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Musanabaganwa C, Wani AH, Donglasan J, Fatumo S, Jansen S, Mutabaruka J, Rutembesa E, Uwineza A, Hermans EJ, Roozendaal B, Wildman DE, Mutesa L, Uddin M. Leukocyte methylomic imprints of exposure to the genocide against the Tutsi in Rwanda: a pilot epigenome-wide analysis. Epigenomics 2022; 14:11-25. [PMID: 34875875 PMCID: PMC8672329 DOI: 10.2217/epi-2021-0310] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Aim & methods: We conducted a pilot epigenome-wide association study of women from Tutsi ethnicity exposed to the genocide while pregnant and their resulting offspring, and a comparison group of women who were pregnant at the time of the genocide but living outside of Rwanda.Results: Fifty-nine leukocyte-derived DNA samples survived quality control: 33 mothers (20 exposed, 13 unexposed) and 26 offspring (16 exposed, 10 unexposed). Twenty-four significant differentially methylated regions (DMRs) were identified in mothers and 16 in children. Conclusions:In utero genocide exposure was associated with CpGs in three of the 24 DMRs: BCOR, PRDM8 and VWDE, with higher DNA methylation in exposed versus unexposed offspring. Of note, BCOR and VWDE show significant correlation between brain and blood DNA methylation within individuals, suggesting these peripherally derived signals of genocide exposure may have relevance to the brain.
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Affiliation(s)
- Clarisse Musanabaganwa
- Centre for Human Genetics, College of Medicine & Health Sciences, University of Rwanda, Kigali, Rwanda,Department of Clinical Psychology, College of Medicine & Health Sciences, University of Rwanda, Huye, Rwanda,Genomics Program, College of Public Health, University of South Florida, Tampa, FL, USA,Department of Cognitive Neuroscience, Radboud University Medical Center – Donders Institute for Brain, Cognition & Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Agaz H Wani
- Genomics Program, College of Public Health, University of South Florida, Tampa, FL, USA
| | - Janelle Donglasan
- Genomics Program, College of Public Health, University of South Florida, Tampa, FL, USA
| | - Segun Fatumo
- London School of Hygiene & Tropical Medicine, London, UK,Uganda Medical Informatics Centre-MRC/UVRI, Entebbe, Uganda
| | - Stefan Jansen
- Directorate of Research & Innovation, College of Medicine & Health Sciences, University of Rwanda, Kigali, Rwanda
| | - Jean Mutabaruka
- Department of Clinical Psychology, College of Medicine & Health Sciences, University of Rwanda, Huye, Rwanda
| | - Eugene Rutembesa
- Department of Clinical Psychology, College of Medicine & Health Sciences, University of Rwanda, Huye, Rwanda
| | - Annette Uwineza
- Centre for Human Genetics, College of Medicine & Health Sciences, University of Rwanda, Kigali, Rwanda
| | - Erno J Hermans
- Department of Cognitive Neuroscience, Radboud University Medical Center – Donders Institute for Brain, Cognition & Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Benno Roozendaal
- Department of Cognitive Neuroscience, Radboud University Medical Center – Donders Institute for Brain, Cognition & Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Derek E Wildman
- Genomics Program, College of Public Health, University of South Florida, Tampa, FL, USA
| | - Leon Mutesa
- Centre for Human Genetics, College of Medicine & Health Sciences, University of Rwanda, Kigali, Rwanda
| | - Monica Uddin
- Genomics Program, College of Public Health, University of South Florida, Tampa, FL, USA,Author for correspondence:
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Yu C, Wong EM, Joo JE, Hodge AM, Makalic E, Schmidt D, Buchanan DD, Severi G, Hopper JL, English DR, Giles GG, Southey MC, Dugué PA. Epigenetic Drift Association with Cancer Risk and Survival, and Modification by Sex. Cancers (Basel) 2021; 13:cancers13081881. [PMID: 33919912 PMCID: PMC8070898 DOI: 10.3390/cancers13081881] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 04/09/2021] [Accepted: 04/10/2021] [Indexed: 01/13/2023] Open
Abstract
Simple Summary Ageing is the strongest cancer risk factor, and men and women exhibit different risk profiles in terms of incidence and survival. DNA methylation is known to strongly vary by age and sex. Epigenetic drift refers to age-related DNA methylation changes and the tendency for increasing discordance between epigenomes over time, but it remains unknown to what extent the epigenetic drift contributes to cancer risk and survival. The aims of this study were to identify age-associated, sex-associated and sexually dimorphic age-associated (age-by-sex-associated) DNA methylation markers and investigate whether age- and age-by-sex-associated markers are associated with cancer risk and survival. Our study, which used a total of 2754 matched case–control pairs with DNA methylation in pre-diagnostic blood, is the first large study to examine the association between sex-specific epigenetic drift and cancer development and progression. The results may be useful for cancer early diagnosis and prediction of prognosis. Abstract To investigate age- and sex-specific DNA methylation alterations related to cancer risk and survival, we used matched case–control studies of colorectal (n = 835), gastric (n = 170), kidney (n = 143), lung (n = 332), prostate (n = 869) and urothelial (n = 428) cancers, and mature B-cell lymphoma (n = 438). Linear mixed-effects models were conducted to identify age-, sex- and age-by-sex-associated methylation markers using a discovery (controls)-replication (cases) strategy. Replication was further examined using summary statistics from Generation Scotland (GS). Associations between replicated markers and risk of and survival from cancer were assessed using conditional logistic regression and Cox models (hazard ratios (HR)), respectively. We found 32,659, 23,141 and 48 CpGs with replicated associations for age, sex and age-by-sex, respectively. The replication rates for these CpGs using GS summary data were 94%, 86% and 91%, respectively. Significant associations for cancer risk and survival were identified at some individual age-related CpGs. Opposite to previous findings using epigenetic clocks, there was a strong negative trend in the association between epigenetic drift and risk of colorectal cancer. Methylation at two CpGs overlapping TMEM49 and ARX genes was associated with survival of overall (HR = 0.91, p = 7.7 × 10−4) and colorectal (HR = 1.52, p = 1.8 × 10−4) cancer, respectively, with significant age-by-sex interaction. Our results may provide markers for cancer early detection and prognosis prediction.
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Affiliation(s)
- Chenglong Yu
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; (C.Y.); (E.M.W.); (G.G.G.); (M.C.S.)
| | - Ee Ming Wong
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; (C.Y.); (E.M.W.); (G.G.G.); (M.C.S.)
- Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Jihoon Eric Joo
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, VIC 3010, Australia; (J.E.J.); (D.D.B.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, VIC 3010, Australia
| | - Allison M. Hodge
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia; (A.M.H.); (D.R.E.)
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3010, Australia; (E.M.); (D.S.); (J.L.H.)
| | - Enes Makalic
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3010, Australia; (E.M.); (D.S.); (J.L.H.)
| | - Daniel Schmidt
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3010, Australia; (E.M.); (D.S.); (J.L.H.)
| | - Daniel D. Buchanan
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, VIC 3010, Australia; (J.E.J.); (D.D.B.)
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, VIC 3010, Australia
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, VIC 3000, Australia
| | - Gianluca Severi
- Centre de Recherche en Epidémiologie et Santé des Populations (CESP, Inserm U1018), Facultés de Médecine Universités Paris-Saclay, UVSQ, Gustave Roussy, 94805 Villejuif, France;
- Department of Statistics, Computer Science and Applications “G. Parenti”, University of Florence, 50121 Firenze, Italy
| | - John L. Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3010, Australia; (E.M.); (D.S.); (J.L.H.)
| | - Dallas R. English
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia; (A.M.H.); (D.R.E.)
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3010, Australia; (E.M.); (D.S.); (J.L.H.)
| | - Graham G. Giles
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; (C.Y.); (E.M.W.); (G.G.G.); (M.C.S.)
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia; (A.M.H.); (D.R.E.)
