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Xing F, Han F, Wu Y, Lv B, Tian H, Wang W, Tian X, Xu C, Duan H, Zhang D, Wu Y. An epigenome-wide association study of waist circumference in Chinese monozygotic twins. Int J Obes (Lond) 2024; 48:1148-1156. [PMID: 38773251 DOI: 10.1038/s41366-024-01538-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 05/05/2024] [Accepted: 05/09/2024] [Indexed: 05/23/2024]
Abstract
OBJECTIVES Central obesity poses significant health risks because it increases susceptibility to multiple chronic diseases. Epigenetic features such as DNA methylation may be associated with specific obesity traits, which could help us understand how genetic and environmental factors interact to influence the development of obesity. This study aims to identify DNA methylation sites associated with the waist circumference (WC) in Northern Han Chinese population, and to elucidate potential causal relationships. METHODS A total of 59 pairs of WC discordant monozygotic twins (ΔWC >0) were selected from the Qingdao Twin Registry in China. Generalized estimated equation model was employed to estimate the methylation levels of CpG sites on WC. Causal relationships between methylation and WC were assessed through the examination of family confounding factors using FAmiliaL CONfounding (ICE FALCON). Additionally, the findings of the epigenome-wide analysis were corroborated in the validation stage. RESULTS We identified 26 CpG sites with differential methylation reached false discovery rate (FDR) < 0.05 and 22 differentially methylated regions (slk-corrected p < 0.05) strongly linked to WC. These findings provided annotations for 26 genes, with notable emphasis on MMP17, ITGA11, COL23A1, TFPI, A2ML1-AS1, MRGPRE, C2orf82, and NINJ2. ICE FALCON analysis indicated the DNA methylation of ITGA11 and TFPI had a causal effect on WC and vice versa (p < 0.05). Subsequent validation analysis successfully replicated 10 (p < 0.05) out of the 26 identified sites. CONCLUSIONS Our research has ascertained an association between specific epigenetic variations and WC in the Northern Han Chinese population. These DNA methylation features can offer fresh insights into the epigenetic regulation of obesity and WC as well as hints to plausible biological mechanisms.
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Affiliation(s)
- Fangjie Xing
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Fulei Han
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Yan Wu
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Bosen Lv
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Huimin Tian
- Zhonglou District Center for Disease Control and Prevention, Changzhou, Jiangsu, China
| | - Weijing Wang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Xiaocao Tian
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, Shandong, China
| | - Chunsheng Xu
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, Shandong, China
| | - Haiping Duan
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, Shandong, China
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Yili Wu
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China.
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2
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Elliott HR, Bennett CL, Caramaschi D, English S. Negative association between higher maternal pre-pregnancy body mass index and breastfeeding outcomes is not mediated by DNA methylation. Sci Rep 2024; 14:14675. [PMID: 38918574 PMCID: PMC11199553 DOI: 10.1038/s41598-024-65605-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 06/21/2024] [Indexed: 06/27/2024] Open
Abstract
The benefits of breastfeeding for the health and wellbeing of both infants and mothers are well documented, yet global breastfeeding rates are low. One factor associated with low breast feeding is maternal body mass index (BMI), which is used as a measure of obesity. The negative relationship between maternal obesity and breastfeeding is likely caused by a variety of social, psychological, and physiological factors. Maternal obesity may also have a direct biological association with breastfeeding through changes in maternal DNA methylation. Here, we investigate this potential biological association using data from a UK-based cohort study, the Avon Longitudinal Study of Parents and Children (ALSPAC). We find that pre-pregnancy body mass index (BMI) is associated with lower initiation to breastfeed and shorter breastfeeding duration. We conduct epigenome-wide association studies (EWAS) of pre-pregnancy BMI and breastfeeding outcomes, and run candidate-gene analysis of methylation sites associated with BMI identified via previous meta-EWAS. We find that DNA methylation at cg11453712, annotated to PHTP1, is associated with pre-pregnancy BMI. From our results, neither this association nor those at candidate-gene sites are likely to mediate the link between pre-pregnancy BMI and breastfeeding.
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Affiliation(s)
- Hannah R Elliott
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Chloe L Bennett
- School of Biological Sciences, University of Bristol, Bristol, UK
| | - Doretta Caramaschi
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Faculty of Health and Life Sciences, Department of Psychology, University of Exeter, Exeter, UK
| | - Sinead English
- School of Biological Sciences, University of Bristol, Bristol, UK.
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3
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Yap CX, Vo DD, Heffel MG, Bhattacharya A, Wen C, Yang Y, Kemper KE, Zeng J, Zheng Z, Zhu Z, Hannon E, Vellame DS, Franklin A, Caggiano C, Wamsley B, Geschwind DH, Zaitlen N, Gusev A, Pasaniuc B, Mill J, Luo C, Gandal MJ. Brain cell-type shifts in Alzheimer's disease, autism, and schizophrenia interrogated using methylomics and genetics. SCIENCE ADVANCES 2024; 10:eadn7655. [PMID: 38781333 PMCID: PMC11114225 DOI: 10.1126/sciadv.adn7655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Accepted: 03/14/2024] [Indexed: 05/25/2024]
Abstract
Few neuropsychiatric disorders have replicable biomarkers, prompting high-resolution and large-scale molecular studies. However, we still lack consensus on a more foundational question: whether quantitative shifts in cell types-the functional unit of life-contribute to neuropsychiatric disorders. Leveraging advances in human brain single-cell methylomics, we deconvolve seven major cell types using bulk DNA methylation profiling across 1270 postmortem brains, including from individuals diagnosed with Alzheimer's disease, schizophrenia, and autism. We observe and replicate cell-type compositional shifts for Alzheimer's disease (endothelial cell loss), autism (increased microglia), and schizophrenia (decreased oligodendrocytes), and find age- and sex-related changes. Multiple layers of evidence indicate that endothelial cell loss contributes to Alzheimer's disease, with comparable effect size to APOE genotype among older people. Genome-wide association identified five genetic loci related to cell-type composition, involving plausible genes for the neurovascular unit (P2RX5 and TRPV3) and excitatory neurons (DPY30 and MEMO1). These results implicate specific cell-type shifts in the pathophysiology of neuropsychiatric disorders.
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Affiliation(s)
- Chloe X. Yap
- Mater Research Institute, University of Queensland, Brisbane, Queensland, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Daniel D. Vo
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Lifespan Brain Institute at Penn Medicine and The Children’s Hospital of Philadelphia, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew G. Heffel
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
| | - Arjun Bhattacharya
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Institute for Quantitative and Computational Biosciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Institute for Data Science in Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Cindy Wen
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Yuanhao Yang
- Mater Research Institute, University of Queensland, Brisbane, Queensland, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Kathryn E. Kemper
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Jian Zeng
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Zhili Zheng
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Zhihong Zhu
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- The National Centre for Register-based Research, Aarhus University, Denmark
| | - Eilis Hannon
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Dorothea Seiler Vellame
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Alice Franklin
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Christa Caggiano
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
| | - Brie Wamsley
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, Los Angeles, CA, USA
| | - Daniel H. Geschwind
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, Los Angeles, CA, USA
| | - Noah Zaitlen
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Alexander Gusev
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Brigham & Women’s Hospital, Boston, MA, USA
- Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Bogdan Pasaniuc
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Computational Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Institute for Precision Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jonathan Mill
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Chongyuan Luo
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Michael J. Gandal
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Lifespan Brain Institute at Penn Medicine and The Children’s Hospital of Philadelphia, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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4
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Ao X, Parisien M, Fillingim RB, Ohrbach R, Slade GD, Diatchenko L, Smith SB. Whole-genome methylation profiling reveals regions associated with painful temporomandibular disorders and active recovery processes. Pain 2024; 165:1060-1073. [PMID: 38015635 PMCID: PMC11018476 DOI: 10.1097/j.pain.0000000000003104] [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: 05/07/2023] [Accepted: 08/24/2023] [Indexed: 11/30/2023]
Abstract
ABSTRACT Temporomandibular disorders (TMDs), collectively representing one of the most common chronic pain conditions, have a substantial genetic component, but genetic variation alone has not fully explained the heritability of TMD risk. Reasoning that the unexplained heritability may be because of DNA methylation, an epigenetic phenomenon, we measured genome-wide DNA methylation using the Illumina MethylationEPIC platform with blood samples from participants in the Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA) study. Associations with chronic TMD used methylation data from 496 chronic painful TMD cases and 452 TMD-free controls. Changes in methylation between enrollment and a 6-month follow-up visit were determined for a separate sample of 62 people with recent-onset painful TMD. More than 750,000 individual CpG sites were examined for association with chronic painful TMD. Six differentially methylated regions were significantly ( P < 5 × 10 -8 ) associated with chronic painful TMD, including loci near genes involved in the regulation of inflammatory and neuronal response. A majority of loci were similarly differentially methylated in acute TMD consistent with observed transience or persistence of symptoms at follow-up. Functional characterization of the identified regions found relationships between methylation at these loci and nearby genetic variation contributing to chronic painful TMD and with gene expression of proximal genes. These findings reveal epigenetic contributions to chronic painful TMD through methylation of the genes FMOD , PM20D1 , ZNF718 , ZFP57 , and RNF39 , following the development of acute painful TMD. Epigenetic regulation of these genes likely contributes to the trajectory of transcriptional events in affected tissues leading to resolution or chronicity of pain.
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Affiliation(s)
- Xiang Ao
- Faculty of Dental Medicine and Oral Health Sciences; Department of Anesthesia, Faculty of Medicine and Health Sciences; Alan Edwards Centre for Research on Pain; McGill University, Montreal, Canada
| | - Marc Parisien
- Faculty of Dental Medicine and Oral Health Sciences; Department of Anesthesia, Faculty of Medicine and Health Sciences; Alan Edwards Centre for Research on Pain; McGill University, Montreal, Canada
| | - Roger B. Fillingim
- Department of Community Dentistry and Behavioral Science, University of Florida, Gainesville, Florida; Pain Research and Intervention Center of Excellence, Department of Community Dentistry and Behavioral Science, College of Dentistry, University of Florida, Gainesville, Florida
| | - Richard Ohrbach
- Department of Oral Diagnostic Sciences, University at Buffalo, Buffalo, New York
| | - Gary D. Slade
- Division of Pediatric and Public Health, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Luda Diatchenko
- Faculty of Dental Medicine and Oral Health Sciences; Department of Anesthesia, Faculty of Medicine and Health Sciences; Alan Edwards Centre for Research on Pain; McGill University, Montreal, Canada
| | - Shad B. Smith
- Center for Translational Pain Medicine, Department of Anesthesiology, Duke University, Durham, North Carolina, USA
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5
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Skowronski AA, Leibel RL, LeDuc CA. Neurodevelopmental Programming of Adiposity: Contributions to Obesity Risk. Endocr Rev 2024; 45:253-280. [PMID: 37971140 PMCID: PMC10911958 DOI: 10.1210/endrev/bnad031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 09/29/2023] [Accepted: 10/19/2023] [Indexed: 11/19/2023]
Abstract
This review analyzes the published evidence regarding maternal factors that influence the developmental programming of long-term adiposity in humans and animals via the central nervous system (CNS). We describe the physiological outcomes of perinatal underfeeding and overfeeding and explore potential mechanisms that may mediate the impact of such exposures on the development of feeding circuits within the CNS-including the influences of metabolic hormones and epigenetic changes. The perinatal environment, reflective of maternal nutritional status, contributes to the programming of offspring adiposity. The in utero and early postnatal periods represent critically sensitive developmental windows during which the hormonal and metabolic milieu affects the maturation of the hypothalamus. Maternal hyperglycemia is associated with increased transfer of glucose to the fetus driving fetal hyperinsulinemia. Elevated fetal insulin causes increased adiposity and consequently higher fetal circulating leptin concentration. Mechanistic studies in animal models indicate important roles of leptin and insulin in central and peripheral programming of adiposity, and suggest that optimal concentrations of these hormones are critical during early life. Additionally, the environmental milieu during development may be conveyed to progeny through epigenetic marks and these can potentially be vertically transmitted to subsequent generations. Thus, nutritional and metabolic/endocrine signals during perinatal development can have lifelong (and possibly multigenerational) impacts on offspring body weight regulation.
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Affiliation(s)
- Alicja A Skowronski
- Division of Molecular Genetics, Department of Pediatrics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY 10032, USA
- Naomi Berrie Diabetes Center, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Rudolph L Leibel
- Division of Molecular Genetics, Department of Pediatrics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY 10032, USA
- Naomi Berrie Diabetes Center, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Charles A LeDuc
- Division of Molecular Genetics, Department of Pediatrics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY 10032, USA
- Naomi Berrie Diabetes Center, Columbia University Irving Medical Center, New York, NY 10032, USA
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6
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Chou PC, Huang YC, Yu S. Mechanisms of Epigenetic Inheritance in Post-Traumatic Stress Disorder. Life (Basel) 2024; 14:98. [PMID: 38255713 PMCID: PMC10817356 DOI: 10.3390/life14010098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 12/22/2023] [Accepted: 01/05/2024] [Indexed: 01/24/2024] Open
Abstract
Post-traumatic stress disorder (PTSD) is a psychiatric disorder that causes debilitating functional impairment in patients. Observations from survivors of traumatic historical events solidify that this disease is not only associated with personal experiences but can also be inherited from familial traumas. Over the past decades, researchers have focused on epigenetic inheritance to understand how responses to adverse experiences can be passed down to future generations. This review aims to present recent findings on epigenetic markers related to PTSD and research in the intergenerational inheritance of trauma. By understanding the information, we hope that epigenetic markers can act as biochemical measurements for future clinical practice.
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Affiliation(s)
- Pei-Chen Chou
- School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan;
| | - Yu-Chi Huang
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan;
| | - Sebastian Yu
- Department of Dermatology, College of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
- Department of Dermatology, Kaohsiung Medical University Hospital, Kaohsiung 80756, Taiwan
- Master of Public Health Degree Program, National Taiwan University, Taipei 10617, Taiwan
- Neuroscience Research Center, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
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7
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Fang F, Quach B, Lawrence KG, van Dongen J, Marks JA, Lundgren S, Lin M, Odintsova VV, Costeira R, Xu Z, Zhou L, Mandal M, Xia Y, Vink JM, Bierut LJ, Ollikainen M, Taylor JA, Bell JT, Kaprio J, Boomsma DI, Xu K, Sandler DP, Hancock DB, Johnson EO. Trans-ancestry epigenome-wide association meta-analysis of DNA methylation with lifetime cannabis use. Mol Psychiatry 2024; 29:124-133. [PMID: 37935791 PMCID: PMC11078760 DOI: 10.1038/s41380-023-02310-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 10/16/2023] [Accepted: 10/23/2023] [Indexed: 11/09/2023]
Abstract
Cannabis is widely used worldwide, yet its links to health outcomes are not fully understood. DNA methylation can serve as a mediator to link environmental exposures to health outcomes. We conducted an epigenome-wide association study (EWAS) of peripheral blood-based DNA methylation and lifetime cannabis use (ever vs. never) in a meta-analysis including 9436 participants (7795 European and 1641 African ancestry) from seven cohorts. Accounting for effects of cigarette smoking, our trans-ancestry EWAS meta-analysis revealed four CpG sites significantly associated with lifetime cannabis use at a false discovery rate of 0.05 ( p < 5.85 × 10 - 7 ) : cg22572071 near gene ADGRF1, cg15280358 in ADAM12, cg00813162 in ACTN1, and cg01101459 near LINC01132. Additionally, our EWAS analysis in participants who never smoked cigarettes identified another epigenome-wide significant CpG site, cg14237301 annotated to APOBR. We used a leave-one-out approach to evaluate methylation scores constructed as a weighted sum of the significant CpGs. The best model can explain 3.79% of the variance in lifetime cannabis use. These findings unravel the DNA methylation changes associated with lifetime cannabis use that are independent of cigarette smoking and may serve as a starting point for further research on the mechanisms through which cannabis exposure impacts health outcomes.
