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Casazza W, Inkster AM, Del Gobbo GF, Yuan V, Delahaye F, Marsit C, Park YP, Robinson WP, Mostafavi S, Dennis JK. Sex-dependent placental methylation quantitative trait loci provide insight into the prenatal origins of childhood onset traits and conditions. iScience 2024; 27:109047. [PMID: 38357671 PMCID: PMC10865402 DOI: 10.1016/j.isci.2024.109047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 06/19/2023] [Accepted: 01/23/2024] [Indexed: 02/16/2024] Open
Abstract
Molecular quantitative trait loci (QTLs) allow us to understand the biology captured in genome-wide association studies (GWASs). The placenta regulates fetal development and shows sex differences in DNA methylation. We therefore hypothesized that placental methylation QTL (mQTL) explain variation in genetic risk for childhood onset traits, and that effects differ by sex. We analyzed 411 term placentas from two studies and found 49,252 methylation (CpG) sites with mQTL and 2,489 CpG sites with sex-dependent mQTL. All mQTL were enriched in regions that typically affect gene expression in prenatal tissues. All mQTL were also enriched in GWAS results for growth- and immune-related traits, but male- and female-specific mQTL were more enriched than cross-sex mQTL. mQTL colocalized with trait loci at 777 CpG sites, with 216 (28%) specific to males or females. Overall, mQTL specific to male and female placenta capture otherwise overlooked variation in childhood traits.
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Affiliation(s)
- William Casazza
- Centre for Molecular Medicine and Therapeutics, BC Children’s Hospital, Vancouver, BC, Canada
- Bioinformatics Graduate Program, University of British Columbia, Vancouver, BC, Canada
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
| | - Amy M. Inkster
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Giulia F. Del Gobbo
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- Children’s Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, ON, Canada
| | - Victor Yuan
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | | | - Carmen Marsit
- Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Yongjin P. Park
- Department of Statistics, University of British Columbia, Vancouver, BC, Canada
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Wendy P. Robinson
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Sara Mostafavi
- Centre for Molecular Medicine and Therapeutics, BC Children’s Hospital, Vancouver, BC, Canada
- Paul Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA
| | - Jessica K. Dennis
- Centre for Molecular Medicine and Therapeutics, BC Children’s Hospital, Vancouver, BC, Canada
- Bioinformatics Graduate Program, University of British Columbia, Vancouver, BC, Canada
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
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2
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Díez-Villanueva A, Martín B, Moratalla-Navarro F, Morón-Duran FD, Galván-Femenía I, Obón-Santacana M, Carreras A, de Cid R, Peinado MA, Moreno V. Identification of intergenerational epigenetic inheritance by whole genome DNA methylation analysis in trios. Sci Rep 2023; 13:21266. [PMID: 38042866 PMCID: PMC10693549 DOI: 10.1038/s41598-023-48517-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 11/27/2023] [Indexed: 12/04/2023] Open
Abstract
Genome-wide association studies have identified thousands of loci associated with common diseases and traits. However, a large fraction of heritability remains unexplained. Epigenetic modifications, such as the observed in DNA methylation have been proposed as a mechanism of intergenerational inheritance. To investigate the potential contribution of DNA methylation to the missing heritability, we analysed the methylomes of four healthy trios (two parents and one offspring) using whole genome bisulphite sequencing. Of the 1.5 million CpGs (19%) with over 20% variability between parents in at least one family and compatible with a Mendelian inheritance pattern, only 3488 CpGs (0.2%) lacked correlation with any SNP in the genome, marking them as potential sites for intergenerational epigenetic inheritance. These markers were distributed genome-wide, with some preference to be located in promoters. They displayed a bimodal distribution, being either fully methylated or unmethylated, and were often found at the boundaries of genomic regions with high/low GC content. This analysis provides a starting point for future investigations into the missing heritability of simple and complex traits.