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3010, Australia; (E.M.); (D.S.); (J.L.H.)
| | - Melissa C. Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; (C.Y.); (E.M.W.); (G.G.G.); (M.C.S.)
- Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, VIC 3010, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia; (A.M.H.); (D.R.E.)
| | - Pierre-Antoine Dugué
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia; (C.Y.); (E.M.W.); (G.G.G.); (M.C.S.)
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia; (A.M.H.); (D.R.E.)
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3010, Australia; (E.M.); (D.S.); (J.L.H.)
- Correspondence:
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Di Risi T, Vinciguerra R, Cuomo M, Della Monica R, Riccio E, Cocozza S, Imbriaco M, Duro G, Pisani A, Chiariotti L. DNA methylation impact on Fabry disease. Clin Epigenetics 2021; 13:24. [PMID: 33531072 PMCID: PMC7852133 DOI: 10.1186/s13148-021-01019-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Accepted: 01/25/2021] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Fabry disease (FD) is a rare X-linked disease caused by mutations in GLA gene with consequent lysosomal accumulation of globotriaosylceramide (Gb3). Women with FD often show highly heterogeneous symptoms that can manifest from mild to severe phenotype. MAIN BODY The phenotypic variability of the clinical manifestations in heterozygous women with FD mainly depends on the degree and direction of inactivation of the X chromosome. Classical approaches to measure XCI skewness might be not sufficient to explain disease manifestation in women. In addition to unbalanced XCI, allele-specific DNA methylation at promoter of GLA gene may influence the expression levels of the mutated allele, thus impacting the onset and the outcome of FD. In this regard, analyses of DNA methylation at GLA promoter, performed by approaches allowing distinction between mutated and non-mutated allele, may be much more informative. The aim of this review is to critically evaluate recent literature articles addressing the potential role of DNA methylation in the context of FD. Although up to date relatively few works have addressed this point, reviewing all pertinent studies may help to evaluate the importance of DNA methylation analysis in FD and to develop new research and technologies aimed to predict whether the carrier females will develop symptoms. CONCLUSIONS Relatively few studies have addressed the complexity of DNA methylation landscape in FD that remains poorly investigated. The hope for the future is that ad hoc and ultradeep methylation analyses of GLA gene will provide epigenetic signatures able to predict whether pre-symptomatic female carriers will develop symptoms thus helping timely interventions.
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Affiliation(s)
- Teodolinda Di Risi
- CEINGE - Biotecnologie Avanzate, Via Gaetano Salvatore, 486, 80145, Naples, Italy
- Department of Public Health, University Federico II of Naples, Via S. Pansini, 5, 80131, Naples, Italy
| | - Roberta Vinciguerra
- CEINGE - Biotecnologie Avanzate, Via Gaetano Salvatore, 486, 80145, Naples, Italy
- Department of Public Health, University Federico II of Naples, Via S. Pansini, 5, 80131, Naples, Italy
| | - Mariella Cuomo
- CEINGE - Biotecnologie Avanzate, Via Gaetano Salvatore, 486, 80145, Naples, Italy
- Department of Molecular Medicine and Medical Biotechnology, University Federico II of Naples, Via S. Pansini, 5, 80131, Naples, Italy
| | - Rosa Della Monica
- CEINGE - Biotecnologie Avanzate, Via Gaetano Salvatore, 486, 80145, Naples, Italy
| | - Eleonora Riccio
- Institute for Biomedical Research and Innovation, National Research Council of Italy (IRIB CNR), Palermo, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University Federico II of Naples, Via S. Pansini, 5, 80131, Naples, Italy
| | - Massimo Imbriaco
- Department of Advanced Biomedical Sciences, University Federico II of Naples, Via S. Pansini, 5, 80131, Naples, Italy
| | - Giovanni Duro
- Institute for Biomedical Research and Innovation, National Research Council of Italy (IRIB CNR), Palermo, Italy
| | - Antonio Pisani
- Department of Public Health, University Federico II of Naples, Via S. Pansini, 5, 80131, Naples, Italy
| | - Lorenzo Chiariotti
- CEINGE - Biotecnologie Avanzate, Via Gaetano Salvatore, 486, 80145, Naples, Italy.
- Department of Molecular Medicine and Medical Biotechnology, University Federico II of Naples, Via S. Pansini, 5, 80131, Naples, Italy.
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4
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Ultra-Deep DNA Methylation Analysis of X-Linked Genes: GLA and AR as Model Genes. Genes (Basel) 2020; 11:genes11060620. [PMID: 32512878 PMCID: PMC7349208 DOI: 10.3390/genes11060620] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 05/28/2020] [Accepted: 06/02/2020] [Indexed: 12/19/2022] Open
Abstract
Recessive X-linked disorders may occasionally evolve in clinical manifestations of variable severity also in female carriers. For some of such diseases, the frequency of the symptoms’ appearance during women’s life may be particularly relevant. This phenomenon has been largely attributed to the potential skewness of the X-inactivation process leading to variable phenotypes. Nonetheless, in many cases, no correlation with X-inactivation unbalance was demonstrated. However, methods for analyzing skewness have been mainly limited to Human Androgen Receptor methylation analysis (HUMARA). Recently, the X-inactivation process has been largely revisited, highlighting the heterogeneity existing among loci in the epigenetic state within inactive and, possibly, active X-chromosomes. We reasoned that gene-specific and ultra-deep DNA methylation analyses could greatly help to unravel details of the X-inactivation process and the roles of specific X genes inactivation in disease manifestations. We recently provided evidence that studying DNA methylation at specific autosomic loci at a single-molecule resolution (epiallele distribution analysis) allows one to analyze cell-to-cell methylation differences in a given cell population. We here apply the epiallele analysis at two X-linked loci to investigate whether females show allele-specific epiallelic patterns. Due to the high potential of this approach, the method allows us to obtain clearly distinct allele-specific epiallele profiles.
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5
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Li S, Lund JB, Christensen K, Baumbach J, Mengel-From J, Kruse T, Li W, Mohammadnejad A, Pattie A, Marioni RE, Deary IJ, Tan Q. Exploratory analysis of age and sex dependent DNA methylation patterns on the X-chromosome in whole blood samples. Genome Med 2020; 12:39. [PMID: 32345361 PMCID: PMC7189689 DOI: 10.1186/s13073-020-00736-3] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Accepted: 04/07/2020] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Large numbers of autosomal sites are found differentially methylated in the aging genome. Due to analytical difficulties in dealing with sex differences in X-chromosome content and X-inactivation (XCI) in females, this has not been explored for the X chromosome. METHODS Using data from middle age to elderly individuals (age 55+ years) from two Danish cohorts of monozygotic twins and the Scottish Lothian Birth Cohort 1921, we conducted an X-chromosome-wide analysis of age-associated DNA methylation patterns with consideration of stably inferred XCI status. RESULTS Through analysing and comparing sex-specific X-linked DNA methylation changes over age late in life, we identified 123, 293 and 55 CpG sites significant (FDR < 0.05) only in males, only in females and in both sexes of Danish twins. All findings were significantly replicated in the two Danish twin cohorts. CpG sites escaping XCI are predominantly de-methylated with increasing age across cohorts. In contrast, CpGs highly methylated in both sexes are methylated even further with increasing age. Among the replicated sites in Danish samples, 16 (13%), 24 (8.2%) and 3 (5.5%) CpGs were further validated in LBC1921 (FDR < 0.05). CONCLUSIONS The X-chromosome of whole blood leukocytes displays age- and sex-dependent DNA methylation patterns in relation to XCI across cohorts.
