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Zhang W, Young JI, Gomez L, Schmidt MA, Lukacsovich D, Varma A, Chen XS, Kunkle B, Martin ER, Wang L. Critical evaluation of the reliability of DNA methylation probes on the Illumina MethylationEPIC v1.0 BeadChip microarrays. Epigenetics 2024; 19:2333660. [PMID: 38564759 PMCID: PMC10989698 DOI: 10.1080/15592294.2024.2333660] [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: 10/06/2023] [Accepted: 03/18/2024] [Indexed: 04/04/2024] Open
Abstract
DNA methylation (DNAm) plays a crucial role in a number of complex diseases. However, the reliability of DNAm levels measured using Illumina arrays varies across different probes. Previous research primarily assessed probe reliability by comparing duplicate samples between the 450k-450k or 450k-EPIC platforms, with limited investigations on Illumina EPIC v1.0 arrays. We conducted a comprehensive assessment of the EPIC v1.0 array probe reliability using 69 blood DNA samples, each measured twice, generated by the Alzheimer's Disease Neuroimaging Initiative study. We observed higher reliability in probes with average methylation beta values of 0.2 to 0.8, and lower reliability in type I probes or those within the promoter and CpG island regions. Importantly, we found that probe reliability has significant implications in the analyses of Epigenome-wide Association Studies (EWAS). Higher reliability is associated with more consistent effect sizes in different studies, the identification of differentially methylated regions (DMRs) and methylation quantitative trait locus (mQTLs), and significant correlations with downstream gene expression. Moreover, blood DNAm measurements obtained from probes with higher reliability are more likely to show concordance with brain DNAm measurements. Our findings, which provide crucial reliability information for probes on the EPIC v1.0 array, will serve as a valuable resource for future DNAm studies.
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Affiliation(s)
- Wei Zhang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL, USA
| | - Juan I Young
- Dr. John T MacDonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL, USA
| | - Lissette Gomez
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL, USA
| | - Michael A Schmidt
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL, USA
| | - David Lukacsovich
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL, USA
| | - Achintya Varma
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL, USA
| | - X Steven Chen
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL, USA
| | - Brian Kunkle
- Dr. John T MacDonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL, USA
| | - Eden R Martin
- Dr. John T MacDonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL, USA
| | - Lily Wang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL, USA
- Dr. John T MacDonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL, USA
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2
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Eckhardt CM, Balte P, Morris JE, Bhatt SP, Couper D, Fetterman J, Freedman N, Jacobs DR, Hou L, Kalhan R, Liu Y, Loehr L, Lutsey PL, Schwartz JE, White W, Yende S, London SJ, Sanchez TR, Oelsner EC. Non-cigarette tobacco products, aryl-hydrocarbon receptor repressor gene methylation and smoking-related health outcomes. Thorax 2024:thorax-2023-220731. [PMID: 39033027 DOI: 10.1136/thorax-2023-220731] [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: 07/18/2023] [Accepted: 07/01/2024] [Indexed: 07/23/2024]
Abstract
INTRODUCTION Cigarette smoking leads to altered DNA methylation at the aryl-hydrocarbon receptor repressor (AHRR) gene. However, it remains unknown whether pipe or cigar smoking is associated with AHRR methylation. We evaluated associations of non-cigarette tobacco use with AHRR methylation and determined if AHRR methylation was associated with smoking-related health outcomes. METHODS Data were pooled across four population-based cohorts that enrolled participants from 1985 to 2002. Tobacco exposures were evaluated using smoking questionnaires. AHRR cg05575921 methylation was measured in peripheral blood leucocyte DNA. Spirometry and respiratory symptoms were evaluated at the time of methylation measurements and in subsequent visits. Vital status was monitored using the National Death Index. RESULTS Among 8252 adults (mean age 56.7±10.3 years, 58.1% women, 40.6% black), 4857 (58.9%) participants used cigarettes and 634 (7.7%) used non-cigarette tobacco products. Exclusive use of non-cigarette tobacco products was independently associated with lower AHRR methylation (-2.44 units, 95% CI -4.42 to -0.45), though to a lesser extent than exclusive use of cigarettes (-6.01 units, 95% CI -6.01 to -4.10). Among participants who exclusively used non-cigarette tobacco products, reduced AHRR methylation was associated with increased respiratory symptom burden (OR 1.60, 95% CI 1.03 to 2.68) and higher all-cause mortality (log-rank p=0.02). CONCLUSION Pipe and cigar smoking were independently associated with lower AHRR methylation in a multiethnic cohort of US adults. Among users of non-cigarette tobacco products, lower AHRR methylation was associated with poor respiratory health outcomes and increased mortality. AHRR methylation may identify non-cigarette tobacco users with an increased risk of adverse smoking-related health outcomes.
