne, Parkville, VIC, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - Dallas R English
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, VIC, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - Gianluca Severi
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, VIC, Australia
- Université Paris-Saclay, University of Paris-Sud, UVSQ, CESP, INSERM, Villejuif, France
- Gustave Roussy, F-94805, Villejuif, France
- HuGeF, Human Genetics Foundation, Torino, Italy
| | - Laura Baglietto
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, VIC, Australia
- Université Paris-Saclay, University of Paris-Sud, UVSQ, CESP, INSERM, Villejuif, France
| | - John Pedersen
- TissuPath, Mount Waverley, Melbourne, VIC, Australia
| | - Graham G Giles
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, VIC, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - Melissa C Southey
- Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, Parkville, VIC, Australia
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409
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Persistent organic pollutants alter DNA methylation during human adipocyte differentiation. Toxicol In Vitro 2017; 40:79-87. [DOI: 10.1016/j.tiv.2016.12.011] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2016] [Revised: 10/17/2016] [Accepted: 12/18/2016] [Indexed: 12/02/2022]
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410
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Maschietto M, Bastos LC, Tahira AC, Bastos EP, Euclydes VLV, Brentani A, Fink G, de Baumont A, Felipe-Silva A, Francisco RPV, Gouveia G, Grisi SJFE, Escobar AMU, Moreira-Filho CA, Polanczyk GV, Miguel EC, Brentani H. Sex differences in DNA methylation of the cord blood are related to sex-bias psychiatric diseases. Sci Rep 2017; 7:44547. [PMID: 28303968 PMCID: PMC5355991 DOI: 10.1038/srep44547] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2016] [Accepted: 02/10/2017] [Indexed: 12/19/2022] Open
Abstract
Sex differences in the prevalence of psychiatric disorders are well documented, with exposure to stress during gestation differentially impacting females and males. We explored sex-specific DNA methylation in the cord blood of 39 females and 32 males born at term and with appropriate weight at birth regarding their potential connection to psychiatric outcomes. Mothers were interviewed to gather information about environmental factors (gestational exposure) that could interfere with the methylation profiles in the newborns. Bisulphite converted DNA was hybridized to Illumina HumanMethylation450 BeadChips. Excluding XYS probes, there were 2,332 differentially methylated CpG sites (DMSs) between sexes, which were enriched within brain modules of co-methylated CpGs during brain development and also differentially methylated in the brains of boys and girls. Genes associated with the DMSs were enriched for neurodevelopmental disorders, particularly for CpG sites found differentially methylated in brain tissue between patients with schizophrenia and controls. Moreover, the DMS had an overlap of 890 (38%) CpG sites with a cohort submitted to toxic exposition during gestation. This study supports the evidences that sex differences in DNA methylation of autosomes act as a primary driver of sex differences that are found in psychiatric outcomes.
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Affiliation(s)
- Mariana Maschietto
- Brazilian Biosciences National Laboratory (LNBio), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas, Brazil
| | | | | | | | | | - Alexandra Brentani
- Department of Pediatrics, University of São Paulo Medical School, SP, Brazil
| | - Günther Fink
- Department of Global Health and Population, Harvard School of Public Health, USA
| | | | | | | | - Gisele Gouveia
- Institute of Psychiatry, University of São Paulo Medical School, SP, Brazil
| | | | | | | | | | | | - Helena Brentani
- Institute of Psychiatry, University of São Paulo Medical School, SP, Brazil
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411
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Nim HT, Furtado MB, Ramialison M, Boyd SE. Combinatorial Ranking of Gene Sets to Predict Disease Relapse: The Retinoic Acid Pathway in Early Prostate Cancer. Front Oncol 2017; 7:30. [PMID: 28361034 PMCID: PMC5350134 DOI: 10.3389/fonc.2017.00030] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2016] [Accepted: 02/20/2017] [Indexed: 11/24/2022] Open
Abstract
Background Quantitative high-throughput data deposited in consortia such as International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) present opportunities and challenges for computational analyses. Methods We present a computational strategy to systematically rank and investigate a large number (210–220) of clinically testable gene sets, using combinatorial gene subset generation and disease-free survival (DFS) analyses. This approach integrates protein–protein interaction networks, gene expression, DNA methylation, and copy number data, in association with DFS profiles from patient clinical records. Results As a case study, we applied this pipeline to systematically analyze the role of ALDH1A2 in prostate cancer (PCa). We have previously found this gene to have multiple roles in disease and homeostasis, and here we investigate the role of the associated ALDH1A2 gene/protein networks in PCa, using our methodology in combination with PCa patient clinical profiles from ICGC and TCGA databases. Relationships between gene signatures and relapse were analyzed using Kaplan–Meier (KM) log-rank analysis and multivariable Cox regression. Relative expression versus pooled mean from diploid population was used for z-statistics calculation. Gene/protein interaction network analyses generated 11 core genes associated with ALDH1A2; combinatorial ranking of the power set of these core genes identified two gene sets (out of 211 − 1 = 2,047 combinations) with significant correlation with disease relapse (KM log rank p < 0.05). For the more significant of these two sets, referred to as the optimal gene set (OGS), patients have median survival 62.7 months with OGS alterations compared to >150 months without OGS alterations (p = 0.0248, hazard ratio = 2.213, 95% confidence interval = 1.1–4.098). Two genes comprising OGS (CYP26A1 and RDH10) are strongly associated with ALDH1A2 in the retinoic acid (RA) pathways, suggesting a major role of RA signaling in early PCa progression. Our pipeline complements human expertise in the search for prognostic biomarkers in large-scale datasets.
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Affiliation(s)
- Hieu T Nim
- Faculty of Information Technology, Monash University, Melbourne, VIC, Australia; Australian Regenerative Medicine Institute, Monash University, Melbourne, VIC, Australia
| | | | - Mirana Ramialison
- Australian Regenerative Medicine Institute, Monash University, Melbourne, VIC, Australia; EMBL - Australia Collaborating Group, Systems Biology Institute Australia, Monash University, Melbourne, VIC, Australia
| | - Sarah E Boyd
- Faculty of Information Technology, Monash University , Melbourne, VIC , Australia
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412
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de Vega WC, Herrera S, Vernon SD, McGowan PO. Epigenetic modifications and glucocorticoid sensitivity in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). BMC Med Genomics 2017; 10:11. [PMID: 28231836 PMCID: PMC5324230 DOI: 10.1186/s12920-017-0248-3] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2016] [Accepted: 02/18/2017] [Indexed: 01/28/2023] Open
Abstract
Background Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating idiopathic disease characterized by unexplained fatigue that fails to resolve with sufficient rest. Diagnosis is based on a list of symptoms and exclusion of other fatigue-related health conditions. Despite a heterogeneous patient population, immune and hypothalamic-pituitary-adrenal (HPA) axis function differences, such as enhanced negative feedback to glucocorticoids, are recurring findings in ME/CFS studies. Epigenetic modifications, such as CpG methylation, are known to regulate long-term phenotypic differences and previous work by our group found DNA methylome differences in ME/CFS, however the relationship between DNA methylome modifications, clinical and functional characteristics associated with ME/CFS has not been examined. Methods We examined the DNA methylome in peripheral blood mononuclear cells (PBMCs) of a larger cohort of female ME/CFS patients using the Illumina HumanMethylation450 BeadChip Array. In parallel to the DNA methylome analysis, we investigated in vitro glucocorticoid sensitivity differences by stimulating PBMCs with phytohaemagglutinin and suppressed growth with dexamethasone. We explored DNA methylation differences using bisulfite pyrosequencing and statistical permutation. Linear regression was implemented to discover epigenomic regions associated with self-reported quality of life and network analysis of gene ontology terms to biologically contextualize results. Results We detected 12,608 differentially methylated sites between ME/CFS patients and healthy controls predominantly localized to cellular metabolism genes, some of which were also related to self-reported quality of life health scores. Among ME/CFS patients, glucocorticoid sensitivity was associated with differential methylation at 13 loci. Conclusions Our results indicate DNA methylation modifications in cellular metabolism in ME/CFS despite a heterogeneous patient population, implicating these processes in immune and HPA axis dysfunction in ME/CFS. Modifications to epigenetic loci associated with differences in glucocorticoid sensitivity may be important as biomarkers for future clinical testing. Overall, these findings align with recent ME/CFS work that point towards impairment in cellular energy production in this patient population. Electronic supplementary material The online version of this article (doi:10.1186/s12920-017-0248-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Wilfred C de Vega
- Department of Biological Sciences, University of Toronto, Scarborough, 1265 Military Trail, Toronto, ON, M1C 1A4, Canada.,Department of Cell and Systems Biology, University of Toronto, Toronto, ON, Canada
| | - Santiago Herrera
- Department of Biological Sciences, University of Toronto, Scarborough, 1265 Military Trail, Toronto, ON, M1C 1A4, Canada.,Present affiliation: Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA
| | - Suzanne D Vernon
- Solve ME/CFS Initiative, Los Angeles, CA, USA.,Present affiliation: The Bateman Horne Center of Excellence, Salt Lake City, UT, USA
| | - Patrick O McGowan
- Department of Biological Sciences, University of Toronto, Scarborough, 1265 Military Trail, Toronto, ON, M1C 1A4, Canada. .,Department of Cell and Systems Biology, University of Toronto, Toronto, ON, Canada. .,Department of Psychology, University of Toronto, Toronto, ON, Canada. .,Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
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413
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Novakovic B, Evain-Brion D, Murthi P, Fournier T, Saffery R. Variable DAXX gene methylation is a common feature of placental trophoblast differentiation, preeclampsia, and response to hypoxia. FASEB J 2017; 31:2380-2392. [PMID: 28223336 DOI: 10.1096/fj.201601189rr] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2016] [Accepted: 01/30/2017] [Indexed: 12/13/2022]
Abstract
Placental functioning relies on the appropriate differentiation of progenitor villous cytotrophoblasts (CTBs) into extravillous cytotrophoblasts (EVCTs), including invasive EVCTs, and the multinucleated syncytiotrophoblast (ST) layer. This is accompanied by a general move away from a proliferative, immature phenotype. Genome-scale expression studies have provided valuable insight into genes that are associated with the shift to both an invasive EVCT and ST phenotype, whereas genome-scale DNA methylation analysis has shown that differentiation to ST involves widespread methylation shifts, which are counteracted by low oxygen. In the current study, we sought to identify DNA methylation variation that is associated with transition from CTB to ST in vitro and from a noninvasive to invasive EVCT phenotype after culture on Matrigel. Of the several hundred differentially methylated regions that were identified in each comparison, the majority showed a loss of methylation with differentiation. This included a large differentially methylated region (DMR) in the gene body of death domain-associated protein 6 (DAXX ), which lost methylation during both CTB syncytialization to ST and EVCT differentiation to invasive EVCT. Comparison to publicly available methylation array data identified the same DMR as among the most consistently differentially methylated genes in placental samples from preeclampsia pregnancies. Of interest, in vitro culture of CTB or ST in low oxygen increases methylation in the same region, which correlates with delayed differentiation. Analysis of combined epigenomics signatures confirmed DAXX DMR as a likely regulatory element, and direct gene expression analysis identified a positive association between methylation at this site and DAXX expression levels. The widespread dynamic nature of DAXX methylation in association with trophoblast differentiation and placenta-associated pathologies is consistent with an important role for this gene in proper placental development and function.-Novakovic, B., Evain-Brion, D., Murthi, P., Fournier, T., Saffery, R. Variable DAXX gene methylation is a common feature of placental trophoblast differentiation, preeclampsia, and response to hypoxia.
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Affiliation(s)
- Boris Novakovic
- Cancer and Disease Epigenetics, Murdoch Children's Research Institute, Parkville, Victoria, Australia.,Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
| | - Danièle Evain-Brion
- Institut National de la Santé et de la Recherche Médicale, Unité Mixte de Recherche S1139, Université Paris Descartes, Sorbonne Paris Cité, Paris, France.,PremUp Foundation, Paris, France
| | - Padma Murthi
- Department of Obstetrics and Gynaecology, University of Melbourne, Parkville, Victoria, Australia.,Department of Medicine, School of Clinical Sciences, Monash University, Clayton, Victoria, Australia
| | - Thiery Fournier
- Institut National de la Santé et de la Recherche Médicale, Unité Mixte de Recherche S1139, Université Paris Descartes, Sorbonne Paris Cité, Paris, France.,PremUp Foundation, Paris, France
| | - Richard Saffery
- Cancer and Disease Epigenetics, Murdoch Children's Research Institute, Parkville, Victoria, Australia; .,Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
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414
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Baharudin R, Ab Mutalib NS, Othman SN, Sagap I, Rose IM, Mohd Mokhtar N, Jamal R. Identification of Predictive DNA Methylation Biomarkers for Chemotherapy Response in Colorectal Cancer. Front Pharmacol 2017; 8:47. [PMID: 28243201 PMCID: PMC5303736 DOI: 10.3389/fphar.2017.00047] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2016] [Accepted: 01/20/2017] [Indexed: 12/19/2022] Open
Abstract
Resistance to 5-Fluorouracil (5-FU) is a major obstacle to the successful treatment of colorectal cancer (CRC) and posed an increased risk of recurrence. DNA methylation has been suggested as one of the underlying mechanisms for recurrent disease and its contribution to the development of drug resistance remains to be clarified. This study aimed to determine the methylation phenotype in CRC for identification of predictive markers for chemotherapy response. We performed DNA methylation profiling on 43 non-recurrent and five recurrent CRC patients using the Illumina Infinium HumanMethylation450 Beadchip assay. In addition, CRC cells with different genetic backgrounds, response to 5-FU and global methylation levels (HT29 and SW48) were treated with 5-FU and DNA methylation inhibitor 5-aza-2′-deoxycytidine (5-azadC). The singular and combined effects of these two drug classes on cell viability and global methylation profiles were investigated. Our genome-wide methylation study on the clinical specimens showed that recurrent CRCs exhibited higher methylation levels compared to non-recurrent CRCs. We identified 4787 significantly differentially methylated genes (P < 0.05); 3112 genes were hyper- while 1675 genes were hypomethylated in the recurrent group compared to the non-recurrent. Fifty eight and 47 of the significantly hypermethylated and hypomethylated genes have an absolute recurrent/non-recurrent methylation difference of ≥20%. Most of the hypermethylated genes were involved in the MAPK signaling pathway which is a key regulator for apoptosis while the hypomethylated genes were involved in the PI3K-AKT signaling pathway and proliferation process. We also demonstrate that 5-azadC treatment enhanced response to 5-FU which resulted in significant growth inhibition compared to 5-FU alone in hypermethylated cell lines SW48. In conclusion, we found the evidence of five potentially biologically important genes in recurrent CRCs that could possibly serve as a new potential therapeutic targets for patients with chemoresistance. We postulate that aberrant methylation of CCNEI, CCNDBP1, PON3, DDX43, and CHL1 in CRC might be associated with the recurrence of CRC and 5-azadC-mediated restoration of 5-FU sensitivity is mediated at least in part by MAPK signaling pathway.