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Affiliation(s)
- Shuxia Li
- Epidemiology and Biostatistics, Department of Public Health, Faculty of Health Science, University of Southern Denmark, J. B. Winsløws Vej 9B, DK-5000, Odense C, Denmark
| | - Jesper B Lund
- Epidemiology and Biostatistics, Department of Public Health, Faculty of Health Science, University of Southern Denmark, J. B. Winsløws Vej 9B, DK-5000, Odense C, Denmark
| | - Kaare Christensen
- Epidemiology and Biostatistics, Department of Public Health, Faculty of Health Science, University of Southern Denmark, J. B. Winsløws Vej 9B, DK-5000, Odense C, Denmark.,Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Jan Baumbach
- Chair of Experimental Bioinformatics, TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany
| | - Jonas Mengel-From
- Epidemiology and Biostatistics, Department of Public Health, Faculty of Health Science, University of Southern Denmark, J. B. Winsløws Vej 9B, DK-5000, Odense C, Denmark
| | - Torben Kruse
- Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Weilong Li
- Epidemiology and Biostatistics, Department of Public Health, Faculty of Health Science, University of Southern Denmark, J. B. Winsløws Vej 9B, DK-5000, Odense C, Denmark
| | - Afsaneh Mohammadnejad
- Epidemiology and Biostatistics, Department of Public Health, Faculty of Health Science, University of Southern Denmark, J. B. Winsløws Vej 9B, DK-5000, Odense C, Denmark
| | - Alison Pattie
- Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, Scotland, UK.,Lothian Birth Cohorts, University of Edinburgh, Edinburgh, Scotland, UK
| | - Ian J Deary
- Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK.,Lothian Birth Cohorts, University of Edinburgh, Edinburgh, Scotland, UK
| | - Qihua Tan
- Epidemiology and Biostatistics, Department of Public Health, Faculty of Health Science, University of Southern Denmark, J. B. Winsløws Vej 9B, DK-5000, Odense C, Denmark. .,Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
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6
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Li S, Di D, Wu X, Zhang L, Liu R, Huang Q, Pan H, Ye D, Leng R. Association study between X-linked susceptibility genes and clinical features in Chinese female patients with systemic lupus erythematosus. Autoimmunity 2019; 52:289-293. [PMID: 31707854 DOI: 10.1080/08916934.2019.1688792] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2019] [Revised: 10/20/2019] [Accepted: 10/31/2019] [Indexed: 10/25/2022]
Abstract
Recent large-scale genetic association studies have identified that several single nucleotide polymorphisms (SNPs) on X chromosome are correlated with risk of systemic lupus erythematosus (SLE) in Chinese population. The aim of this study was to estimate association between these loci and clinical features in female patients with SLE. Six SNPs identified in previous studies were genotyped. Odds ratio (OR) was calculated with adjusting for potential confounding factors. A total of 772 SLE patients were included in the final analysis. The data showed that 3 SNPs (rs5914778, rs3853839 and rs1059702) were marginally associated with several clinical subphenotypes. Furthermore, consistent associations were also found in two independent cohorts. However, the cumulative genetic risk score (GRS) was not associated with clinical manifestations as well as the disease activity index at disease diagnosis. In summary, genetic variants in X-linked genes may be potentially associated with presence of specific clinical feature. Further studies in distinct ethnical populations are required to clarify the association between these loci and presence of SLE clinical features.
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Affiliation(s)
- Shen Li
- Department of Medical Services, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Dongsheng Di
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, China
| | - Xiaoxiao Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, China
| | - Linlin Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, China
| | - Ruishan Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, China
| | - Qian Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, China
| | - Haifeng Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, China
| | - Dongqing Ye
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, China
| | - Ruixue Leng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, China
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7
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Manca M, Pessoa V, Myers P, Pickles A, Hill J, Sharp H, Murgatroyd C, Bubb VJ, Quinn JP. Distinct chromatin structures at the monoamine oxidase-A promoter correlate with allele-specific expression in SH-SY5Y cells. GENES, BRAIN, AND BEHAVIOR 2019; 18:e12483. [PMID: 29667298 PMCID: PMC6617726 DOI: 10.1111/gbb.12483] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/02/2017] [Revised: 02/19/2018] [Accepted: 04/13/2018] [Indexed: 11/30/2022]
Abstract
Monoamine oxidase-A (MAOA) metabolises monoamines and is implicated in the pathophysiology of psychiatric disorders. A polymorphic repetitive DNA domain, termed the uVNTR (upstream variable number tandem repeat), located at the promoter of the MAOA gene is a risk factor for many of these disorders. MAOA is on the X chromosome suggesting gender could play a role in regulation. We analysed MAOA regulation in the human female cell line, SH-SY5Y, which is polymorphic for the uVNTR. This heterozygosity allowed us to correlate allele-specific gene expression with allele-specific transcription factor binding and epigenetic marks for MAOA. Gene regulation was analysed under basal conditions and in response to the mood stabiliser sodium valproate. Both alleles were transcriptionally active under basal growth conditions; however, the alleles showed distinct transcription factor binding and epigenetic marks at their respective promoters. Exposure of the cells to sodium valproate resulted in differential allelic expression which correlated with allele-specific changes in distinct transcription factor binding and epigenetic marks at the region encompassing the uVNTR. Biochemically our model for MAOA promoter function has implications for gender differences in gene × environment responses in which the uVNTR has been implicated as a genetic risk.
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Affiliation(s)
- M. Manca
- Department of Molecular and Clinical Pharmacology, Institute of Translational MedicineUniversity of LiverpoolLiverpoolUK
- Institute of Psychology, Health and SocietyUniversity of LiverpoolLiverpoolUK
| | - V. Pessoa
- Department of Molecular and Clinical Pharmacology, Institute of Translational MedicineUniversity of LiverpoolLiverpoolUK
- Institute of Psychology, Health and SocietyUniversity of LiverpoolLiverpoolUK
| | - P. Myers
- Department of Molecular and Clinical Pharmacology, Institute of Translational MedicineUniversity of LiverpoolLiverpoolUK
| | - A. Pickles
- King's College London, MRC Social Genetic and Developmental Psychiatry Research CentreInstitute of PsychiatryLondonUK
| | - J. Hill
- School for Psychology and Clinical Language SciencesUniversity of ReadingReadingUK
| | - H. Sharp
- Institute of Psychology, Health and SocietyUniversity of LiverpoolLiverpoolUK
| | - C. Murgatroyd
- School of Healthcare ScienceManchester Metropolitan UniversityManchesterUK
| | - V. J. Bubb
- Department of Molecular and Clinical Pharmacology, Institute of Translational MedicineUniversity of LiverpoolLiverpoolUK
| | - J. P. Quinn
- Department of Molecular and Clinical Pharmacology, Institute of Translational MedicineUniversity of LiverpoolLiverpoolUK
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8
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Jung CH, Park DJ, Georgeson P, Mahmood K, Milne RL, Southey MC, Pope BJ. sEst: Accurate Sex-Estimation and Abnormality Detection in Methylation Microarray Data. Int J Mol Sci 2018; 19:ijms19103172. [PMID: 30326623 PMCID: PMC6213967 DOI: 10.3390/ijms19103172] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Revised: 10/08/2018] [Accepted: 10/09/2018] [Indexed: 01/21/2023] Open
Abstract
DNA methylation influences predisposition, development and prognosis for many diseases, including cancer. However, it is not uncommon to encounter samples with incorrect sex labelling or atypical sex chromosome arrangement. Sex is one of the strongest influencers of the genomic distribution of DNA methylation and, therefore, correct assignment of sex and filtering of abnormal samples are essential for the quality control of study data. Differences in sex chromosome copy numbers between sexes and X-chromosome inactivation in females result in distinctive sex-specific patterns in the distribution of DNA methylation levels. In this study, we present a software tool, sEst, which incorporates clustering analysis to infer sex and to detect sex-chromosome abnormalities from DNA methylation microarray data. Testing with two publicly available datasets demonstrated that sEst not only correctly inferred the sex of the test samples, but also identified mislabelled samples and samples with potential sex-chromosome abnormalities, such as Klinefelter syndrome and Turner syndrome, the latter being a feature not offered by existing methods. Considering that sex and the sex-chromosome abnormalities can have large effects on many phenotypes, including diseases, our method can make a significant contribution to DNA methylation studies that are based on microarray platforms.