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Affiliation(s)
- Anna Díez-Villanueva
- Unit of Biomarkers and Susceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L'Hospitalet del Llobregat, 08908, Barcelona, Spain
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, 08908, Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029, Madrid, Spain
| | - Berta Martín
- Germans Trias i Pujol Institute (IGTP), Translational Program in Cancer Research (CARE), Camí de les Escoles, s/n, Can Ruti Biomedical Campus, 08916, Badalona, Catalonia, Spain
| | - Ferran Moratalla-Navarro
- Unit of Biomarkers and Susceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L'Hospitalet del Llobregat, 08908, Barcelona, Spain
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, 08908, Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029, Madrid, Spain
- Department of Clinical Sciences, Faculty of Medicine and Universitat de Barcelona Institute of Complex Systems (UBICS), University of Barcelona, 08907, Barcelona, Spain
| | - Francisco D Morón-Duran
- Unit of Biomarkers and Susceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L'Hospitalet del Llobregat, 08908, Barcelona, Spain
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, 08908, Barcelona, Spain
- Department of Clinical Sciences, Faculty of Medicine and Universitat de Barcelona Institute of Complex Systems (UBICS), University of Barcelona, 08907, Barcelona, Spain
| | - Iván Galván-Femenía
- Genomes for Life-GCAT lab., Germans Trias i Pujol Research Institute (IGTP), Camí de les Escoles, s/n, Can Ruti Biomedical Campus, 08916, Badalona, Catalonia, Spain
| | - Mireia Obón-Santacana
- Unit of Biomarkers and Susceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L'Hospitalet del Llobregat, 08908, Barcelona, Spain
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, 08908, Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029, Madrid, Spain
| | - Anna Carreras
- Genomes for Life-GCAT lab., Germans Trias i Pujol Research Institute (IGTP), Camí de les Escoles, s/n, Can Ruti Biomedical Campus, 08916, Badalona, Catalonia, Spain
| | - Rafael de Cid
- Genomes for Life-GCAT lab., Germans Trias i Pujol Research Institute (IGTP), Camí de les Escoles, s/n, Can Ruti Biomedical Campus, 08916, Badalona, Catalonia, Spain
| | - Miguel A Peinado
- Germans Trias i Pujol Institute (IGTP), Translational Program in Cancer Research (CARE), Camí de les Escoles, s/n, Can Ruti Biomedical Campus, 08916, Badalona, Catalonia, Spain
| | - Victor Moreno
- Unit of Biomarkers and Susceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L'Hospitalet del Llobregat, 08908, Barcelona, Spain.
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, 08908, Barcelona, Spain.
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029, Madrid, Spain.
- Department of Clinical Sciences, Faculty of Medicine and Universitat de Barcelona Institute of Complex Systems (UBICS), University of Barcelona, 08907, Barcelona, Spain.
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3
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Fang Y, Ji Z, Zhou W, Abante J, Koldobskiy MA, Ji H, Feinberg A. DNA methylation entropy is associated with DNA sequence features and developmental epigenetic divergence. Nucleic Acids Res 2023; 51:2046-2065. [PMID: 36762477 PMCID: PMC10018346 DOI: 10.1093/nar/gkad050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 12/02/2022] [Accepted: 02/04/2023] [Indexed: 02/11/2023] Open
Abstract
Epigenetic information defines tissue identity and is largely inherited in development through DNA methylation. While studied mostly for mean differences, methylation also encodes stochastic change, defined as entropy in information theory. Analyzing allele-specific methylation in 49 human tissue sample datasets, we find that methylation entropy is associated with specific DNA binding motifs, regulatory DNA, and CpG density. Then applying information theory to 42 mouse embryo methylation datasets, we find that the contribution of methylation entropy to time- and tissue-specific patterns of development is comparable to the contribution of methylation mean, and methylation entropy is associated with sequence and chromatin features conserved with human. Moreover, methylation entropy is directly related to gene expression variability in development, suggesting a role for epigenetic entropy in developmental plasticity.