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Affiliation(s)
- Rashidah Baharudin
- UKM Medical Molecular Biology Institute, Universiti Kebangsaan Malaysia Kuala Lumpur, Malaysia
| | | | - Sri N Othman
- UKM Medical Molecular Biology Institute, Universiti Kebangsaan Malaysia Kuala Lumpur, Malaysia
| | - Ismail Sagap
- Department of Surgery, Faculty of Medicine, Universiti Kebangsaan Malaysia Kuala Lumpur, Malaysia
| | - Isa M Rose
- Department of Clinical Oral Biology, Faculty of Dentistry, Universiti Kebangsaan Malaysia Kuala Lumpur, Malaysia
| | - Norfilza Mohd Mokhtar
- Department of Physiology, Faculty of Medicine, Universiti Kebangsaan Malaysia Kuala Lumpur, Malaysia
| | - Rahman Jamal
- UKM Medical Molecular Biology Institute, Universiti Kebangsaan Malaysia Kuala Lumpur, Malaysia
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415
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Wiencke JK, Koestler DC, Salas LA, Wiemels JL, Roy RP, Hansen HM, Rice T, McCoy LS, Bracci PM, Molinaro AM, Kelsey KT, Wrensch MR, Christensen BC. Immunomethylomic approach to explore the blood neutrophil lymphocyte ratio (NLR) in glioma survival. Clin Epigenetics 2017; 9:10. [PMID: 28184256 PMCID: PMC5288996 DOI: 10.1186/s13148-017-0316-8] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Accepted: 01/19/2017] [Indexed: 01/04/2023] Open
Abstract
Background Differentially methylated regions (DMRs) within DNA isolated from whole blood can be used to estimate the proportions of circulating leukocyte subtypes. We use the term “immunomethylomics” to describe the application of these immune lineage DMRs to studying leukocyte profiles. Here, we applied this approach to peripheral blood DNA from 72 glioma patients with molecularly defined brain tumors, representing common patient groups with defined characteristic survival times and risk factors. We first estimated the proportions of leukocyte subtypes in samples using deconvolution algorithms with reference DMR libraries from isolated leukocyte populations and Illumina 450K DNA methylation data. Then, we calculated the neutrophil to lymphocyte ratio (NLR) using methylation-derived cell composition estimates (mdNLR). The NLR is considered an indicator of immunosuppressive cells in cancer patients. Results Elevated mdNLR scores were observed in glioma patients compared to mdNLR values of published controls. Significantly decreased survival times were associated with mdNLR ≥ 4.0 in Cox proportional hazards models adjusted for age, gender, tumor grade, and molecular subtype (HR 2.02, 95% CI, 1.11–3.69). We also identified five myeloid-related CpGs that were highly correlated with the mdNLR (adjusted R2 ≥ 0.80). Each of the five myeloid CpG loci was associated with survival when adjusted for the above covariates and offer a simplified approach for utilizing fresh or archived peripheral blood samples for interrogating a very small number of methylation markers to estimate myeloid immune influences in glioma survival. Conclusions The mdNLR (based on DNA methylation) is a novel candidate methylation biomarker that represents immunosuppressive myeloid cells within the blood of glioma patients with potential application in clinical trials and future epidemiologic studies of glioma risk and survival. Electronic supplementary material The online version of this article (doi:10.1186/s13148-017-0316-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- John K Wiencke
- Department of Neurological Surgery, University of California San Francisco, 1450 3rd Street, San Francisco, CA 94158-0520 USA
| | - Devin C Koestler
- Department of Biostatistics, University of Kansas Medical Center, Kansas City, KS 66160 USA
| | - Lucas A Salas
- Computational Biology Core, University of California San Francisco, San Francisco, CA 94158 USA
| | - Joseph L Wiemels
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158 USA
| | - Ritu P Roy
- Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA 94158 USA.,Computational Biology Core, University of California San Francisco, San Francisco, CA 94158 USA
| | - Helen M Hansen
- Department of Neurological Surgery, University of California San Francisco, 1450 3rd Street, San Francisco, CA 94158-0520 USA
| | - Terri Rice
- Department of Neurological Surgery, University of California San Francisco, 1450 3rd Street, San Francisco, CA 94158-0520 USA
| | - Lucie S McCoy
- Department of Neurological Surgery, University of California San Francisco, 1450 3rd Street, San Francisco, CA 94158-0520 USA
| | - Paige M Bracci
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158 USA
| | - Annette M Molinaro
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158 USA
| | - Karl T Kelsey
- Department of Epidemiology, Department of Pathology and Laboratory Medicine, Brown University, Providence, RI 02912 USA
| | - Margaret R Wrensch
- Department of Neurological Surgery, University of California San Francisco, 1450 3rd Street, San Francisco, CA 94158-0520 USA
| | - Brock C Christensen
- Departments of Epidemiology, Pharmacology & Toxicology, and Community and Family Medicine, Geisel School of Medicine at Dartmouth College, Lebanon, NH 03756 USA
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416
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Chatterton Z, Hartley BJ, Seok MH, Mendelev N, Chen S, Milekic M, Rosoklija G, Stankov A, Trencevsja-Ivanovska I, Brennand K, Ge Y, Dwork AJ, Haghighi F. In utero exposure to maternal smoking is associated with DNA methylation alterations and reduced neuronal content in the developing fetal brain. Epigenetics Chromatin 2017; 10:4. [PMID: 28149327 PMCID: PMC5270321 DOI: 10.1186/s13072-017-0111-y] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2016] [Accepted: 01/09/2017] [Indexed: 12/31/2022] Open
Abstract
Background Intrauterine exposure to maternal smoking is linked to impaired executive function and behavioral problems in the offspring. Maternal smoking is associated with reduced fetal brain growth and smaller volume of cortical gray matter in childhood, indicating that prenatal exposure to tobacco may impact cortical development and manifest as behavioral problems. Cellular development is mediated by changes in epigenetic modifications such as DNA methylation, which can be affected by exposure to tobacco. Results In this study, we sought to ascertain how maternal smoking during pregnancy affects global DNA methylation profiles of the developing dorsolateral prefrontal cortex (DLPFC) during the second trimester of gestation. When DLPFC methylation profiles (assayed via Illumina, HM450) of smoking-exposed and unexposed fetuses were compared, no differentially methylated regions (DMRs) passed the false discovery correction (FDR ≤ 0.05). However, the most significant DMRs were hypomethylated CpG Islands within the promoter regions of GNA15 and SDHAP3 of smoking-exposed fetuses. Interestingly, the developmental up-regulation of SDHAP3 mRNA was delayed in smoking-exposed fetuses. Interaction analysis between gestational age and smoking exposure identified significant DMRs annotated to SYCE3, C21orf56/LSS, SPAG1 and RNU12/POLDIP3 that passed FDR. Furthermore, utilizing established methods to estimate cell proportions by DNA methylation, we found that exposed DLPFC samples contained a lower proportion of neurons in samples from fetuses exposed to maternal smoking. We also show through in vitro experiments that nicotine impedes the differentiation of neurons independent of cell death. Conclusions We found evidence that intrauterine smoking exposure alters the developmental patterning of DNA methylation and gene expression and is associated with reduced mature neuronal content, effects that are likely driven by nicotine. Electronic supplementary material The online version of this article (doi:10.1186/s13072-017-0111-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Zac Chatterton
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029 USA.,Department of Neuroscience, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, Floor 10, Room 10-70D, New York, NY 10029 USA.,Medical Epigenetics, James J. Peters VA Medical Center, Bronx, NY 10468 USA
| | - Brigham J Hartley
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029 USA.,Department of Neuroscience, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, Floor 10, Room 10-70D, New York, NY 10029 USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029 USA
| | - Man-Ho Seok
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029 USA.,Department of Neuroscience, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, Floor 10, Room 10-70D, New York, NY 10029 USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029 USA
| | - Natalia Mendelev
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029 USA.,Department of Neuroscience, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, Floor 10, Room 10-70D, New York, NY 10029 USA.,Medical Epigenetics, James J. Peters VA Medical Center, Bronx, NY 10468 USA
| | - Sean Chen
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029 USA.,Department of Neuroscience, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, Floor 10, Room 10-70D, New York, NY 10029 USA.,Medical Epigenetics, James J. Peters VA Medical Center, Bronx, NY 10468 USA
| | - Maria Milekic
- Department of Psychiatry, Columbia University, New York, NY 10032 USA
| | - Gorazd Rosoklija
- Department of Psychiatry, Columbia University, New York, NY 10032 USA.,Macedonian Academy of Sciences and Arts, Skopje, Macedonia.,School of Medicine, Skopje, Macedonia
| | | | | | - Kristen Brennand
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029 USA.,Department of Neuroscience, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, Floor 10, Room 10-70D, New York, NY 10029 USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029 USA
| | - Yongchao Ge
- Department of Neurology, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029 USA
| | - Andrew J Dwork
- Department of Psychiatry, Columbia University, New York, NY 10032 USA.,Department of Pathology and Cell Biology, Columbia University, New York, NY 10032 USA.,Macedonian Academy of Sciences and Arts, Skopje, Macedonia
| | - Fatemeh Haghighi
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY 10029 USA.,Department of Neuroscience, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, Floor 10, Room 10-70D, New York, NY 10029 USA.,Medical Epigenetics, James J. Peters VA Medical Center, Bronx, NY 10468 USA
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417
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Ecker S, Chen L, Pancaldi V, Bagger FO, Fernández JM, Carrillo de Santa Pau E, Juan D, Mann AL, Watt S, Casale FP, Sidiropoulos N, Rapin N, Merkel A, Stunnenberg HG, Stegle O, Frontini M, Downes K, Pastinen T, Kuijpers TW, Rico D, Valencia A, Beck S, Soranzo N, Paul DS. Genome-wide analysis of differential transcriptional and epigenetic variability across human immune cell types. Genome Biol 2017; 18:18. [PMID: 28126036 PMCID: PMC5270224 DOI: 10.1186/s13059-017-1156-8] [Citation(s) in RCA: 78] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Accepted: 01/17/2017] [Indexed: 12/11/2022] Open
Abstract
Background A healthy immune system requires immune cells that adapt rapidly to environmental challenges. This phenotypic plasticity can be mediated by transcriptional and epigenetic variability. Results We apply a novel analytical approach to measure and compare transcriptional and epigenetic variability genome-wide across CD14+CD16− monocytes, CD66b+CD16+ neutrophils, and CD4+CD45RA+ naïve T cells from the same 125 healthy individuals. We discover substantially increased variability in neutrophils compared to monocytes and T cells. In neutrophils, genes with hypervariable expression are found to be implicated in key immune pathways and are associated with cellular properties and environmental exposure. We also observe increased sex-specific gene expression differences in neutrophils. Neutrophil-specific DNA methylation hypervariable sites are enriched at dynamic chromatin regions and active enhancers. Conclusions Our data highlight the importance of transcriptional and epigenetic variability for the key role of neutrophils as the first responders to inflammatory stimuli. We provide a resource to enable further functional studies into the plasticity of immune cells, which can be accessed from: http://blueprint-dev.bioinfo.cnio.es/WP10/hypervariability. Electronic supplementary material The online version of this article (doi:10.1186/s13059-017-1156-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Simone Ecker
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro 3, 28029, Madrid, Spain. .,UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT, UK.
| | - Lu Chen
- Department of Human Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1HH, UK.,Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge, Hinxton, UK
| | - Vera Pancaldi
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro 3, 28029, Madrid, Spain
| | - Frederik O Bagger
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge, Hinxton, UK.,National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Long Road, Cambridge, CB2 0PT, UK.,European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - José María Fernández
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro 3, 28029, Madrid, Spain
| | - Enrique Carrillo de Santa Pau
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro 3, 28029, Madrid, Spain
| | - David Juan
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro 3, 28029, Madrid, Spain
| | - Alice L Mann
- Department of Human Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1HH, UK
| | - Stephen Watt
- Department of Human Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1HH, UK
| | - Francesco Paolo Casale
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Nikos Sidiropoulos
- The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark.,Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark.,The Bioinformatics Centre, Department of Biology, Faculty of Natural Sciences, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
| | - Nicolas Rapin
- The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark.,Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark.,The Bioinformatics Centre, Department of Biology, Faculty of Natural Sciences, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
| | - Angelika Merkel
- National Center for Genomic Analysis (CNAG), Center for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Carrer Baldiri i Reixac 4, 08028, Barcelona, Spain
| | | | - Hendrik G Stunnenberg
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen, 6525GA, The Netherlands
| | - Oliver Stegle
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Mattia Frontini
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge, Hinxton, UK.,National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Long Road, Cambridge, CB2 0PT, UK.,British Heart Foundation Centre of Excellence, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge, CB2 0PT, UK
| | - Kate Downes
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge, Hinxton, UK.,National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Long Road, Cambridge, CB2 0PT, UK
| | - Tomi Pastinen
- Department of Human Genetics, McGill University, 740 Dr. Penfield, Montreal, H3A 0G1, Canada
| | - Taco W Kuijpers
- Blood Cell Research, Sanquin Research and Landsteiner Laboratory, Plesmanlaan 125, Amsterdam, 1066CX, The Netherlands.,Emma Children's Hospital, Academic Medical Center (AMC), University of Amsterdam, Location H7-230, Meibergdreef 9, Amsterdam, 1105AX, The Netherlands
| | - Daniel Rico
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro 3, 28029, Madrid, Spain.,Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, NE2 4HH, UK
| | - Alfonso Valencia
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro 3, 28029, Madrid, Spain
| | - Stephan Beck
- UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT, UK
| | - Nicole Soranzo
- Department of Human Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1HH, UK. .,Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge, Hinxton, UK.
| | - Dirk S Paul
- UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT, UK. .,Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Wort's Causeway, Cambridge, CB1 8RN, UK.
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418
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META2: Intercellular DNA Methylation Pairwise Annotation and Integrative Analysis. BIOMED RESEARCH INTERNATIONAL 2017; 2016:1597489. [PMID: 28116291 PMCID: PMC5223072 DOI: 10.1155/2016/1597489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/17/2016] [Accepted: 12/12/2016] [Indexed: 11/17/2022]
Abstract
Genome-wide deciphering intercellular differential DNA methylation as well as its roles in transcriptional regulation remains elusive in cancer epigenetics. Here we developed a toolkit META2 for DNA methylation annotation and analysis, which aims to perform integrative analysis on differentially methylated loci and regions through deep mining and statistical comparison methods. META2 contains multiple versatile functions for investigating and annotating DNA methylation profiles. Benchmarked with T-47D cell, we interrogated the association within differentially methylated CpG (DMC) and region (DMR) candidate count and region length and identified major transition zones as clues for inferring statistically significant DMRs; together we validated those DMRs with the functional annotation. Thus META2 can provide a comprehensive analysis approach for epigenetic research and clinical study.
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419
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Morin A, Laviolette M, Pastinen T, Boulet LP, Laprise C. Combining omics data to identify genes associated with allergic rhinitis. Clin Epigenetics 2017; 9:3. [PMID: 28149331 PMCID: PMC5270349 DOI: 10.1186/s13148-017-0310-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2016] [Accepted: 01/03/2017] [Indexed: 01/26/2023] Open
Abstract
Allergic rhinitis is a common chronic disorder characterized by immunoglobulin E-mediated inflammation. To identify new genes associated with this trait, we performed genome- and epigenome-wide association studies and linked marginally significant CpGs located in genes or its promoter and SNPs located 1 Mb from the CpGs, by identifying cis methylation quantitative trait loci (mQTL). This approach relies on functional cellular aspects rather than stringent statistical correction. We were able to identify one gene with significant cis-mQTL for allergic rhinitis, caudal-type homeobox 1 (CDX1). We also identified 11 genes with marginally significant cis-mQTLs (p < 0.05) including one with both allergic rhinitis with or without asthma (RNF39). Moreover, most SNPs identified were not located closest to the gene they were linked to through cis-mQTLs counting the one linked to CDX1 located in a gene previously associated with asthma and atopic dermatitis. By combining omics data, we were able to identify new genes associated with allergic rhinitis and better assess the genes linked to associated SNPs.