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Affiliation(s)
- Chol-Hee Jung
- Melbourne Bioinformatics, The University of Melbourne, Parkville, VIC 3010, Australia.
| | - Daniel J Park
- Melbourne Bioinformatics, The University of Melbourne, Parkville, VIC 3010, Australia.
| | - Peter Georgeson
- Melbourne Bioinformatics, The University of Melbourne, Parkville, VIC 3010, Australia.
- Department of Clinical Pathology, The University of Melbourne, Parkville, VIC 3010, Australia.
| | - Khalid Mahmood
- Melbourne Bioinformatics, The University of Melbourne, Parkville, VIC 3010, Australia.
| | - Roger L Milne
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia.
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3010, Australia.
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia.
| | - Melissa C Southey
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia.
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia.
- Genetic Epidemiology Laboratory, The University of Melbourne, Parkville, VIC 3010, Australia.
| | - Bernard J Pope
- Melbourne Bioinformatics, The University of Melbourne, Parkville, VIC 3010, Australia.
- Department of Clinical Pathology, The University of Melbourne, Parkville, VIC 3010, Australia.
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3010, Australia.
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9
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Dosage compensation and DNA methylation landscape of the X chromosome in mouse liver. Sci Rep 2018; 8:10138. [PMID: 29973619 PMCID: PMC6031675 DOI: 10.1038/s41598-018-28356-3] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2017] [Accepted: 06/18/2018] [Indexed: 01/01/2023] Open
Abstract
DNA methylation plays a key role in X-chromosome inactivation (XCI), a process that achieves dosage compensation for X-encoded gene products between mammalian female and male cells. However, differential sex chromosome dosage complicates genome-wide epigenomic assessments, and the X chromosome is frequently excluded from female-to-male comparative analyses. Using the X chromosome in the sexually dimorphic mouse liver as a model, we provide a general framework for comparing base-resolution DNA methylation patterns across samples that have different chromosome numbers and ask at a systematic level if predictions by historical analyses of X-linked DNA methylation hold true at a base-resolution chromosome-wide level. We demonstrate that sex-specific methylation patterns on the X chromosome largely reflect the effects of XCI. While our observations concur with longstanding observations of XCI at promoter-proximal CpG islands, we provide evidence that sex-specific DNA methylation differences are not limited to CpG island boundaries. Moreover, these data support a model in which maintenance of CpG islands in the inactive state does not require complete regional methylation. Further, we validate an intragenic non-CpG methylation signature in genes escaping XCI in mouse liver. Our analyses provide insight into underlying methylation patterns that should be considered when assessing sex differences in genome-wide methylation analyses.
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10
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Rajpathak SN, Deobagkar DD. Aneuploidy: an important model system to understand salient aspects of functional genomics. Brief Funct Genomics 2018; 17:181-190. [PMID: 29228117 DOI: 10.1093/bfgp/elx041] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Maintaining a balance in gene dosage and protein activity is essential to sustain normal cellular functions. Males and females have a wide range of genetic as well as epigenetic differences, where X-linked gene dosage is an essential regulatory factor. Basic understanding of gene dosage maintenance has emerged from the studies carried out using mouse models with FCG (four core genotype) and chromosomal aneuploidy as well as from mono-chromosomal hybrid cells. In mammals, aneuploidy often leads to embryonic lethality particularly in early development with major developmental and structural abnormalities. Thus, in-depth analysis of the causes and consequences of gene dosage alterations is needed to unravel its effects on basic cellular and developmental functions as well as in understanding its medical implications. Cells isolated from individuals with naturally occurring chromosomal aneuploidy can be considered as true representatives, as these cells have stable chromosomal alterations/gene dosage imbalance, which have occurred by modulation of the basic molecular machinery. Therefore, innovative use of these natural aneuploidy cells/organisms with recent molecular and high-throughput techniques will provide an understanding of the basic mechanisms involved in gene dosage balance and the related consequences for functional genomics.
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11
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Allele-specific non-CG DNA methylation marks domains of active chromatin in female mouse brain. Proc Natl Acad Sci U S A 2017; 114:E2882-E2890. [PMID: 28320934 DOI: 10.1073/pnas.1611905114] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
DNA methylation at gene promoters in a CG context is associated with transcriptional repression, including at genes silenced on the inactive X chromosome in females. Non-CG methylation (mCH) is a distinct feature of the neuronal epigenome that is differentially distributed between males and females on the X chromosome. However, little is known about differences in mCH on the active (Xa) and inactive (Xi) X chromosomes because stochastic X-chromosome inactivation (XCI) confounds allele-specific epigenomic profiling. We used whole-genome bisulfite sequencing in a mouse model with nonrandom XCI to examine allele-specific DNA methylation in frontal cortex. Xi was largely devoid of mCH, whereas Xa contained abundant mCH similar to the male X chromosome and the autosomes. In contrast to the repressive association of DNA methylation at CG dinucleotides (mCG), mCH accumulates on Xi in domains with transcriptional activity, including the bodies of most genes that escape XCI and at the X-inactivation center, validating this epigenetic mark as a signature of transcriptional activity. Escape genes showing CH hypermethylation were the only genes with CG-hypomethylated promoters on Xi, a well-known mark of active transcription. Finally, we found extensive allele-specific mCH and mCG at autosomal imprinted regions, some with a negative correlation between methylation in the two contexts, further supporting their distinct functions. Our findings show that neuronal mCH functions independently of mCG and is a highly dynamic epigenomic correlate of allele-specific gene regulation.
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12
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Machiela MJ, Zhou W, Karlins E, Sampson JN, Freedman ND, Yang Q, Hicks B, Dagnall C, Hautman C, Jacobs KB, Abnet CC, Aldrich MC, Amos C, Amundadottir LT, Arslan AA, Beane-Freeman LE, Berndt SI, Black A, Blot WJ, Bock CH, Bracci PM, Brinton LA, Bueno-de-Mesquita HB, Burdett L, Buring JE, Butler MA, Canzian F, Carreón T, Chaffee KG, Chang IS, Chatterjee N, Chen C, Chen C, Chen K, Chung CC, Cook LS, Crous Bou M, Cullen M, Davis FG, De Vivo I, Ding T, Doherty J, Duell EJ, Epstein CG, Fan JH, Figueroa JD, Fraumeni JF, Friedenreich CM, Fuchs CS, Gallinger S, Gao YT, Gapstur SM, Garcia-Closas M, Gaudet MM, Gaziano JM, Giles GG, Gillanders EM, Giovannucci EL, Goldin L, Goldstein AM, Haiman CA, Hallmans G, Hankinson SE, Harris CC, Henriksson R, Holly EA, Hong YC, Hoover RN, Hsiung CA, Hu N, Hu W, Hunter DJ, Hutchinson A, Jenab M, Johansen C, Khaw KT, Kim HN, Kim YH, Kim YT, Klein AP, Klein R, Koh WP, Kolonel LN, Kooperberg C, Kraft P, Krogh V, Kurtz RC, LaCroix A, Lan Q, Landi MT, Marchand LL, Li D, Liang X, Liao LM, Lin D, Liu J, Lissowska J, Lu L, Magliocco AM, Malats N, Matsuo K, McNeill LH, McWilliams RR, Melin BS, Mirabello L, Moore L, Olson SH, Orlow I, Park JY, Patiño-Garcia A, Peplonska B, Peters U, Petersen GM, Pooler L, Prescott J, Prokunina-Olsson L, Purdue MP, Qiao YL, Rajaraman P, Real FX, Riboli E, Risch HA, Rodriguez-Santiago B, Ruder AM, Savage SA, Schumacher F, Schwartz AG, Schwartz KL, Seow A, Wendy Setiawan V, Severi G, Shen H, Sheng X, Shin MH, Shu XO, Silverman DT, Spitz MR, Stevens VL, Stolzenberg-Solomon R, Stram D, Tang ZZ, Taylor PR, Teras LR, Tobias GS, Van Den Berg D, Visvanathan K, Wacholder S, Wang JC, Wang Z, Wentzensen N, Wheeler W, White E, Wiencke JK, Wolpin BM, Wong MP, Wu C, Wu T, Wu X, Wu YL, Wunder JS, Xia L, Yang HP, Yang PC, Yu K, Zanetti KA, Zeleniuch-Jacquotte A, Zheng W, Zhou B, Ziegler RG, Perez-Jurado LA, Caporaso NE, Rothman N, Tucker M, Dean MC, Yeager M, Chanock SJ. Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome. Nat Commun 2016; 7:11843. [PMID: 27291797 PMCID: PMC4909985 DOI: 10.1038/ncomms11843] [Citation(s) in RCA: 76] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2015] [Accepted: 05/06/2016] [Indexed: 02/07/2023] Open
Abstract
To investigate large structural clonal mosaicism of chromosome X, we analysed the SNP microarray intensity data of 38,303 women from cancer genome-wide association studies (20,878 cases and 17,425 controls) and detected 124 mosaic X events >2 Mb in 97 (0.25%) women. Here we show rates for X-chromosome mosaicism are four times higher than mean autosomal rates; X mosaic events more often include the entire chromosome and participants with X events more likely harbour autosomal mosaic events. X mosaicism frequency increases with age (0.11% in 50-year olds; 0.45% in 75-year olds), as reported for Y and autosomes. Methylation array analyses of 33 women with X mosaicism indicate events preferentially involve the inactive X chromosome. Our results provide further evidence that the sex chromosomes undergo mosaic events more frequently than autosomes, which could have implications for understanding the underlying mechanisms of mosaic events and their possible contribution to risk for chronic diseases.