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Affiliation(s)
- Fang Fang
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA.
| | - Bryan Quach
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Kaitlyn G Lawrence
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Jesse A Marks
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Sara Lundgren
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Mingkuan Lin
- Department of Psychiatry, Yale School of Medicine, West Haven, CT, USA
| | - Veronika V Odintsova
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Ricardo Costeira
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Linran Zhou
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Meisha Mandal
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Yujing Xia
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Jacqueline M Vink
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Laura J Bierut
- Department of Psychiatry, Washington University in Saint Louis School of Medicine, St. Louis, MO, USA
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Jordana T Bell
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Ke Xu
- Department of Psychiatry, Yale School of Medicine, West Haven, CT, USA
- VA Connecticut Healthcare System, West Haven, CT, USA
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Dana B Hancock
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Eric O Johnson
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
- Fellow Program, RTI International, Research Triangle Park, NC, USA
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8
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Derakhshan M, Kessler NJ, Hellenthal G, Silver MJ. Metastable epialleles in humans. Trends Genet 2024; 40:52-68. [PMID: 38000919 DOI: 10.1016/j.tig.2023.09.007] [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: 05/22/2023] [Revised: 09/20/2023] [Accepted: 09/21/2023] [Indexed: 11/26/2023]
Abstract
First identified in isogenic mice, metastable epialleles (MEs) are loci where the extent of DNA methylation (DNAm) is variable between individuals but correlates across tissues derived from different germ layers within a given individual. This property, termed systemic interindividual variation (SIV), is attributed to stochastic methylation establishment before germ layer differentiation. Evidence suggests that some putative human MEs are sensitive to environmental exposures in early development. In this review we introduce key concepts pertaining to human MEs, describe methods used to identify MEs in humans, and review their genomic features. We also highlight studies linking DNAm at putative human MEs to early environmental exposures and postnatal (including disease) phenotypes.
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Affiliation(s)
- Maria Derakhshan
- London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
| | - Noah J Kessler
- Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK
| | | | - Matt J Silver
- London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK; Medical Research Council (MRC) Unit The Gambia at the London School of Hygiene and Tropical Medicine, Fajara, Banjul, The Gambia.
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9
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Walton E, Baltramonaityte V, Calhoun V, Heijmans BT, Thompson PM, Cecil CAM. A systematic review of neuroimaging epigenetic research: calling for an increased focus on development. Mol Psychiatry 2023; 28:2839-2847. [PMID: 37185958 PMCID: PMC10615743 DOI: 10.1038/s41380-023-02067-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 03/03/2023] [Accepted: 04/03/2023] [Indexed: 05/17/2023]
Abstract
Epigenetic mechanisms, such as DNA methylation (DNAm), have gained increasing attention as potential biomarkers and mechanisms underlying risk for neurodevelopmental, psychiatric and other brain-based disorders. Yet, surprisingly little is known about the extent to which DNAm is linked to individual differences in the brain itself, and how these associations may unfold across development - a time of life when many of these disorders emerge. Here, we systematically review evidence from the nascent field of Neuroimaging Epigenetics, combining structural or functional neuroimaging measures with DNAm, and the extent to which the developmental period (birth to adolescence) is represented in these studies. We identified 111 articles published between 2011-2021, out of which only a minority (21%) included samples under 18 years of age. Most studies were cross-sectional (85%), employed a candidate-gene approach (67%), and examined DNAm-brain associations in the context of health and behavioral outcomes (75%). Nearly half incorporated genetic data, and a fourth investigated environmental influences. Overall, studies support a link between peripheral DNAm and brain imaging measures, but there is little consistency in specific findings and it remains unclear whether DNAm markers present a cause, correlate or consequence of brain alterations. Overall, there is large heterogeneity in sample characteristics, peripheral tissue and brain outcome examined as well as the methods used. Sample sizes were generally low to moderate (median nall = 98, ndevelopmental = 80), and attempts at replication or meta-analysis were rare. Based on the strengths and weaknesses of existing studies, we propose three recommendations on how advance the field of Neuroimaging Epigenetics. We advocate for: (1) a greater focus on developmentally oriented research (i.e. pre-birth to adolescence); (2) the analysis of large, prospective, pediatric cohorts with repeated measures of DNAm and imaging to assess directionality; and (3) collaborative, interdisciplinary science to identify robust signals, triangulate findings and enhance translational potential.
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Affiliation(s)
- Esther Walton
- Department of Psychology, University of Bath, Bath, UK.
| | | | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Bastiaan T Heijmans
- Molecular Epidemiology, Dept. of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA, USA
| | - Charlotte A M Cecil
- Molecular Epidemiology, Dept. of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
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10
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Hahn J, Bressler J, Domingo-Relloso A, Chen MH, McCartney DL, Teumer A, van Dongen J, Kleber ME, Aïssi D, Swenson BR, Yao J, Zhao W, Huang J, Xia Y, Brown MR, Costeira R, de Geus EJC, Delgado GE, Dobson DA, Elliott P, Grabe HJ, Guo X, Harris SE, Huffman JE, Kardia SLR, Liu Y, Lorkowski S, Marioni RE, Nauck M, Ratliff SM, Sabater-Lleal M, Spector TD, Suchon P, Taylor KD, Thibord F, Trégouët DA, Wiggins KL, Willemsen G, Bell JT, Boomsma DI, Cole SA, Cox SR, Dehghan A, Greinacher A, Haack K, März W, Morange PE, Rotter JI, Sotoodehnia N, Tellez-Plaza M, Navas-Acien A, Smith JA, Johnson AD, Fornage M, Smith NL, Wolberg AS, Morrison AC, de Vries PS. DNA methylation analysis is used to identify novel genetic loci associated with circulating fibrinogen levels in blood. J Thromb Haemost 2023; 21:1135-1147. [PMID: 36716967 DOI: 10.1016/j.jtha.2023.01.015] [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: 07/25/2022] [Revised: 11/04/2022] [Accepted: 01/17/2023] [Indexed: 01/30/2023]
Abstract
BACKGROUND Fibrinogen plays an essential role in blood coagulation and inflammation. Circulating fibrinogen levels may be determined based on interindividual differences in DNA methylation at cytosine-phosphate-guanine (CpG) sites and vice versa. OBJECTIVES To perform an EWAS to examine an association between blood DNA methylation levels and circulating fibrinogen levels to better understand its biological and pathophysiological actions. METHODS We performed an epigenome-wide association study of circulating fibrinogen levels in 18 037 White, Black, American Indian, and Hispanic participants, representing 14 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium. Circulating leukocyte DNA methylation was measured using the Illumina 450K array in 12 904 participants and using the EPIC array in 5133 participants. In each study, an epigenome-wide association study of fibrinogen was performed using linear mixed models adjusted for potential confounders. Study-specific results were combined using array-specific meta-analysis, followed by cross-replication of epigenome-wide significant associations. We compared models with and without CRP adjustment to examine the role of inflammation. RESULTS We identified 208 and 87 significant CpG sites associated with fibrinogen levels from the 450K (p < 1.03 × 10-7) and EPIC arrays (p < 5.78 × 10-8), respectively. There were 78 associations from the 450K array that replicated in the EPIC array and 26 vice versa. After accounting for overlapping sites, there were 83 replicated CpG sites located in 61 loci, of which only 4 have been previously reported for fibrinogen. The examples of genes located near these CpG sites were SOCS3 and AIM2, which are involved in inflammatory pathways. The associations of all 83 replicated CpG sites were attenuated after CRP adjustment, although many remained significant. CONCLUSION We identified 83 CpG sites associated with circulating fibrinogen levels. These associations are partially driven by inflammatory pathways shared by both fibrinogen and CRP.
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Affiliation(s)
- Julie Hahn
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA.
| | - Jan Bressler
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Arce Domingo-Relloso
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA; Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institutes, Madrid, Spain; Department of Statistics and Operations Research, University of Valencia, Burjassot, Spain
| | - Ming-Huei Chen
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, Massachusetts, USA
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Alexander Teumer
- Department SHIP/Clinical-Epidemiological Research, Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany; DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany; Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Marcus E Kleber
- Vth Department of Medicine, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany; SYNLAB MVZ Humangenetik Mannheim, Mannheim, Germany
| | - Dylan Aïssi
- Univ. Bordeaux, INSERM, Bordeaux Population Health Research Center, UMR 1219, Molecular Epidemiology of Vascular and Brain Disorders, Bordeaux, France
| | - Brenton R Swenson
- Cardiovascular Health Research Unit, School of Public Health, University of Washington, Seattle, Washington, USA
| | - Jie Yao
- Pediatrics, Genomic Outcomes, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA; Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Jian Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Yujing Xia
- Department of Twin Research and Genetic Epidemiology, St Thomas Hospital Campus, King's College London, London, United Kingdom
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Ricardo Costeira
- Department of Twin Research and Genetic Epidemiology, St Thomas Hospital Campus, King's College London, London, United Kingdom
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Graciela E Delgado
- Vth Department of Medicine, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Dre'Von A Dobson
- Pathology and Laboratory Medicine and UNC Blood Research Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom; UK Dementia Research Institute, Imperial College London, London, United Kingdom; British Heart Foundation Centre for Research Excellence, Imperial College London, London, United Kingdom
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany; German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Xiuqing Guo
- Pediatrics, Genomic Outcomes, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Sarah E Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Jennifer E Huffman
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Yongmei Liu
- Medicine, Cardiology, Duke Molecular Physiology Institute, Durham, North Carolina, USA
| | - Stefan Lorkowski
- Institute of Nutritional Sciences, Friedrich Schiller University Jena, Jena, Germany; Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig, Jena, Germany
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Matthias Nauck
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany; Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Scott M Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Maria Sabater-Lleal
- Genomics of Complex Disease Unit, Sant Pau Biomedical Research Institute (IIB Sant Pau), Barcelona, Spain; Department of Medicine, Cardiovascular Medicine Unit, Karolinska Institutet, Stockholm, Sweden
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, St Thomas Hospital Campus, King's College London, London, United Kingdom
| | - Pierre Suchon
- Center for CardioVascular and Nutrition research (C2VN), INSERM 1263, INRAE 1260, Hematology Laboratory, La Timone University Hospital of Marseille, Aix-Marseille University, Marseille, France
| | - Kent D Taylor
- Pediatrics, Genomic Outcomes, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Florian Thibord
- Population Sciences Branch, National Heart, Lung, and Blood Institute, Framingham, Massachusetts, USA
| | - David-Alexandre Trégouët
- Univ. Bordeaux, INSERM, Bordeaux Population Health Research Center, UMR 1219, Molecular Epidemiology of Vascular and Brain Disorders, Bordeaux, France
| | - Kerri L Wiggins
- Department of Medicine, Division of General Internal Medicine, University of Washington, Seattle, Washington, USA
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, St Thomas Hospital Campus, King's College London, London, United Kingdom
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Shelley A Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Simon R Cox
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Abbas Dehghan
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Andreas Greinacher
- Institute for Immunology and Transfusion Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Karin Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany; SYNLAB Academy, SYNLAB Holding Deutschland GmbH, Mannheim, Germany; Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
| | - Pierre-Emmanuel Morange
- Cardiovascular and Nutrition Reserach Center (C2VN), INSERM, INRAE, Aix-Marseille University, Marseille, France
| | - Jerome I Rotter
- Pediatrics, Genomic Outcomes, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Nona Sotoodehnia
- Department of Medicine, Division of Cardiology, University of Washington, Seattle, Washington, USA
| | - Maria Tellez-Plaza
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institutes, Madrid, Spain
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA; Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Andrew D Johnson
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, Massachusetts, USA
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA; Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Nicholas L Smith
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington, USA; Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Washington, USA; Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, Washington, USA
| | - Alisa S Wolberg
- Pathology and Laboratory Medicine and UNC Blood Research Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA.
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11
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Becerra CY, Wells RK, Kunihiro BP, Lee RH, Umeda L, Allan NP, Rubas NC, McCracken TA, Nunokawa CKL, Lee MH, Pidlaoan FGS, Phankitnirondorn K, Dye CK, Yamamoto BY, Peres R, Juarez R, Maunakea AK. Examining the immunoepigenetic-gut microbiome axis in the context of self-esteem among Native Hawaiians and other Pacific Islanders. Front Genet 2023; 14:1125217. [PMID: 37152987 PMCID: PMC10154580 DOI: 10.3389/fgene.2023.1125217] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 03/21/2023] [Indexed: 05/09/2023] Open
Abstract
Introduction: Native Hawaiian and other Pacific Islander (NHPI) populations experience higher rates of immunometabolic diseases compared to other racial-ethnic groups in Hawaii. As annual NHPI mortality rates for suicide and type 2 diabetes mellitus (T2DM) exceed those of the state as a whole, understanding the social and biological mechanisms underlying these disparities are urgently needed to enable preventive strategies. Methods: A community-based approach was used to investigate the immunoepigenetic-gut microbiome axis in an NHPI-enriched cohort of Oahu residents (N = 68). Self-esteem (SE) data was collected using a modified Rosenberg self-esteem (SE) assessment as a proxy measure for mental wellbeing in consideration for cultural competency. T2DM status was evaluated using point-of-care A1c (%) tests. Stool samples were collected for 16s-based metagenomic sequencing analyses. Plasma from blood samples were isolated by density-gradient centrifugation. Peripheral blood mononuclear cells (PBMCs) were collected from the same samples and enriched for monocytes using negative selection techniques. Flow-cytometry was used for immunoprofiling assays. Monocyte DNA was extracted for Illumina EPIC array-based methylation analysis. Results: Compared to individuals with normal SE (NSE), those with low SE (LSE) exhibited significantly higher plasma concentrations (pg/ml) of proinflammatory cytokines IL-8 (p = 0.051) and TNF-α (p = 0.011). Metagenomic analysis revealed that the relative abundance (%) of specific gut bacteria significantly differed between SE groups - some of which directly correlated with SE scores. Gene ontology analysis revealed that 104 significantly differentially methylated loci (DML) between SE groups were preferentially located at genes involved in immunometabolic processes. Horvath clock analyses indicated epigenetic age (Epi-Age) deceleration in individuals with LSE and acceleration in individuals with NSE (p = 0.042), yet was not reproduced by other clocks. Discussion: These data reveal novel differences in the immunoepigenetic-gut microbiome axis with respect to SE, warranting further investigation into its relationship to brain activity and mental health in NHPI. Unexpected results from Epi-Age analyses warrant further investigation into the relationship between biological age and disparate health outcomes among the NHPI population. The modifiable component of epigenetic processes and the gut microbiome makes this axis an attractive target for potential therapeutics, biomarker discovery, and novel prevention strategies.
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Affiliation(s)
- Celyna Y Becerra
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
- IDeA Networks of Biomedical Research Excellence (INBRE), University of Hawaii at Manoa, Honolulu, HI, United States
| | - Riley K Wells
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
- Department of Molecular Biosciences and Bioengineering, University of Hawaii at Manoa, Honolulu, HI, United States
| | - Braden P Kunihiro
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
- IDeA Networks of Biomedical Research Excellence (INBRE), University of Hawaii at Manoa, Honolulu, HI, United States
| | - Rosa H Lee
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Lesley Umeda
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
- Department of Molecular Biosciences and Bioengineering, University of Hawaii at Manoa, Honolulu, HI, United States
| | - Nina P Allan
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Noelle C Rubas
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Trevor A McCracken
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Chandler K L Nunokawa
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Ming-Hao Lee
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Felix Gerard S Pidlaoan
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Krit Phankitnirondorn
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Christian K Dye
- Department of Environmental Health Sciences, Columbia University Irving Medical Center, NY, NY, United States
| | - Brennan Y Yamamoto
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Rafael Peres
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Ruben Juarez
- Department of Economics, University of Hawaii at Manoa, Honolulu, HI, United States
- University of Hawaii Economic Research Organization (UHERO), University of Hawaii at Manoa, Honolulu, HI, United States
| | - Alika K Maunakea
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
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12
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Bell-Glenn S, Salas LA, Molinaro AM, Butler RA, Christensen BC, Kelsey KT, Wiencke JK, Koestler DC. Calculating detection limits and uncertainty of reference-based deconvolution of whole-blood DNA methylation data. Epigenomics 2023; 15:435-451. [PMID: 37337720 PMCID: PMC10308256 DOI: 10.2217/epi-2023-0006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Accepted: 05/16/2023] [Indexed: 06/21/2023] Open
Abstract
DNA methylation (DNAm)-based cell mixture deconvolution (CMD) has become a quintessential part of epigenome-wide association studies where DNAm is profiled in heterogeneous tissue types. Despite being introduced over a decade ago, detection limits, which represent the smallest fraction of a cell type in a mixed biospecimen that can be reliably detected, have yet to be determined in the context of DNAm-based CMD. Moreover, there has been little attention given to approaches for quantifying the uncertainty associated with DNAm-based CMD. Here, analytical frameworks for determining both cell-specific limits of detection and quantification of uncertainty associated with DNAm-based CMD are described. This work may contribute to improved rigor, reproducibility and replicability of epigenome-wide association studies involving CMD.