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Affiliation(s)
- Andréanne Morin
- Department of Human Genetics, McGill University and Genome Quebec Innovation Centre, 740 Dr. Penfield Avenue, Montréal, Québec H3A 1A5 Canada.,Département des sciences fondamentales, Université du Québec à Chicoutimi, 555 boulevard de l'Université, Saguenay, Québec G7H 2B1 Canada
| | - Michel Laviolette
- Institut Universitaire de Cardiologie et de Pneumologie de Québec, Université Laval, 2725 chemin Sainte-Foy, Québec, Québec G1V 4G5 Canada
| | - Tomi Pastinen
- Department of Human Genetics, McGill University and Genome Quebec Innovation Centre, 740 Dr. Penfield Avenue, Montréal, Québec H3A 1A5 Canada
| | - Louis-Philippe Boulet
- Institut Universitaire de Cardiologie et de Pneumologie de Québec, Université Laval, 2725 chemin Sainte-Foy, Québec, Québec G1V 4G5 Canada
| | - Catherine Laprise
- Département des sciences fondamentales, Université du Québec à Chicoutimi, 555 boulevard de l'Université, Saguenay, Québec G7H 2B1 Canada
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420
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Interleukin-2 receptor-α proximal promoter hypomethylation is associated with multiple sclerosis. Genes Immun 2017; 18:59-66. [PMID: 28077880 DOI: 10.1038/gene.2016.50] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2016] [Revised: 11/23/2016] [Accepted: 11/28/2016] [Indexed: 12/23/2022]
Abstract
Genetic studies have demonstrated association between single-nucleotide polymorphisms within the IL2RA (interleukin-2 receptor α-subunit) gene and risk of developing multiple sclerosis (MS); however, these variants do not have obvious functional consequences. DNA methylation is a source of genetic variation that could impact on autoimmune disease risk. We investigated DNA methylation of the IL2RA promoter in genomic DNA obtained from peripheral blood mononuclear cells and neural tissue using matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry. A differential methylation profile of IL2RA was identified, suggesting that IL2RA expression was regulated by DNA methylation. We extended our analysis of DNA methylation to peripheral blood mononuclear cell (PBMC) of MS cases and controls using MALDI-TOF and Illumina HumanMethylation450 arrays. Analyses of CpG sites within the proximal promoter of IL2RA in PBMC showed no differences between MS cases and controls despite an increase in IL2RA expression. In contrast, we inferred significant DNA methylation differences specific to particular leukocyte subtypes in MS cases compared with controls by deconvolution of the array data. The decrease in methylation in patients correlated with an increase in IL2RA expression in T cells from MS cases in comparison with controls. Our data suggest that differential methylation of the IL2RA promoter in T cells could be an important pathogenic mechanism in MS.
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421
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Rahmani E, Shenhav L, Schweiger R, Yousefi P, Huen K, Eskenazi B, Eng C, Huntsman S, Hu D, Galanter J, Oh SS, Waldenberger M, Strauch K, Grallert H, Meitinger T, Gieger C, Holland N, Burchard EG, Zaitlen N, Halperin E. Genome-wide methylation data mirror ancestry information. Epigenetics Chromatin 2017; 10:1. [PMID: 28149326 PMCID: PMC5267476 DOI: 10.1186/s13072-016-0108-y] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Accepted: 12/14/2016] [Indexed: 11/15/2022] Open
Abstract
Background Genetic data are known to harbor information about human demographics, and genotyping data are commonly used for capturing ancestry information by leveraging genome-wide differences between populations. In contrast, it is not clear to what extent population structure is captured by whole-genome DNA methylation data. Results We demonstrate, using three large-cohort 450K methylation array data sets, that ancestry information signal is mirrored in genome-wide DNA methylation data and that it can be further isolated more effectively by leveraging the correlation structure of CpGs with cis-located SNPs. Based on these insights, we propose a method, EPISTRUCTURE, for the inference of ancestry from methylation data, without the need for genotype data. Conclusions EPISTRUCTURE can be used to infer ancestry information of individuals based on their methylation data in the absence of corresponding genetic data. Although genetic data are often collected in epigenetic studies of large cohorts, these are typically not made publicly available, making the application of EPISTRUCTURE especially useful for anyone working on public data. Implementation of EPISTRUCTURE is available in GLINT, our recently released toolset for DNA methylation analysis at: http://glint-epigenetics.readthedocs.io. Electronic supplementary material The online version of this article (doi:10.1186/s13072-016-0108-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Elior Rahmani
- Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
| | - Liat Shenhav
- Department of Statistics, Tel Aviv University, Tel Aviv, Israel
| | - Regev Schweiger
- Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
| | - Paul Yousefi
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley, Berkeley, CA USA
| | - Karen Huen
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley, Berkeley, CA USA
| | - Brenda Eskenazi
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley, Berkeley, CA USA
| | - Celeste Eng
- Department of Medicine, University of California San Francisco, San Francisco, CA USA
| | - Scott Huntsman
- Department of Medicine, University of California San Francisco, San Francisco, CA USA
| | - Donglei Hu
- Department of Medicine, University of California San Francisco, San Francisco, CA USA
| | - Joshua Galanter
- Department of Medicine, University of California San Francisco, San Francisco, CA USA.,Department of Bioengineering and Therapeutic Science, University of California San Francisco, San Francisco, CA USA
| | - Sam S Oh
- Department of Medicine, University of California San Francisco, San Francisco, CA USA
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany.,Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany.,Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany.,Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, Munich, Germany.,Institute of Human Genetics, Technische Universität München, Munich, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany.,Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Nina Holland
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley, Berkeley, CA USA
| | - Esteban G Burchard
- Department of Medicine, University of California San Francisco, San Francisco, CA USA.,Department of Bioengineering and Therapeutic Science, University of California San Francisco, San Francisco, CA USA
| | - Noah Zaitlen
- Department of Medicine, University of California San Francisco, San Francisco, CA USA
| | - Eran Halperin
- Department of Computer Science, University of California Los Angeles, Los Angeles, CA USA.,Department of Anesthesiology and Perioperative Medicine, University of California Los Angeles, Los Angeles, CA USA
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422
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Xu Z, Langie SAS, De Boever P, Taylor JA, Niu L. RELIC: a novel dye-bias correction method for Illumina Methylation BeadChip. BMC Genomics 2017; 18:4. [PMID: 28049437 PMCID: PMC5209853 DOI: 10.1186/s12864-016-3426-3] [Citation(s) in RCA: 87] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2016] [Accepted: 12/15/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The Illumina Infinium HumanMethylation450 BeadChip and its successor, Infinium MethylationEPIC BeadChip, have been extensively utilized in epigenome-wide association studies. Both arrays use two fluorescent dyes (Cy3-green/Cy5-red) to measure methylation level at CpG sites. However, performance difference between dyes can result in biased estimates of methylation levels. RESULTS Here we describe a novel method, called REgression on Logarithm of Internal Control probes (RELIC) to correct for dye bias on whole array by utilizing the intensity values of paired internal control probes that monitor the two color channels. We evaluate the method in several datasets against other widely used dye-bias correction methods. Results on data quality improvement showed that RELIC correction statistically significantly outperforms alternative dye-bias correction methods. We incorporated the method into the R package ENmix, which is freely available from the Bioconductor website ( https://www.bioconductor.org/packages/release/bioc/html/ENmix.html ). CONCLUSIONS RELIC is an efficient and robust method to correct for dye-bias in Illumina Methylation BeadChip data. It outperforms other alternative methods and conveniently implemented in R package ENmix to facilitate DNA methylation studies.
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Affiliation(s)
- Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Sabine A S Langie
- Environmental Risk and Health unit, Flemish Institute for Technological Research (VITO), Mol, Belgium.,Faculty of Sciences, Hasselt University, Diepenbeek, Belgium
| | - Patrick De Boever
- Environmental Risk and Health unit, Flemish Institute for Technological Research (VITO), Mol, Belgium.,Faculty of Sciences, Hasselt University, Diepenbeek, Belgium
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA.,Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Liang Niu
- Division of Biostatistics and Bioinformatics, Department of Environmental Health, College of Medicine, University of Cincinnati, Cincinnati, OH, USA.
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423
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Zhao S, Geybels MS, Leonardson A, Rubicz R, Kolb S, Yan Q, Klotzle B, Bibikova M, Hurtado-Coll A, Troyer D, Lance R, Lin DW, Wright JL, Ostrander EA, Fan JB, Feng Z, Stanford JL. Epigenome-Wide Tumor DNA Methylation Profiling Identifies Novel Prognostic Biomarkers of Metastatic-Lethal Progression in Men Diagnosed with Clinically Localized Prostate Cancer. Clin Cancer Res 2017; 23:311-319. [PMID: 27358489 PMCID: PMC5199634 DOI: 10.1158/1078-0432.ccr-16-0549] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2016] [Revised: 06/08/2016] [Accepted: 06/11/2016] [Indexed: 01/22/2023]
Abstract
PURPOSE Aside from Gleason sum, few factors accurately identify the subset of prostate cancer patients at high risk for metastatic progression. We hypothesized that epigenetic alterations could distinguish prostate tumors with life-threatening potential. EXPERIMENTAL DESIGN Epigenome-wide DNA methylation profiling was performed in surgically resected primary tumor tissues from a population-based (n = 430) and a replication (n = 80) cohort of prostate cancer patients followed prospectively for at least 5 years. Metastasis was confirmed by positive bone scan, MRI, CT, or biopsy, and death certificates confirmed cause of death. AUC, partial AUC (pAUC, 95% specificity), and P value criteria were used to select differentially methylated CpG sites that robustly stratify patients with metastatic-lethal from nonrecurrent tumors, and which were complementary to Gleason sum. RESULTS Forty-two CpG biomarkers stratified patients with metastatic-lethal versus nonrecurrent prostate cancer in the discovery cohort, and eight of these CpGs replicated in the validation cohort based on a significant (P < 0.05) AUC (range, 0.66-0.75) or pAUC (range, 0.007-0.009). The biomarkers that improved discrimination of patients with metastatic-lethal prostate cancer include CpGs in five genes (ALKBH5, ATP11A, FHAD1, KLHL8, and PI15) and three intergenic regions. In the validation dataset, the AUC for Gleason sum alone (0.82) significantly increased with the addition of four individual CpGs (range, 0.86-0.89; all P <0.05). CONCLUSIONS Eight differentially methylated CpGs that distinguish patients with metastatic-lethal from nonrecurrent tumors were validated. These novel epigenetic biomarkers warrant further investigation as they may improve prognostic classification of patients with clinically localized prostate cancer and provide new insights on tumor aggressiveness. Clin Cancer Res; 23(1); 311-9. ©2016 AACR.
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Affiliation(s)
- Shanshan Zhao
- National Institute of Environmental Health Sciences, Biostatistics and Computational Biology Branch, Research Triangle Park, Durham, North Carolina
| | - Milan S Geybels
- Division of Public Health Sciences, Fred Hutchison Cancer Research Center, Seattle, Washington
- Department of Epidemiology, GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, the Netherlands
| | - Amy Leonardson
- Division of Public Health Sciences, Fred Hutchison Cancer Research Center, Seattle, Washington
| | - Rohina Rubicz
- Division of Public Health Sciences, Fred Hutchison Cancer Research Center, Seattle, Washington
| | - Suzanne Kolb
- Division of Public Health Sciences, Fred Hutchison Cancer Research Center, Seattle, Washington
| | - Qingxiang Yan
- MD Anderson Cancer Center, Department of Biostatistics, Houston, Texas
| | | | | | - Antonio Hurtado-Coll
- Department of Urologic Sciences, University of British Columbia, and the Prostate Center, Vancouver General Hospital, Vancouver, Canada
| | - Dean Troyer
- Departments of Pathology, Microbiology, and Molecular Cell Biology, Eastern Virginia Medical School, Norfolk, Virginia
| | - Raymond Lance
- Department of Urology, Eastern Virginia Medical School, Norfolk, Virginia
| | - Daniel W Lin
- Division of Public Health Sciences, Fred Hutchison Cancer Research Center, Seattle, Washington
- Department of Urology, University of Washington School of Medicine, Seattle, Washington
| | - Jonathan L Wright
- Division of Public Health Sciences, Fred Hutchison Cancer Research Center, Seattle, Washington
- Department of Urology, University of Washington School of Medicine, Seattle, Washington
| | - Elaine A Ostrander
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland
| | | | - Ziding Feng
- MD Anderson Cancer Center, Department of Biostatistics, Houston, Texas
| | - Janet L Stanford
- Division of Public Health Sciences, Fred Hutchison Cancer Research Center, Seattle, Washington.
- Department of Epidemiology, University of Washington School of Public Health, Seattle, Washington
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424
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Maschietto M, Rodrigues TC, Kashiwabara AY, de Araujo ÉSS, Marques Aguiar TF, da Costa CML, da Cunha IW, Dos Reis Vasques L, Cypriano M, Brentani H, de Toledo SRC, Pearson PL, Carraro DM, Rosenberg C, Krepischi ACV. DNA methylation landscape of hepatoblastomas reveals arrest at early stages of liver differentiation and cancer-related alterations. Oncotarget 2016; 8:97871-97889. [PMID: 29228658 PMCID: PMC5716698 DOI: 10.18632/oncotarget.14208] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2016] [Accepted: 12/05/2016] [Indexed: 12/18/2022] Open
Abstract
Hepatoblastomas are uncommon embryonal liver tumors accounting for approximately 80% of childhood hepatic cancer. We hypothesized that epigenetic changes, including DNA methylation, could be relevant to hepatoblastoma onset. The methylomes of eight matched hepatoblastomas and non-tumoral liver tissues were characterized, and data were validated in an independent group (11 hepatoblastomas). In comparison to differentiated livers, hepatoblastomas exhibited a widespread and non-stochastic pattern of global low-level hypomethylation. The analysis revealed 1,359 differentially methylated CpG sites (DMSs) between hepatoblastomas and control livers, which are associated with 765 genes. Hypomethylation was detected in hepatoblastomas for ~58% of the DMSs with enrichment at intergenic sites, and most of the hypermethylated CpGs were located in CpG islands. Functional analyses revealed enrichment in signaling pathways involved in metabolism, negative regulation of cell differentiation, liver development, cancer, and Wnt signaling pathway. Strikingly, an important overlap was observed between the 1,359 DMSs and the CpG sites reported to exhibit methylation changes through liver development (p<0.0001), with similar patterns of methylation in both hepatoblastomas and fetal livers compared to adult livers. Overall, our results suggest an arrest at early stages of liver cell differentiation, in line with the hypothesis that hepatoblastoma ontogeny involves the disruption of liver development. This genome-wide methylation dysfunction, taken together with a relatively small number of driver genetic mutations reported for both adult and pediatric liver cancers, shed light on the relevance of epigenetic mechanisms for hepatic tumorigenesis.