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Affiliation(s)
- Mitchell J. Machiela
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Weiyin Zhou
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
- Cancer Genomics Research Laboratory, National Cancer Institute, Division of Cancer Epidemiology and Genetics, Leidos Biomedical Research Inc., Bethesda, Maryland 20892, USA
| | - Eric Karlins
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
- Cancer Genomics Research Laboratory, National Cancer Institute, Division of Cancer Epidemiology and Genetics, Leidos Biomedical Research Inc., Bethesda, Maryland 20892, USA
| | - Joshua N. Sampson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Neal D. Freedman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Qi Yang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
- Cancer Genomics Research Laboratory, National Cancer Institute, Division of Cancer Epidemiology and Genetics, Leidos Biomedical Research Inc., Bethesda, Maryland 20892, USA
| | - Belynda Hicks
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
- Cancer Genomics Research Laboratory, National Cancer Institute, Division of Cancer Epidemiology and Genetics, Leidos Biomedical Research Inc., Bethesda, Maryland 20892, USA
| | - Casey Dagnall
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
- Cancer Genomics Research Laboratory, National Cancer Institute, Division of Cancer Epidemiology and Genetics, Leidos Biomedical Research Inc., Bethesda, Maryland 20892, USA
| | - Christopher Hautman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
- Cancer Genomics Research Laboratory, National Cancer Institute, Division of Cancer Epidemiology and Genetics, Leidos Biomedical Research Inc., Bethesda, Maryland 20892, USA
| | - Kevin B. Jacobs
- Cancer Genomics Research Laboratory, National Cancer Institute, Division of Cancer Epidemiology and Genetics, Leidos Biomedical Research Inc., Bethesda, Maryland 20892, USA
- Bioinformed, LLC, Gaithersburg, Maryland 20877, USA
| | - Christian C. Abnet
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Melinda C. Aldrich
- Department of Thoracic Surgery, Vanderbilt University School of Medicine, Nashville, Tennessee 37232, USA
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA
| | - Christopher Amos
- Department of Epidemiology, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA
| | - Laufey T. Amundadottir
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Alan A. Arslan
- Department of Obstetrics and Gynecology, New York University School of Medicine, New York, New York 10016, USA
- Department of Environmental Medicine, New York University School of Medicine, New York, New York 10016, USA
- New York University Cancer Institute, New York, New York 10016, USA
| | - Laura E. Beane-Freeman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Sonja I. Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Amanda Black
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - William J. Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA
- International Epidemiology Institute, Rockville, Maryland 20850, USA
| | - Cathryn H. Bock
- Karmanos Cancer Institute and Department of Oncology, Wayne State University School of Medicine, Detroit, Michigan 48201, USA
| | - Paige M. Bracci
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California 94143, USA
| | - Louise A. Brinton
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - H Bas Bueno-de-Mesquita
- Department for Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM), 3721 Bilthoven, The Netherlands
- Department of Gastroenterology and Hepatology, University Medical Center, 3584 CX Utrecht, The Netherlands
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London SW7 2AZ, UK
- Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur 50603, Malaysia
| | - Laurie Burdett
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
- Cancer Genomics Research Laboratory, National Cancer Institute, Division of Cancer Epidemiology and Genetics, Leidos Biomedical Research Inc., Bethesda, Maryland 20892, USA
| | - Julie E. Buring
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts 02115, USA
| | - Mary A. Butler
- National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Cincinnati, Ohio 45226, USA
| | - Federico Canzian
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Tania Carreón
- National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Cincinnati, Ohio 45226, USA
| | - Kari G. Chaffee
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota 55905, USA
| | - I-Shou Chang
- National Institute of Cancer Research, National Health Research Institutes, Zhunan 35053, Taiwan
| | - Nilanjan Chatterjee
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Chu Chen
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA
| | - Constance Chen
- Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, Massachusetts 02115, USA
| | - Kexin Chen
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300040, China
| | - Charles C. Chung
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
- Cancer Genomics Research Laboratory, National Cancer Institute, Division of Cancer Epidemiology and Genetics, Leidos Biomedical Research Inc., Bethesda, Maryland 20892, USA
| | - Linda S. Cook
- University of New Mexico, Albuquerque, New Mexico 87131, USA
| | - Marta Crous Bou
- Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, Massachusetts 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Michael Cullen
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
- Cancer Genomics Research Laboratory, National Cancer Institute, Division of Cancer Epidemiology and Genetics, Leidos Biomedical Research Inc., Bethesda, Maryland 20892, USA
| | - Faith G. Davis
- Department of Public Health Sciences, School of Public Health, University of Alberta, Edmonton, Alberta, Canada T6G 2R3
| | - Immaculata De Vivo
- Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, Massachusetts 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Ti Ding
- Shanxi Cancer Hospital, Taiyuan, Shanxi 030013, China
| | - Jennifer Doherty
- Geisel School of Medicine, Dartmouth College, Lebanon, New Hampshire 03755, USA
| | - Eric J. Duell
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Bellvitge Biomedical Research Institute, Catalan Institute of Oncology (ICO-IDIBELL), 08908 Barcelona, Spain
| | - Caroline G. Epstein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Jin-Hu Fan
- Shanghai Cancer Institute, Shanghai 200032, China
| | - Jonine D. Figueroa
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Joseph F. Fraumeni
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Christine M. Friedenreich
- Department of Population Health Research, Cancer Control Alberta, Alberta Health Services, Calgary, Alberta, Canada T2N 2T9
| | - Charles S. Fuchs
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA
| | - Steven Gallinger
- Fred A Litwin Centre for Cancer Genetics, Samuel Lunenfeld Research Institute, Toronto, Ontario, Canada M5G 1X5
| | - Yu-Tang Gao
- Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotaong University School of Medicine, Shanghai 200032, China
| | - Susan M. Gapstur
- Epidemiology Research Program, American Cancer Society, Atlanta, Georgia 30303, USA
| | - Montserrat Garcia-Closas
- Division of Genetics and Epidemiology, and Breakthrough Breast Cancer Centre, Institute for Cancer Research, London SM2 5NG, UK
| | - Mia M. Gaudet
- Epidemiology Research Program, American Cancer Society, Atlanta, Georgia 30303, USA
| | - J. Michael Gaziano
- Divisions of Preventive Medicine and Aging, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA
- Massachusetts Veterans Epidemiology Research and Information Center/VA Cooperative Studies Programs, Veterans Affairs Boston Healthcare System, Boston, Massachusetts 02130, USA
| | - Graham G. Giles
- Cancer Epidemiology Centre, Cancer Council Victoria & Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria 3010, Australia
| | - Elizabeth M. Gillanders
- Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland 20892, USA
| | - Edward L. Giovannucci
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA
- Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts 02115, USA
| | - Lynn Goldin
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Alisa M. Goldstein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Christopher A. Haiman
- Department of Preventive Medicine, Biostatistics Division, Keck School of Medicine at the University of Southern California, Los Angeles, California 90033, USA
| | - Goran Hallmans
- Department of Public Health and Clinical Medicine/Nutritional Research, Umeå University, 901 87 Umeå, Sweden
| | - Susan E. Hankinson
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA
- Division of Biostatistics and Epidemiology, University of Massachusetts School of Public Health and Health Sciences, Amherst, Massachusetts 01003, USA
| | - Curtis C. Harris
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland 20892, USA
| | - Roger Henriksson
- Department of Radiation Sciences, Oncology, Umeå University, 901 87 Umeå, Sweden
| | - Elizabeth A. Holly