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Affiliation(s)
- Shelby Bell-Glenn
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Lucas A Salas
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Hanover, NH 03756, USA
| | - Annette M Molinaro
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
| | - Rondi A Butler
- Departments of Epidemiology & Pathology & Laboratory Medicine, Brown University, Providence, RI 02912, USA
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Hanover, NH 03756, USA
- Department of Molecular & Systems Biology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
- Department of Community & Family Medicine, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
| | - Karl T Kelsey
- Departments of Epidemiology & Pathology & Laboratory Medicine, Brown University, Providence, RI 02912, USA
| | - John K Wiencke
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA 94143, USA
| | - Devin C Koestler
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66160, USA
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13
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Treble-Barna A, Heinsberg LW, Stec Z, Breazeale S, Davis TS, Kesbhat AA, Chattopadhyay A, VonVille HM, Ketchum AM, Yeates KO, Kochanek PM, Weeks DE, Conley YP. Brain-derived neurotrophic factor (BDNF) epigenomic modifications and brain-related phenotypes in humans: A systematic review. Neurosci Biobehav Rev 2023; 147:105078. [PMID: 36764636 PMCID: PMC10164361 DOI: 10.1016/j.neubiorev.2023.105078] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 01/17/2023] [Accepted: 02/04/2023] [Indexed: 02/11/2023]
Abstract
Epigenomic modifications of the brain-derived neurotrophic factor (BDNF) gene have been postulated to underlie the pathogenesis of neurodevelopmental, psychiatric, and neurological conditions. This systematic review summarizes current evidence investigating the association of BDNF epigenomic modifications (DNA methylation, non-coding RNA, histone modifications) with brain-related phenotypes in humans. A novel contribution is our creation of an open access web-based application, the BDNF DNA Methylation Map, to interactively visualize specific positions of CpG sites investigated across all studies for which relevant data were available. Our literature search of four databases through September 27, 2021 returned 1701 articles, of which 153 met inclusion criteria. Our review revealed exceptional heterogeneity in methodological approaches, hindering the identification of clear patterns of robust and/or replicated results. We summarize key findings and provide recommendations for future epigenomic research. The existing literature appears to remain in its infancy and requires additional rigorous research to fulfill its potential to explain BDNF-linked risk for brain-related conditions and improve our understanding of the molecular mechanisms underlying their pathogenesis.
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Affiliation(s)
- Amery Treble-Barna
- Department of Physical Medicine & Rehabilitation, School of Medicine, University of Pittsburgh, PA 15261, USA.
| | - Lacey W Heinsberg
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA.
| | - Zachary Stec
- Department of Physical Medicine & Rehabilitation, School of Medicine, University of Pittsburgh, PA 15261, USA.
| | - Stephen Breazeale
- Department of Health and Human Development, School of Nursing, University of Pittsburgh, Pittsburgh, PA 15261, USA.
| | - Tara S Davis
- Department of Health Promotion and Development, School of Nursing, University of Pittsburgh, PA 15261, USA.
| | | | - Ansuman Chattopadhyay
- Molecular Biology Information Service, Health Sciences Library System, University of Pittsburgh, USA
| | - Helena M VonVille
- Health Sciences Library System, University of Pittsburgh, PA 15261, USA.
| | - Andrea M Ketchum
- Emeritus Health Sciences Library System, University of Pittsburgh, Pittsburgh, PA 15261, USA.
| | - Keith Owen Yeates
- Department of Psychology, Alberta Children's Hospital Research Institute and Hotchkiss Brain Institute, University of Calgary, Calgary, AB T2N1N4, Canada.
| | - Patrick M Kochanek
- Safar Center for Resuscitation Research, Department of Critical Care Medicine, School of Medicine, University of Pittsburgh, PA 15261, USA.
| | - Daniel E Weeks
- Department of Human Genetics and Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA.
| | - Yvette P Conley
- Department of Human Genetics, School of Nursing, University of Pittsburgh, Pittsburgh, PA 15261, USA.
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14
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Allen PC, Smith S, Wilson RC, Wirth JR, Wilson NH, Baker Frost D, Flume J, Gilkeson GS, Cunningham MA, Langefeld CD, Absher DM, Ramos PS. Distinct genome-wide DNA methylation and gene expression signatures in classical monocytes from African American patients with systemic sclerosis. Clin Epigenetics 2023; 15:25. [PMID: 36803404 PMCID: PMC9938585 DOI: 10.1186/s13148-023-01445-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 02/08/2023] [Indexed: 02/19/2023] Open
Abstract
BACKGROUND Systemic sclerosis (SSc) is a multisystem autoimmune disorder that has an unclear etiology and disproportionately affects women and African Americans. Despite this, African Americans are dramatically underrepresented in SSc research. Additionally, monocytes show heightened activation in SSc and in African Americans relative to European Americans. In this study, we sought to investigate DNA methylation and gene expression patterns in classical monocytes in a health disparity population. METHODS Classical monocytes (CD14+ + CD16-) were FACS-isolated from 34 self-reported African American women. Samples from 12 SSc patients and 12 healthy controls were hybridized on MethylationEPIC BeadChip array, while RNA-seq was performed on 16 SSc patients and 18 healthy controls. Analyses were computed to identify differentially methylated CpGs (DMCs), differentially expressed genes (DEGs), and CpGs associated with changes in gene expression (eQTM analysis). RESULTS We observed modest DNA methylation and gene expression differences between cases and controls. The genes harboring the top DMCs, the top DEGs, as well as the top eQTM loci were enriched for metabolic processes. Genes involved in immune processes and pathways showed a weak upregulation in the transcriptomic analysis. While many genes were newly identified, several other have been previously reported as differentially methylated or expressed in different blood cells from patients with SSc, supporting for their potential dysregulation in SSc. CONCLUSIONS While contrasting with results found in other blood cell types in largely European-descent groups, the results of this study support that variation in DNA methylation and gene expression exists among different cell types and individuals of different genetic, clinical, social, and environmental backgrounds. This finding supports the importance of including diverse, well-characterized patients to understand the different roles of DNA methylation and gene expression variability in the dysregulation of classical monocytes in diverse populations, which might help explaining the health disparities.
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Affiliation(s)
- Peter C Allen
- Department of Genetics, University of Alabama at Birmingham, Birmingham, AL, USA
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Sarah Smith
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Robert C Wilson
- Department of Pathology and Laboratory Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Jena R Wirth
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Nathan H Wilson
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - DeAnna Baker Frost
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Jonathan Flume
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Gary S Gilkeson
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Melissa A Cunningham
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Carl D Langefeld
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, NC, USA
- Center for Precision Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Devin M Absher
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Paula S Ramos
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA.
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
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15
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Systematic and benchmarking studies of pipelines for mammal WGBS data in the novel NGS platform. BMC Bioinformatics 2023; 24:33. [PMID: 36721080 PMCID: PMC9890740 DOI: 10.1186/s12859-023-05163-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 01/27/2023] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Whole genome bisulfite sequencing (WGBS), possesses the aptitude to dissect methylation status at the nucleotide-level resolution of 5-methylcytosine (5-mC) on a genome-wide scale. It is a powerful technique for epigenome in various cell types, and tissues. As a recently established next-generation sequencing (NGS) platform, GenoLab M is a promising alternative platform. However, its comprehensive evaluation for WGBS has not been reported. We sequenced two bisulfite-converted mammal DNA in this research using our GenoLab M and NovaSeq 6000, respectively. Then, we systematically compared those data via four widely used WGBS tools (BSMAP, Bismark, BatMeth2, BS-Seeker2) and a new bisulfite-seq tool (BSBolt). We interrogated their computational time, genome depth and coverage, and evaluated their percentage of methylated Cs. RESULT Here, benchmarking a combination of pre- and post-processing methods, we found that trimming improved the performance of mapping efficiency in eight datasets. The data from two platforms uncovered ~ 80% of CpG sites genome-wide in the human cell line. Those data sequenced by GenoLab M achieved a far lower proportion of duplicates (~ 5.5%). Among pipelines, BSMAP provided an intriguing representation of 5-mC distribution at CpG sites with 5-mC levels > ~ 78% in datasets from human cell lines, especially in the GenoLab M. BSMAP performed more advantages in running time, uniquely mapped reads percentages, genomic coverage, and quantitative accuracy. Finally, compared with the previous methylation pattern of human cell line and mouse tissue, we confirmed that the data from GenoLab M performed similar consistency and accuracy in methylation levels of CpG sites with that from NovaSeq 6000. CONCLUSION Together we confirmed that GenoLab M was a qualified NGS platform for WGBS with high performance. Our results showed that BSMAP was the suitable pipeline that allowed for WGBS studies on the GenoLab M platform.
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16
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Wattacheril JJ, Raj S, Knowles DA, Greally JM. Using epigenomics to understand cellular responses to environmental influences in diseases. PLoS Genet 2023; 19:e1010567. [PMID: 36656803 PMCID: PMC9851565 DOI: 10.1371/journal.pgen.1010567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
It is a generally accepted model that environmental influences can exert their effects, at least in part, by changing the molecular regulators of transcription that are described as epigenetic. As there is biochemical evidence that some epigenetic regulators of transcription can maintain their states long term and through cell division, an epigenetic model encompasses the idea of maintenance of the effect of an exposure long after it is no longer present. The evidence supporting this model is mostly from the observation of alterations of molecular regulators of transcription following exposures. With the understanding that the interpretation of these associations is more complex than originally recognised, this model may be oversimplistic; therefore, adopting novel perspectives and experimental approaches when examining how environmental exposures are linked to phenotypes may prove worthwhile. In this review, we have chosen to use the example of nonalcoholic fatty liver disease (NAFLD), a common, complex human disease with strong environmental and genetic influences. We describe how epigenomic approaches combined with emerging functional genetic and single-cell genomic techniques are poised to generate new insights into the pathogenesis of environmentally influenced human disease phenotypes exemplified by NAFLD.
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Affiliation(s)
- Julia J. Wattacheril
- Department of Medicine, Center for Liver Disease and Transplantation, Columbia University Irving Medical Center, New York Presbyterian Hospital, New York, New York, United States of America
| | - Srilakshmi Raj
- Division of Genomics, Department of Genetics, Albert Einstein College of Medicine, Bronx, New York, United States of America
| | - David A. Knowles
- New York Genome Center, New York, New York, United States of America
- Department of Computer Science, Columbia University, New York, New York, United States of America
- Department of Systems Biology, Columbia University, New York, New York, United States of America
| | - John M. Greally
- Division of Genomics, Department of Genetics, Albert Einstein College of Medicine, Bronx, New York, United States of America
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17
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Du H, Ma J, Zhou W, Li M, Huai C, Shen L, Wu H, Zhao X, Zhang N, Gao S, Wang Q, He L, Wu X, Qin S, Zhao M. Methylome-wide association study of different responses to risperidone in schizophrenia. Front Pharmacol 2022; 13:1078464. [PMID: 36618913 PMCID: PMC9815458 DOI: 10.3389/fphar.2022.1078464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 12/12/2022] [Indexed: 12/24/2022] Open
Abstract
Background: Accumulating evidence shows that DNA methylation plays a role in antipsychotic response. However, the mechanisms by which DNA methylation changes are associated with antipsychotic responses remain largely unknown. Methods: We performed a methylome-wide association study (MWAS) to evaluate the association between DNA methylation and the response to risperidone in schizophrenia. Genomic DNA methylation patterns were assessed using the Agilent Human DNA Methylation Microarray. Results: We identified numerous differentially methylated positions (DMPs) and regions (DMRs) associated with antipsychotic response. CYP46A1, SPATS2, and ATP6V1E1 had the most significant DMPs, with p values of 2.50 × 10-6, 3.53 × 10-6, and 5.71 × 10-6, respectively. The top-ranked DMR was located on chromosome 7, corresponding to the PTPRN2 gene with a Šidák-corrected p-value of 9.04 × 10-13. Additionally, a significant enrichment of synaptic function and neurotransmitters was found in the differentially methylated genes after gene ontology and pathway analysis. Conclusion: The identified DMP- and DMR-overlapping genes associated with antipsychotic response are related to synaptic function and neurotransmitters. These findings may improve understanding of the mechanisms underlying antipsychotic response and guide the choice of antipsychotic in schizophrenia.
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Affiliation(s)
- Huihui Du
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Jingsong Ma
- School o f Engineering, Westlake University, Hangzhou, Zhejiang, China,Institute of Advanced Technology, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Wei Zhou
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Mo Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Cong Huai
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Lu Shen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Hao Wu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Xianglong Zhao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Na Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Songyin Gao
- Zhumadian Psychiatric Hospital, Zhumadian, China
| | - Qi Wang
- Hebei Mental Health Center, Hebei Sixth People’s Hospital, Baoding, China
| | - Lin He
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Xuming Wu
- Nantong Fourth People’s Hospital, Nantong, China,*Correspondence: Xuming Wu, ; Shengying Qin, ; Mingzhe Zhao,
| | - Shengying Qin
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China,*Correspondence: Xuming Wu, ; Shengying Qin, ; Mingzhe Zhao,
| | - Mingzhe Zhao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders Ministry of Education, Shanghai Jiao Tong University, Shanghai, China,Affiliated Mental Health Center and Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China,*Correspondence: Xuming Wu, ; Shengying Qin, ; Mingzhe Zhao,
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18
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Childhood Trauma and Epigenetics: State of the Science and Future. Curr Environ Health Rep 2022; 9:661-672. [PMID: 36242743 DOI: 10.1007/s40572-022-00381-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/22/2022] [Indexed: 01/31/2023]
Abstract
PURPOSE OF REVIEW There is a great deal of interest regarding the biological embedding of childhood trauma and social exposures through epigenetic mechanisms, including DNA methylation (DNAm), but a comprehensive understanding has been hindered by issues of limited reproducibility between studies. This review presents a summary of the literature on childhood trauma and DNAm, highlights issues in the field, and proposes some potential solutions. RECENT FINDINGS Investigations of the associations between DNAm and childhood trauma are commonly performed using candidate gene approaches, specifically involving genes related to neurological and stress pathways. Childhood trauma is defined in a wide range of ways in several societal contexts. However, although variations in DNAm are frequently found in stress-related genes, unsupervised epigenome-wide association studies (EWAS) have shown limited reproducibility both between studies and in relating these changes to exposures. The reproducibility of childhood trauma DNAm studies, and the field of social epigenetics in general, may be improved by increasing sample sizes, standardizing variables, making use of effect size thresholds, collecting longitudinal and intervention samples, appropriately accounting for known confounding factors, and applying causal analysis wherever possible, such as "two-step epigenetic Mendelian randomization."
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19
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Epigenetic impact of a 1-week intensive multimodal group program for adolescents with multiple adverse childhood experiences. Sci Rep 2022; 12:17177. [PMID: 36266402 PMCID: PMC9585146 DOI: 10.1038/s41598-022-21246-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 09/26/2022] [Indexed: 01/04/2023] Open
Abstract
Adverse childhood experiences (ACEs, i.e., abuse, neglect, household dysfunction) represent a potential risk factor for a wide range of long-lasting diseases and shorter life expectancy. We recently described a 1-week residential group program, based on mindfulness training, artistic expression and EMDR group therapy, that significantly reduced PTSD-related symptoms and increased attention/awareness-related outcomes in adolescent girls with multiple ACEs in a randomized controlled study. Since epigenetic mechanisms (i.e., DNA methylation) have been associated with the long-lasting effects of ACEs, the present report extends these prior findings by exploring genome-wide DNA methylation changes following the program. Saliva samples from all participants (n = 44) were collected and genomic DNA was extracted prior (T1) and following (T2) the intervention. Genome-wide DNA methylation analysis using the MethylationEPIC beadchip array (Illumina) revealed 49 differentially methylated loci (DML; p value < 0.001; methylation change > 10%) that were annotated to genes with roles in biological processes linked to early childhood adversity (i.e., neural, immune, and endocrine pathways, cancer and cardiovascular disease). DNA sequences flanking these DML showed significant enrichment of transcription factor binding sites involved in inflammation, cancer, cardiovascular disease, and brain development. Methylation changes in SIRT5 and TRAPPC2L genes showed associations with changes in trauma-related psychological measures. Results presented here suggest that this multimodal group program for adolescents with multiple victimization modulates the DNA methylome at sites of potential relevance for health and behavioral disorders associated with ACEs.