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Affiliation(s)
- Mariana Maschietto
- Brazilian Biosciences National Laboratory (LNBio), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas, Brazil
| | - Tatiane Cristina Rodrigues
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, São Paulo, Brazil
| | | | | | | | | | | | - Luciana Dos Reis Vasques
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, São Paulo, Brazil
| | - Monica Cypriano
- Department of Pediatrics, Pediatric Oncology Institute (GRAACC), Federal University of São Paulo, São Paulo, Brazil
| | - Helena Brentani
- Department of Psychiatry, School of Medicine, University of São Paulo, São Paulo, Brazil
| | | | - Peter Lees Pearson
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, São Paulo, Brazil
| | - Dirce Maria Carraro
- International Research Center, A. C. Camargo Cancer Center, São Paulo, Brazil
| | - Carla Rosenberg
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, São Paulo, Brazil
| | - Ana C V Krepischi
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, São Paulo, Brazil
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425
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Koestler DC, Usset J, Christensen BC, Marsit CJ, Karagas MR, Kelsey KT, Wiencke JK. DNA Methylation-Derived Neutrophil-to-Lymphocyte Ratio: An Epigenetic Tool to Explore Cancer Inflammation and Outcomes. Cancer Epidemiol Biomarkers Prev 2016; 26:328-338. [PMID: 27965295 DOI: 10.1158/1055-9965.epi-16-0461] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2016] [Revised: 09/27/2016] [Accepted: 10/19/2016] [Indexed: 01/04/2023] Open
Abstract
Background: The peripheral blood neutrophil-to-lymphocyte ratio (NLR) is a cytologic marker of both inflammation and poor outcomes in patients with cancer. DNA methylation is a key element of the epigenetic program defining different leukocyte subtypes and may provide an alternative to cytology in assessing leukocyte profiles. Our aim was to create a bioinformatic tool to estimate NLR using DNA methylation, and to assess its diagnostic and prognostic performance in human populations.Methods: We developed a DNA methylation-derived NLR (mdNLR) index based on normal isolated leukocyte methylation libraries and established cell-mixture deconvolution algorithms. The method was applied to cancer case-control studies of the bladder, head and neck, ovary, and breast, as well as publicly available data on cancer-free subjects.Results: Across cancer studies, mdNLR scores were either elevated in cases relative to controls, or associated with increased hazard of death. High mdNLR values (>5) were strong indicators of poor survival. In addition, mdNLR scores were elevated in males, in nonHispanic white versus Hispanic ethnicity, and increased with age. We also observed a significant interaction between cigarette smoking history and mdNLR on cancer survival.Conclusions: These results mean that our current understanding of mature leukocyte methylomes is sufficient to allow researchers and clinicians to apply epigenetically based analyses of NLR in clinical and epidemiologic studies of cancer risk and survival.Impact: As cytologic measurements of NLR are not always possible (i.e., archival blood), mdNLR, which is computed from DNA methylation signatures alone, has the potential to expand the scope of epigenome-wide association studies. Cancer Epidemiol Biomarkers Prev; 26(3); 328-38. ©2016 AACR.
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Affiliation(s)
- Devin C Koestler
- Department of Biostatistics, University of Kansas Medical Center, Kansas City, Kansas.
| | - Joseph Usset
- Department of Biostatistics, University of Kansas Medical Center, Kansas City, Kansas
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine at Dartmouth College, Lebanon New Hampshire.,Department of Pharmacology and Toxicology, Geisel School of Medicine at Dartmouth College, New Hampshire.,Department of Community and Family Medicine, Geisel School of Medicine at Dartmouth College, Lebanon New Hampshire
| | - Carmen J Marsit
- Department of Epidemiology, Geisel School of Medicine at Dartmouth College, Lebanon New Hampshire.,Department of Pharmacology and Toxicology, Geisel School of Medicine at Dartmouth College, New Hampshire.,Department of Community and Family Medicine, Geisel School of Medicine at Dartmouth College, Lebanon New Hampshire
| | - Margaret R Karagas
- Department of Epidemiology, Geisel School of Medicine at Dartmouth College, Lebanon New Hampshire.,Department of Community and Family Medicine, Geisel School of Medicine at Dartmouth College, Lebanon New Hampshire
| | - Karl T Kelsey
- Department of Epidemiology, Brown University, Providence, Rhode Island
| | - John K Wiencke
- Department of Neurological Surgery, Helen Diller Family Cancer Center, University of California San Francisco, San Francisco, California
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426
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Nicodemus-Johnson J, Myers RA, Sakabe NJ, Sobreira DR, Hogarth DK, Naureckas ET, Sperling AI, Solway J, White SR, Nobrega MA, Nicolae DL, Gilad Y, Ober C. DNA methylation in lung cells is associated with asthma endotypes and genetic risk. JCI Insight 2016; 1:e90151. [PMID: 27942592 DOI: 10.1172/jci.insight.90151] [Citation(s) in RCA: 102] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
The epigenome provides a substrate through which environmental exposures can exert their effects on gene expression and disease risk, but the relative importance of epigenetic variation on human disease onset and progression is poorly characterized. Asthma is a heterogeneous disease of the airways, for which both onset and clinical course result from interactions between host genotype and environmental exposures, yet little is known about the molecular mechanisms for these interactions. We assessed genome-wide DNA methylation using the Infinium Human Methylation 450K Bead Chip and characterized the transcriptome by RNA sequencing in primary airway epithelial cells from 74 asthmatic and 41 nonasthmatic adults. Asthma status was based on doctor's diagnosis and current medication use. Genotyping was performed using various Illumina platforms. Our study revealed a regulatory locus on chromosome 17q12-21 associated with asthma risk and epigenetic signatures of specific asthma endotypes and molecular networks. Overall, these data support a central role for DNA methylation in lung cells, which promotes distinct molecular pathways of asthma pathogenesis and modulates the effects of genetic variation on disease risk and clinical heterogeneity.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Dan L Nicolae
- Department of Human Genetics.,Department of Medicine, and.,Department of Statistics, University of Chicago, Chicago, Illinois, USA
| | - Yoav Gilad
- Department of Human Genetics.,Department of Medicine, and
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427
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Milnik A, Vogler C, Demougin P, Egli T, Freytag V, Hartmann F, Heck A, Peter F, Spalek K, Stetak A, de Quervain DJF, Papassotiropoulos A, Vukojevic V. Common epigenetic variation in a European population of mentally healthy young adults. J Psychiatr Res 2016; 83:260-268. [PMID: 27710795 DOI: 10.1016/j.jpsychires.2016.08.012] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2016] [Revised: 08/03/2016] [Accepted: 08/18/2016] [Indexed: 12/25/2022]
Abstract
DNA methylation represents an important link between structural genetic variation and complex phenotypes. The study of genome-wide CpG methylation and its relation to traits relevant to psychiatry has become increasingly important. Here, we analyzed quality metrics of 394,043 CpG sites in two samples of 568 and 319 mentally healthy young adults. For 25% of all CpGs we observed medium to large common epigenetic variation. These CpGs were overrepresented in open sea and shore regions, as well as in intergenic regions. They also showed a strong enrichment of significant hits in association analyses. Furthermore, a significant proportion of common DNA methylation is at least partially genetically driven and thus may be observed similarly across tissues. These findings could be of particular relevance for studies of complex neuropsychiatric traits, which often rely on proxy tissues.
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Affiliation(s)
- Annette Milnik
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055, Basel, Switzerland; Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055, Basel, Switzerland; Psychiatric University Clinics, University of Basel, CH-4055, Basel, Switzerland.
| | - Christian Vogler
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055, Basel, Switzerland; Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055, Basel, Switzerland; Psychiatric University Clinics, University of Basel, CH-4055, Basel, Switzerland
| | - Philippe Demougin
- Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055, Basel, Switzerland; Department Biozentrum, Life Sciences Training Facility, University of Basel, CH-4056, Basel, Switzerland
| | - Tobias Egli
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055, Basel, Switzerland; Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055, Basel, Switzerland
| | - Virginie Freytag
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055, Basel, Switzerland; Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055, Basel, Switzerland
| | - Francina Hartmann
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055, Basel, Switzerland; Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055, Basel, Switzerland
| | - Angela Heck
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055, Basel, Switzerland; Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055, Basel, Switzerland; Psychiatric University Clinics, University of Basel, CH-4055, Basel, Switzerland
| | - Fabian Peter
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055, Basel, Switzerland; Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055, Basel, Switzerland; Department Biozentrum, Life Sciences Training Facility, University of Basel, CH-4056, Basel, Switzerland
| | - Klara Spalek
- Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055, Basel, Switzerland; Division of Cognitive Neuroscience, Department of Psychology, University of Basel, CH-4055, Basel, Switzerland
| | - Attila Stetak
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055, Basel, Switzerland; Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055, Basel, Switzerland; Psychiatric University Clinics, University of Basel, CH-4055, Basel, Switzerland; Department Biozentrum, Life Sciences Training Facility, University of Basel, CH-4056, Basel, Switzerland
| | - Dominique J-F de Quervain
- Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055, Basel, Switzerland; Psychiatric University Clinics, University of Basel, CH-4055, Basel, Switzerland; Division of Cognitive Neuroscience, Department of Psychology, University of Basel, CH-4055, Basel, Switzerland
| | - Andreas Papassotiropoulos
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055, Basel, Switzerland; Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055, Basel, Switzerland; Psychiatric University Clinics, University of Basel, CH-4055, Basel, Switzerland; Department Biozentrum, Life Sciences Training Facility, University of Basel, CH-4056, Basel, Switzerland
| | - Vanja Vukojevic
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055, Basel, Switzerland; Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055, Basel, Switzerland; Department Biozentrum, Life Sciences Training Facility, University of Basel, CH-4056, Basel, Switzerland
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428
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Glossop JR, Nixon NB, Emes RD, Sim J, Packham JC, Mattey DL, Farrell WE, Fryer AA. DNA methylation at diagnosis is associated with response to disease-modifying drugs in early rheumatoid arthritis. Epigenomics 2016; 9:419-428. [PMID: 27885849 DOI: 10.2217/epi-2016-0042] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
AIM A proof-of-concept study to explore whether DNA methylation at first diagnosis is associated with response to disease-modifying antirheumatic drugs (DMARDs) in patients with early rheumatoid arthritis (RA). PATIENTS & METHODS DNA methylation was quantified in T-lymphocytes from 46 treatment-naive patients using HumanMethylation450 BeadChips. Treatment response was determined in 6 months using the European League Against Rheumatism (EULAR) response criteria. RESULTS Initial filtering identified 21 cytosine-phosphate-guanines (CpGs) that were differentially methylated between responders and nonresponders. After conservative adjustment for multiple testing, six sites remained statistically significant, of which four showed high sensitivity and/or specificity (≥75%) for response to treatment. Moreover, methylation at two sites in combination was the strongest factor associated with response (80.0% sensitivity, 90.9% specificity, AUC 0.85). CONCLUSION DNA methylation at diagnosis is associated with disease-modifying antirheumatic drug treatment response in early RA.
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Affiliation(s)
- John R Glossop
- Guy Hilton Research Centre, Institute for Applied Clinical Sciences, Keele University, Thornburrow Drive, Hartshill, Stoke-on-Trent, Staffordshire, ST4 7QB, UK.,Haywood Rheumatology Centre, Haywood Hospital, High Lane, Burslem, Stoke-on-Trent, Staffordshire, ST6 7AG, UK
| | - Nicola B Nixon
- Haywood Rheumatology Centre, Haywood Hospital, High Lane, Burslem, Stoke-on-Trent, Staffordshire, ST6 7AG, UK
| | - Richard D Emes
- School of Veterinary Medicine & Science, University of Nottingham, Sutton Bonington Campus, Sutton Bonington, Leicestershire, LE12 5RD, UK.,Advanced Data Analysis Centre, University of Nottingham, Sutton Bonington Campus, Sutton Bonington, Leicestershire, LE12 5RD, UK
| | - Julius Sim
- School of Health & Rehabilitation, Keele University, Staffordshire, ST5 5BG, UK
| | - Jon C Packham
- Guy Hilton Research Centre, Institute for Applied Clinical Sciences, Keele University, Thornburrow Drive, Hartshill, Stoke-on-Trent, Staffordshire, ST4 7QB, UK.,Haywood Rheumatology Centre, Haywood Hospital, High Lane, Burslem, Stoke-on-Trent, Staffordshire, ST6 7AG, UK
| | - Derek L Mattey
- Guy Hilton Research Centre, Institute for Applied Clinical Sciences, Keele University, Thornburrow Drive, Hartshill, Stoke-on-Trent, Staffordshire, ST4 7QB, UK.,Haywood Rheumatology Centre, Haywood Hospital, High Lane, Burslem, Stoke-on-Trent, Staffordshire, ST6 7AG, UK
| | - William E Farrell
- Guy Hilton Research Centre, Institute for Applied Clinical Sciences, Keele University, Thornburrow Drive, Hartshill, Stoke-on-Trent, Staffordshire, ST4 7QB, UK
| | - Anthony A Fryer
- Guy Hilton Research Centre, Institute for Applied Clinical Sciences, Keele University, Thornburrow Drive, Hartshill, Stoke-on-Trent, Staffordshire, ST4 7QB, UK
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429
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Svendsen AJ, Gervin K, Lyle R, Christiansen L, Kyvik K, Junker P, Nielsen C, Houen G, Tan Q. Differentially Methylated DNA Regions in Monozygotic Twin Pairs Discordant for Rheumatoid Arthritis: An Epigenome-Wide Study. Front Immunol 2016; 7:510. [PMID: 27909437 PMCID: PMC5112246 DOI: 10.3389/fimmu.2016.00510] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Accepted: 11/02/2016] [Indexed: 12/29/2022] Open
Abstract
Objectives In an explorative epigenome-wide association study (EWAS) to search for gene independent, differentially methylated DNA positions and regions (DMRs) associated with rheumatoid arthritis (RA) by studying monozygotic (MZ) twin pairs discordant for RA. Methods Genomic DNA was isolated from whole blood samples from 28 MZ twin pairs discordant for RA. DNA methylation was measured using the HumanMethylation450 BeadChips. Smoking, anti-cyclic citrullinated peptide antibodies, and immunosuppressive treatment were included as covariates. Pathway analysis was performed using GREAT. Results Smoking was significantly associated with hypomethylation of a DMR overlapping the promoter region of the RNF5 and the AGPAT1, which are implicated in inflammation and autoimmunity, whereas DMARD treatment induced hypermethylation of the same region. Additionally, the promotor region of both S100A6 and EFCAB4B were hypomethylated, and both genes have previously been associated with RA. We replicated several candidate genes identified in a previous EWAS in treatment-naïve RA singletons. Gene-set analysis indicated the involvement of immunologic signatures and cancer-related pathways in RA. Conclusion We identified several differentially methylated regions associated with RA, which may represent environmental effects or consequences of the disease and plausible biological pathways pertinent to the pathogenesis of RA.