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Affiliation(s)
- Yuqi Fang
- Center for Epigenetics, Johns Hopkins University, 855 N. Wolfe St., Baltimore, MD 21205, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Zhicheng Ji
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St., Baltimore, MD 21205, USA
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC 27708, USA
| | - Weiqiang Zhou
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St., Baltimore, MD 21205, USA
| | - Jordi Abante
- Department of Electrical & Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Michael A Koldobskiy
- Center for Epigenetics, Johns Hopkins University, 855 N. Wolfe St., Baltimore, MD 21205, USA
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, 855 N. Wolfe St., Baltimore, MD 21205, USA
| | - Hongkai Ji
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St., Baltimore, MD 21205, USA
| | - Andrew P Feinberg
- Center for Epigenetics, Johns Hopkins University, 855 N. Wolfe St., Baltimore, MD 21205, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St., Baltimore, MD 21205, USA
- Department of Medicine, Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD 21205, USA
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4
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Katrinli S, Maihofer AX, Wani AH, Pfeiffer JR, Ketema E, Ratanatharathorn A, Baker DG, Boks MP, Geuze E, Kessler RC, Risbrough VB, Rutten BPF, Stein MB, Ursano RJ, Vermetten E, Logue MW, Nievergelt CM, Smith AK, Uddin M. Epigenome-wide meta-analysis of PTSD symptom severity in three military cohorts implicates DNA methylation changes in genes involved in immune system and oxidative stress. Mol Psychiatry 2022; 27:1720-1728. [PMID: 34992238 PMCID: PMC9106882 DOI: 10.1038/s41380-021-01398-2] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 11/13/2021] [Accepted: 11/23/2021] [Indexed: 11/08/2022]
Abstract
Epigenetic factors modify the effects of environmental factors on biological outcomes. Identification of epigenetic changes that associate with PTSD is therefore a crucial step in deciphering mechanisms of risk and resilience. In this study, our goal is to identify epigenetic signatures associated with PTSD symptom severity (PTSS) and changes in PTSS over time, using whole blood DNA methylation (DNAm) data (MethylationEPIC BeadChip) of military personnel prior to and following combat deployment. A total of 429 subjects (858 samples across 2 time points) from three male military cohorts were included in the analyses. We conducted two different meta-analyses to answer two different scientific questions: one to identify a DNAm profile of PTSS using a random effects model including both time points for each subject, and the other to identify a DNAm profile of change in PTSS conditioned on pre-deployment DNAm. Four CpGs near four genes (F2R, CNPY2, BAIAP2L1, and TBXAS1) and 88 differentially methylated regions (DMRs) were associated with PTSS. Change in PTSS after deployment was associated with 15 DMRs, of those 2 DMRs near OTUD5 and ELF4 were also associated with PTSS. Notably, three PTSS-associated CpGs near F2R, BAIAP2L1 and TBXAS1 also showed nominal evidence of association with change in PTSS. This study, which identifies PTSD-associated changes in genes involved in oxidative stress and immune system, provides novel evidence that epigenetic differences are associated with PTSS.
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Affiliation(s)
- Seyma Katrinli
- Department of Gynecology and Obstetrics, Emory University, Atlanta, GA, USA
| | - Adam X Maihofer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Agaz H Wani
- Genomics Program, College of Public Health, University of South Florida, Tampa, FL, USA
| | - John R Pfeiffer
- Department of Psychology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Carl R. Woese Institute for Genomic Biology, Urbana, IL, USA
| | - Elizabeth Ketema
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | | | - Dewleen G Baker
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
- Veterans Affairs Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Marco P Boks
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Elbert Geuze
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
- Brain Research and Innovation Centre, Netherlands Ministry of Defence, Utrecht, The Netherlands
| | - Ronald C Kessler
- Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
| | - Victoria B Risbrough
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Veterans Affairs Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Bart P F Rutten
- Department of Psychiatry and Neuropsychology, Maastricht University Medical Centre, School for Mental Health and Neuroscience, Maastricht, The Netherlands
| | - Murray B Stein
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
- School of Public Health, University of California San Diego, La Jolla, CA, USA
| | - Robert J Ursano
- Center for the Study of Traumatic Stress, Department of Psychiatry, Uniformed Services University School of Medicine, Bethesda, MD, USA
| | - Eric Vermetten
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Psychiatry, Leiden University Medical Center, ZA, Leiden, The Netherlands
- Research Center, Netherlands Defense Department, UT, AA Utrecht, The Netherlands
- Arq Psychotrauma Expert Group, XE, Diemen, The Netherlands
| | - Mark W Logue
- National Center for PTSD, Behavioral Science Division at VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Caroline M Nievergelt
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
- Veterans Affairs Center of Excellence for Stress and Mental Health, San Diego, CA, USA
| | - Alicia K Smith
- Department of Gynecology and Obstetrics, Emory University, Atlanta, GA, USA
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, USA
| | - Monica Uddin
- Genomics Program, College of Public Health, University of South Florida, Tampa, FL, USA.