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20
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No evidence for intervention-associated DNA methylation changes in monocytes of patients with posttraumatic stress disorder. Sci Rep 2022; 12:17347. [PMID: 36253434 PMCID: PMC9576776 DOI: 10.1038/s41598-022-22177-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 10/11/2022] [Indexed: 01/10/2023] Open
Abstract
DNA methylation patterns can be responsive to environmental influences. This observation has sparked interest in the potential for psychological interventions to influence epigenetic processes. Recent studies have observed correlations between DNA methylation changes and therapy outcome. However, most did not control for changes in cell composition. This study had two aims: first, we sought to replicate therapy-associated changes in DNA methylation of commonly assessed candidate genes in isolated monocytes from 60 female patients with post-traumatic stress disorder (PTSD). Our second, exploratory goal was to identify novel genomic regions with substantial pre-to-post intervention DNA methylation changes by performing whole-genome bisulfite sequencing (WGBS) in two patients with PTSD. Equivalence testing and Bayesian analyses provided evidence against physiologically meaningful intervention-associated DNA methylation changes in monocytes of PTSD patients in commonly investigated target genes (NR3C1, FKBP5, SLC6A4, OXTR). Furthermore, WGBS yielded only a limited set of candidate regions with suggestive evidence of differential DNA methylation pre- to post-therapy. These differential DNA methylation patterns did not prove replicable when investigated in the entire cohort. We conclude that there is no evidence for major, recurrent intervention-associated DNA methylation changes in the investigated genes in monocytes of patients with PTSD.
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21
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Miao R, Dang Q, Cai J, Huang HH, Xie SL, Liang Y. Sparse principal component analysis based on genome network for correcting cell type heterogeneity in epigenome-wide association studies. Med Biol Eng Comput 2022; 60:2601-2618. [DOI: 10.1007/s11517-022-02599-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 04/30/2022] [Indexed: 10/17/2022]
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22
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Vara EL, Langefeld CD, Wolf BJ, Howard TD, Hawkins GA, Quet Q, Moultrie LH, Quinnette King L, Molano ID, Bray SL, Ueberroth LA, Lim SS, Williams EM, Kamen DL, Ramos PS. Social Factors, Epigenomics and Lupus in African American Women (SELA) Study: protocol for an observational mechanistic study examining the interplay of multiple individual and social factors on lupus outcomes in a health disparity population. Lupus Sci Med 2022; 9:9/1/e000698. [PMID: 35768168 PMCID: PMC9244713 DOI: 10.1136/lupus-2022-000698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 06/14/2022] [Indexed: 11/08/2022]
Abstract
Introduction Despite the disproportional impact of SLE on historically marginalised communities, the individual and sociocultural factors underlying these health disparities remain elusive. We report the design and methods for a study aimed at identifying epigenetic biomarkers associated with racism and resiliency that affect gene function and thereby influence SLE in a health disparity population. Methods and analysis The Social Factors, Epigenomics and Lupus in African American Women (SELA) Study is a cross-sectional, case–control study. A total of 600 self-reported African American women will be invited to participate. All participants will respond to questionnaires that capture detailed sociodemographic and medical history, validated measures of racial discrimination, social support, as well as disease activity and damage for cases. Participants who wish will receive their genetic ancestry estimates and be involved in research. Blood samples are required to provide peripheral blood mononuclear cell counts, DNA and RNA. The primary goals of SELA are to identify variation in DNA methylation (DNAm) associated with self-reported exposure to racial discrimination and social support, to evaluate whether social DNAm sites affect gene expression, to identify the synergistic effects of social factors on DNAm changes on SLE and to develop a social factors-DNAm predictive model for disease outcomes. This study is conducted in cooperation with the Sea Island Families Project Citizen Advisory Committee. Discussion and dissemination SELA will respond to the pressing need to clarify the interplay and regulatory mechanism by which various positive and negative social exposures influence SLE. Results will be published and shared with patients and the community. Knowledge of the biological impact of social exposures on SLE, as informed by the results of this study, can be leveraged by advocacy efforts to develop psychosocial interventions that prevent or mitigate risk exposures, and services or interventions that promote positive exposures. Implementation of such interventions is paramount to the closure of the health disparities gap.
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Affiliation(s)
- Emily L Vara
- Department of Medicine, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Carl D Langefeld
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.,Center for Precision Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Bethany J Wolf
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Timothy D Howard
- Center for Precision Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.,Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Gregory A Hawkins
- Center for Precision Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.,Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Queen Quet
- Gullah/Geechee Nation, St Helena Island, South Carolina, USA
| | - Lee H Moultrie
- Lee H Moultrie & Associates, North Charleston, South Carolina, USA
| | - L Quinnette King
- Department of Medicine, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Ivan D Molano
- Department of Medicine, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Stephanie L Bray
- Department of Medicine, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Lori Ann Ueberroth
- Department of Medicine, Medical University of South Carolina, Charleston, South Carolina, USA
| | - S Sam Lim
- Department of Medicine, Emory University, Atlanta, Georgia, USA.,Department of Epidemiology, Emory University, Atlanta, Georgia, USA
| | - Edith M Williams
- Department of Medicine, Medical University of South Carolina, Charleston, South Carolina, USA.,Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Diane L Kamen
- Department of Medicine, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Paula S Ramos
- Department of Medicine, Medical University of South Carolina, Charleston, South Carolina, USA .,Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina, USA
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23
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Lancaster EE, Vladimirov VI, Riley BP, Landry JW, Roberson-Nay R, York TP. LARGE-SCALE INTEGRATION OF DNA METHYLATION AND GENE EXPRESSION ARRAY PLATFORMS IDENTIFIES BOTH cis AND trans RELATIONSHIPS. Epigenetics 2022; 17:1753-1773. [PMID: 35608069 PMCID: PMC9621057 DOI: 10.1080/15592294.2022.2079293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Although epigenome-wide association studies (EWAS) have been successful in identifying DNA methylation (DNAm) patterns associated with disease states, any further characterization of etiologic mechanisms underlying disease remains elusive. This knowledge gap does not originate from a lack of DNAm–trait associations, but rather stems from study design issues that affect the interpretability of EWAS results. Despite known limitations in predicting the function of a particular CpG site, most EWAS maintain the broad assumption that altered DNAm results in a concomitant change of transcription at the most proximal gene. This study integrated DNAm and gene expression (GE) measurements in two cohorts, the Adolescent and Young Adult Twin Study (AYATS) and the Pregnancy, Race, Environment, Genes (PREG) study, to improve the understanding of epigenomic regulatory mechanisms. CpG sites associated with GE in cis were enriched in areas of transcription factor binding and areas of intermediate-to-low CpG density. CpG sites associated with trans GE were also enriched in areas of known regulatory significance, including enhancer regions. These results highlight issues with restricting DNAm-transcript annotations to small genomic intervals and question the validity of assuming a cis DNAm–GE pathway. Based on these findings, the interpretation of EWAS results is limited in studies without multi-omic support and further research should identify genomic regions in which GE-associated DNAm is overrepresented. An in-depth characterization of GE-associated CpG sites could improve predictions of the downstream functional impact of altered DNAm and inform best practices for interpreting DNAm–trait associations generated by EWAS.
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Affiliation(s)
- Eva E Lancaster
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA 23220
| | | | - Brien P Riley
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA 23220.,Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA 23220
| | - Joseph W Landry
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA 23220
| | - Roxann Roberson-Nay
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA 23220.,Department of Psychology, Virginia Commonwealth University, Richmond, VA 23220
| | - Timothy P York
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA 23220.,Department of Obstetrics and Gynecology, Virginia Commonwealth University, Richmond, VA 23220
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24
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Lombardo SD, Wangsaputra IF, Menche J, Stevens A. Network Approaches for Charting the Transcriptomic and Epigenetic Landscape of the Developmental Origins of Health and Disease. Genes (Basel) 2022; 13:764. [PMID: 35627149 PMCID: PMC9141211 DOI: 10.3390/genes13050764] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 04/04/2022] [Accepted: 04/13/2022] [Indexed: 02/04/2023] Open
Abstract
The early developmental phase is of critical importance for human health and disease later in life. To decipher the molecular mechanisms at play, current biomedical research is increasingly relying on large quantities of diverse omics data. The integration and interpretation of the different datasets pose a critical challenge towards the holistic understanding of the complex biological processes that are involved in early development. In this review, we outline the major transcriptomic and epigenetic processes and the respective datasets that are most relevant for studying the periconceptional period. We cover both basic data processing and analysis steps, as well as more advanced data integration methods. A particular focus is given to network-based methods. Finally, we review the medical applications of such integrative analyses.
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Affiliation(s)
- Salvo Danilo Lombardo
- Max Perutz Labs, Department of Structural and Computational Biology, University of Vienna, 1030 Vienna, Austria;
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1030 Vienna, Austria
| | - Ivan Fernando Wangsaputra
- Maternal and Fetal Health Research Group, Division of Developmental Biology and Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9WL, UK;
| | - Jörg Menche
- Max Perutz Labs, Department of Structural and Computational Biology, University of Vienna, 1030 Vienna, Austria;
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1030 Vienna, Austria
- Faculty of Mathematics, University of Vienna, 1030 Vienna, Austria
| | - Adam Stevens
- Maternal and Fetal Health Research Group, Division of Developmental Biology and Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9WL, UK;
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25
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Lucia RM, Huang WL, Pathak KV, McGilvrey M, David-Dirgo V, Alvarez A, Goodman D, Masunaka I, Odegaard AO, Ziogas A, Pirrotte P, Norden-Krichmar TM, Park HL. Association of Glyphosate Exposure with Blood DNA Methylation in a Cross-Sectional Study of Postmenopausal Women. ENVIRONMENTAL HEALTH PERSPECTIVES 2022; 130:47001. [PMID: 35377194 PMCID: PMC8978648 DOI: 10.1289/ehp10174] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 03/05/2022] [Accepted: 03/08/2022] [Indexed: 05/14/2023]
Abstract
BACKGROUND Glyphosate is the most commonly used herbicide in the world and is purported to have a variety of health effects, including endocrine disruption and an elevated risk of several types of cancer. Blood DNA methylation has been shown to be associated with many other environmental exposures, but to our knowledge, no studies to date have examined the association between blood DNA methylation and glyphosate exposure. OBJECTIVE We conducted an epigenome-wide association study to identify DNA methylation loci associated with urinary glyphosate and its metabolite aminomethylphosphonic acid (AMPA) levels. Secondary goals were to determine the association of epigenetic age acceleration with glyphosate and AMPA and develop blood DNA methylation indices to predict urinary glyphosate and AMPA levels. METHODS For 392 postmenopausal women, white blood cell DNA methylation was measured using the Illumina Infinium MethylationEPIC BeadChip array. Glyphosate and AMPA were measured in two urine samples per participant using liquid chromatography-tandem mass spectrometry. Methylation differences at the probe and regional level associated with glyphosate and AMPA levels were assessed using a resampling-based approach. Probes and regions that had an false discovery rate q < 0.1 in ≥ 90 % of 1,000 subsamples of the study population were considered differentially methylated. Differentially methylated sites from the probe-specific analysis were combined into a methylation index. Epigenetic age acceleration from three epigenetic clocks and an epigenetic measure of pace of aging were examined for associations with glyphosate and AMPA. RESULTS We identified 24 CpG sites whose methylation level was associated with urinary glyphosate concentration and two associated with AMPA. Four regions, within the promoters of the MSH4, KCNA6, ABAT, and NDUFAF2/ERCC8 genes, were associated with glyphosate levels, along with an association between ESR1 promoter hypomethylation and AMPA. The methylation index accurately predicted glyphosate levels in an internal validation cohort. AMPA, but not glyphosate, was associated with greater epigenetic age acceleration. DISCUSSION Glyphosate and AMPA exposure were associated with DNA methylation differences that could promote the development of cancer and other diseases. Further studies are warranted to replicate our results, determine the functional impact of glyphosate- and AMPA-associated differential DNA methylation, and further explore whether DNA methylation could serve as a biomarker of glyphosate exposure. https://doi.org/10.1289/EHP10174.
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Affiliation(s)
- Rachel M. Lucia
- Department of Epidemiology and Biostatistics, University of California, Irvine, California, USA
| | - Wei-Lin Huang
- Department of Epidemiology and Biostatistics, University of California, Irvine, California, USA
| | - Khyatiben V. Pathak
- Integrated Mass Spectrometry Shared Resource, City of Hope Comprehensive Cancer Center, Duarte, California, USA
- Cancer & Cell Biology Division, Translational Genomics Research Institute, Phoenix, Arizona, USA
| | - Marissa McGilvrey
- Integrated Mass Spectrometry Shared Resource, City of Hope Comprehensive Cancer Center, Duarte, California, USA
- Cancer & Cell Biology Division, Translational Genomics Research Institute, Phoenix, Arizona, USA
| | - Victoria David-Dirgo
- Integrated Mass Spectrometry Shared Resource, City of Hope Comprehensive Cancer Center, Duarte, California, USA
- Cancer & Cell Biology Division, Translational Genomics Research Institute, Phoenix, Arizona, USA
| | - Andrea Alvarez
- Department of Medicine, University of California, Irvine, California, USA
| | - Deborah Goodman
- Department of Epidemiology and Biostatistics, University of California, Irvine, California, USA
| | - Irene Masunaka
- Department of Medicine, University of California, Irvine, California, USA
| | - Andrew O. Odegaard
- Department of Epidemiology and Biostatistics, University of California, Irvine, California, USA
| | - Argyrios Ziogas
- Department of Medicine, University of California, Irvine, California, USA
| | - Patrick Pirrotte
- Integrated Mass Spectrometry Shared Resource, City of Hope Comprehensive Cancer Center, Duarte, California, USA
- Cancer & Cell Biology Division, Translational Genomics Research Institute, Phoenix, Arizona, USA
| | | | - Hannah Lui Park
- Department of Epidemiology and Biostatistics, University of California, Irvine, California, USA
- Department of Pathology and Laboratory Medicine, University of California, Irvine, California, USA
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Bell-Glenn S, Thompson JA, Salas LA, Koestler DC. A Novel Framework for the Identification of Reference DNA Methylation Libraries for Reference-Based Deconvolution of Cellular Mixtures. FRONTIERS IN BIOINFORMATICS 2022; 2. [PMID: 35419567 PMCID: PMC9004796 DOI: 10.3389/fbinf.2022.835591] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Reference-based deconvolution methods use reference libraries of cell-specific DNA methylation (DNAm) measurements as a means toward deconvoluting cell proportions in heterogeneous biospecimens (e.g., whole-blood). As the accuracy of such methods depends highly on the CpG loci comprising the reference library, recent research efforts have focused on the selection of libraries to optimize deconvolution accuracy. While existing approaches for library selection work extremely well, the best performing approaches require a training data set consisting of both DNAm profiles over a heterogeneous cell population and gold-standard measurements of cell composition (e.g., flow cytometry) in the same samples. Here, we present a framework for reference library selection without a training dataset (RESET) and benchmark it against the Legacy method (minfi:pickCompProbes), where libraries are constructed based on a pre-specified number of cell-specific differentially methylated loci (DML). RESET uses a modified version of the Dispersion Separability Criteria (DSC) for comparing different libraries and has four main steps: 1) identify a candidate set of cell-specific DMLs, 2) randomly sample DMLs from the candidate set, 3) compute the Modified DSC of the selected DMLs, and 4) update the selection probabilities of DMLs based on their contribution to the Modified DSC. Steps 2–4 are repeated many times and the library with the largest Modified DSC is selected for subsequent reference-based deconvolution. We evaluated RESET using several publicly available datasets consisting of whole-blood DNAm measurements with corresponding measurements of cell composition. We computed the RMSE and R2 between the predicted cell proportions and their measured values. RESET outperformed the Legacy approach in selecting libraries that improve the accuracy of deconvolution estimates. Additionally, reference libraries constructed using RESET resulted in cellular composition estimates that explained more variation in DNAm as compared to the Legacy approach when evaluated in the context of epigenome-wide association studies (EWAS) of several publicly available data sets. This finding has implications for the statistical power of EWAS. RESET combats potential challenges associated with existing approaches for reference library assembly and thus, may serve as a viable strategy for library construction in the absence of a training data set.