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Affiliation(s)
- Anders J Svendsen
- The Danish Twin Registry, Epidemiology, Institute of Public Health, University of Southern Denmark , Odense , Denmark
| | - Kristina Gervin
- Department of Medical Genetics, Oslo University Hospital, University of Oslo , Oslo , Norway
| | - Robert Lyle
- Department of Medical Genetics, Oslo University Hospital, University of Oslo , Oslo , Norway
| | - Lene Christiansen
- The Danish Twin Registry, Epidemiology, Institute of Public Health, University of Southern Denmark , Odense , Denmark
| | - Kirsten Kyvik
- Denmark and Odense Patient data Explorative Network (OPEN), Institute of Clinical Research, Odense University Hospital, University of Southern Denmark , Odense , Denmark
| | - Peter Junker
- Department of Rheumatology, Odense University Hospital, University of Southern Denmark , Odense , Denmark
| | - Christian Nielsen
- Department of Clinical Immunology, Odense University Hospital , Odense , Denmark
| | - Gunnar Houen
- Department of Clinical Biochemistry and Immunology, Statens Serum Institute , Copenhagen , Denmark
| | - Qihua Tan
- The Danish Twin Registry, Epidemiology, Institute 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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430
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Jones BE, Yang J, Muthigi A, Hogan SL, Hu Y, Starmer J, Henderson CD, Poulton CJ, Brant EJ, Pendergraft WF, Jennette JC, Falk RJ, Ciavatta DJ. Gene-Specific DNA Methylation Changes Predict Remission in Patients with ANCA-Associated Vasculitis. J Am Soc Nephrol 2016; 28:1175-1187. [PMID: 27821628 DOI: 10.1681/asn.2016050548] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2016] [Accepted: 09/19/2016] [Indexed: 12/14/2022] Open
Abstract
ANCA-associated vasculitis is an autoimmune condition characterized by vascular inflammation and organ damage. Pharmacologically induced remission of this condition is complicated by relapses. Potential triggers of relapse are immunologic challenges and environmental insults, both of which associate with changes in epigenetic silencing modifications. Altered histone modifications implicated in gene silencing associate with aberrant autoantigen expression. To establish a link between DNA methylation, a model epigenetic gene silencing modification, and autoantigen gene expression and disease status in ANCA-associated vasculitis, we measured gene-specific DNA methylation of the autoantigen genes myeloperoxidase (MPO) and proteinase 3 (PRTN3) in leukocytes of patients with ANCA-associated vasculitis observed longitudinally (n=82) and of healthy controls (n=32). Patients with active disease demonstrated hypomethylation of MPO and PRTN3 and increased expression of the autoantigens; in remission, DNA methylation generally increased. Longitudinal analysis revealed that patients with ANCA-associated vasculitis could be divided into two groups, on the basis of whether DNA methylation increased or decreased from active disease to remission. In patients with increased DNA methylation, MPO and PRTN3 expression correlated with DNA methylation. Kaplan-Meier estimate of relapse revealed patients with increased DNA methylation at the PRTN3 promoter had a significantly greater probability of a relapse-free period (P<0.001), independent of ANCA serotype. Patients with decreased DNA methylation at the PRTN3 promoter had a greater risk of relapse (hazard ratio, 4.55; 95% confidence interval, 2.09 to 9.91). Thus, changes in the DNA methylation status of the PRTN3 promoter may predict the likelihood of stable remission and explain autoantigen gene regulation.
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Affiliation(s)
- Britta E Jones
- Kidney Center, Department of Medicine, Division of Nephrology and Hypertension.,Department of Pathology and Laboratory Medicine, and
| | - Jiajin Yang
- Kidney Center, Department of Medicine, Division of Nephrology and Hypertension
| | - Akhil Muthigi
- Kidney Center, Department of Medicine, Division of Nephrology and Hypertension
| | - Susan L Hogan
- Kidney Center, Department of Medicine, Division of Nephrology and Hypertension
| | - Yichun Hu
- Kidney Center, Department of Medicine, Division of Nephrology and Hypertension
| | - Joshua Starmer
- Kidney Center, Department of Medicine, Division of Nephrology and Hypertension.,Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Candace D Henderson
- Kidney Center, Department of Medicine, Division of Nephrology and Hypertension
| | - Caroline J Poulton
- Kidney Center, Department of Medicine, Division of Nephrology and Hypertension
| | - Elizabeth J Brant
- Kidney Center, Department of Medicine, Division of Nephrology and Hypertension
| | | | - J Charles Jennette
- Kidney Center, Department of Medicine, Division of Nephrology and Hypertension.,Department of Pathology and Laboratory Medicine, and
| | - Ronald J Falk
- Kidney Center, Department of Medicine, Division of Nephrology and Hypertension
| | - Dominic J Ciavatta
- Kidney Center, Department of Medicine, Division of Nephrology and Hypertension, .,Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
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431
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Song MA, Brasky TM, Marian C, Weng DY, Taslim C, Dumitrescu RG, Llanos AA, Freudenheim JL, Shields PG. Racial differences in genome-wide methylation profiling and gene expression in breast tissues from healthy women. Epigenetics 2016; 10:1177-87. [PMID: 26680018 DOI: 10.1080/15592294.2015.1121362] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
Abstract
Breast cancer is more common in European Americans (EAs) than in African Americans (AAs) but mortality from breast cancer is higher among AAs. While there are racial differences in DNA methylation and gene expression in breast tumors, little is known whether such racial differences exist in breast tissues of healthy women. Genome-wide DNA methylation and gene expression profiling was performed in histologically normal breast tissues of healthy women. Linear regression models were used to identify differentially-methylated CpG sites (CpGs) between EAs (n = 61) and AAs (n = 22). Correlations for methylation and expression were assessed. Biological functions of the differentially-methylated genes were assigned using the Ingenuity Pathway Analysis. Among 485 differentially-methylated CpGs by race, 203 were hypermethylated in EAs, and 282 were hypermethylated in AAs. Promoter-related differentially-methylated CpGs were more frequently hypermethylated in EAs (52%) than AAs (27%) while gene body and intergenic CpGs were more frequently hypermethylated in AAs. The differentially-methylated CpGs were enriched for cancer-associated genes with roles in cell death and survival, cellular development, and cell-to-cell signaling. In a separate analysis for correlation in EAs and AAs, different patterns of correlation were found between EAs and AAs. The correlated genes showed different biological networks between EAs and AAs; networks were connected by Ubiquitin C. To our knowledge, this is the first comprehensive genome-wide study to identify differences in methylation and gene expression between EAs and AAs in breast tissues from healthy women. These findings may provide further insights regarding the contribution of epigenetic differences to racial disparities in breast cancer.
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Affiliation(s)
- Min-Ae Song
- a Comprehensive Cancer Center; The Ohio State University and James Cancer Hospital ; Columbus , Ohio , USA
| | - Theodore M Brasky
- a Comprehensive Cancer Center; The Ohio State University and James Cancer Hospital ; Columbus , Ohio , USA
| | - Catalin Marian
- a Comprehensive Cancer Center; The Ohio State University and James Cancer Hospital ; Columbus , Ohio , USA.,b Biochemistry and Pharmacology Department ; Victor Babes University of Medicine and Pharmacy ; 300041 Timisoara , Romania
| | - Daniel Y Weng
- a Comprehensive Cancer Center; The Ohio State University and James Cancer Hospital ; Columbus , Ohio , USA
| | - Cenny Taslim
- a Comprehensive Cancer Center; The Ohio State University and James Cancer Hospital ; Columbus , Ohio , USA
| | | | - Adana A Llanos
- d Department of Epidemiology ; Rutgers School of Public Health and Rutgers Cancer Institute of New Jersey ; New Brunswick , NJ 08903 , USA
| | - Jo L Freudenheim
- e Department of Epidemiology and Environmental Health; School of Public Health and Health Professions ; University at Buffalo ; Buffalo , NY 14214 , USA
| | - Peter G Shields
- a Comprehensive Cancer Center; The Ohio State University and James Cancer Hospital ; Columbus , Ohio , USA
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432
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Esposito EA, Jones MJ, Doom JR, MacIsaac JL, Gunnar MR, Kobor MS. Differential DNA methylation in peripheral blood mononuclear cells in adolescents exposed to significant early but not later childhood adversity. Dev Psychopathol 2016; 28:1385-1399. [PMID: 26847422 PMCID: PMC5903568 DOI: 10.1017/s0954579416000055] [Citation(s) in RCA: 51] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Internationally adopted adolescents who are adopted as young children from conditions of poverty and deprivation have poorer physical and mental health outcomes than do adolescents conceived, born, and raised in the United States by families similar to those who adopt internationally. Using a sample of Russian and Eastern European adoptees to control for Caucasian race and US birth, and nonadopted offspring of well-educated and well-resourced parents to control for postadoption conditions, we hypothesized that the important differences in environments, conception to adoption, might be reflected in epigenetic patterns between groups, specifically in DNA methylation. Thus, we conducted an epigenome-wide association study to compare DNA methylation profiles at approximately 416,000 individual CpG loci from peripheral blood mononuclear cells of 50 adopted youth and 33 nonadopted youth. Adopted youth averaged 22 months at adoption, and both groups averaged 15 years at testing; thus, roughly 80% of their lives were lived in similar circumstances. Although concurrent physical health did not differ, cell-type composition predicted using the DNA methylation data revealed a striking difference in the white blood cell-type composition of the adopted and nonadopted youth. After correcting for cell type and removing invariant probes, 30 CpG sites in 19 genes were more methylated in the adopted group. We also used an exploratory functional analysis that revealed that 223 gene ontology terms, clustered in neural and developmental categories, were significantly enriched between groups.
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Affiliation(s)
- Elisa A. Esposito
- Institute of Child Development, University of Minnesota, 51 East River Parkway, Minneapolis, MN 55455
- Widener University, One University Place, Chester, PA 19013
| | - Meaghan J. Jones
- Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, University of British Columbia, 950 West 28 Avenue, Vancouver, V5Z 4H4, Canada
| | - Jenalee R. Doom
- Institute of Child Development, University of Minnesota, 51 East River Parkway, Minneapolis, MN 55455
| | - Julia L MacIsaac
- Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, University of British Columbia, 950 West 28 Avenue, Vancouver, V5Z 4H4, Canada
| | - Megan R. Gunnar
- Institute of Child Development, University of Minnesota, 51 East River Parkway, Minneapolis, MN 55455
- Child and Brain Development Program, Canadian Institute for Advanced Research, Canada
| | - Michael S. Kobor
- Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, University of British Columbia, 950 West 28 Avenue, Vancouver, V5Z 4H4, Canada
- Child and Brain Development Program, Canadian Institute for Advanced Research, Canada
- Human Early Learning Partnership, School of Population and Public Health, University of British Columbia
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433
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Yang IV, Pedersen BS, Liu AH, O'Connor GT, Pillai D, Kattan M, Misiak RT, Gruchalla R, Szefler SJ, Khurana Hershey GK, Kercsmar C, Richards A, Stevens AD, Kolakowski CA, Makhija M, Sorkness CA, Krouse RZ, Visness C, Davidson EJ, Hennessy CE, Martin RJ, Togias A, Busse WW, Schwartz DA. The nasal methylome and childhood atopic asthma. J Allergy Clin Immunol 2016; 139:1478-1488. [PMID: 27745942 DOI: 10.1016/j.jaci.2016.07.036] [Citation(s) in RCA: 107] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2015] [Revised: 06/24/2016] [Accepted: 07/14/2016] [Indexed: 12/13/2022]
Abstract
BACKGROUND Given the strong environmental influence on both epigenetic marks and allergic asthma in children, the epigenetic alterations in respiratory epithelia might provide insight into allergic asthma. OBJECTIVE We sought to identify DNA methylation and gene expression changes associated with childhood allergic persistent asthma. METHODS We compared genomic DNA methylation patterns and gene expression in African American children with persistent atopic asthma (n = 36) versus healthy control subjects (n = 36). Results were validated in an independent population of asthmatic children (n = 30) by using a shared healthy control population (n = 36) and in an independent population of white adult atopic asthmatic patients (n = 12) and control subjects (n = 12). RESULTS We identified 186 genes with significant methylation changes, differentially methylated regions or differentially methylated probes, after adjustment for age, sex, race/ethnicity, batch effects, inflation, and multiple comparisons. Genes differentially methylated included those with established roles in asthma and atopy and genes related to extracellular matrix, immunity, cell adhesion, epigenetic regulation, and airflow obstruction. The methylation changes were substantial (median, 9.5%; range, 2.6% to 29.5%). Hypomethylated and hypermethylated genes were associated with increased and decreased gene expression, respectively (P < 2.8 × 10-6 for differentially methylated regions and P < 7.8 × 10-10 for differentially methylated probes). Quantitative analysis in 53 differentially expressed genes demonstrated that 32 (60%) have significant methylation-expression relationships within 5 kb of the gene. Ten loci selected based on the relevance to asthma, magnitude of methylation change, and methylation-expression relationships were validated in an independent cohort of children with atopic asthma. Sixty-seven of 186 genes also have significant asthma-associated methylation changes in nasal epithelia of adult white asthmatic patients. CONCLUSIONS Epigenetic marks in respiratory epithelia are associated with allergic asthma and gene expression changes in inner-city children.
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Affiliation(s)
- Ivana V Yang
- Department of Medicine and University of Colorado, School of Medicine, Aurora, Colo; National Jewish Health, Denver, Colo; Department of Epidemiology, Colorado School of Public Health, Aurora, Colo.
| | - Brent S Pedersen
- Department of Medicine and University of Colorado, School of Medicine, Aurora, Colo
| | | | - George T O'Connor
- Department of Medicine, Boston University School of Medicine, Boston, Mass
| | | | - Meyer Kattan
- Columbia University Medical Center, New York, NY
| | | | | | - Stanley J Szefler
- Department of Pediatrics, Children's Hospital Colorado and University of Colorado, School of Medicine, Aurora, Colo
| | | | | | - Adam Richards
- Department of Medicine and University of Colorado, School of Medicine, Aurora, Colo
| | | | | | | | - Christine A Sorkness
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wis
| | | | | | - Elizabeth J Davidson
- Department of Medicine and University of Colorado, School of Medicine, Aurora, Colo
| | - Corinne E Hennessy
- Department of Medicine and University of Colorado, School of Medicine, Aurora, Colo
| | | | - Alkis Togias
- National Institute of Allergy and Infectious Diseases, Bethesda, Md; and University of Colorado, Aurora, CO
| | - William W Busse
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wis
| | - David A Schwartz
- Department of Medicine and University of Colorado, School of Medicine, Aurora, Colo; National Jewish Health, Denver, Colo; Department of Immunology, University of Colorado, Aurora, Colo.
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434
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Qin Z, Li B, Conneely KN, Wu H, Hu M, Ayyala D, Park Y, Jin VX, Zhang F, Zhang H, Li L, Lin S. Statistical challenges in analyzing methylation and long-range chromosomal interaction data. STATISTICS IN BIOSCIENCES 2016; 8:284-309. [PMID: 28008337 PMCID: PMC5167536 DOI: 10.1007/s12561-016-9145-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2015] [Revised: 02/22/2016] [Accepted: 02/22/2016] [Indexed: 12/21/2022]
Abstract
With the rapid development of high throughput technologies such as array and next generation sequencing (NGS), genome-wide, nucleotide-resolution epigenomic data are increasingly available. In recent years, there has been particular interest in data on DNA methylation and 3-dimensional (3D) chromosomal organization, which are believed to hold keys to understand biological mechanisms, such as transcription regulation, that are closely linked to human health and diseases. However, small sample size, complicated correlation structure, substantial noise, biases, and uncertainties, all present difficulties for performing statistical inference. In this review, we present an overview of the new technologies that are frequently utilized in studying DNA methylation and 3D chromosomal organization. We focus on reviewing recent developments in statistical methodologies designed for better interrogating epigenomic data, pointing out statistical challenges facing the field whenever appropriate.