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5
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Carmel M, Michaelovsky E, Weinberger R, Frisch A, Mekori-Domachevsky E, Gothelf D, Weizman A. Differential methylation of imprinting genes and MHC locus in 22q11.2 deletion syndrome-related schizophrenia spectrum disorders. World J Biol Psychiatry 2021; 22:46-57. [PMID: 32212948 DOI: 10.1080/15622975.2020.1747113] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
OBJECTIVES 22q11.2 deletion syndrome (DS) is the strongest known genetic risk for schizophrenia. Methylome screening was conducted to elucidate possible involvement of epigenetic alterations in the emergence of schizophrenia spectrum disorders (SZ-SD) in 22q11.2DS. METHODS Sixteen adult men with/without SZ-SD were recruited from a 22q11.2DS cohort and underwent genome-wide DNA methylation profile analysis. Differentially methylated probes (DMPs) and regions (DMRs) were analysed using the ChAMP software. RESULTS The DMPs (p-value <10-6) and DMRs (p-valueArea <0.01) were enriched in two gene sets, 'imprinting genes' and 'chr6p21', a region overlapping the MHC locus. Most of the identified imprinting genes are involved in neurodevelopment and located in clusters under imprinting control region (ICR) regulation, including PEG10, SGCE (7q21.3), GNAS, GNAS-AS1 (20q13.32) and SNHG14, SNURF-SNRPN, SNORD115 (15q11.2). The differentially methylated genes from the MHC locus included immune HLA-genes and non-immune genes, RNF39, PPP1R18 and NOTCH4, implicated in neurodevelopment and synaptic plasticity. The most significant DMR is located in MHC locus and covered the transcription regulator ZFP57 that is required for control and maintenance of gene imprinting at multiple ICRs. CONCLUSIONS The differential methylation in imprinting genes and in chr6p21-22 indicate the neurodevelopmental nature of 22q11.2DS-related SZ and the major role of MHC locus in the risk to develop SZ.
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Affiliation(s)
- Miri Carmel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.,Felsenstein Medical Research Center, Petach Tikva, Israel
| | - Elena Michaelovsky
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.,Felsenstein Medical Research Center, Petach Tikva, Israel
| | - Ronnie Weinberger
- The Behavioral Neurogenetics Center and Child Psychiatry Division, Sheba Medical Center, Ramat Gan, Israel
| | - Amos Frisch
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.,Felsenstein Medical Research Center, Petach Tikva, Israel
| | - Ehud Mekori-Domachevsky
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.,The Behavioral Neurogenetics Center and Child Psychiatry Division, Sheba Medical Center, Ramat Gan, Israel
| | - Doron Gothelf
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.,The Behavioral Neurogenetics Center and Child Psychiatry Division, Sheba Medical Center, Ramat Gan, Israel.,Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Abraham Weizman
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.,Felsenstein Medical Research Center, Petach Tikva, Israel.,Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.,Geha Mental Health Center, Petach Tikva, Israel
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6
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Chiba H, Kakuta Y, Kinouchi Y, Kawai Y, Watanabe K, Nagao M, Naito T, Onodera M, Moroi R, Kuroha M, Kanazawa Y, Kimura T, Shiga H, Endo K, Negoro K, Nagasaki M, Unno M, Shimosegawa T. Allele-specific DNA methylation of disease susceptibility genes in Japanese patients with inflammatory bowel disease. PLoS One 2018; 13:e0194036. [PMID: 29547621 PMCID: PMC5856270 DOI: 10.1371/journal.pone.0194036] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2017] [Accepted: 02/25/2018] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Inflammatory bowel disease (IBD) has an unknown etiology; however, accumulating evidence suggests that IBD is a multifactorial disease influenced by a combination of genetic and environmental factors. The influence of genetic variants on DNA methylation in cis and cis effects on expression have been demonstrated. We hypothesized that IBD susceptibility single-nucleotide polymorphisms (SNPs) regulate susceptibility gene expressions in cis by regulating DNA methylation around SNPs. For this, we determined cis-regulated allele-specific DNA methylation (ASM) around IBD susceptibility genes in CD4+ effector/memory T cells (Tem) in lamina propria mononuclear cells (LPMCs) in patients with IBD and examined the association between the