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California 94143, USA
| | - Yun-Chul Hong
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul 151-742, Republic of Korea
| | - Robert N. Hoover
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Chao A. Hsiung
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan 35053, Taiwan
| | - Nan Hu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Wei Hu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - David J. Hunter
- Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, Massachusetts 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA
| | - Amy Hutchinson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
- Cancer Genomics Research Laboratory, National Cancer Institute, Division of Cancer Epidemiology and Genetics, Leidos Biomedical Research Inc., Bethesda, Maryland 20892, USA
| | - Mazda Jenab
- International Agency for Research on Cancer (IARC-WHO), 69372 Lyon, France
| | - Christoffer Johansen
- Oncology, Finsen Centre, Rigshospitalet, 2100 Copenhagen, Denmark
- Unit of Survivorship Research, The Danish Cancer Society Research Centre, 2100 Copenhagen, Denmark
| | - Kay-Tee Khaw
- School of Clinical Medicine, University of Cambridge, Cambridge CB2 1TN, UK
| | - Hee Nam Kim
- Center for Creative Biomedical Scientists, Chonnam National University, Gwangju 500-757, Republic of Korea
| | - Yeul Hong Kim
- Department of Internal Medicine, Division of Oncology/Hematology, College of Medicine, Korea University Anam Hospital, Seoul 151-742, Republic of Korea
| | - Young Tae Kim
- Department of Thoracic and Cardiovascular Surgery, Cancer Research Institute, Seoul National University College of Medicine, Seoul 03080, Republic of Korea
| | - Alison P. Klein
- Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA
| | - Robert Klein
- Program in Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center, New York, New York, 10065, USA
| | - Woon-Puay Koh
- Duke-NUS Graduate Medical School, Singapore 169857, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore 119077, Singapore
| | - Laurence N. Kolonel
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii 96813, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA
| | - Peter Kraft
- Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, Massachusetts 02115, USA
| | - Vittorio Krogh
- Fondazione IRCCS Istituto Nazionale dei Tumori, Milano 20133, Italy
| | - Robert C. Kurtz
- Department of Medicine, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA
| | - Andrea LaCroix
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA
| | - Qing Lan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Maria Teresa Landi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii 96813, USA
| | - Donghui Li
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA
| | - Xiaolin Liang
- Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA
| | - Linda M. Liao
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Dongxin Lin
- Department of Etiology & Carcinogenesis, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
- State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Jianjun Liu
- Department of Human Genetics, Genome Institute of Singapore 138672, Singapore
- School of Life Sciences, Anhui Medical University, Hefei 230032, China
| | - Jolanta Lissowska
- Department of Cancer Epidemiology and Prevention, Maria Sklodowska-Curie Cancer Center and Institute of Oncology, Warsaw 02-781, Poland
| | - Lingeng Lu
- Yale School of Public Health, New Haven, Connecticut 06510, USA
| | | | - Nuria Malats
- Spanish National Cancer Research Centre (CNIO), Madrid 28029, Spain
| | - Keitaro Matsuo
- Division of Molecular Medicine, Aichi Cancer Center Research Institute, Nagoya 464-8681, Japan
| | - Lorna H. McNeill
- Department of Health Disparities Research, Division of OVP, Cancer Prevention and Population Sciences, and Center for Community-Engaged Translational Research, Duncan Family Institute, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA
| | | | - Beatrice S. Melin
- Department of Radiation Sciences, Oncology, Umeå University, 901 87 Umeå, Sweden
| | - Lisa Mirabello
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Lee Moore
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Sara H. Olson
- Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA
| | - Irene Orlow
- Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA
| | - Jae Yong Park
- Lung Cancer Center, Kyungpook National University Medical Center, Daegu 101, Republic of Korea
| | - Ana Patiño-Garcia
- Department of Pediatrics, University Clinic of Navarra, Universidad de Navarra, IdiSNA, Navarra Institute for Health Research, Pamplona 31080, Spain
| | - Beata Peplonska
- Nofer Institute of Occupational Medicine, Lodz 91-348, Poland
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA
| | - Gloria M. Petersen
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota 55905, USA
| | - Loreall Pooler
- University of Southern California, Los Angeles, California 90007, USA
| | - Jennifer Prescott
- Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, Massachusetts 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Ludmila Prokunina-Olsson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Mark P. Purdue
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - You-Lin Qiao
- Department of Epidemiology, Cancer Institute (Hospital), Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Preetha Rajaraman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Francisco X. Real
- Spanish National Cancer Research Centre (CNIO), Madrid 28029, Spain
- Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Barcelona 08002, Spain
| | - Elio Riboli
- Division of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London SW7 2AZ, UK
| | - Harvey A. Risch
- Yale School of Public Health, New Haven, Connecticut 06510, USA
| | - Benjamin Rodriguez-Santiago
- Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Barcelona 08002, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Barcelona, 28029, Spain
- Quantitative Genomic Medicine Laboratory, qGenomics, Barcelona 08003, Spain
| | - Avima M. Ruder
- National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Cincinnati, Ohio 45226, USA
| | - Sharon A. Savage
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Fredrick Schumacher
- Department of Preventive Medicine, Biostatistics Division, Keck School of Medicine at the University of Southern California, Los Angeles, California 90033, USA
| | - Ann G. Schwartz
- Karmanos Cancer Institute and Department of Oncology, Wayne State University School of Medicine, Detroit, Michigan 48201, USA
| | - Kendra L. Schwartz
- Karmanos Cancer Institute and Department of Family Medicine and Public Health Sciences, Wayne State University School of Medicine, Detroit, Michigan 48201, USA
| | - Adeline Seow
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore 119077, Singapore
| | - Veronica Wendy Setiawan
- Department of Preventive Medicine, Biostatistics Division, Keck School of Medicine at the University of Southern California, Los Angeles, California 90033, USA
| | - Gianluca Severi
- Cancer Epidemiology Centre, Cancer Council Victoria & Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria 3010, Australia
- Human Genetics Foundation (HuGeF), Torino, 10126, Italy
| | - Hongbing Shen
- Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Nanjing Medical University, Nanjing 210029, China
- Department of Epidemiology, Nanjing Medical University School of Public Health, Nanjing 210029, China
| | - Xin Sheng
- University of Southern California, Los Angeles, California 90007, USA
| | - Min-Ho Shin
- Department of Preventive Medicine, Chonnam National University Medical School, Gwanju 501-746, Republic of Korea
| | - Xiao-Ou Shu
- Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA
| | - Debra T. Silverman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | | | - Victoria L. Stevens
- Epidemiology Research Program, American Cancer Society, Atlanta, Georgia 30303, USA
| | - Rachael Stolzenberg-Solomon
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Daniel Stram
- Department of Preventive Medicine, Biostatistics Division, Keck School of Medicine at the University of Southern California, Los Angeles, California 90033, USA
| | - Ze-Zhong Tang
- Shanxi Cancer Hospital, Taiyuan, Shanxi 030013, China
| | - Philip R. Taylor
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Lauren R. Teras
- Epidemiology Research Program, American Cancer Society, Atlanta, Georgia 30303, USA
| | - Geoffrey S. Tobias
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - David Van Den Berg
- Department of Preventive Medicine, Biostatistics Division, Keck School of Medicine at the University of Southern California, Los Angeles, California 90033, USA
| | - Kala Visvanathan
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21218, USA
| | - Sholom Wacholder
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Jiu-Cun Wang
- Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200433, China
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Zhaoming Wang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