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Affiliation(s)
- Zhaohui Qin
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Ben Li
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Karen N Conneely
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Hao Wu
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Ming Hu
- Division of Biostatistics, Department of Population Health, New York University School of Medicine, New York, NY 10016, USA
| | - Deepak Ayyala
- Department of Statistics, The Ohio State University, Columbus, OH 43210, USA
| | - Yongseok Park
- Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA 15261 USA
| | - Victor X Jin
- Department of Molecular Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA
| | - Fangyuan Zhang
- Department of Mathematics & Statistics, Texas Tech University, Lubbock, TX 79409, USA
| | - Han Zhang
- Department of Statistics, The Ohio State University, Columbus, OH 43210, USA
| | - Li Li
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Shili Lin
- Department of Statistics, The Ohio State University, Columbus, OH 43210, USA
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435
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de Goede OM, Lavoie PM, Robinson WP. Characterizing the hypomethylated DNA methylation profile of nucleated red blood cells from cord blood. Epigenomics 2016; 8:1481-1494. [PMID: 27687885 DOI: 10.2217/epi-2016-0069] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
AIM To provide insight into fetal nucleated red blood cell (nRBC) development using genome-wide DNA methylation (DNAm) profiling. MATERIALS & METHODS The DNAm profile (Illumina 450K array) of cord blood (n = 7) derived nRBCs was compared with B cells, CD4 and CD8 T cells, natural killer cells, granulocytes, monocytes and placenta (n = 5). RESULTS nRBCs and placenta had similarly low array-wide DNAm compared with white blood cells, but their patterns of hypomethylation differed at biologically relevant subsets of the array. High interindividual variability in nRBC DNAm was driven by a negative association between DNAm and nRBC count. CONCLUSION nRBC hypomethylation is likely an epigenetic signature of erythropoiesis rather than of early development. Variability in nRBC DNAm may stem from differences in the cell population's maturity or hematopoietic source.
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Affiliation(s)
- Olivia M de Goede
- Child & Family Research Institute, Vancouver, British Columbia, V5Z 4H4, Canada.,Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, V6T 1Z3, Canada
| | - Pascal M Lavoie
- Child & Family Research Institute, Vancouver, British Columbia, V5Z 4H4, Canada.,Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, V6T 1Z3, Canada
| | - Wendy P Robinson
- Child & Family Research Institute, Vancouver, British Columbia, V5Z 4H4, Canada.,Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, V6T 1Z3, Canada
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436
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Geybels MS, Wright JL, Bibikova M, Klotzle B, Fan JB, Zhao S, Feng Z, Ostrander EA, Lin DW, Nelson PS, Stanford JL. Epigenetic signature of Gleason score and prostate cancer recurrence after radical prostatectomy. Clin Epigenetics 2016; 8:97. [PMID: 27651837 PMCID: PMC5024414 DOI: 10.1186/s13148-016-0260-z] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2016] [Accepted: 08/24/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Identifying the subset of patients with clinically localized prostate cancer (PCa) at the highest risk of recurrence remains challenging, and better prognostic markers are needed. Gleason score is the best predictor of PCa aggressiveness and prognosis. In the present study, we generated an epigenetic signature based on high versus low Gleason score tumors and evaluated its ability to predict recurrence after radical prostatectomy. METHODS Genome-wide DNA methylation data from The Cancer Genome Atlas (TCGA; no. of patients = 333) and the elastic net method were used to generate an epigenetic signature by contrasting patients with high (8-10) versus low (≤6) Gleason score tumors. The signature was then tested in a cohort of 523 patients with clinically localized disease who had radical prostatectomy. Samples taken from the primary tumor were used for DNA methylation and mRNA expression profiling. Patients were followed for PCa recurrence on average for 8 years after diagnosis. RESULTS The epigenetic signature includes 52 differentially methylated CpG sites. In the testing cohort, the signature was associated with poorer recurrence-free survival (hazard ratio per 25 % increase = 1.78; 95 % confidence interval 1.48, 2.16). The signature significantly improved the area under the curve (AUC) for PCa recurrence compared to clinical-pathological parameters alone, particularly among patients diagnosed with Gleason score 7 tumors (0.64 vs. 0.76, P = 1.34E-4). Results were comparable for patients with Gleason 3 + 4 and those with 4 + 3 tumors. Gene Set Enrichment Analysis showed that higher levels of the signature were associated with increased expression of genes related to cell cycle proliferation and decreased expression of androgen-responsive genes. CONCLUSIONS This report shows evidence that DNA methylation patterns measured in prostate tumor cells are predictive of PCa aggressiveness. The epigenetic signature may have clinical utility to improve prognostication particularly in patients with intermediate Gleason score 7 tumors.
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Affiliation(s)
- Milan S Geybels
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA 98109-1024 USA ; Department of Epidemiology, GROW School for Oncology and Developmental biology, Maastricht University, Maastricht, The Netherlands
| | - Jonathan L Wright
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA 98109-1024 USA ; Department of Urology, University of Washington School of Medicine, Seattle, WA USA
| | | | | | - Jian-Bing Fan
- Illumina, Inc., San Diego, CA USA ; Current address: AnchorDx Corp., Guangzhou, 510300 People's Republic of China
| | - Shanshan Zhao
- Biostatistics & Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, Durham, NC USA
| | - Ziding Feng
- Department of Biostatistics, MD Anderson Cancer Center, Houston, TX USA
| | - Elaine A Ostrander
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, NIH, Bethesda, MD USA
| | - Daniel W Lin
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA 98109-1024 USA ; Department of Urology, University of Washington School of Medicine, Seattle, WA USA
| | - Peter S Nelson
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA USA ; Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA USA ; Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Janet L Stanford
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA 98109-1024 USA ; Department of Epidemiology, University of Washington School of Public Health, Seattle, WA USA
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437
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Corley MJ, Dye C, D'Antoni ML, Byron MM, Yo KLA, Lum-Jones A, Nakamoto B, Valcour V, SahBandar I, Shikuma CM, Ndhlovu LC, Maunakea AK. Comparative DNA Methylation Profiling Reveals an Immunoepigenetic Signature of HIV-related Cognitive Impairment. Sci Rep 2016; 6:33310. [PMID: 27629381 PMCID: PMC5024304 DOI: 10.1038/srep33310] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2016] [Accepted: 08/24/2016] [Indexed: 11/20/2022] Open
Abstract
Monocytes/macrophages contribute to the neuropathogenesis of HIV-related cognitive impairment (CI); however, considerable gaps in our understanding of the precise mechanisms driving this relationship remain. Furthermore, whether a distinct biological profile associated with HIV-related CI resides in immune cell populations remains unknown. Here, we profiled DNA methylomes and transcriptomes of monocytes derived from HIV-infected individuals with and without CI using genome-wide DNA methylation and gene expression profiling. We identified 1,032 CI-associated differentially methylated loci in monocytes. These loci related to gene networks linked to the central nervous system (CNS) and interactions with HIV. Most (70.6%) of these loci exhibited higher DNA methylation states in the CI group and were preferentially distributed over gene bodies and intergenic regions of the genome. CI-associated DNA methylation states at 12 CpG sites associated with neuropsychological testing performance scores. CI-associated DNA methylation also associated with gene expression differences including CNS genes CSRNP1 (P = 0.017), DISC1 (P = 0.012), and NR4A2 (P = 0.005); and a gene known to relate to HIV viremia, THBS1 (P = 0.003). This discovery cohort data unveils cell type-specific DNA methylation patterns related to HIV-associated CI and provide an immunoepigenetic DNA methylation “signature” potentially useful for corroborating clinical assessments, informing pathogenic mechanisms, and revealing new therapeutic targets against CI.
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Affiliation(s)
- Michael J Corley
- Department of Native Hawaiian Health, John A. Burns School of Medicine, Suite 1016B, University of Hawaii, Honolulu, HI 96813, USA
| | - Christian Dye
- Department of Native Hawaiian Health, John A. Burns School of Medicine, Suite 1016B, University of Hawaii, Honolulu, HI 96813, USA
| | - Michelle L D'Antoni
- Department of Tropical Medicine, John A. Burns School of Medicine, University of Hawaii, 651 Ilalo Street, BSB325C, Honolulu, HI 96813, USA
| | - Mary Margaret Byron
- Department of Tropical Medicine, John A. Burns School of Medicine, University of Hawaii, 651 Ilalo Street, BSB325C, Honolulu, HI 96813, USA
| | - Kaahukane Leite-Ah Yo
- Department of Native Hawaiian Health, John A. Burns School of Medicine, Suite 1016B, University of Hawaii, Honolulu, HI 96813, USA
| | - Annette Lum-Jones
- Department of Native Hawaiian Health, John A. Burns School of Medicine, Suite 1016B, University of Hawaii, Honolulu, HI 96813, USA
| | - Beau Nakamoto
- Hawaii Center for AIDS, John A. Burns School of Medicine, University of Hawaii, 651 Ilalo Street, BSB, Honolulu, HI 96815, USA
| | - Victor Valcour
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Ivo SahBandar
- Department of Tropical Medicine, John A. Burns School of Medicine, University of Hawaii, 651 Ilalo Street, BSB325C, Honolulu, HI 96813, USA
| | - Cecilia M Shikuma
- Hawaii Center for AIDS, John A. Burns School of Medicine, University of Hawaii, 651 Ilalo Street, BSB, Honolulu, HI 96815, USA
| | - Lishomwa C Ndhlovu
- Department of Tropical Medicine, John A. Burns School of Medicine, University of Hawaii, 651 Ilalo Street, BSB325C, Honolulu, HI 96813, USA.,Hawaii Center for AIDS, John A. Burns School of Medicine, University of Hawaii, 651 Ilalo Street, BSB, Honolulu, HI 96815, USA
| | - Alika K Maunakea
- Department of Native Hawaiian Health, John A. Burns School of Medicine, Suite 1016B, University of Hawaii, Honolulu, HI 96813, USA
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438
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Analysis of the breast cancer methylome using formalin-fixed paraffin-embedded tumour. Breast Cancer Res Treat 2016; 160:173-180. [PMID: 27604360 DOI: 10.1007/s10549-016-3971-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2016] [Accepted: 09/01/2016] [Indexed: 12/31/2022]
Abstract
PURPOSE Aberrant DNA methylation occurs frequently in breast carcinogenesis. Tools for translational epigenetic studies of breast cancer involving formalin-fixed paraffin-embedded (FFPE) human tissues have now been developed. Few studies have measured genome-wide methylation in DNA derived from paraffin-embedded tumour tissues and compared the DNA methylation in corresponding adjacent non-tumour ductal epithelium (ADJNT). These studies are technically challenging due to the spectrum of breast cancer pathologies, the variable suitability of DNA extracted from FFPE material and the difficulties in identifying ADJNT. We assessed the suitability of FFPE breast cancer material for genome-wide DNA methylation assessment of tumour and ADJNT. METHODS Twenty-one archival breast tumour tissues with paired ADJNT obtained from separate blocks and at least 2 cm from the tumour were sourced from The Melbourne Collaborative Cohort Study (MCCS). DNA was prepared from macrodissected tissue samples and assessed for genome-wide methylation using the Infinium HumanMethylation450 Beadchip (HM450K) array. RESULTS The 1000 most differentially methylated probes between tumour and ADJNT in this FFPE-derived dataset differentiated tumour and ADJNT in The Cancer Genome Atlas Network data (TCGA; derived from high molecular weight DNA using the same HM450K array). CONCLUSIONS Large-scale studies of genome-wide DNA methylation using FFPE breast cancer specimens offer the opportunity to further refine the pathological classification of tumours, to include subtypes that are underrepresented in the TCGA data and provide the capacity to further explore intra-tumoural heterogeneity.
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439
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Yue W, Cheng W, Liu Z, Tang Y, Lu T, Zhang D, Tang M, Huang Y. Genome-wide DNA methylation analysis in obsessive-compulsive disorder patients. Sci Rep 2016; 6:31333. [PMID: 27527274 PMCID: PMC4985637 DOI: 10.1038/srep31333] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2015] [Accepted: 07/18/2016] [Indexed: 11/09/2022] Open
Abstract
Literatures have suggested that not only genetic but also environmental factors, interactively accounted for susceptibility of obsessive-compulsive disorder (OCD). DNA methylation may regulate expression of genes as the heritable epigenetic modification. The examination for genome-wide DNA methylation was performed on blood samples from 65 patients with OCD, as well as 96 healthy control subjects. The DNA methylation was examined at over 485,000 CpG sites using the Illumina Infinium Human Methylation450 BeadChip. As a result, 8,417 probes corresponding to 2,190 unique genes were found to be differentially methylated between OCD and healthy control subjects. Of those genes, 4,013 loci were located in CpG islands and 2,478 were in promoter regions. These included BCYRN1, BCOR, FGF13, HLA-DRB1, ARX, etc., which have previously been reported to be associated with OCD. Pathway analyses indicated that regulation of actin cytoskeleton, cell adhesion molecules (CAMs), actin binding, transcription regulator activity, and other pathways might be further associated with risk of OCD. Unsupervised clustering analysis of the top 3,000 most variable probes revealed two distinct groups with significantly more people with OCD in cluster one compared with controls (67.74% of cases v.s. 27.13% of controls, Chi-square = 26.011, df = 1, P = 3.41E-07). These results strongly suggested that differential DNA methylation might play an important role in etiology of OCD.
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Affiliation(s)
- Weihua Yue
- Peking University Sixth Hospital &Institute of Mental Health, Beijing 100191, China.,National Clinical Research Center for Mental Disorders &Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing 100191, China
| | - Weiqiu Cheng
- Peking University Sixth Hospital &Institute of Mental Health, Beijing 100191, China.,National Clinical Research Center for Mental Disorders &Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing 100191, China
| | - Zhaorui Liu
- Peking University Sixth Hospital &Institute of Mental Health, Beijing 100191, China.,National Clinical Research Center for Mental Disorders &Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing 100191, China
| | - Yi Tang
- Peking University Sixth Hospital &Institute of Mental Health, Beijing 100191, China.,National Clinical Research Center for Mental Disorders &Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing 100191, China.,Department of Mental Health, Guangdong Provincial People's Hospital, Guangzhou, China
| | - Tianlan Lu
- Peking University Sixth Hospital &Institute of Mental Health, Beijing 100191, China.,National Clinical Research Center for Mental Disorders &Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing 100191, China
| | - Dai Zhang
- Peking University Sixth Hospital &Institute of Mental Health, Beijing 100191, China.,National Clinical Research Center for Mental Disorders &Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing 100191, China.,Peking-Tsinghua Center for Life Sciences/PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Muni Tang
- Guangzhou Psychiatry Hospital, Guangzhou, 510080, China
| | - Yueqin Huang
- Peking University Sixth Hospital &Institute of Mental Health, Beijing 100191, China.,National Clinical Research Center for Mental Disorders &Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing 100191, China
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440
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Abstract
Pan-cancer analysis can identify cell- and tissue-specific genomic loci and regions with underlying biological functions. Here we present an online curated DNA Methylation Annotation Knowledgebase, DMAK, which includes the pan-cancer analysis results for differentially-methylated loci and regions by the Reduced Representation Bisulfite Sequencing profiling technology. DMAK contains 3 modules of curated information and analysis results on 688,445 CpG sites across 19 cancer and embryonic stem cell lines from ENCODE, and further analysis of survival associations with clinical sources retrieved from TCGA. The knowledgebase covers all identified differentially-methylated CpG sites and regions of interest, further annotated genomic information, together with tumor suppressor genes information and calculated methylation level. DMAK provides meaningful clues for deriving functional association network and related clinical association results based on protein-coding genes, including tumor suppressor genes, identified from differentially methylated regions of interest. Thus DMAK constitutes a comprehensive reference source for the current epigenetic research and clinical study.