ASM SNP genotype and neighboring susceptibility gene expressions. METHODS CD4+ effector/memory T cells (Tem) were isolated from LPMCs in 15 Japanese IBD patients (ten Crohn's disease [CD] and five ulcerative colitis [UC] patients). ASM analysis was performed by methylation-sensitive SNP array analysis. We defined ASM as a changing average relative allele score ([Formula: see text]) >0.1 after digestion by methylation-sensitive restriction enzymes. Among SNPs showing [Formula: see text] >0.1, we extracted the probes located on tag-SNPs of 200 IBD susceptibility loci and around IBD susceptibility genes as candidate ASM SNPs. To validate ASM, bisulfite-pyrosequencing was performed. Transcriptome analysis was examined in 11 IBD patients (seven CD and four UC patients). The relation between rs36221701 genotype and neighboring gene expressions were analyzed. RESULTS We extracted six candidate ASM SNPs around IBD susceptibility genes. The top of [Formula: see text] (0.23) was rs1130368 located on HLA-DQB1. ASM around rs36221701 ([Formula: see text] = 0.14) located near SMAD3 was validated using bisulfite pyrosequencing. The SMAD3 expression was significantly associated with the rs36221701 genotype (p = 0.016). CONCLUSIONS We confirmed the existence of cis-regulated ASM around IBD susceptibility genes and the association between ASM SNP (rs36221701) genotype and SMAD3 expression, a susceptibility gene for IBD. These results give us supporting evidence that DNA methylation mediates genetic effects on disease susceptibility.
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Affiliation(s)
- Hirofumi Chiba
- Division of Gastroenterology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Yoichi Kakuta
- Division of Gastroenterology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Yoshitaka Kinouchi
- Institute for Excellence in Higher Education, Tohoku University, Sendai, Japan
| | - Yosuke Kawai
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Kazuhiro Watanabe
- Department of Surgery, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Munenori Nagao
- Department of Surgery, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Takeo Naito
- Division of Gastroenterology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Motoyuki Onodera
- Division of Gastroenterology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Rintaro Moroi
- Division of Gastroenterology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Masatake Kuroha
- Division of Gastroenterology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Yoshitake Kanazawa
- Division of Gastroenterology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Tomoya Kimura
- Division of Gastroenterology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Hisashi Shiga
- Division of Gastroenterology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Katsuya Endo
- Division of Gastroenterology, Tohoku Medical and Pharmaceutical University, Sendai, Japan
| | - Kenichi Negoro
- Division of Gastroenterology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Masao Nagasaki
- Institute for Excellence in Higher Education, Tohoku University, Sendai, Japan
| | - Michiaki Unno
- Department of Surgery, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Tooru Shimosegawa
- Division of Gastroenterology, Tohoku University Graduate School of Medicine, Sendai, Japan
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7
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Do C, Shearer A, Suzuki M, Terry MB, Gelernter J, Greally JM, Tycko B. Genetic-epigenetic interactions in cis: a major focus in the post-GWAS era. Genome Biol 2017. [PMID: 28629478 PMCID: PMC5477265 DOI: 10.1186/s13059-017-1250-y] [Citation(s) in RCA: 88] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Studies on genetic-epigenetic interactions, including the mapping of methylation quantitative trait loci (mQTLs) and haplotype-dependent allele-specific DNA methylation (hap-ASM), have become a major focus in the post-genome-wide-association-study (GWAS) era. Such maps can nominate regulatory sequence variants that underlie GWAS signals for common diseases, ranging from neuropsychiatric disorders to cancers. Conversely, mQTLs need to be filtered out when searching for non-genetic effects in epigenome-wide association studies (EWAS). Sequence variants in CCCTC-binding factor (CTCF) and transcription factor binding sites have been mechanistically linked to mQTLs and hap-ASM. Identifying these sites can point to disease-associated transcriptional pathways, with implications for targeted treatment and prevention.