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Affiliation(s)
- Shelby Bell-Glenn
- Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, KS, United States
| | - Jeffrey A. Thompson
- Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, KS, United States
| | - Lucas A. Salas
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Hanover, NH, United States
| | - Devin C. Koestler
- Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, KS, United States
- *Correspondence: Devin C. Koestler,
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Ehrlich M. Risks and rewards of big-data in epigenomics research: an interview with Melanie Ehrlich. Epigenomics 2022; 14:351-358. [PMID: 35255735 DOI: 10.2217/epi-2022-0056] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Melanie Ehrlich, PhD, is a professor in the Tulane Cancer Center, the Tulane Center for Medical Bioinformatics and Genomics and the Hayward Human Genetics Program at Tulane Medical School, New Orleans, LA. She obtained her PhD in molecular biology in 1971 from the State University of New York at Stony Brook and completed postdoctoral research at Albert Einstein College of Medicine in 1972. She has been working on various aspects of epigenetics, starting with DNA methylation, since 1973. Her group made many first findings about DNA methylation (see below). For example, in 1982 and 1983, in collaboration with Charles Gehrke at the University of Missouri, she was the first to report tissue-specific and cancer-specific differences in overall DNA methylation in humans. In 1985, Xian-Yang Zhang and Richard Wang in her lab discovered a class of human DNA sequences specifically hypomethylated in sperm. In 1998, her group was the first to describe extensive losses of DNA methylation in pericentromeric and centromeric DNA repeats in human cancer. Her lab's many publications on the prevalence of both DNA hypermethylation and hypomethylation in the same cancers brought needed balance to our understanding of the epigenetics of cancer and to its clinical implications [1]. Besides working on cancer epigenetics, her research group has helped elucidate cytogenetic and gene expression abnormalities in the immunodeficiency, centromeric and facial anomalies (ICF) syndrome, a rare recessive disease often caused by mutations in DNMT3B. Her group also studied the epigenetics and transcriptomics of facioscapulohumeral muscular dystrophy (FSHD), whose disease locus is a tandem 3.3-kb repeat at subtelomeric 4q (that happens to be hypomethylated in ICF DNA [2]). Her study of FSHD has taken her in the direction of muscle (skeletal muscle, heart and aorta) epigenetics [3-6]. Recently, she has led research that applies epigenetics much more rigorously than usual to the evaluation of genetic variants from genome-wide association studies (GWAS) of osteoporosis and obesity. In continued collaboration with Sriharsa Pradhan at New England Biolabs and Michelle Lacey at Tulane University, she has compared 5-hydroxymethylcytosine and 5-methylcytosine clustering in various human tissues [7] and is studying myoblast methylomes that they generated by a new high-resolution enzymatic technique (enzymatic methyl-seq).
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Affiliation(s)
- Melanie Ehrlich
- Tulane Cancer Center, Center for Medical Bioinformatics & Genomics, & Hayward Genetics Center, Tulane University, New Orleans, LA 70112, USA
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Polinski KJ, Putnick DL, Robinson SL, Schliep KC, Silver RM, Guan W, Schisterman EF, Mumford SL, Yeung EH. Periconception and Prenatal Exposure to Maternal Perceived Stress and Cord Blood DNA Methylation. Epigenet Insights 2022; 15:25168657221082045. [PMID: 35237744 PMCID: PMC8882928 DOI: 10.1177/25168657221082045] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 01/23/2022] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Maternal prenatal stress is associated with physiologic and adverse mental health outcomes in the offspring, but the underlying biologic mechanisms are unknown. We examined the associations of maternal perceived stress, including preconception exposure, with DNA methylation (DNAm) alterations in the cord blood buffy coats of 358 singleton infants. METHODS Maternal perceived stress was measured prior to and throughout pregnancy in a cohort of women enrolled in Effects of Aspirin in Gestation and Reproduction Trial (EAGeR) trial. Perceived stress assessments based on a standardized Likert-scale were obtained in periconception (~2 months preconception and 2-8 weeks of gestation) and pregnancy (8-36 weeks of gestation). Cumulative perceived stress was estimated by calculating the predicted area under the curve of stress reported prior to and during pregnancy. DNAm was measured by the Infinium MethylationEPIC BeadChip. Multivariable robust linear regression was used to assess associations of perceived stress with individual CpG probes. RESULTS Based on a 0 to 3 scale, average reported preconception and early pregnancy stress were 0.76 (0.60) and 0.67 (0.50), respectively. Average mid- to late-pregnancy stress, based on a 0 to 10 scale, was 4.9 (1.6). Neither periconception nor pregnancy perceived stress were associated with individual CpG sites in neonatal cord blood (all false discovery rate [FDR] >5%). CONCLUSION No effects of maternal perceived stress exposure on array-wide cord blood neonatal methylation differences were found.
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Affiliation(s)
- Kristen J Polinski
- Division of Population Health Research,
Eunice Kennedy Shriver National Institute of Child Health and
Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Diane L Putnick
- Division of Population Health Research,
Eunice Kennedy Shriver National Institute of Child Health and
Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Sonia L Robinson
- Division of Population Health Research,
Eunice Kennedy Shriver National Institute of Child Health and
Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Karen C Schliep
- Department of Family and Preventive
Medicine, University of Utah, Salt Lake City, UT, USA
| | - Robert M Silver
- Department of Family and Preventive
Medicine, University of Utah, Salt Lake City, UT, USA
| | - Weihua Guan
- Division of Biostatistics, University
of Minnesota, Minneapolis, MN, USA
| | - Enrique F Schisterman
- Department of Biostatistics,
Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA,
USA
| | - Sunni L Mumford
- Department of Biostatistics,
Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA,
USA
| | - Edwina H Yeung
- Division of Population Health Research,
Eunice Kennedy Shriver National Institute of Child Health and
Human Development, National Institutes of Health, Bethesda, MD, USA,Edwina H Yeung, Epidemiology Branch,
Division of Population Health Research, Division of Intramural Research,
Eunice Kennedy Shriver National Institute of Child Health
and Human Development, National Institutes of Health, 6710B Rockledge Dr, MSC
7004, Bethesda, MD 20817, USA.
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Joshi RO, Kukshal P, Chellappan S, Guhathakurta S. "The study of expression levels of DNA methylation regulators in patients affected with congenital heart defects (CHDs)". Birth Defects Res 2022; 114:228-237. [PMID: 35191222 DOI: 10.1002/bdr2.1988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Revised: 01/25/2022] [Accepted: 01/31/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND Congenial heart defects (CHDs) have multifactorial etiology with complex interplay of genetic and environmental factors. Environmental impact can have epigenetic mechanism of CHD development. Many studies have reported the causal association between CHD and distinct DNA methylation profile which is one of the key epigenetic events, which has vital role in normal embryonic development. The products of DNMT1, DNMT3A, DNMT3B, and MBD2 are important regulators of DNA methylation process. Changes in the expression of these genes are implicated in congenital structural cardiac defects. Hence, in this proof-of-concept study, we have compared the expression levels of these genes in the blood samples of healthy controls and CHD cases while investigating the etiology of CHD. METHODS In this study with 48 CHD cases and 47 healthy controls, total RNA was isolated from the whole blood samples using TRI reagent. Quantitative RT PCR (qRT-PCR) was used to analyze the mRNA levels of DNMT1, DNMT3A, DNMT3B, and MBD2. The expression levels have been analyzed by relative quantification. RESULTS We observed that DNMT3B (fold change = -2.563; p = .0018) and DNMT3A (fold change = -2.169; p = .05) were significantly downregulated in CHD patients, whereas the expression of DNMT1 and MBD2 was not significantly different between cases and controls. CONCLUSIONS Lower expression of de novo methyltransferases, namely, DNMT3B and DNMT3A in CHD cases, may be an important contributor to the mechanism of CHD pathogenesis. Further studies with age-matched controls and analysis of global DNA methylation profile are required to investigate the proposed causal association.
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Affiliation(s)
- Radha O Joshi
- Department of Genomics Research, Sri Sathya Sai Sanjeevani Research Foundation, Palwal, India
| | - Prachi Kukshal
- Department of Genomics Research, Sri Sathya Sai Sanjeevani Research Foundation, Palwal, India
| | - Subramanian Chellappan
- Department of Anaesthesia, Sri Sathya Sai Sanjeevani International Centre for Child Heart Care and Research, Palwal, India
| | - Soma Guhathakurta
- Department of Genomics Research, Sri Sathya Sai Sanjeevani Research Foundation, Palwal, India
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30
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Mavioglu RN, Ramo-Fernandez L, Gumpp AM, Kolassa IT, Karabatsiakis A. A history of childhood maltreatment is associated with altered DNA methylation levels of DNA methyltransferase 1 in maternal but not neonatal mononuclear immune cells. Front Psychiatry 2022; 13:945343. [PMID: 36440389 PMCID: PMC9685310 DOI: 10.3389/fpsyt.2022.945343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 10/24/2022] [Indexed: 11/11/2022] Open
Abstract
Childhood maltreatment (CM) is associated with alterations in DNA methylation (DNAm) especially in stress response genes. Due to the higher risk of overall health complications of individuals with a parental history of CM, intergenerational transmission of CM-associated DNAm changes has been investigated but remains unclear. In this study, we investigated if different severities of CM have any influence on the DNAm of DNA methyltransferase 1 (DNMT1), an important enzyme of the DNAm machinery, in immune and buccal cells of mother-newborn dyads. DNAm was assessed by mass spectrometry using immune cell DNA from mothers (N = 117) and their newborns (N = 113), and buccal cell DNA of mother-newborn dyads (N = 68 each). Mothers with a history of CM had lower mean methylation of DNMT1 in immune cells compared to the mothers without a CM history. CM status only influenced maternal DNMT1 gene expression when at least moderate CM was reported. Buccal cell DNAm was not associated with CM status. Maternal history of CM was not linked to any alterations in DNMT1 mean DNAm in any of the cell types studied in newborns. We conclude that the CM-associated alterations in DNMT1 DNAm might point to allostatic load and can be physiologically relevant, especially in individuals with more severe CM experiences, resulting in an activated DNA methylation machinery that might influence stress response genes. Our lack of significant findings in buccal cells shows the tissue-specific effects of CM on DNAm. In our sample with low to moderate maternal CM history, there was no intergenerational transmission of DNMT1 DNAm in newborns.
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Affiliation(s)
- Rezan Nehir Mavioglu
- Department of Clinical and Biological Psychology, Institute of Psychology and Education, Ulm University, Ulm, Germany
| | - Laura Ramo-Fernandez
- Department of Clinical and Biological Psychology, Institute of Psychology and Education, Ulm University, Ulm, Germany
| | - Anja M Gumpp
- Department of Clinical and Biological Psychology, Institute of Psychology and Education, Ulm University, Ulm, Germany
| | - Iris-Tatjana Kolassa
- Department of Clinical and Biological Psychology, Institute of Psychology and Education, Ulm University, Ulm, Germany
| | - Alexander Karabatsiakis
- Department of Clinical and Biological Psychology, Institute of Psychology and Education, Ulm University, Ulm, Germany.,Department of Psychology, Clinical Psychology II, University of Innsbruck, Innsbruck, Austria
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Ronkainen J, Heiskala A, Vehmeijer FO, Lowry E, Caramaschi D, Estrada Gutierrez G, Heiss JA, Hummel N, Keikkala E, Kvist T, Kupsco A, Melton PE, Pesce G, Soomro MH, Vives-Usano M, Baiz N, Binder E, Czamara D, Guxens M, Mustaniemi S, London SJ, Rauschert S, Vääräsmäki M, Vrijheid M, Ziegler AG, Annesi-Maesano I, Bustamante M, Huang RC, Hummel S, Just AC, Kajantie E, Lahti J, Lawlor D, Räikkönen K, Järvelin MR, Felix JF, Sebert S. Maternal haemoglobin levels in pregnancy and child DNA methylation: a study in the pregnancy and childhood epigenetics consortium. Epigenetics 2022; 17:19-31. [PMID: 33331245 PMCID: PMC8813068 DOI: 10.1080/15592294.2020.1864171] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 11/26/2020] [Accepted: 12/08/2020] [Indexed: 01/05/2023] Open
Abstract
Altered maternal haemoglobin levels during pregnancy are associated with pre-clinical and clinical conditions affecting the fetus. Evidence from animal models suggests that these associations may be partially explained by differential DNA methylation in the newborn with possible long-term consequences. To test this in humans, we meta-analyzed the epigenome-wide associations of maternal haemoglobin levels during pregnancy with offspring DNA methylation in 3,967 newborn cord blood and 1,534 children and 1,962 adolescent whole-blood samples derived from 10 cohorts. DNA methylation was measured using Illumina Infinium Methylation 450K or MethylationEPIC arrays covering 450,000 and 850,000 methylation sites, respectively. There was no statistical support for the association of maternal haemoglobin levels with offspring DNA methylation either at individual methylation sites or clustered in regions. For most participants, maternal haemoglobin levels were within the normal range in the current study, whereas adverse perinatal outcomes often arise at the extremes. Thus, this study does not rule out the possibility that associations with offspring DNA methylation might be seen in studies with more extreme maternal haemoglobin levels.
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Affiliation(s)
- Justiina Ronkainen
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Anni Heiskala
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Florianne O.L. Vehmeijer
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Estelle Lowry
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- School of Natural and Built Environment, Queen’s University Belfast, Belfast, Northern Ireland
| | - Doretta Caramaschi
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, Population Health Science, University of Bristol, Bristol, UK
| | | | - Jonathan A. Heiss
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Nadine Hummel
- Institute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany
| | - Elina Keikkala
- Department of Obstetrics and Gynecology, PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki and Oulu, Finland
| | - Tuomas Kvist
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Finland
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, USA
| | - Allison Kupsco
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Phillip E. Melton
- School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin University, Bentley, Australia
- School of Biomedical Sciences, Faculty of Health and Medical Sciences, The University of Western Australia, Crawley, Australia
| | - Giancarlo Pesce
- Sorbonne Université, Institut Pierre Louis D’épidémiologie Et De Santé Publique (IPLESP), Paris, France
- Epidemiology of Allergic and Respiratory Diseases Department (EPAR), Institut National De La Santé Et De La Recherche Médicale (INSERM) UMR-S 1136, Institut Pierre Louis D’épidémiologie Et De Santé Publique (IPLESP), Team EPAR, Paris, France
| | - Munawar H. Soomro
- Sorbonne Université, Institut Pierre Louis D’épidémiologie Et De Santé Publique (IPLESP), Paris, France
- Epidemiology of Allergic and Respiratory Diseases Department (EPAR), Institut National De La Santé Et De La Recherche Médicale (INSERM) UMR-S 1136, Institut Pierre Louis D’épidémiologie Et De Santé Publique (IPLESP), Team EPAR, Paris, France
| | - Marta Vives-Usano
- Centre for Genomic Regulation (CRG), the Barcelona Institute of Science and Technology, Barcelona, Spain
- CIBER Epidemiología Y Salud Pública (CIBERESP), Madrid, Spain
| | - Nour Baiz
- Sorbonne Université, Institut Pierre Louis D’épidémiologie Et De Santé Publique (IPLESP), Paris, France
- Epidemiology of Allergic and Respiratory Diseases Department (EPAR), Institut National De La Santé Et De La Recherche Médicale (INSERM) UMR-S 1136, Institut Pierre Louis D’épidémiologie Et De Santé Publique (IPLESP), Team EPAR, Paris, France
| | - Elisabeth Binder
- Department of Translational Research in Psychiatry, Max-Planck-Institute of Psychiatry, Munich, Germany
| | - Darina Czamara
- Department of Translational Research in Psychiatry, Max-Planck-Institute of Psychiatry, Munich, Germany
| | - Mònica Guxens
- CIBER Epidemiología Y Salud Pública (CIBERESP), Madrid, Spain
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Sophia Children’s Hospital, Rotterdam, The Netherlands
| | - Sanna Mustaniemi
- Department of Obstetrics and Gynecology, PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki and Oulu, Finland
| | - Stephanie J. London
- National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, WashingtonDC, USA
| | | | - Marja Vääräsmäki
- Department of Obstetrics and Gynecology, PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki and Oulu, Finland
| | - Martine Vrijheid
- CIBER Epidemiología Y Salud Pública (CIBERESP), Madrid, Spain
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Anette-G. Ziegler
- Institute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany
- Forschergruppe Diabetes, Technical University Munich, Klinikum Rechts Der Isar, Munich-Neuherberg, Germany
- Forschergruppe Diabetes e.V., Helmholtz Zentrum München, Munich-Neuherberg, Germany
| | - Isabella Annesi-Maesano
- Sorbonne Université, Institut Pierre Louis D’épidémiologie Et De Santé Publique (IPLESP), Paris, France
- Epidemiology of Allergic and Respiratory Diseases Department (EPAR), Institut National De La Santé Et De La Recherche Médicale (INSERM) UMR-S 1136, Institut Pierre Louis D’épidémiologie Et De Santé Publique (IPLESP), Team EPAR, Paris, France
| | - Mariona Bustamante
- CIBER Epidemiología Y Salud Pública (CIBERESP), Madrid, Spain
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Rae-Chi Huang
- Telethon Kids Institute, University of Western Australia, Australia
| | - Sandra Hummel
- Institute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany
- Forschergruppe Diabetes, Technical University Munich, Klinikum Rechts Der Isar, Munich-Neuherberg, Germany
- Forschergruppe Diabetes e.V., Helmholtz Zentrum München, Munich-Neuherberg, Germany
| | - Allan C. Just
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Eero Kajantie
- Department of Obstetrics and Gynecology, PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki and Oulu, Finland
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
- Children’s Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Jari Lahti
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Finland
- Turku Institute for Advanced Studies, University of Turku, Turku, Finland
| | - Deborah Lawlor
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, Population Health Science, University of Bristol, Bristol, UK
| | - Katri Räikkönen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Finland
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Janine F. Felix
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Sylvain Sebert
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Department for Genomics of Common Diseases, School of Medicine, Imperial College London, LondonUK
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Shanthikumar S, Neeland MR, Saffery R, Ranganathan SC, Oshlack A, Maksimovic J. DNA Methylation Profiles of Purified Cell Types in Bronchoalveolar Lavage: Applications for Mixed Cell Paediatric Pulmonary Studies. Front Immunol 2021; 12:788705. [PMID: 35003108 PMCID: PMC8727592 DOI: 10.3389/fimmu.2021.788705] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Accepted: 12/03/2021] [Indexed: 01/15/2023] Open
Abstract
In epigenome-wide association studies analysing DNA methylation from samples containing multiple cell types, it is essential to adjust the analysis for cell type composition. One well established strategy for achieving this is reference-based cell type deconvolution, which relies on knowledge of the DNA methylation profiles of purified constituent cell types. These are then used to estimate the cell type proportions of each sample, which can then be incorporated to adjust the association analysis. Bronchoalveolar lavage is commonly used to sample the lung in clinical practice and contains a mixture of different cell types that can vary in proportion across samples, affecting the overall methylation profile. A current barrier to the use of bronchoalveolar lavage in DNA methylation-based research is the lack of reference DNA methylation profiles for each of the constituent cell types, thus making reference-based cell composition estimation difficult. Herein, we use bronchoalveolar lavage samples collected from children with cystic fibrosis to define DNA methylation profiles for the four most common and clinically relevant cell types: alveolar macrophages, granulocytes, lymphocytes and alveolar epithelial cells. We then demonstrate the use of these methylation profiles in conjunction with an established reference-based methylation deconvolution method to estimate the cell type composition of two different tissue types; a publicly available dataset derived from artificial blood-based cell mixtures and further bronchoalveolar lavage samples. The reference DNA methylation profiles developed in this work can be used for future reference-based cell type composition estimation of bronchoalveolar lavage. This will facilitate the use of this tissue in studies examining the role of DNA methylation in lung health and disease.