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Affiliation(s)
- Binhua Tang
- a Epigenetics and Function Group, School of Internet of Things, Hohai University , Jiangsu , China.,b School of Public Health, Shanghai Jiao Tong University , Shanghai , China
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441
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Tan Q, Heijmans BT, Hjelmborg JVB, Soerensen M, Christensen K, Christiansen L. Epigenetic drift in the aging genome: a ten-year follow-up in an elderly twin cohort. Int J Epidemiol 2016; 45:1146-1158. [PMID: 27498152 DOI: 10.1093/ije/dyw132] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/29/2016] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Current epigenetic studies on aging are dominated by the cross-sectional design that correlates subjects' ages or age groups with their measured epigenetic profiles. Such studies have been more aimed at age prediction or building up the epigenetic clock of age rather than focusing on the dynamic patterns in epigenetic changes during the aging process. METHODS We performed an epigenome-wide association study of intra-individual longitudinal changes in DNA methylation at CpG (cytosine-phosphate-guanine) sites measured in whole-blood samples of a cohort of 43 elderly twin pairs followed for 10 years (age at intake 73-82 years). Biological pathway analysis and survival analysis were also conducted on CpGs showing longitudinal change in their DNA-methylation levels. Classical twin models were fitted to each CpG site to estimate the genetic and environmental effects on DNA-methylation. RESULTS Our analysis identified 2284 CpG sites whose DNA-methylation levels changed longitudinally over the follow-up. Twin modelling revealed that the longitudinal change for 90% of these CpG sites was explained solely by individual unique environmental factors and only for 10% of these sites was it influenced by familial factors (genetic or shared environment). Over 60% of the identified CpG sites were replicated (same direction and replication P < 0.05) in an independent cross-sectional sample of 300 twins aged from 30 to 74 years. The replication rate went up to 91% for the top 53 CpGs with P < 1 × 10-07. Pathway analysis of genes linked to these CpGs identified biologically meaningful gene-sets involved in cellular-signalling events and in transmission across chemical synapses, which are important molecular underpinnings of aging-related degenerative disorders. CONCLUSION Our epigenome-wide association studies on a cohort of old twins followed up for 10 years identified highly replicable epigenetic biomarkers predominantly implicated in signalling pathways of degenerative disorders and survival in the elderly.
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Affiliation(s)
- Qihua Tan
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense C, Denmark, .,Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark and Odense University Hospital, Odense C, Denmark and
| | - Bastiaan T Heijmans
- Molecular Epidemiology Section, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
| | - Jacob V B Hjelmborg
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense C, Denmark
| | - Mette Soerensen
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense C, Denmark.,Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark and Odense University Hospital, Odense C, Denmark and
| | - Kaare Christensen
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense C, Denmark.,Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark and Odense University Hospital, Odense C, Denmark and
| | - Lene Christiansen
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense C, Denmark
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442
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Genome-wide measures of DNA methylation in peripheral blood and the risk of urothelial cell carcinoma: a prospective nested case-control study. Br J Cancer 2016; 115:664-73. [PMID: 27490804 PMCID: PMC5023776 DOI: 10.1038/bjc.2016.237] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2016] [Revised: 05/13/2016] [Accepted: 07/08/2016] [Indexed: 12/23/2022] Open
Abstract
Background: Global DNA methylation has been reported to be associated with urothelial cell carcinoma (UCC) by studies using blood samples collected at diagnosis. Using the Illumina HumanMethylation450 assay, we derived genome-wide measures of blood DNA methylation and assessed them for their prospective association with UCC risk. Methods: We used 439 case–control pairs from the Melbourne Collaborative Cohort Study matched on age, sex, country of birth, DNA sample type, and collection period. Conditional logistic regression was used to compute odds ratios (OR) of UCC risk per s.d. of each genome-wide measure of DNA methylation and 95% confidence intervals (CIs), adjusted for potential confounders. We also investigated associations by disease subtype, sex, smoking, and time since blood collection. Results: The risk of superficial UCC was decreased for individuals with higher levels of our genome-wide DNA methylation measure (OR=0.71, 95% CI: 0.54–0.94; P=0.02). This association was particularly strong for current smokers at sample collection (OR=0.47, 95% CI: 0.27–0.83). Intermediate levels of our genome-wide measure were associated with decreased risk of invasive UCC. Some variation was observed between UCC subtypes and the location and regulatory function of the CpGs included in the genome-wide measures of methylation. Conclusions: Higher levels of our genome-wide DNA methylation measure were associated with decreased risk of superficial UCC and intermediate levels were associated with reduced risk of invasive disease. These findings require replication by other prospective studies.
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443
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Yuen RKC, Merico D, Cao H, Pellecchia G, Alipanahi B, Thiruvahindrapuram B, Tong X, Sun Y, Cao D, Zhang T, Wu X, Jin X, Zhou Z, Liu X, Nalpathamkalam T, Walker S, Howe JL, Wang Z, MacDonald JR, Chan A, D'Abate L, Deneault E, Siu MT, Tammimies K, Uddin M, Zarrei M, Wang M, Li Y, Wang J, Wang J, Yang H, Bookman M, Bingham J, Gross SS, Loy D, Pletcher M, Marshall CR, Anagnostou E, Zwaigenbaum L, Weksberg R, Fernandez BA, Roberts W, Szatmari P, Glazer D, Frey BJ, Ring RH, Xu X, Scherer SW. Genome-wide characteristics of de novo mutations in autism. NPJ Genom Med 2016; 1:160271-1602710. [PMID: 27525107 PMCID: PMC4980121 DOI: 10.1038/npjgenmed.2016.27] [Citation(s) in RCA: 144] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
De novo mutations (DNMs) are important in Autism Spectrum Disorder (ASD), but so far analyses have mainly been on the ~1.5% of the genome encoding genes. Here, we performed whole genome sequencing (WGS) of 200 ASD parent-child trios and characterized germline and somatic DNMs. We confirmed that the majority of germline DNMs (75.6%) originated from the father, and these increased significantly with paternal age only (p=4.2×10-10). However, when clustered DNMs (those within 20kb) were found in ASD, not only did they mostly originate from the mother (p=7.7×10-13), but they could also be found adjacent to de novo copy number variations (CNVs) where the mutation rate was significantly elevated (p=2.4×10-24). By comparing DNMs detected in controls, we found a significant enrichment of predicted damaging DNMs in ASD cases (p=8.0×10-9; OR=1.84), of which 15.6% (p=4.3×10-3) and 22.5% (p=7.0×10-5) were in the non-coding or genic non-coding, respectively. The non-coding elements most enriched for DNM were untranslated regions of genes, boundaries involved in exon-skipping and DNase I hypersensitive regions. Using microarrays and a novel outlier detection test, we also found aberrant methylation profiles in 2/185 (1.1%) of ASD cases. These same individuals carried independently identified DNMs in the ASD risk- and epigenetic- genes DNMT3A and ADNP. Our data begins to characterize different genome-wide DNMs, and highlight the contribution of non-coding variants, to the etiology of ASD.
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Affiliation(s)
- Ryan K C Yuen
- The Centre for Applied Genomics, Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Daniele Merico
- The Centre for Applied Genomics, Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | | | - Giovanna Pellecchia
- The Centre for Applied Genomics, Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Babak Alipanahi
- Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canada
| | - Bhooma Thiruvahindrapuram
- The Centre for Applied Genomics, Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Xin Tong
- BGI-Shenzhen, Yantian, Shenzhen, China
| | - Yuhui Sun
- BGI-Shenzhen, Yantian, Shenzhen, China
| | | | - Tao Zhang
- BGI-Shenzhen, Yantian, Shenzhen, China
| | - Xueli Wu
- BGI-Shenzhen, Yantian, Shenzhen, China
| | - Xin Jin
- BGI-Shenzhen, Yantian, Shenzhen, China
| | - Ze Zhou
- BGI-Shenzhen, Yantian, Shenzhen, China
| | | | - Thomas Nalpathamkalam
- The Centre for Applied Genomics, Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Susan Walker
- The Centre for Applied Genomics, Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Jennifer L Howe
- The Centre for Applied Genomics, Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Zhuozhi Wang
- The Centre for Applied Genomics, Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Jeffrey R MacDonald
- The Centre for Applied Genomics, Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Ada Chan
- The Centre for Applied Genomics, Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Lia D'Abate
- The Centre for Applied Genomics, Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Eric Deneault
- The Centre for Applied Genomics, Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Michelle T Siu
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Kristiina Tammimies
- Center of Neurodevelopmental Disorders (KIND), Pediatric Neuropsychiatry Unit, Karolinska Institutet, Stockholm, Sweden
| | - Mohammed Uddin
- The Centre for Applied Genomics, Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Mehdi Zarrei
- The Centre for Applied Genomics, Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | | | | | - Jun Wang
- BGI-Shenzhen, Yantian, Shenzhen, China
| | - Jian Wang
- BGI-Shenzhen, Yantian, Shenzhen, China
| | | | | | | | | | - Dion Loy
- Google, Mountain View, California, USA
| | | | - Christian R Marshall
- The Centre for Applied Genomics, Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada; Department of Molecular Genetics, Paediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Evdokia Anagnostou
- Bloorview Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Lonnie Zwaigenbaum
- Department of Pediatrics, University of Alberta, Edmonton, Alberta, Canada
| | - Rosanna Weksberg
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada; Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Bridget A Fernandez
- Disciplines of Genetics and Medicine, Memorial University of Newfoundland, St. John's, Newfoundland, Canada; Provincial Medical Genetic Program, Eastern Health, St. John's, Newfoundland, Canada
| | - Wendy Roberts
- Autism Research Unit, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Peter Szatmari
- Autism Research Unit, The Hospital for Sick Children, Toronto, Ontario, Canada; Child Youth and Family Services, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - David Glazer
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Brendan J Frey
- Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canada; Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada
| | | | - Xun Xu
- BGI-Shenzhen, Yantian, Shenzhen, China
| | - Stephen W Scherer
- The Centre for Applied Genomics, Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada; Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada; McLaughlin Centre, University of Toronto, Toronto, Ontario, Canada
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444
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El Hajj N, Dittrich M, Böck J, Kraus TFJ, Nanda I, Müller T, Seidmann L, Tralau T, Galetzka D, Schneider E, Haaf T. Epigenetic dysregulation in the developing Down syndrome cortex. Epigenetics 2016; 11:563-78. [PMID: 27245352 PMCID: PMC4990229 DOI: 10.1080/15592294.2016.1192736] [Citation(s) in RCA: 57] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2016] [Revised: 05/12/2016] [Accepted: 05/17/2016] [Indexed: 12/18/2022] Open
Abstract
Using Illumina 450K arrays, 1.85% of all analyzed CpG sites were significantly hypermethylated and 0.31% hypomethylated in fetal Down syndrome (DS) cortex throughout the genome. The methylation changes on chromosome 21 appeared to be balanced between hypo- and hyper-methylation, whereas, consistent with prior reports, all other chromosomes showed 3-11 times more hyper- than hypo-methylated sites. Reduced NRSF/REST expression due to upregulation of DYRK1A (on chromosome 21q22.13) and methylation of REST binding sites during early developmental stages may contribute to this genome-wide excess of hypermethylated sites. Upregulation of DNMT3L (on chromosome 21q22.4) could lead to de novo methylation in neuroprogenitors, which then persists in the fetal DS brain where DNMT3A and DNMT3B become downregulated. The vast majority of differentially methylated promoters and genes was hypermethylated in DS and located outside chromosome 21, including the protocadherin gamma (PCDHG) cluster on chromosome 5q31, which is crucial for neural circuit formation in the developing brain. Bisulfite pyrosequencing and targeted RNA sequencing showed that several genes of PCDHG subfamilies A and B are hypermethylated and transcriptionally downregulated in fetal DS cortex. Decreased PCDHG expression is expected to reduce dendrite arborization and growth in cortical neurons. Since constitutive hypermethylation of PCDHG and other genes affects multiple tissues, including blood, it may provide useful biomarkers for DS brain development and pharmacologic targets for therapeutic interventions.
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Affiliation(s)
- Nady El Hajj
- Institute of Human Genetics, Julius Maximilians University, Würzburg, Germany
| | - Marcus Dittrich
- Institute of Human Genetics, Julius Maximilians University, Würzburg, Germany
- Department of Bioinformatics, Julius Maximilians University, Würzburg, Germany
| | - Julia Böck
- Institute of Human Genetics, Julius Maximilians University, Würzburg, Germany
| | - Theo F. J. Kraus
- Center for Neuropathology and Prion Research, Ludwig Maximilians University, Munich, Germany
| | - Indrajit Nanda
- Institute of Human Genetics, Julius Maximilians University, Würzburg, Germany
| | - Tobias Müller
- Department of Bioinformatics, Julius Maximilians University, Würzburg, Germany
| | - Larissa Seidmann
- Department of Pathology, University Medical Center, Mainz, Germany
| | - Tim Tralau
- Rehabilitation Clinic for Children and Adolescents, Westerland/Sylt, Germany
| | - Danuta Galetzka
- Department of Radiation Oncology and Radiotherapy, University Medical Center, Mainz, Germany
| | - Eberhard Schneider
- Institute of Human Genetics, Julius Maximilians University, Würzburg, Germany
| | - Thomas Haaf
- Institute of Human Genetics, Julius Maximilians University, Würzburg, Germany
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445
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Reliability of DNA methylation measures from dried blood spots and mononuclear cells using the HumanMethylation450k BeadArray. Sci Rep 2016; 6:30317. [PMID: 27457678 PMCID: PMC4960587 DOI: 10.1038/srep30317] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2016] [Accepted: 07/04/2016] [Indexed: 01/29/2023] Open
Abstract
The reliability of methylation measures from the widely used HumanMethylation450 (HM450K) microarray has not been assessed for DNA from dried blood spots (DBS) or peripheral blood mononuclear cells (PBMC), nor for combined data from different studies. Repeated HM450K methylation measures in DNA from DBS and PBMC samples were available from participants in six case-control studies nested within the Melbourne Collaborative Cohort Study. Reliability was assessed for individual CpGs by calculating the intraclass correlation coefficient (ICC) based on technical replicates (samples repeated in a single study; 126 PBMC, 136 DBS) and study duplicates (samples repeated across studies; 280 PBMC, 769 DBS) using mixed-effects models. Reliability based on technical replicates was moderate for PBMC (median ICC = 0.42), but lower for DBS (median ICC = 0.20). Study duplicates gave lower ICCs than technical replicates. CpGs that were either highly methylated or unmethylated generally had lower ICCs, which appeared to be mostly related to their lower variability. The ICCs for global methylation measures were high, typically greater than 0.70. The reliability of methylation measures determined by the HM450K microarray is wide-ranging and depends primarily on the variability in methylation at individual CpG sites. The power of association studies is low for a substantial proportion of CpGs in the HM450K assay.
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446
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Schneider E, Dittrich M, Böck J, Nanda I, Müller T, Seidmann L, Tralau T, Galetzka D, El Hajj N, Haaf T. CpG sites with continuously increasing or decreasing methylation from early to late human fetal brain development. Gene 2016; 592:110-118. [PMID: 27468947 DOI: 10.1016/j.gene.2016.07.058] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2016] [Revised: 06/28/2016] [Accepted: 07/23/2016] [Indexed: 01/03/2023]
Abstract
Normal human brain development is dependent on highly dynamic epigenetic processes for spatial and temporal gene regulation. Recent work identified wide-spread changes in DNA methylation during fetal brain development. We profiled CpG methylation in frontal cortex of 27 fetuses from gestational weeks 12-42, using Illumina 450K methylation arrays. Sites showing genome-wide significant correlation with gestational age were compared to a publicly available data set from gestational weeks 3-26. Altogether, we identified 2016 matching developmentally regulated differentially methylated positions (m-dDMPs): 1767m-dDMPs were hypermethylated and 1149 hypomethylated during fetal development. M-dDMPs are underrepresented in CpG islands and gene promoters, and enriched in gene bodies. They appear to cluster in certain chromosome regions. M-dDMPs are significantly enriched in autism-associated genes and CpGs. Our results promote the idea that reduced methylation dynamics during fetal brain development may predispose to autism. In addition, m-dDMPs are enriched in genes with human-specific brain expression patterns and/or histone modifications. Collectively, we defined a subset of dDMPs exhibiting constant methylation changes from early to late pregnancy. The same epigenetic mechanisms involving methylation changes in cis-regulatory regions may have been adopted for human brain evolution and ontogeny.