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Affiliation(s)
- Catherine Do
- Institute for Cancer Genetics and Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, 10032, USA
| | - Alyssa Shearer
- Institute for Cancer Genetics and Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, 10032, USA
| | - Masako Suzuki
- Center for Epigenomics, Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Mary Beth Terry
- Department of Epidemiology, Columbia University Mailman School of Public Health, and Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, 10032, USA
| | - Joel Gelernter
- Departments of Psychiatry, Genetics, and Neurobiology, Yale University School of Medicine, New Haven, CT, 06520, USA
| | - John M Greally
- Center for Epigenomics, Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Benjamin Tycko
- Institute for Cancer Genetics, Herbert Irving Comprehensive Cancer Center, Taub Institute for Research on Alzheimer's disease and the Aging Brain, New York, NY, 10032, USA. .,Department of Pathology and Cell Biology, Columbia University, New York, NY, 10032, USA.
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8
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Day K, Waite LL, Alonso A, Irvin MR, Zhi D, Thibeault KS, Aslibekyan S, Hidalgo B, Borecki IB, Ordovas JM, Arnett DK, Tiwari HK, Absher DM. Heritable DNA Methylation in CD4+ Cells among Complex Families Displays Genetic and Non-Genetic Effects. PLoS One 2016; 11:e0165488. [PMID: 27792787 PMCID: PMC5085095 DOI: 10.1371/journal.pone.0165488] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Accepted: 10/12/2016] [Indexed: 12/20/2022] Open
Abstract
DNA methylation at CpG sites is both heritable and influenced by environment, but the relative contributions of each to DNA methylation levels are unclear. We conducted a heritability analysis of CpG methylation in human CD4+ cells across 975 individuals from 163 families in the Genetics of Lipid-lowering Drugs and Diet Network (GOLDN). Based on a broad-sense heritability (H2) value threshold of 0.4, we identified 20,575 highly heritable CpGs among the 174,445 most variable autosomal CpGs (SD > 0.02). Tests for associations of heritable CpGs with genotype at 2,145,360 SNPs using 717 of 975 individuals showed that ~74% were cis-meQTLs (< 1 Mb away from the CpG), 6% of CpGs exhibited trans-meQTL associations (>1 Mb away from the CpG or located on a different chromosome), and 20% of CpGs showed no strong significant associations with genotype (based on a p-value threshold of 1e-7). Genes proximal to the genotype independent heritable CpGs were enriched for functional terms related to regulation of T cell activation. These CpGs were also among those that distinguished T cells from other blood cell lineages. Compared to genes proximal to meQTL-associated heritable CpGs, genotype independent heritable CpGs were moderately enriched in the same genomic regions that escape erasure during primordial germ cell development and could carry potential for generational transmission.