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Affiliation(s)
- Shivanthan Shanthikumar
- Respiratory and Sleep Medicine, Royal Children’s Hospital, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
- Respiratory Diseases, Murdoch Children’s Research Institute, Parkville, VIC, Australia
- *Correspondence: Shivanthan Shanthikumar,
| | - Melanie R. Neeland
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
- Molecular Immunity, Murdoch Children’s Research Institute, Parkville, VIC, Australia
| | - Richard Saffery
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
- Molecular Immunity, Murdoch Children’s Research Institute, Parkville, VIC, Australia
| | - Sarath C. Ranganathan
- Respiratory and Sleep Medicine, Royal Children’s Hospital, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
- Respiratory Diseases, Murdoch Children’s Research Institute, Parkville, VIC, Australia
| | - Alicia Oshlack
- Computational Biology Program, Peter MacCallum Cancer Centre, Parkville, VIC, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, VIC, Australia
- School of BioScience, University of Melbourne, Parkville, VIC, Australia
| | - Jovana Maksimovic
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
- Respiratory Diseases, Murdoch Children’s Research Institute, Parkville, VIC, Australia
- Computational Biology Program, Peter MacCallum Cancer Centre, Parkville, VIC, Australia
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Bengtsen M, Winje IM, Eftestøl E, Landskron J, Sun C, Nygård K, Domanska D, Millay DP, Meza-Zepeda LA, Gundersen K. Comparing the epigenetic landscape in myonuclei purified with a PCM1 antibody from a fast/glycolytic and a slow/oxidative muscle. PLoS Genet 2021; 17:e1009907. [PMID: 34752468 PMCID: PMC8604348 DOI: 10.1371/journal.pgen.1009907] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 11/19/2021] [Accepted: 10/23/2021] [Indexed: 01/04/2023] Open
Abstract
Muscle cells have different phenotypes adapted to different usage, and can be grossly divided into fast/glycolytic and slow/oxidative types. While most muscles contain a mixture of such fiber types, we aimed at providing a genome-wide analysis of the epigenetic landscape by ChIP-Seq in two muscle extremes, the fast/glycolytic extensor digitorum longus (EDL) and slow/oxidative soleus muscles. Muscle is a heterogeneous tissue where up to 60% of the nuclei can be of a different origin. Since cellular homogeneity is critical in epigenome-wide association studies we developed a new method for purifying skeletal muscle nuclei from whole tissue, based on the nuclear envelope protein Pericentriolar material 1 (PCM1) being a specific marker for myonuclei. Using antibody labelling and a magnetic-assisted sorting approach, we were able to sort out myonuclei with 95% purity in muscles from mice, rats and humans. The sorting eliminated influence from the other cell types in the tissue and improved the myo-specific signal. A genome-wide comparison of the epigenetic landscape in EDL and soleus reflected the differences in the functional properties of the two muscles, and revealed distinct regulatory programs involving distal enhancers, including a glycolytic super-enhancer in the EDL. The two muscles were also regulated by different sets of transcription factors; e.g. in soleus, binding sites for MEF2C, NFATC2 and PPARA were enriched, while in EDL MYOD1 and SIX1 binding sites were found to be overrepresented. In addition, more novel transcription factors for muscle regulation such as members of the MAF family, ZFX and ZBTB14 were identified. Complex tissues like skeletal muscle contain a variety of cells which confound the analysis of each cell type when based on homogenates, thus only about half of the cell nuclei in muscles reside inside the muscle cells. We here describe a labelling and sorting technique that allowed us to study the epigenetic landscape in purified muscle cell nuclei leaving the other cell types out. Differences between a fast/glycolytic and a slow/oxidative muscle were studied. While all skeletal muscle fibers have a similar make up and basic function, they differ in their physiology and the way they are used. Thus, some fibers are fast contracting but fatigable, and are used for short lasting explosive tasks such as sprinting. Other fibers are slow and are used for more prolonged tasks such as standing or long distance running. Since fiber type correlate with metabolic profile these features can also be related to metabolic diseases. We here show that the epigenetic landscape differed in gene loci corresponding to the differences in functional properties, and revealed that the two types are enriched in different gene regulatory networks. Exercise can alter muscle phenotype, and the epigenetic landscape might be related to how plastic different properties are.
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Affiliation(s)
- Mads Bengtsen
- Department of Biosciences, University of Oslo, Oslo, Norway
| | | | - Einar Eftestøl
- Department of Biosciences, University of Oslo, Oslo, Norway
- Division of Molecular Cardiovascular Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, United States of America
| | | | - Chengyi Sun
- Division of Molecular Cardiovascular Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, United States of America
| | - Kamilla Nygård
- Department of Biosciences, University of Oslo, Oslo, Norway
| | - Diana Domanska
- Department of Pathology, University of Oslo, Oslo, Norway
| | - Douglas P. Millay
- Division of Molecular Cardiovascular Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, United States of America
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
| | - Leonardo A. Meza-Zepeda
- Department of Core Facilities, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
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Abstract
PURPOSE OF REVIEW Both social and genetic factors are associated with health outcomes in systemic lupus erythematosus (SLE), thus playing a role in its health disparities. Despite the growing list of social and genetic factors associated with SLE outcomes, studies integrating sociocultural and individual determinants of health to understand health disparities in SLE are lacking. We review the contributions of different social and genetic factors to the disparities in SLE, and propose a socioecological model to integrate and examine the complex interactions between individual and social factors in SLE outcomes. RECENT FINDINGS Multiple studies collecting comprehensive social data and biospecimens from diverse populations are underway, which will contribute to the elucidation of the interplay and underlying mechanisms by which positive and negative social determinants of health influence epigenomic variation, and how the resulting biological changes may contribute to the lupus health disparities. SUMMARY There is growing awareness of the need to integrate genomic and health disparities research to understand how social exposures affect disease outcomes. Understanding the contributions of these factors to the SLE health disparity will inform the development of interventions to eliminate risk exposures and close the health disparity gap.
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Konigsberg IR, Barnes B, Campbell M, Davidson E, Zhen Y, Pallisard O, Boorgula MP, Cox C, Nandy D, Seal S, Crooks K, Sticca E, Harrison GF, Hopkinson A, Vest A, Arnold CG, Kahn MG, Kao DP, Peterson BR, Wicks SJ, Ghosh D, Horvath S, Zhou W, Mathias RA, Norman PJ, Porecha R, Yang IV, Gignoux CR, Monte AA, Taye A, Barnes KC. Host methylation predicts SARS-CoV-2 infection and clinical outcome. COMMUNICATIONS MEDICINE 2021; 1:42. [PMID: 35072167 PMCID: PMC8767772 DOI: 10.1038/s43856-021-00042-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 09/24/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Since the onset of the SARS-CoV-2 pandemic, most clinical testing has focused on RT-PCR1. Host epigenome manipulation post coronavirus infection2-4 suggests that DNA methylation signatures may differentiate patients with SARS-CoV-2 infection from uninfected individuals, and help predict COVID-19 disease severity, even at initial presentation. METHODS We customized Illumina's Infinium MethylationEPIC array to enhance immune response detection and profiled peripheral blood samples from 164 COVID-19 patients with longitudinal measurements of disease severity and 296 patient controls. RESULTS Epigenome-wide association analysis revealed 13,033 genome-wide significant methylation sites for case-vs-control status. Genes and pathways involved in interferon signaling and viral response were significantly enriched among differentially methylated sites. We observe highly significant associations at genes previously reported in genetic association studies (e.g. IRF7, OAS1). Using machine learning techniques, models built using sparse regression yielded highly predictive findings: cross-validated best fit AUC was 93.6% for case-vs-control status, and 79.1%, 80.8%, and 84.4% for hospitalization, ICU admission, and progression to death, respectively. CONCLUSIONS In summary, the strong COVID-19-specific epigenetic signature in peripheral blood driven by key immune-related pathways related to infection status, disease severity, and clinical deterioration provides insights useful for diagnosis and prognosis of patients with viral infections.
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Affiliation(s)
- Iain R. Konigsberg
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | | | - Monica Campbell
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Elizabeth Davidson
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Yingfei Zhen
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Olivia Pallisard
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | | | - Corey Cox
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Debmalya Nandy
- Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Souvik Seal
- Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Kristy Crooks
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Evan Sticca
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Genelle F. Harrison
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Andrew Hopkinson
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Alexis Vest
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Cosby G. Arnold
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Michael G. Kahn
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - David P. Kao
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Brett R. Peterson
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Stephen J. Wicks
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Debashis Ghosh
- Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Steve Horvath
- University of California Los Angeles, Los Angeles, CA USA
| | - Wanding Zhou
- The Children’s Hospital of Philadelphia, Philadelphia, PA USA
| | - Rasika A. Mathias
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
- Johns Hopkins University, Baltimore, MD USA
| | - Paul J. Norman
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | | | - Ivana V. Yang
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | | | - Andrew A. Monte
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | | | - Kathleen C. Barnes
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
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Polinski KJ, Purdue-Smithe A, Robinson SL, Zhao SK, Schliep KC, Silver RM, Guan W, Schisterman EF, Mumford SL, Yeung EH. Maternal caffeine intake and DNA methylation in newborn cord blood. Am J Clin Nutr 2021; 115:482-491. [PMID: 34669932 PMCID: PMC8827095 DOI: 10.1093/ajcn/nqab348] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 10/12/2021] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Epigenetic mechanisms may underlie associations between maternal caffeine consumption and adverse childhood metabolic outcomes. However, limited studies have examined neonate DNA methylation (DNAm) patterns in the context of preconception or prenatal exposure to caffeine metabolites. OBJECTIVES We examined preconception and pregnancy caffeine exposure with DNAm alterations in neonate cord blood (n = 378). METHODS In a secondary analysis of the Effects of Aspirin in Gestation and Reproduction Trial (EAGeR), we measured maternal caffeine, paraxanthine, and theobromine concentrations from stored serum collected preconception (on average 2 months before pregnancy) and at 8 weeks of gestation. In parallel, self-reported caffeinated beverage intake was captured via administration of questionnaires and daily diaries. We profiled DNAm from the cord blood buffy coat of singletons using the MethylationEPIC BeadChip. We assessed associations of maternal caffeine exposure and methylation β values using multivariable robust linear regression. A false discovery rate (FDR) correction was applied using the Benjamini-Hochberg method. RESULTS In preconception, the majority of women reported consuming 1 or fewer servings/day of caffeine on average, and caffeine and paraxanthine metabolite levels were 88 and 36 µmol/L, respectively. Preconception serum caffeine metabolites were not associated with individual cytosine-guanine (CpG) sites (FDR >5%), though pregnancy theobromine was associated with DNAm at cg09460369 near RAB2A (β = 0.028; SE = 0.005; FDR P = 0.012). Preconception self-reported caffeinated beverage intake compared to no intake was associated with DNAm at cg09002832 near GLIS3 (β = -0.013; SE = 0.002; FDR P = 0.036). No associations with self-reported intake during pregnancy were found. CONCLUSIONS Few effects of maternal caffeine exposure on neonate methylation differences in leukocytes were identified in this population with relatively low caffeine consumption.
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Affiliation(s)
- Kristen J Polinski
- Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Alexandra Purdue-Smithe
- Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Sonia L Robinson
- Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Sifang Kathy Zhao
- Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Karen C Schliep
- Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, USA
| | - Robert M Silver
- Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, USA
| | - Weihua Guan
- University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Enrique F Schisterman
- Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Sunni L Mumford
- Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, USA
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Tian Y, Yang X, Du J, Zeng W, Wu W, Di J, Huang X, Tian K. Differential Methylation and Transcriptome Integration Analysis Identified Differential Methylation Annotation Genes and Functional Research Related to Hair Follicle Development in Sheep. Front Genet 2021; 12:735827. [PMID: 34659357 PMCID: PMC8515899 DOI: 10.3389/fgene.2021.735827] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Accepted: 08/30/2021] [Indexed: 11/13/2022] Open
Abstract
Hair follicle growth and development are a complex and long-term physiological process, which is regulated by a variety of physical factors and signal pathways. Increasing the understanding of the epigenetic regulation and function of candidate genes related to hair follicle development will help to better understand the molecular regulatory mechanisms of hair follicle development. In this study, the methylated DNA immunoprecipitation sequencing (MeDIP-seq) was used to obtain the genome-wide methylation map of the hair follicular development of Super Merino sheep in six stages (fetal skin tissue at 65d, 85d, 105d, 135d, 7d, and 30d after birth). Combined with the results of previous RNA-sequencing, 65 genes were screened out that were both differential methylation and differential expression, including EDN1, LAMC2, NR1D1, RORB, MyOZ3, and WNT2 gene. Differential methylation genes were enriched in Wnt, TNF, TGF-beta, and other signaling pathways related to hair follicle development. The bisulfite sequencing PCR results and MeDIP-seq were basically consistent, indicating that the sequencing results were accurate. As a key gene in the Wnt signaling pathway, both differential methylation and expression gene identified by MeDIP-seq and RNA-seq, further exploration of the function of WNT2 gene revealed that the DNA methylation of exon 5 (CpG11 site) promoted the expression of WNT2 gene. The overexpression vector of lentivirus pLEX-MCS-WNT2 was constructed, and WNT2 gene effectively promoted the proliferation of sheep skin fibroblasts. The results showed that WNT2 gene could promote the growth and development of skin and hair follicles. The results of this study will provide a theoretical basis for further research on sheep hair follicle development and gene regulation mechanisms.