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Affiliation(s)
- Eberhard Schneider
- Institute of Human Genetics, Julius Maximilians University, 97074 Würzburg, Germany
| | - Marcus Dittrich
- Institute of Human Genetics, Julius Maximilians University, 97074 Würzburg, Germany; Department of Bioinformatics, Julius Maximilians University, 97074 Würzburg, Germany
| | - Julia Böck
- Institute of Human Genetics, Julius Maximilians University, 97074 Würzburg, Germany
| | - Indrajit Nanda
- Institute of Human Genetics, Julius Maximilians University, 97074 Würzburg, Germany
| | - Tobias Müller
- Department of Bioinformatics, Julius Maximilians University, 97074 Würzburg, Germany
| | - Larissa Seidmann
- Department of Pathology, University Medical Center, 55131 Mainz, Germany
| | - Tim Tralau
- Department of Pathology, University Medical Center, 55131 Mainz, Germany; Rehabilitation Clinic for Children and Adolescents, 25980 Westerland/Sylt, Germany
| | - Danuta Galetzka
- Department of Radiation Oncology and Radiotherapy, University Medical Center, 55131 Mainz, Germany
| | - Nady El Hajj
- Institute of Human Genetics, Julius Maximilians University, 97074 Würzburg, Germany
| | - Thomas Haaf
- Institute of Human Genetics, Julius Maximilians University, 97074 Würzburg, Germany.
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447
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Bi C, Chung TH, Huang G, Zhou J, Yan J, Ahmann GJ, Fonseca R, Chng WJ. Genome-wide pharmacologic unmasking identifies tumor suppressive microRNAs in multiple myeloma. Oncotarget 2016; 6:26508-18. [PMID: 26164366 PMCID: PMC4694918 DOI: 10.18632/oncotarget.4769] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2015] [Accepted: 06/25/2015] [Indexed: 01/09/2023] Open
Abstract
Epigenetic alterations have emerged as an important cause of microRNA (miRNA) deregulation. In Multiple Myeloma (MM), a few tumor suppressive miRNAs silenced by DNA hypermethylation have been reported, but so far there are few systemic investigations on epigenetically silenced miRNAs. We conducted genome-wide screening for tumor suppressive miRNAs epigenetically silenced in MM. Four Human MM Cell lines were treated with demethylating agent 5'azacytidine (5'aza). Consistently upregulated miRNAs include miR-155, miR-198, miR-135a*, miR-200c, miR-125a-3p, miR-188-5p, miR-483-5p, miR-663, and miR-630. Methylation array analysis revealed increased methylation at or near miRNA-associated CpG islands in MM patients. Ectopic restoration of miR-155, miR-198, miR-135a*, miR-200c, miR-663 and miR-483-5p significantly repressed MM cell proliferation, migration and colony formation. Furthermore, we derived a 33-gene signature from predicted miRNA target genes that were also upregulated in MM patients and associated with patient survival in three independent myeloma datasets. In summary, we have revealed important, epigenetically silenced tumor suppressive miRNAs by pharmacologic reversal of epigenetic silencing.
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Affiliation(s)
- Chonglei Bi
- Experimental Therapeutics, Cancer Science Institute of Singapore, Singapore.,Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Tae-Hoon Chung
- Experimental Therapeutics, Cancer Science Institute of Singapore, Singapore
| | - Gaofeng Huang
- Experimental Therapeutics, Cancer Science Institute of Singapore, Singapore
| | - Jianbiao Zhou
- Experimental Therapeutics, Cancer Science Institute of Singapore, Singapore
| | - Junli Yan
- Experimental Therapeutics, Cancer Science Institute of Singapore, Singapore
| | | | | | - Wee Joo Chng
- Experimental Therapeutics, Cancer Science Institute of Singapore, Singapore.,Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.,Department of Hematology-Oncology, National University Cancer Institute, National University Health System, Singapore
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448
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Lim AM, Wong NC, Pidsley R, Zotenko E, Corry J, Dobrovic A, Clark SJ, Rischin D, Solomon B. Genome-scale methylation assessment did not identify prognostic biomarkers in oral tongue carcinomas. Clin Epigenetics 2016; 8:74. [PMID: 27433284 PMCID: PMC4948090 DOI: 10.1186/s13148-016-0235-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2016] [Accepted: 06/06/2016] [Indexed: 01/01/2023] Open
Abstract
Background DNA methylation profiling of heterogeneous head and neck squamous cell carcinoma (HNSCC) cohorts has been reported to predict patient outcome. We investigated if a prognostic DNA methylation profile could be found in tumour tissue from a single uniform subsite, the oral tongue. The methylation status of 109 comprehensively annotated oral tongue squamous cell carcinoma (OTSCC) formalin-fixed paraffin-embedded (FFPE) samples from a single institution were examined with the Illumina HumanMethylation450K (HM450K) array. Data pre-processing, quality control and analysis were performed using R packages. Probes mapping to SNPs, sex chromosomes and unreliable probes were accounted for prior to downstream analyses. The relationship between methylation and patient survival was examined using both agnostic approaches and feature selection. The cohort was enlarged by incorporation of 331 The Cancer Genome Atlas (TCGA) HNSCC samples, which included 91 TCGA OTSCC samples with HM450K and survival data available. Results Given the use of FFPE-derived DNA, we defined different cohorts for separate analyses. Overall, similar results were found between cohorts. With an unsupervised approach, no distinct hypermethylated group of samples was identified and nor was a prognostic methylation profile identified. The use of multiple downstream feature selection approaches, including a linear models for microarray data (LIMMA), centroid feature selection (CFS), and recursive feature elimination (RFE) support vector machines, similarly failed to identify a significant methylation signature informative for patient prognosis or any clinicopathological data available. Furthermore, we were unable to confirm the prognostic methylation profiles or specific prognostic loci reported within the literature for HNSCC. Conclusions With genome-scale assessment of DNA methylation using HM450K in one of the largest OTSCC cohorts to date, we were unable to identify a hypermethylated group of tumours or a prognostic methylation signature. This suggests that either DNA methylation in isolation is not likely to be of prognostic value or larger cohorts are required to identify such a biomarker for OTSCC. Electronic supplementary material The online version of this article (doi:10.1186/s13148-016-0235-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Annette M Lim
- Department of Medical Oncology, Sir Charles Gairdner Hospital, Hospital Ave, Nedlands, Western Australia 6009 Australia.,The University of Western Australia, Perth, Australia
| | - Nicholas C Wong
- Department of Paediatrics, The University of Melbourne, Parkville, Victoria 3010 Australia
| | - Ruth Pidsley
- Epigenetics Research Laboratory, Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst, New South Wales 2010 Australia
| | - Elena Zotenko
- Epigenetics Research Laboratory, Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst, New South Wales 2010 Australia
| | - June Corry
- Department of Radiation Oncology, Peter MacCallum Cancer Centre, Victorian Comprehensive Cancer Centre Building, 305 Grattan St, Melbourne, Victoria 3000 Australia
| | - Alexander Dobrovic
- The University of Melbourne, Melbourne, Australia.,Translational Genomics and Epigenomics Laboratory, Olivia Newton-John Cancer Research Institute, 145 Studley Rd, Heidelberg, Victoria 3084 Australia.,Department of Cancer Biology, La Trobe University, Bundoora, Victoria 3084 Australia
| | - Susan J Clark
- Epigenetics Research Laboratory, Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst, New South Wales 2010 Australia
| | - Danny Rischin
- Department of Medical Oncology, Peter MacCallum Cancer Centre, Victorian Comprehensive Cancer Centre Building, 305 Grattan St, Melbourne, Victoria 3000 Australia
| | - Benjamin Solomon
- Department of Medical Oncology, Peter MacCallum Cancer Centre, Victorian Comprehensive Cancer Centre Building, 305 Grattan St, Melbourne, Victoria 3000 Australia
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Cazaly E, Thomson R, Marthick JR, Holloway AF, Charlesworth J, Dickinson JL. Comparison of pre-processing methodologies for Illumina 450k methylation array data in familial analyses. Clin Epigenetics 2016; 8:75. [PMID: 27429663 PMCID: PMC4947255 DOI: 10.1186/s13148-016-0241-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2016] [Accepted: 06/26/2016] [Indexed: 02/06/2023] Open
Abstract
Background Human methylome mapping in health and disease states has largely relied on Illumina Human Methylation 450k array (450k array) technology. Accompanying this has been the necessary evolution of analysis pipelines to facilitate data processing. The majority of these pipelines, however, cater for experimental designs where matched ‘controls’ or ‘normal’ samples are available. Experimental designs where no appropriate ‘reference’ exists remain challenging. Herein, we use data generated from our study of the inheritance of methylome profiles in families to evaluate the performance of eight normalisation pre-processing methods. Fifty individual samples representing four families were interrogated on five 450k array BeadChips. Eight normalisation methods were tested using qualitative and quantitative metrics, to assess efficacy and suitability. Results Stratified quantile normalisation combined with ComBat were consistently found to be the most appropriate when assessed using density, MDS and cluster plots. This was supported quantitatively by ANOVA on the first principal component where the effect of batch dropped from p < 0.01 to p = 0.97 after stratified QN and ComBat. Median absolute differences between replicated samples were the lowest after stratified QN and ComBat as were the standard error measures on known imprinted regions. Biological information was preserved after normalisation as indicated by the maintenance of a significant association between a known mQTL and methylation (p = 1.05e-05). Conclusions A strategy combining stratified QN with ComBat is appropriate for use in the analyses when no reference sample is available but preservation of biological variation is paramount. There is great potential for use of 450k array data to further our understanding of the methylome in a variety of similar settings. Such advances will be reliant on the determination of appropriate methodologies for processing these data such as established here. Electronic supplementary material The online version of this article (doi:10.1186/s13148-016-0241-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Emma Cazaly
- Menzies Institute for Medical Research, University of Tasmania, Private Bag 23, Medical Sciences Building 2, Hobart, TAS Australia
| | - Russell Thomson
- Menzies Institute for Medical Research, University of Tasmania, Private Bag 23, Medical Sciences Building 2, Hobart, TAS Australia ; Centre for Research in Mathematics, School of Computing, Engineering and Mathematics, Western Sydney University, Parramatta Campus, Locked Bag 1797, Penrith, NSW 2751 Australia
| | - James R Marthick
- Menzies Institute for Medical Research, University of Tasmania, Private Bag 23, Medical Sciences Building 2, Hobart, TAS Australia
| | - Adele F Holloway
- School of Medicine, University of Tasmania, Medical Sciences Building 2, Hobart, TAS 7001 Australia
| | - Jac Charlesworth
- Menzies Institute for Medical Research, University of Tasmania, Private Bag 23, Medical Sciences Building 2, Hobart, TAS Australia
| | - Joanne L Dickinson
- Menzies Institute for Medical Research, University of Tasmania, Private Bag 23, Medical Sciences Building 2, Hobart, TAS Australia
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450
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Toraño EG, Bayón GF, Del Real Á, Sierra MI, García MG, Carella A, Belmonte T, Urdinguio RG, Cubillo I, García-Castro J, Delgado-Calle J, Pérez-Campo FM, Riancho JA, Fraga MF, Fernández AF. Age-associated hydroxymethylation in human bone-marrow mesenchymal stem cells. J Transl Med 2016; 14:207. [PMID: 27393146 PMCID: PMC4938941 DOI: 10.1186/s12967-016-0966-x] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2016] [Accepted: 07/01/2016] [Indexed: 12/20/2022] Open
Abstract
Background Age-associated changes in genomic DNA methylation have been primarily attributed to 5-methylcytosine (5mC). However, the recent discovery of 5-hydroxymethylcytosine (5hmC) suggests that this epigenetic mark might also play a role in the process. Methods Here, we analyzed the genome-wide profile of 5hmc in mesenchymal stem cells (MSCs) obtained from bone-marrow donors, aged 2–89 years. Results We identified 10,685 frequently hydroxymethylated CpG sites in MSCs that were, as in other cell types, significantly associated with low density CpG regions, introns, the histone posttranslational modification H3k4me1 and enhancers. Study of the age-associated changes to 5hmC identified 785 hyper- and 846 hypo-hydroxymethylated CpG sites in the MSCs obtained from older individuals. Conclusions DNA hyper-hydroxymethylation in the advanced-age group was associated with loss of 5mC, which suggests that, at specific CpG sites, this epigenetic modification might play a role in DNA methylation changes during lifetime. Since bone-marrow MSCs have many clinical applications, and the fact that the epigenomic alterations in this cell type associated with aging identified in this study could have associated functional effects, the age of donors should be taken into account in clinical settings. Electronic supplementary material The online version of this article (doi:10.1186/s12967-016-0966-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Estela G Toraño
- Cancer Epigenetics Laboratory, Institute of Oncology of Asturias (IUOPA), HUCA, Universidad de Oviedo, Oviedo, Spain
| | - Gustavo F Bayón
- Cancer Epigenetics Laboratory, Institute of Oncology of Asturias (IUOPA), HUCA, Universidad de Oviedo, Oviedo, Spain
| | - Álvaro Del Real
- Cancer Epigenetics Laboratory, Institute of Oncology of Asturias (IUOPA), HUCA, Universidad de Oviedo, Oviedo, Spain
| | - Marta I Sierra
- Cancer Epigenetics Laboratory, Institute of Oncology of Asturias (IUOPA), HUCA, Universidad de Oviedo, Oviedo, Spain
| | - María G García
- Cancer Epigenetics Laboratory, Institute of Oncology of Asturias (IUOPA), HUCA, Universidad de Oviedo, Oviedo, Spain
| | - Antonella Carella
- Cancer Epigenetics Laboratory, Institute of Oncology of Asturias (IUOPA), HUCA, Universidad de Oviedo, Oviedo, Spain
| | - Thalia Belmonte
- Cancer Epigenetics Laboratory, Institute of Oncology of Asturias (IUOPA), HUCA, Universidad de Oviedo, Oviedo, Spain
| | - Rocío G Urdinguio
- Cancer Epigenetics Laboratory, Institute of Oncology of Asturias (IUOPA), HUCA, Universidad de Oviedo, Oviedo, Spain
| | - Isabel Cubillo
- Unidad de Biotecnología Celular, Área de Genética Humana, Instituto de Salud Carlos III, Madrid, Spain
| | - Javier García-Castro
- Unidad de Biotecnología Celular, Área de Genética Humana, Instituto de Salud Carlos III, Madrid, Spain
| | - Jesús Delgado-Calle
- Department of Internal Medicine, Hospital U.M. Valdecilla, University of Cantabria, IDIVAL, Santander, Spain
| | - Flor M Pérez-Campo
- Department of Internal Medicine, Hospital U.M. Valdecilla, University of Cantabria, IDIVAL, Santander, Spain
| | - José A Riancho
- Department of Internal Medicine, Hospital U.M. Valdecilla, University of Cantabria, IDIVAL, Santander, Spain
| | - Mario F Fraga
- Nanomaterials and Nanotechnology Research Center (CINN-CSIC)-Universidad de Oviedo-Principado de Asturias, El Entrego, Spain.
| | - Agustín F Fernández
- Cancer Epigenetics Laboratory, Institute of Oncology of Asturias (IUOPA), HUCA, Universidad de Oviedo, Oviedo, Spain.
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