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Affiliation(s)
- Kenneth Day
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, United States of America
| | - Lindsay L. Waite
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, United States of America
- University of Alabama at Birmingham, School of Public Health, Department of Biostatistics, Birmingham, Alabama, United States of America
| | - Arnald Alonso
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, United States of America
| | - Marguerite R. Irvin
- University of Alabama at Birmingham, School of Public Health, Department of Epidemiology, Birmingham, Alabama, United States of America
| | - Degui Zhi
- University of Alabama at Birmingham, School of Public Health, Department of Biostatistics, Birmingham, Alabama, United States of America
| | - Krista S. Thibeault
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, United States of America
| | - Stella Aslibekyan
- University of Alabama at Birmingham, School of Public Health, Department of Epidemiology, Birmingham, Alabama, United States of America
| | - Bertha Hidalgo
- University of Alabama at Birmingham, School of Public Health, Department of Biostatistics, Birmingham, Alabama, United States of America
| | - Ingrid B. Borecki
- Washington University, Division of Statistical Genomics, St. Louis, Missouri, United States of America
| | - Jose M. Ordovas
- Tufts University, Jean Mayer USDA Human Nutrition Research Center on Aging, Boston, Massachusetts, United States of America
- IMDEA-Food, Madrid, Spain
| | - Donna K. Arnett
- University of Alabama at Birmingham, School of Public Health, Department of Epidemiology, Birmingham, Alabama, United States of America
| | - Hemant K. Tiwari
- University of Alabama at Birmingham, School of Public Health, Department of Biostatistics, Birmingham, Alabama, United States of America
| | - Devin M. Absher
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, United States of America
- * E-mail:
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9
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Do C, Lang C, Lin J, Darbary H, Krupska I, Gaba A, Petukhova L, Vonsattel JP, Gallagher M, Goland R, Clynes R, Dwork A, Kral J, Monk C, Christiano A, Tycko B. Mechanisms and Disease Associations of Haplotype-Dependent Allele-Specific DNA Methylation. Am J Hum Genet 2016; 98:934-955. [PMID: 27153397 DOI: 10.1016/j.ajhg.2016.03.027] [Citation(s) in RCA: 78] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Accepted: 03/25/2016] [Indexed: 10/21/2022] Open
Abstract
Haplotype-dependent allele-specific methylation (hap-ASM) can impact disease susceptibility, but maps of this phenomenon using stringent criteria in disease-relevant tissues remain sparse. Here we apply array-based and Methyl-Seq approaches to multiple human tissues and cell types, including brain, purified neurons and glia, T lymphocytes, and placenta, and identify 795 hap-ASM differentially methylated regions (DMRs) and 3,082 strong methylation quantitative trait loci (mQTLs), most not previously reported. More than half of these DMRs have cell type-restricted ASM, and among them are 188 hap-ASM DMRs and 933 mQTLs located near GWAS signals for immune and neurological disorders. Targeted bis-seq confirmed hap-ASM in 12/13 loci tested, including CCDC155, CD69, FRMD1, IRF1, KBTBD11, and S100A(∗)-ILF2, associated with immune phenotypes, MYT1L, PTPRN2, CMTM8 and CELF2, associated with neurological disorders, NGFR and HLA-DRB6, associated with both immunological and brain disorders, and ZFP57, a trans-acting regulator of genomic imprinting. Polymorphic CTCF and transcription factor (TF) binding sites were over-represented among hap-ASM DMRs and mQTLs, and analysis of the human data, supplemented by cross-species comparisons to macaques, indicated that CTCF and TF binding likelihood predicts the strength and direction of the allelic methylation asymmetry. These results show that hap-ASM is highly tissue specific; an important trans-acting regulator of genomic imprinting is regulated by this phenomenon; and variation in CTCF and TF binding sites is an underlying mechanism, and maps of hap-ASM and mQTLs reveal regulatory sequences underlying supra- and sub-threshold GWAS peaks in immunological and neurological disorders.