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Affiliation(s)
- Yuezhen Tian
- The Key Laboratory for Genetics Breeding and Reproduction of Xinjiang Cashmere and Wool Sheep, Institute of Animal Science, Xinjiang Academy of Animal Sciences, Urumqi, China
| | - Xuemei Yang
- College of Animal Science, Xinjiang Agricultural University, Urumqi, China
| | - Jianwen Du
- College of Animal Science, Xinjiang Agricultural University, Urumqi, China
| | - Weidan Zeng
- College of Animal Science, Xinjiang Agricultural University, Urumqi, China
| | - Weiwei Wu
- The Key Laboratory for Genetics Breeding and Reproduction of Xinjiang Cashmere and Wool Sheep, Institute of Animal Science, Xinjiang Academy of Animal Sciences, Urumqi, China
| | - Jiang Di
- The Key Laboratory for Genetics Breeding and Reproduction of Xinjiang Cashmere and Wool Sheep, Institute of Animal Science, Xinjiang Academy of Animal Sciences, Urumqi, China
| | - Xixia Huang
- College of Animal Science, Xinjiang Agricultural University, Urumqi, China
| | - Kechuan Tian
- The Key Laboratory for Genetics Breeding and Reproduction of Xinjiang Cashmere and Wool Sheep, Institute of Animal Science, Xinjiang Academy of Animal Sciences, Urumqi, China
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Wei S, Tao J, Xu J, Chen X, Wang Z, Zhang N, Zuo L, Jia Z, Chen H, Sun H, Yan Y, Zhang M, Lv H, Kong F, Duan L, Ma Y, Liao M, Xu L, Feng R, Liu G, Project TEWAS, Jiang Y. Ten Years of EWAS. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2021; 8:e2100727. [PMID: 34382344 PMCID: PMC8529436 DOI: 10.1002/advs.202100727] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 05/11/2021] [Indexed: 06/13/2023]
Abstract
Epigenome-wide association study (EWAS) has been applied to analyze DNA methylation variation in complex diseases for a decade, and epigenome as a research target has gradually become a hot topic of current studies. The DNA methylation microarrays, next-generation, and third-generation sequencing technologies have prepared a high-quality platform for EWAS. Here, the progress of EWAS research is reviewed, its contributions to clinical applications, and mainly describe the achievements of four typical diseases. Finally, the challenges encountered by EWAS and make bold predictions for its future development are presented.
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Affiliation(s)
- Siyu Wei
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
- The EWAS ProjectHarbinChina
| | - Junxian Tao
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
- The EWAS ProjectHarbinChina
| | - Jing Xu
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
- The EWAS ProjectHarbinChina
| | - Xingyu Chen
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Zhaoyang Wang
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Nan Zhang
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Lijiao Zuo
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Zhe Jia
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Haiyan Chen
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Hongmei Sun
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Yubo Yan
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Mingming Zhang
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Hongchao Lv
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Fanwu Kong
- The EWAS ProjectHarbinChina
- Department of NephrologyThe Second Affiliated HospitalHarbin Medical UniversityHarbin150001China
| | - Lian Duan
- The EWAS ProjectHarbinChina
- The First Affiliated Hospital of Wenzhou Medical UniversityWenzhou325000China
| | - Ye Ma
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
- The EWAS ProjectHarbinChina
| | - Mingzhi Liao
- The EWAS ProjectHarbinChina
- College of Life SciencesNorthwest A&F UniversityYanglingShanxi712100China
| | - Liangde Xu
- The EWAS ProjectHarbinChina
- School of Biomedical EngineeringWenzhou Medical UniversityWenzhou325035China
| | - Rennan Feng
- The EWAS ProjectHarbinChina
- Department of Nutrition and Food HygienePublic Health CollegeHarbin Medical UniversityHarbin150081China
| | - Guiyou Liu
- The EWAS ProjectHarbinChina
- Beijing Institute for Brain DisordersCapital Medical UniversityBeijing100069China
| | | | - Yongshuai Jiang
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
- The EWAS ProjectHarbinChina
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Ramirez K, Fernández R, Collet S, Kiyar M, Delgado-Zayas E, Gómez-Gil E, Van Den Eynde T, T'Sjoen G, Guillamon A, Mueller SC, Pásaro E. Epigenetics Is Implicated in the Basis of Gender Incongruence: An Epigenome-Wide Association Analysis. Front Neurosci 2021; 15:701017. [PMID: 34489625 PMCID: PMC8418298 DOI: 10.3389/fnins.2021.701017] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 07/30/2021] [Indexed: 11/13/2022] Open
Abstract
Introduction The main objective was to carry out a global DNA methylation analysis in a population with gender incongruence before gender-affirming hormone treatment (GAHT), in comparison to a cisgender population. Methods A global CpG (cytosine-phosphate-guanine) methylation analysis was performed on blood from 16 transgender people before GAHT vs. 16 cisgender people using the Illumina© Infinium Human Methylation 850k BeadChip, after bisulfite conversion. Changes in the DNA methylome in cisgender vs. transgender populations were analyzed with the Partek® Genomics Suite program by a 2-way ANOVA test comparing populations by group and their sex assigned at birth. Results The principal components analysis (PCA) showed that both populations (cis and trans) differ in the degree of global CpG methylation prior to GAHT. The 2-way ANOVA test showed 71,515 CpGs that passed the criterion FDR p < 0.05. Subsequently, in male assigned at birth population we found 87 CpGs that passed both criteria (FDR p < 0.05; fold change ≥ ± 2) of which 22 were located in islands. The most significant CpGs were related to genes: WDR45B, SLC6A20, NHLH1, PLEKHA5, UBALD1, SLC37A1, ARL6IP1, GRASP, and NCOA6. Regarding the female assigned at birth populations, we found 2 CpGs that passed both criteria (FDR p < 0.05; fold change ≥ ± 2), but none were located in islands. One of these CpGs, related to the MPPED2 gene, is shared by both, trans men and trans women. The enrichment analysis showed that these genes are involved in functions such as negative regulation of gene expression (GO:0010629), central nervous system development (GO:0007417), brain development (GO:0007420), ribonucleotide binding (GO:0032553), and RNA binding (GO:0003723), among others. Strengths and Limitations It is the first time that a global CpG methylation analysis has been carried out in a population with gender incongruence before GAHT. A prospective study before/during GAHT would provide a better understanding of the influence of epigenetics in this process. Conclusion The main finding of this study is that the cis and trans populations have different global CpG methylation profiles prior to GAHT. Therefore, our results suggest that epigenetics may be involved in the etiology of gender incongruence.
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Affiliation(s)
- Karla Ramirez
- Laboratory of Psychobiology, Department of Psychology, Institute Advanced Scientific Research Center (CICA), University of A Coruña, A Coruña, Spain.,Laboratory of Neurophysiology, Center for Biophysics and Biochemistry, Venezuelan Institute for Scientific Research (IVIC), Caracas, Venezuela
| | - Rosa Fernández
- Laboratory of Psychobiology, Department of Psychology, Institute Advanced Scientific Research Center (CICA), University of A Coruña, A Coruña, Spain
| | - Sarah Collet
- Department of Endocrinology, Ghent University, Ghent, Belgium
| | - Meltem Kiyar
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| | - Enrique Delgado-Zayas
- Laboratory of Psychobiology, Department of Psychology, Institute Advanced Scientific Research Center (CICA), University of A Coruña, A Coruña, Spain
| | | | | | - Guy T'Sjoen
- Department of Endocrinology, Ghent University, Ghent, Belgium
| | - Antonio Guillamon
- Department of Psychobiology, Faculty of Psychology, National University of Distance Education (UNED), Madrid, Spain
| | - Sven C Mueller
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| | - Eduardo Pásaro
- Laboratory of Psychobiology, Department of Psychology, Institute Advanced Scientific Research Center (CICA), University of A Coruña, A Coruña, Spain
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40
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Brandes RP, Gilsbach R. Is It in the EPIgenome?: Epigenetics Marks at Birth Are Associated With Arterial Stiffness in Children. Hypertension 2021; 78:801-803. [PMID: 34379434 DOI: 10.1161/hypertensionaha.121.17777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Ralf P Brandes
- Institute for Cardiovascular Physiology, Faculty of Medicine, Goethe-University Frankfurt, Germany. DZHK - German Center for Cardiovascular Research, Partner site Rhine-Main
| | - Ralf Gilsbach
- Institute for Cardiovascular Physiology, Faculty of Medicine, Goethe-University Frankfurt, Germany. DZHK - German Center for Cardiovascular Research, Partner site Rhine-Main
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41
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Abstract
Epigenetics has enriched human disease studies by adding new interpretations to disease features that cannot be explained by genetic and environmental factors. However, identifying causal mechanisms of epigenetic origin has been challenging. New opportunities have risen from recent findings in intra-individual and cyclical epigenetic variation, which includes circadian epigenetic oscillations. Cytosine modifications display deterministic temporal rhythms, which may drive ageing and complex disease. Temporality in the epigenome, or the 'chrono' dimension, may help the integration of epigenetic, environmental and genetic disease studies, and reconcile several disparities stemming from the arbitrarily delimited research fields. The ultimate goal of chrono-epigenetics is to predict disease risk, age of onset and disease dynamics from within individual-specific temporal dynamics of epigenomes.
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42
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Vrettou M, Yan L, Nilsson KW, Wallén-Mackenzie Å, Nylander I, Comasco E. DNA methylation of Vesicular Glutamate Transporters in the mesocorticolimbic brain following early-life stress and adult ethanol exposure-an explorative study. Sci Rep 2021; 11:15322. [PMID: 34321562 PMCID: PMC8319394 DOI: 10.1038/s41598-021-94739-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 07/14/2021] [Indexed: 02/07/2023] Open
Abstract
DNA methylation and gene expression can be altered by early life stress (ELS) and/or ethanol consumption. The present study aimed to investigate whether DNA methylation of the Vesicular Glutamate Transporters (Vglut)1-3 is related to previously observed Vglut1-3 transcriptional differences in the ventral tegmental area (VTA), nucleus accumbens (Acb), dorsal striatum (dStr) and medial prefrontal cortex (mPFC) of adult rats exposed to ELS, modelled by maternal separation, and voluntary ethanol consumption. Targeted next-generation bisulfite sequencing was performed to identify the methylation levels on 61 5′-cytosine-phosphate-guanosine-3′ sites (CpGs) in potential regulatory regions of Vglut1, 53 for Vglut2, and 51 for Vglut3. In the VTA, ELS in ethanol-drinking rats was associated with Vglut1-2 CpG-specific hypomethylation, whereas bidirectional Vglut2 methylation differences at single CpGs were associated with ELS alone. Exposure to both ELS and ethanol, in the Acb, was associated with lower promoter and higher intronic Vglut3 methylation; and in the dStr, with higher and lower methylation in 26% and 43% of the analyzed Vglut1 CpGs, respectively. In the mPFC, lower Vglut2 methylation was observed upon exposure to ELS or ethanol. The present findings suggest Vglut1-3 CpG-specific methylation signatures of ELS and ethanol drinking, underlying previously reported Vglut1-3 transcriptional differences in the mesocorticolimbic brain.
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Affiliation(s)
- Maria Vrettou
- Department of Neuroscience, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | | | - Kent W Nilsson
- Centre for Clinical Research Västerås, Uppsala University, Västmanland County Hospital Västerås, Uppsala, Sweden.,The School of Health, Care and Social Welfare, Mälardalen University, Västerås, Sweden
| | | | - Ingrid Nylander
- Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
| | - Erika Comasco
- Department of Neuroscience, Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
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43
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Jhun MA, Mendelson M, Wilson R, Gondalia R, Joehanes R, Salfati E, Zhao X, Braun KVE, Do AN, Hedman ÅK, Zhang T, Carnero-Montoro E, Shen J, Bartz TM, Brody JA, Montasser ME, O'Connell JR, Yao C, Xia R, Boerwinkle E, Grove M, Guan W, Liliane P, Singmann P, Müller-Nurasyid M, Meitinger T, Gieger C, Peters A, Zhao W, Ware EB, Smith JA, Dhana K, van Meurs J, Uitterlinden A, Ikram MA, Ghanbari M, Zhi D, Gustafsson S, Lind L, Li S, Sun D, Spector TD, Chen YDI, Damcott C, Shuldiner AR, Absher DM, Horvath S, Tsao PS, Kardia S, Psaty BM, Sotoodehnia N, Bell JT, Ingelsson E, Chen W, Dehghan A, Arnett DK, Waldenberger M, Hou L, Whitsel EA, Baccarelli A, Levy D, Fornage M, Irvin MR, Assimes TL. A multi-ethnic epigenome-wide association study of leukocyte DNA methylation and blood lipids. Nat Commun 2021; 12:3987. [PMID: 34183656 PMCID: PMC8238961 DOI: 10.1038/s41467-021-23899-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Accepted: 05/25/2021] [Indexed: 02/06/2023] Open
Abstract
Here we examine the association between DNA methylation in circulating leukocytes and blood lipids in a multi-ethnic sample of 16,265 subjects. We identify 148, 35, and 4 novel associations among Europeans, African Americans, and Hispanics, respectively, and an additional 186 novel associations through a trans-ethnic meta-analysis. We observe a high concordance in the direction of effects across racial/ethnic groups, a high correlation of effect sizes between high-density lipoprotein and triglycerides, a modest overlap of associations with epigenome-wide association studies of other cardio-metabolic traits, and a largely non-overlap with lipid loci identified to date through genome-wide association studies. Thirty CpGs reached significance in at least 2 racial/ethnic groups including 7 that showed association with the expression of an annotated gene. CpGs annotated to CPT1A showed evidence of being influenced by triglycerides levels. DNA methylation levels of circulating leukocytes show robust and consistent association with blood lipid levels across multiple racial/ethnic groups.
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Affiliation(s)
- Min-A Jhun
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA.
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
| | - Michael Mendelson
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Department of Cardiology, Boston Children's Hospital, Boston, MA, USA
| | - Rory Wilson
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Rahul Gondalia
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Roby Joehanes
- Hebrew SeniorLife, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Elias Salfati
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Xiaoping Zhao
- The Brown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | | | - Anh Nguyet Do
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Åsa K Hedman
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Tao Zhang
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Elena Carnero-Montoro
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, UK
- GENYO, Center for Genomics and Oncological Research Pfizer/University of Granada/Andalusian Regional Government, Granada, Spain
| | - Jincheng Shen
- Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Departments of Medicine and Biostatistics, University of Washington, Seattle, WA, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - May E Montasser
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jeff R O'Connell
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Chen Yao
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Rui Xia
- The Brown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Eric Boerwinkle
- School of Public Health, University of Texas Health Science Center at Houston, Huston, TX, USA
| | - Megan Grove
- School of Public Health, University of Texas Health Science Center at Houston, Huston, TX, USA
| | - Weihua Guan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Pfeiffer Liliane
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Paula Singmann
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- IBE, Faculty of Medicine, LMU Munich, Munich, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Thomas Meitinger
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Human Genetics, Technical University Munich, Munich, Germany
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Wei Zhao
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Erin B Ware
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, Ann Arbor, MI, USA
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, Ann Arbor, MI, USA
| | - Klodian Dhana
- Department of Internal Medicine, Rush University Medical Center, Chicago, IL, USA
| | - Joyce van Meurs
- Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Andre Uitterlinden
- Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Mohammad Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Deugi Zhi
- School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Stefan Gustafsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Lars Lind
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Shengxu Li
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Dianjianyi Sun
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, UK
| | - Yii-der Ida Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Coleen Damcott
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alan R Shuldiner
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Devin M Absher
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Philip S Tsao
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- VA Palo Alto Healthcare System, Palo Alto, CA, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
| | - Sharon Kardia
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Epidemiology, Medicine, and Health Services, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, WA, USA
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, UK
| | - Erik Ingelsson
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, USA
| | - Wei Chen
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Abbas Dehghan
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Biostatistics and Epidemiology, MRC Centre for Environment and Health, School of Public Health, Imperial College, London, UK
| | - Donna K Arnett
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Eric A Whitsel
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
- Department of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Andrea Baccarelli
- Department of Environmental Health Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Myriam Fornage
- The Brown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Themistocles L Assimes
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
- VA Palo Alto Healthcare System, Palo Alto, CA, USA.
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA.