- Cancer Genomics Research Laboratory, National Cancer Institute, Division of Cancer Epidemiology and Genetics, Leidos Biomedical Research Inc., Bethesda, Maryland 20892, USA
| | - Nicolas Wentzensen
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - William Wheeler
- Information Management Services Inc., Calverton, Maryland, 20904, USA
| | - Emily White
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA
| | - John K. Wiencke
- University of California San Francisco, San Francisco, California 94143, USA
| | - Brian M. Wolpin
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA
| | - Maria Pik Wong
- Department of Pathology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Chen Wu
- Department of Etiology & Carcinogenesis, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
- State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Tangchun Wu
- Institute of Occupational Medicine and Ministry of Education Key Laboratory for Environment and Health, School of Public Health, Huazhong University of Science and Technology, Wuhan 430400, China
| | - Xifeng Wu
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA
| | - Yi-Long Wu
- Guangdong Lung Cancer Institute, Guangdong General Hospital & Guangdong Academy of Medical Sciences, Guangzhou 515200, China
| | - Jay S. Wunder
- Guangdong Lung Cancer Institute, Guangdong General Hospital & Guangdong Academy of Medical Sciences, Guangzhou 515200, China
| | - Lucy Xia
- University of Southern California, Los Angeles, California 90007, USA
| | - Hannah P. Yang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Pan-Chyr Yang
- Division of Urologic Surgery, Washington University School of Medicine, St Louis, Missouri 63110, USA
| | - Kai Yu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Krista A. Zanetti
- Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland 20892, USA
| | - Anne Zeleniuch-Jacquotte
- New York University Cancer Institute, New York, New York 10016, USA
- Department of Population Health, New York University School of Medicine, New York, New York 10016, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA
| | - Baosen Zhou
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang 110001, China
| | - Regina G. Ziegler
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Luis A. Perez-Jurado
- Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Barcelona 08002, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Barcelona, 28029, Spain
| | - Neil E. Caporaso
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Margaret Tucker
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Michael C. Dean
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
| | - Meredith Yeager
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
- Cancer Genomics Research Laboratory, National Cancer Institute, Division of Cancer Epidemiology and Genetics, Leidos Biomedical Research Inc., Bethesda, Maryland 20892, USA
| | - Stephen J. Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, Maryland 20892, USA
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Bianco-Miotto T, Mayne BT, Buckberry S, Breen J, Rodriguez Lopez CM, Roberts CT. Recent progress towards understanding the role of DNA methylation in human placental development. Reproduction 2016; 152:R23-30. [PMID: 27026712 PMCID: PMC5064761 DOI: 10.1530/rep-16-0014] [Citation(s) in RCA: 51] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2016] [Accepted: 03/29/2016] [Indexed: 12/20/2022]
Abstract
Epigenetic modifications, and particularly DNA methylation, have been studied in many tissues, both healthy and diseased, and across numerous developmental stages. The placenta is the only organ that has a transient life of 9 months and undergoes rapid growth and dynamic structural and functional changes across gestation. Additionally, the placenta is unique because although developing within the mother, its genome is identical to that of the foetus. Given these distinctive characteristics, it is not surprising that the epigenetic landscape affecting placental gene expression may be different to that in other healthy tissues. However, the role of epigenetic modifications, and particularly DNA methylation, in placental development remains largely unknown. Of particular interest is the fact that the placenta is the most hypomethylated human tissue and is characterized by the presence of large partially methylated domains (PMDs) containing silenced genes. Moreover, how and why the placenta is hypomethylated and what role DNA methylation plays in regulating placental gene expression across gestation are poorly understood. We review genome-wide DNA methylation studies in the human placenta and highlight that the different cell types that make up the placenta have very different DNA methylation profiles. Summarizing studies on DNA methylation in the placenta and its relationship with pregnancy complications are difficult due to the limited number of studies available for comparison. To understand the key steps in placental development and hence what may be perturbed in pregnancy complications requires large-scale genome-wide DNA methylation studies coupled with transcriptome analyses.
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Affiliation(s)
- Tina Bianco-Miotto
- School of Agriculture, Food and WineUniversity of Adelaide, Adelaide, South Australia, Australia Robinson Research InstituteUniversity of Adelaide, Adelaide, South Australia, Australia
| | - Benjamin T Mayne
- Robinson Research InstituteUniversity of Adelaide, Adelaide, South Australia, Australia School of MedicineUniversity of Adelaide, Adelaide, South Australia, Australia
| | - Sam Buckberry
- Harry Perkins Institute of Medical ResearchThe University of Western Australia, Crawley, Western Australia, Australia Plant Energy BiologyARC Centre of Excellence, The University of Western Australia, Crawley, Western Australia, Australia
| | - James Breen
- Robinson Research InstituteUniversity of Adelaide, Adelaide, South Australia, Australia Bioinformatics HubUniversity of Adelaide, Adelaide, South Australia, Australia
| | - Carlos M Rodriguez Lopez
- School of Agriculture, Food and WineUniversity of Adelaide, Adelaide, South Australia, Australia
| | - Claire T Roberts
- Robinson Research InstituteUniversity of Adelaide, Adelaide, South Australia, Australia School of MedicineUniversity of Adelaide, Adelaide, South Australia, Australia
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14
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Zhu Z, Liang Z, Liany H, Yang C, Wen L, Lin Z, Sheng Y, Lin Y, Ye L, Cheng Y, Chang Y, Liu L, Yang L, Shi Y, Shen C, Zhou F, Zheng X, Zhu J, Liang B, Ding Y, Zhou Y, Yin X, Tang H, Zuo X, Sun L, Bei JX, Liu J, Yang S, Yang W, Cui Y, Zhang X. Discovery of a novel genetic susceptibility locus on X chromosome for systemic lupus erythematosus. Arthritis Res Ther 2015; 17:349. [PMID: 26635088 PMCID: PMC4669597 DOI: 10.1186/s13075-015-0857-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2015] [Accepted: 11/09/2015] [Indexed: 01/21/2023] Open
Abstract
Introduction Systemic lupus erythematosus (SLE) is an autoimmune connective tissue disease affecting predominantly females. To discover additional genetic risk variants for SLE on the X chromosome, we performed a follow-up study of our previously published genome-wide association study (GWAS) data set in this study. Methods Twelve single nucleotide polymorphisms (SNPs) within novel or unpublished loci with P-value < 1.00 × 10−02 were selected for genotype with a total of 2,442 cases and 2,798 controls(including 1,156 cases and 2,330 controls from central China, 1,012 cases and 335 controls from southern China and 274 cases and 133 controls from northern China) using Sequenom Massarry system. Associaton analyses were performed using logistic regression with sample region as a covariate through PLINK 1.07 software. Results Combined analysis in discovery and central validation dataset discovered a novel locus rs5914778 within LINC01420 associated with SLE at genome-wide significance (P = 1.00 × 10−08; odds ratio (OR) = 1.32). We also confirmed rs5914778 in the southern Chinese sample cohort (P = 5.31 × 10−05; OR = 1.51), and meta-analysis of the samples from the discovery, central and southern validations regions provided robust evidence for the association of rs5914778 (P = 5.26 × 10−12; OR = 1.35). However, this SNP did not show association with SLE in the northern sample (P = 0.33). Further analysis represent the association of northern was significantly heterogeneous compared to central and southern respectively. Conclusions Our study increases the number of established susceptibility loci for SLE in Han Chinese population and has further demonstrated the important role of X-linked genetic risk variants in the pathogenesis of SLE in Chinese Han population. Electronic supplementary material The online version of this article (doi:10.1186/s13075-015-0857-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Zhengwei Zhu
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China. .,Department of Dermatology, China-Japan Friendship Hospital, East Street Cherry Park, Chaoyang District, Beijing, 100029, China.