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10
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Al Tuwaijri A, Gagné-Ouellet V, Madore AM, Laprise C, Naumova AK. Local genotype influences DNA methylation at two asthma-associated regions, 5q31 and 17q21, in a founder effect population. J Med Genet 2015; 53:232-41. [PMID: 26671913 DOI: 10.1136/jmedgenet-2015-103313] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Accepted: 11/14/2015] [Indexed: 02/06/2023]
Abstract
BACKGROUND Two asthma-associated regions 17q12-q21 and 5q31.1 harbour genes that show strong effect of genotype on expression levels. DNA methylation has an important role in gene regulation; therefore, we examined DNA methylation at promoters of 12 genes from 5q31 and 17q12-q21 regions. Our goal was to determine whether DNA methylation was associated with predisposition to asthma and whether such a relationship was independent from genetic association. METHODS Using sodium bisulfite sequencing and pyrosequencing methylation assays, we examined the effect of genotype on DNA methylation in peripheral blood cells from individuals from the Saguenay-Lac-Saint-Jean asthma familial collection and lymphoblastoid cell lines. RESULTS The local genotype influenced methylation levels of solute carrier family 22 (organic 3 cation/carnitine transporter) member 5 (SLC22A5), zona pellucida binding protein 2 (ZPBP2) and gasdermin A (GSDMA) promoter regions. The genotype had a dominant effect on ZPBP2 and GSDMA methylation with lower methylation levels in individuals that carry the asthma-predisposing alleles. Males also had lower methylation at the ZPBP2 promoter than females. We did not observe an effect of asthma status that would be independent of the genotype and the sex effects in the GSDMA, ZPBP2 and SLC22A5 regions; however, GSDMA and ZPBP2 data were suggestive of interaction between asthma and methylation levels in females and SLC22A5 in males. CONCLUSIONS The local genotype influences methylation levels at SLC22A5 and ZPBP2 promoters independently of the asthma status. Further studies are necessary to confirm the relationship between GSDMA-ZPBP2 and SLC22A5 methylation and asthma in females and males separately.
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Affiliation(s)
- Abeer Al Tuwaijri
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
| | - Valérie Gagné-Ouellet
- Département des sciences fondamentales, Université du Québec à Chicoutimi, Chicoutimi, Quebec, Canada
| | - Anne-Marie Madore
- Département des sciences fondamentales, Université du Québec à Chicoutimi, Chicoutimi, Quebec, Canada
| | - Catherine Laprise
- Département des sciences fondamentales, Université du Québec à Chicoutimi, Chicoutimi, Quebec, Canada
| | - Anna K Naumova
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada Department of Obstetrics and Gynecology, McGill University, Montreal, Quebec, Canada The Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
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11
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Lea AJ, Tung J, Zhou X. A Flexible, Efficient Binomial Mixed Model for Identifying Differential DNA Methylation in Bisulfite Sequencing Data. PLoS Genet 2015; 11:e1005650. [PMID: 26599596 PMCID: PMC4657956 DOI: 10.1371/journal.pgen.1005650] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2015] [Accepted: 10/14/2015] [Indexed: 11/26/2022] Open
Abstract
Identifying sources of variation in DNA methylation levels is important for understanding gene regulation. Recently, bisulfite sequencing has become a popular tool for investigating DNA methylation levels. However, modeling bisulfite sequencing data is complicated by dramatic variation in coverage across sites and individual samples, and because of the computational challenges of controlling for genetic covariance in count data. To address these challenges, we present a binomial mixed model and an efficient, sampling-based algorithm (MACAU: Mixed model association for count data via data augmentation) for approximate parameter estimation and p-value computation. This framework allows us to simultaneously account for both the over-dispersed, count-based nature of bisulfite sequencing data, as well as genetic relatedness among individuals. Using simulations and two real data sets (whole genome bisulfite sequencing (WGBS) data from Arabidopsis thaliana and reduced representation bisulfite sequencing (RRBS) data from baboons), we show that our method provides well-calibrated test statistics in the presence of population structure. Further, it improves power to detect differentially methylated sites: in the RRBS data set, MACAU detected 1.6-fold more age-associated CpG sites than a beta-binomial model (the next best approach). Changes in these sites are consistent with known age-related shifts in DNA methylation levels, and are enriched near genes that are differentially expressed with age in the same population. Taken together, our results indicate that MACAU is an efficient, effective tool for analyzing bisulfite sequencing data, with particular salience to analyses of structured populations. MACAU is freely available at www.xzlab.org/software.html.
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Affiliation(s)
- Amanda J. Lea
- Department of Biology, Duke University, Durham, North Carolina, United States of America
| | - Jenny Tung
- Department of Biology, Duke University, Durham, North Carolina, United States of America
- Institute of Primate Research, National Museums of Kenya, Karen, Nairobi, Kenya
- Department of Evolutionary Anthropology, Duke University, Durham, North Carolina, United States of America
- Duke University Population Research Institute, Duke University, Durham, North Carolina, United States of America
| | - Xiang Zhou
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
- Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
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