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44
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He S, Wu Y, Yan S, Liu J, Zhao L, Xie H, Ge S, Ye H. Methylation of CYP1A1 and VKORC1 promoter associated with stable dosage of warfarin in Chinese patients. PeerJ 2021; 9:e11549. [PMID: 34221714 PMCID: PMC8231338 DOI: 10.7717/peerj.11549] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 05/11/2021] [Indexed: 01/01/2023] Open
Abstract
Objective To investigate the association between DNA methylation and the stable warfarin dose through genome-wide DNA methylation analysis and pyrosequencing assay. Method This study included 161 patients and genome-wide DNA methylation analysis was used to screen potential warfarin dose-associated CpGs through Illumina Infinium HumanMethylation 450 K BeadChip; then, the pyrosequencing assay was used to further validate the association between the stable warfarin dose and alterations in the methylation of the screened CpGs. GenomeStudio Software and R were used to analyze the differentially methylated CpGs. Results The methylation levels of CpGs surrounding the xenobiotic response element (XRE) within the CYP1A1 promoter, differed significantly between the different dose groups (P < 0.05), and these CpGs presented a positive correlation (r> 0, P < 0.05) with an increase in the stable dose of warfarin. At the VKORC1 promoter, two CpGs methylation levels were significantly different between the differential dose groups (P < 0.05), and one CpG (Chr16: 31106793) presented a significant negative correlation (r < 0, P < 0.05) among different dose (low, medium, and high) groups. Conclusion This is a novel report of the methylation levels of six CpGs surrounding the XRE within the CYP1A1 promoter and one differential CpG at the VKORC1 promoter associated with stable warfarin dosage; these methylation levels might be applied as molecular signatures for warfarin.
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Affiliation(s)
- Shiwei He
- Department of Clinical Laboratory, Women and Children's Hospital, School of Medicine, Xiamen University, Xiamen, China.,National Institute of Diagnostics and Vaccine Development in Infectious Diseases (Xiamen University), School of Public Health, Xiamen University, Xiamen, China
| | - Yuan Wu
- Xiamen Cardiovascular Hospital, School of Medicine, Xiamen University, Xiamen, China
| | - Shuidi Yan
- Department of Clinical Laboratory, Zhongshan Hospital, School of Medicine, Xiamen University, Xiamen, China
| | - Jumei Liu
- Department of Clinical Laboratory, Women and Children's Hospital, School of Medicine, Xiamen University, Xiamen, China
| | - Li Zhao
- Department of Clinical Laboratory, Women and Children's Hospital, School of Medicine, Xiamen University, Xiamen, China.,School of Medicine, Xiamen University, Xiamen, China
| | - Huabin Xie
- Xiamen Cardiovascular Hospital, School of Medicine, Xiamen University, Xiamen, China
| | - Shengxiang Ge
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases (Xiamen University), School of Public Health, Xiamen University, Xiamen, China
| | - Huiming Ye
- Department of Clinical Laboratory, Women and Children's Hospital, School of Medicine, Xiamen University, Xiamen, China.,National Institute of Diagnostics and Vaccine Development in Infectious Diseases (Xiamen University), School of Public Health, Xiamen University, Xiamen, China.,School of Medicine, Xiamen University, Xiamen, China
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45
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Lucia RM, Huang WL, Alvarez A, Masunaka I, Ziogas A, Goodman D, Odegaard AO, Norden-Krichmar TM, Park HL. Association of mammographic density with blood DNA methylation. Epigenetics 2021; 17:531-546. [PMID: 34116608 PMCID: PMC9067527 DOI: 10.1080/15592294.2021.1928994] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Background: Altered DNA methylation may be an intermediate phenotype between breast cancer risk factors and disease. Mammographic density is a strong risk factor for breast cancer. However, no studies to date have identified an epigenetic signature of mammographic density. We performed an epigenome-wide association study of mammographic density. Methods: White blood cell DNA methylation was measured for 385 postmenopausal women using the Illumina Infinium MethylationEPIC BeadChip array. Differential methylation was assessed using genome-wide, probe-level, and regional analyses. We implemented a resampling-based approach to improve the stability of our findings. Results: On average, women with elevated mammographic density exhibited DNA hypermethylation within CpG islands and gene promoters compared to women with lower mammographic density. We identified 250 CpG sites for which DNA methylation was significantly associated with mammographic density. The top sites were located within genes associated with cancer, including HDLBP, TGFB2, CCT4, and PAX8, and were more likely to be located in regulatory regions of the genome. We also identified differential DNA methylation in 37 regions, including within the promoters of PAX8 and PF4, a gene involved in the regulation of angiogenesis. Overall, our results paint a picture of epigenetic dysregulation associated with mammographic density. Conclusion: Mammographic density is associated with differential DNA methylation throughout the genome, including within genes associated with cancer. Our results suggest the potential involvement of several genes in the biological mechanisms behind differences in breast density between women. Further studies are warranted to explore these potential mechanisms and potential links to breast cancer risk.
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Affiliation(s)
- Rachel M Lucia
- Department of Epidemiology, University of California, Irvine, USA
| | - Wei-Lin Huang
- Department of Epidemiology, University of California, Irvine, USA
| | - Andrea Alvarez
- Department of Medicine, University of California, Irvine, USA
| | - Irene Masunaka
- Department of Medicine, University of California, Irvine, USA
| | - Argyrios Ziogas
- Department of Medicine, University of California, Irvine, USA
| | - Deborah Goodman
- Department of Epidemiology, University of California, Irvine, USA
| | | | | | - Hannah Lui Park
- Department of Epidemiology, University of California, Irvine, USA.,Department of Pathology and Laboratory Medicine, University of California, Irvine, USA
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46
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Dean DC, Madrid A, Planalp EM, Moody JF, Papale LA, Knobel KM, Wood EK, McAdams RM, Coe CL, Hill Goldsmith H, Davidson RJ, Alisch RS, Kling PJ. Cord blood DNA methylation modifications in infants are associated with white matter microstructure in the context of prenatal maternal depression and anxiety. Sci Rep 2021; 11:12181. [PMID: 34108589 PMCID: PMC8190282 DOI: 10.1038/s41598-021-91642-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 05/17/2021] [Indexed: 12/12/2022] Open
Abstract
Maternal and environmental factors influence brain networks and architecture via both physiological pathways and epigenetic modifications. In particular, prenatal maternal depression and anxiety symptoms appear to impact infant white matter (WM) microstructure, leading us to investigate whether epigenetic modifications (i.e., DNA methylation) contribute to these WM differences. To determine if infants of women with depression and anxiety symptoms exhibit epigenetic modifications linked to neurodevelopmental changes, 52 umbilical cord bloods (CBs) were profiled. We observed 219 differentially methylated genomic positions (DMPs; FDR p < 0.05) in CB that were associated with magnetic resonance imaging measures of WM microstructure at 1 month of age and in regions previously described to be related to maternal depression and anxiety symptoms. Genomic characterization of these associated DMPs revealed 143 unique genes with significant relationships to processes involved in neurodevelopment, GTPase activity, or the canonical Wnt signaling pathway. Separate regression models for female (n = 24) and male (n = 28) infants found 142 associated DMPs in females and 116 associated DMPs in males (nominal p value < 0.001, R > 0.5), which were annotated to 98 and 81 genes, respectively. Together, these findings suggest that umbilical CB DNA methylation levels at birth are associated with 1-month WM microstructure.
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Affiliation(s)
- Douglas C Dean
- Department of Pediatrics, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, USA.,Department of Medical Physics, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA.,Waisman Center, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Andy Madrid
- Department of Neurosurgery, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Elizabeth M Planalp
- Waisman Center, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA.,Department of Psychology, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Jason F Moody
- Department of Medical Physics, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Ligia A Papale
- Department of Neurosurgery, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Karla M Knobel
- Waisman Center, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Elizabeth K Wood
- Harlow Center for Biological Psychology, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Ryan M McAdams
- Department of Pediatrics, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, USA
| | - Christopher L Coe
- Waisman Center, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA.,Department of Psychology, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA.,Harlow Center for Biological Psychology, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - H Hill Goldsmith
- Waisman Center, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA.,Department of Psychology, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Richard J Davidson
- Waisman Center, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA.,Department of Psychology, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA.,Center for Healthy Minds, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA.,Department of Psychiatry, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Reid S Alisch
- Department of Neurosurgery, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, WI, USA.
| | - Pamela J Kling
- Department of Pediatrics, School of Medicine & Public Health, University of Wisconsin-Madison, Madison, USA
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47
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Luo M, Meehan AJ, Walton E, Röder S, Herberth G, Zenclussen AC, Cosín-Tomás M, Sunyer J, Mulder RH, Cortes Hidalgo AP, Bakermans-Kranenburg MJ, Felix JF, Relton C, Suderman M, Pappa I, Kok R, Tiemeier H, van IJzendoorn MH, Barker ED, Cecil CAM. Neonatal DNA methylation and childhood low prosocial behavior: An epigenome-wide association meta-analysis. Am J Med Genet B Neuropsychiatr Genet 2021; 186:228-241. [PMID: 34170065 DOI: 10.1002/ajmg.b.32862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 05/26/2021] [Accepted: 06/02/2021] [Indexed: 11/10/2022]
Abstract
Low prosocial behavior in childhood has been consistently linked to later psychopathology, with evidence supporting the influence of both genetic and environmental factors on its development. Although neonatal DNA methylation (DNAm) has been found to prospectively associate with a range of psychological traits in childhood, its potential role in prosocial development has yet to be investigated. This study investigated prospective associations between cord blood DNAm at birth and low prosocial behavior within and across four longitudinal birth cohorts from the Pregnancy And Childhood Epigenetics (PACE) Consortium. We examined (a) developmental trajectories of "chronic-low" versus "typical" prosocial behavior across childhood in a case-control design (N = 2,095), and (b) continuous "low prosocial" scores at comparable cross-cohort time-points (N = 2,121). Meta-analyses were performed to examine differentially methylated positions and regions. At the cohort-specific level, three CpGs were found to associate with chronic low prosocial behavior; however, none of these associations was replicated in another cohort. Meta-analysis revealed no epigenome-wide significant CpGs or regions. Overall, we found no evidence for associations between DNAm patterns at birth and low prosocial behavior across childhood. Findings highlight the importance of employing multi-cohort approaches to replicate epigenetic associations and reduce the risk of false positive discoveries.
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Affiliation(s)
- Mannan Luo
- Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, The Netherlands.,Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Alan J Meehan
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Yale Child Study Center, Yale School of Medicine, New Haven, USA
| | - Esther Walton
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.,Department of Psychology, University of Bath, Bath, UK
| | - Stefan Röder
- Department for Environmental Immunology, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany
| | - Gunda Herberth
- Department for Environmental Immunology, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany
| | - Ana C Zenclussen
- Department for Environmental Immunology, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany
| | - Marta Cosín-Tomás
- ISGlobal, Barcelona, Catalonia, Spain.,Universitat Pompeu Fabra, Barcelona, Catalonia, Spain.,Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Jordi Sunyer
- ISGlobal, Barcelona, Catalonia, Spain.,Universitat Pompeu Fabra, Barcelona, Catalonia, Spain.,Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.,IMIM Parc Salut Mar, Barcelona, Catalonia, Spain
| | - Rosa H Mulder
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Andrea P Cortes Hidalgo
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | | | - Janine F Felix
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Irene Pappa
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Rianne Kok
- Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, The Netherlands
| | - Henning Tiemeier
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Social and Behavioral Science, Harvard TH Chan School of Public Health, Boston, Massachusetts, USA
| | - Marinus H van IJzendoorn
- Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, The Netherlands.,Department of Clinical, Educational and Health Psychology, Faculty of Brain Sciences, University College London, London, UK
| | - Edward D Barker
- Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Charlotte A M Cecil
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
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48
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The role of DNA methylation in syndromic and non-syndromic congenital heart disease. Clin Epigenetics 2021; 13:93. [PMID: 33902696 PMCID: PMC8077695 DOI: 10.1186/s13148-021-01077-7] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Accepted: 04/13/2021] [Indexed: 02/07/2023] Open
Abstract
Congenital heart disease (CHD) is a common structural birth defect worldwide, and defects typically occur in the walls and valves of the heart or enlarged blood vessels. Chromosomal abnormalities and genetic mutations only account for a small portion of the pathogenic mechanisms of CHD, and the etiology of most cases remains unknown. The role of epigenetics in various diseases, including CHD, has attracted increased attention. The contributions of DNA methylation, one of the most important epigenetic modifications, to CHD have not been illuminated. Increasing evidence suggests that aberrant DNA methylation is related to CHD. Here, we briefly introduce DNA methylation and CHD and then review the DNA methylation profiles during cardiac development and in CHD, abnormalities in maternal genome-wide DNA methylation patterns are also described. Whole genome methylation profile and important differentially methylated genes identified in recent years are summarized and clustered according to the sample type and methodologies. Finally, we discuss the novel technology for and prospects of CHD-related DNA methylation.
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49
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Maden SK, Thompson RF, Hansen KD, Nellore A. Human methylome variation across Infinium 450K data on the Gene Expression Omnibus. NAR Genom Bioinform 2021; 3:lqab025. [PMID: 33937763 PMCID: PMC8061458 DOI: 10.1093/nargab/lqab025] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 02/11/2021] [Accepted: 04/19/2021] [Indexed: 12/16/2022] Open
Abstract
While DNA methylation (DNAm) is the most-studied epigenetic mark, few recent studies probe the breadth of publicly available DNAm array samples. We collectively analyzed 35 360 Illumina Infinium HumanMethylation450K DNAm array samples published on the Gene Expression Omnibus. We learned a controlled vocabulary of sample labels by applying regular expressions to metadata and used existing models to predict various sample properties including epigenetic age. We found approximately two-thirds of samples were from blood, one-quarter were from brain and one-third were from cancer patients. About 19% of samples failed at least one of Illumina's 17 prescribed quality assessments; signal distributions across samples suggest modifying manufacturer-recommended thresholds for failure would make these assessments more informative. We further analyzed DNAm variances in seven tissues (adipose, nasal, blood, brain, buccal, sperm and liver) and characterized specific probes distinguishing them. Finally, we compiled DNAm array data and metadata, including our learned and predicted sample labels, into database files accessible via the recountmethylation R/Bioconductor companion package. Its vignettes walk the user through some analyses contained in this paper.
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Affiliation(s)
- Sean K Maden
- Computational Biology Program, Oregon Health & Science University, Portland, OR 97239, USA
| | - Reid F Thompson
- Computational Biology Program, Oregon Health & Science University, Portland, OR 97239, USA
| | - Kasper D Hansen
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Abhinav Nellore
- Computational Biology Program, Oregon Health & Science University, Portland, OR 97239, USA
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50
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Ueda S, Yamashita S, Watanabe SI, Wakabayashi M, Motoi N, Noguchi M, Sekine S, Sato Y, Ushijima T. Influence of degree of DNA degradation in formalin-fixed and paraffin-embedded tissue samples on accuracy of genome-wide DNA methylation analysis. Epigenomics 2021; 13:565-576. [PMID: 33820444 DOI: 10.2217/epi-2020-0431] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aim: Depending upon the degree of DNA degradation of formalin-fixed and paraffin-embedded tissue samples, accuracy of measurement by Infinium MethylationEPIC BeadChip assay (Illumina, CA, USA) was assessed. Materials & methods: DNA quality of six formalin-fixed and paraffin-embedded lung tissue samples with different formalin fixation periods was assessed by Illumina quality control, DNA copy number and DNA integrity number value. Infinium data from restored bisulfite treated DNA were compared with datum from a fresh-frozen sample. Results: The correlation coefficient decreased from 0.993 to 0.970 depending upon DNA degradation, even if the Illumina quality control was met. Exclusion of specific probes improved the correlation regardless of tissue. Conclusion: Poor DNA quality can be assessed as an amplifiable DNA copy number and DNA integrity number value. Probe filtering has the potential to improve assay accuracy.
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Affiliation(s)
- Sho Ueda
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo 104 0045, Japan.,Department of Pathology, Faculty of Medicine, University of Tsukuba, Ibaraki 305 8575, Japan.,Department of Thoracic Surgery, Faculty of Medicine, University of Tsukuba, Ibaraki 305 8575, Japan
| | - Satoshi Yamashita
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo 104 0045, Japan
| | - Shun-Ichi Watanabe
- Department of Thoracic Surgery, National Cancer Center Hospital, Tokyo 104 0045, Japan
| | - Mika Wakabayashi
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo 104 0045, Japan
| | - Noriko Motoi
- Department of Diagnostic Pathology, National Cancer Center Hospital, Tokyo 104 0045, Japan
| | - Masayuki Noguchi
- Department of Pathology, Faculty of Medicine, University of Tsukuba, Ibaraki 305 8575, Japan
| | - Shigeki Sekine
- Department of Diagnostic Pathology, National Cancer Center Hospital, Tokyo 104 0045, Japan
| | - Yukio Sato
- Department of Thoracic Surgery, Faculty of Medicine, University of Tsukuba, Ibaraki 305 8575, Japan
| | - Toshikazu Ushijima
- Division of Epigenomics, National Cancer Center Research Institute, Tokyo 104 0045, Japan
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