| | - Zhuoyuan Liang
- Department of Nephrology, Jiangmen Central Hospital, Jiangmen, Guangdong, 529030, China.
| | - Herty Liany
- Human Genetics, Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore.
| | - Chao Yang
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China. .,Department of Dermatology, China-Japan Friendship Hospital, East Street Cherry Park, Chaoyang District, Beijing, 100029, China.
| | - Leilei Wen
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Zhiming Lin
- Department of Rheumatology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, 510630, China.
| | - Yujun Sheng
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Yan Lin
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Lei Ye
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Yuyan Cheng
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Yan Chang
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Lu Liu
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Lulu Yang
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Yinjuan Shi
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Changbing Shen
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Fusheng Zhou
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Xiaodong Zheng
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Jun Zhu
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Bo Liang
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Yantao Ding
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Yi Zhou
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Xianyong Yin
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Huayang Tang
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Xianbo Zuo
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Liangdan Sun
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Jin-Xin Bei
- Human Genetics, Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore.
| | - Jianjun Liu
- Human Genetics, Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore. .,Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
| | - Sen Yang
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
| | - Wanling Yang
- Department of Paediatrics and Adolescent Medicine, Queen Mary Hospital, LKS Faculty of Medicine, The University of Hong Kong, 21 Sassoon Road, Hong Kong, China. .,Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
| | - Yong Cui
- Department of Dermatology, China-Japan Friendship Hospital, East Street Cherry Park, Chaoyang District, Beijing, 100029, China.
| | - Xuejun Zhang
- Institute of Dermatology and Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China. .,Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei, Anhui, 230032, China.
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15
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Yousefi P, Huen K, Davé V, Barcellos L, Eskenazi B, Holland N. Sex differences in DNA methylation assessed by 450 K BeadChip in newborns. BMC Genomics 2015; 16:911. [PMID: 26553366 PMCID: PMC4640166 DOI: 10.1186/s12864-015-2034-y] [Citation(s) in RCA: 122] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2015] [Accepted: 10/08/2015] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND DNA methylation is an important epigenetic mark that can potentially link early life exposures to adverse health outcomes later in life. Host factors like sex and age strongly influence biological variation of DNA methylation, but characterization of these relationships is still limited, particularly in young children. METHODS In a sample of 111 Mexican-American subjects (58 girls , 53 boys), we interrogated DNA methylation differences by sex at birth using the 450 K BeadChip in umbilical cord blood specimens, adjusting for cell composition. RESULTS We observed that ~3% of CpG sites were differentially methylated between girls and boys at birth (FDR P < 0.05). Of those CpGs, 3031 were located on autosomes, and 82.8% of those were hypermethylated in girls compared to boys. Beyond individual CpGs, we found 3604 sex-associated differentially methylated regions (DMRs) where the majority (75.8%) had higher methylation in girls. Using pathway analysis, we found that sex-associated autosomal CpGs were significantly enriched for gene ontology terms related to nervous system development and behavior. Among hits in our study, 35.9% had been previously reported as sex-associated CpG sites in other published human studies. Further, for replicated hits, the direction of the association with methylation was highly concordant (98.5-100%) with previous studies. CONCLUSIONS To our knowledge, this is the first reported epigenome-wide analysis by sex at birth that examined DMRs and adjusted for confounding by cell composition. We confirmed previously reported trends that methylation profiles are sex-specific even in autosomal genes, and also identified novel sex-associated CpGs in our methylome-wide analysis immediately after birth, a critical yet relatively unstudied developmental window.
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Affiliation(s)
- Paul Yousefi
- School of Public Health, University of California, 733 University Hall, School of Public Health, UC, Berkeley, CA, 94720-7360, USA
| | - Karen Huen
- School of Public Health, University of California, 733 University Hall, School of Public Health, UC, Berkeley, CA, 94720-7360, USA
| | - Veronica Davé
- School of Public Health, University of California, 733 University Hall, School of Public Health, UC, Berkeley, CA, 94720-7360, USA
| | - Lisa Barcellos
- School of Public Health, University of California, 733 University Hall, School of Public Health, UC, Berkeley, CA, 94720-7360, USA
| | - Brenda Eskenazi
- School of Public Health, University of California, 733 University Hall, School of Public Health, UC, Berkeley, CA, 94720-7360, USA
| | - Nina Holland
- School of Public Health, University of California, 733 University Hall, School of Public Health, UC, Berkeley, CA, 94720-7360, USA.
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16
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Cotton AM, Price EM, Jones MJ, Balaton BP, Kobor MS, Brown CJ. Landscape of DNA methylation on the X chromosome reflects CpG density, functional chromatin state and X-chromosome inactivation. Hum Mol Genet 2014; 24:1528-39. [PMID: 25381334 PMCID: PMC4381753 DOI: 10.1093/hmg/ddu564] [Citation(s) in RCA: 175] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
X-chromosome inactivation (XCI) achieves dosage compensation between males and females through the silencing of the majority of genes on one of the female X chromosomes. Thus, the female X chromosomes provide a unique opportunity to study euchromatin and heterochromatin of allelic regions within the same nuclear environment. We examined the interplay of DNA methylation (DNAm) with CpG density, transcriptional activity and chromatin state at genes on the X chromosome using over 1800 female samples analysed with the Illumina Infinium Human Methylation450 BeadChip. DNAm was used to predict an inactivation status for 63 novel transcription start sites (TSSs) across 27 tissues. There was high concordance of inactivation status across tissues, with 62% of TSSs subject to XCI in all 27 tissues examined, whereas 9% escaped from XCI in all tissues, and the remainder showed variable escape from XCI between females in subsets of tissues. Inter-female and twin data supported a model of predominately cis-acting influences on inactivation status. The level of expression from the inactive X relative to the active X correlated with the amount of female promoter DNAm to a threshold of ∼30%, beyond which genes were consistently subject to inactivation. The inactive X showed lower DNAm than the active X at intragenic and intergenic regions for genes subject to XCI, but not at genes that escape from inactivation. Our categorization of genes that escape from X inactivation provides candidates for sex-specific differences in disease.
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Affiliation(s)
- Allison M Cotton
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada V6T 1Z3, Molecular Epigenetics Group, Life Sciences Institute, Vancouver, BC, Canada V6T 1Z3
| | - E Magda Price
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada V6T 1Z3, Department of Obstetrics and Gynaecology, University of British Columbia, Vancouver, BC, Canada V5Z 4H4, The Child and Family Research Institute, Vancouver, BC, Canada V5Z 4H4
| | - Meaghan J Jones
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada V6T 1Z3, The Child and Family Research Institute, Vancouver, BC, Canada V5Z 4H4 Centre for Molecular Medicine and Therapeutics, Vancouver, BC, Canada V5Z 4H4
| | - Bradley P Balaton
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada V6T 1Z3, Molecular Epigenetics Group, Life Sciences Institute, Vancouver, BC, Canada V6T 1Z3
| | - Michael S Kobor
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada V6T 1Z3, The Child and Family Research Institute, Vancouver, BC, Canada V5Z 4H4 Centre for Molecular Medicine and Therapeutics, Vancouver, BC, Canada V5Z 4H4
| | - Carolyn J Brown
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada V6T 1Z3, Molecular Epigenetics Group, Life Sciences Institute, Vancouver, BC, Canada V6T 1Z3,
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