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Affiliation(s)
- Christina M Eckhardt
- Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, New York, USA
- Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Pallavi Balte
- Columbia University Vagelos College of Physicians and Surgeons, New York, New York, USA
| | - Jack E Morris
- Columbia University Mailman School of Public Health, New York, New York, USA
| | - Surya P Bhatt
- Pulmonary, Allergy and Critical Care Medicine, University of Alabama School of Natural Sciences and Mathematics, Birmingham, Alabama, USA
| | - David Couper
- Biostatistics, The University of North Carolina, Chapel Hill, North Carolina, USA
| | | | - Neal Freedman
- Nutritional Epidemiology, National Institutes of Health, Bethesda, Maryland, USA
| | - David R Jacobs
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA
| | - Lifang Hou
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Ravi Kalhan
- Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Yongmei Liu
- Duke University, Durham, North Carolina, USA
| | - Laura Loehr
- The University of North Carolina, Chapel Hill, North Carolina, USA
| | - Pamela L Lutsey
- University of Minnesota School of Public Health, Minneapolis, Minnesota, USA
| | - Joseph E Schwartz
- Center for Behavioral Cardiovascular Health, Columbia University Vagelos College of Physicians and Surgeons, New York, New York, USA
| | - Wendy White
- Tougaloo College, Tougaloo, Mississippi, USA
| | - Sachin Yende
- University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | | | - Tiffany R Sanchez
- Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Elizabeth C Oelsner
- Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, New York, USA
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3
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Zhuang BC, Jude MS, Konwar C, Ryan CP, Whitehead J, Engelbrecht HR, MacIsaac JL, Dever K, Toan TK, Korinek K, Zimmer Z, Huffman KM, Lee NR, McDade TW, Kuzawa CW, Belsky DW, Kobor MS. Comparison of Infinium MethylationEPIC v2.0 to v1.0 for human population epigenetics: considerations for addressing EPIC version differences in DNA methylation-based tools. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.02.600461. [PMID: 39005299 PMCID: PMC11245009 DOI: 10.1101/2024.07.02.600461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Background The recently launched DNA methylation profiling platform, Illumina MethylationEPIC BeadChip Infinium microarray v2.0 (EPICv2), is highly correlated with measurements obtained from its predecessor MethylationEPIC BeadChip Infinium microarray v1.0 (EPICv1). However, the concordance between the two versions in the context of DNA methylation-based tools, including cell type deconvolution algorithms, epigenetic clocks, and inflammation and lifestyle biomarkers has not yet been investigated. Findings We profiled DNA methylation on both EPIC versions using matched venous blood samples from individuals spanning early to late adulthood across three cohorts. On combining the DNA methylomes of the cohorts, we observed that samples primarily clustered by the EPIC version they were measured on. Within each cohort, when we calculated cell type proportions, epigenetic age acceleration (EAA), rate of aging estimates, and biomarker scores for the matched samples on each version, we noted significant differences between EPICv1 and EPICv2 in the majority of these estimates. These differences were not significant, however, when estimates were adjusted for EPIC version or when EAAs were calculated separately for each EPIC version. Conclusions Our findings indicate that EPIC version differences predominantly explain DNA methylation variation and influence estimates of DNA methylation-based tools, and therefore we recommend caution when combining cohorts run on different versions. We demonstrate the importance of calculating DNA methylation-based estimates separately for each EPIC version or accounting for EPIC version either as a covariate in statistical models or by using version correction algorithms.
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Affiliation(s)
- Beryl C Zhuang
- BC Children's Hospital Research Institute, 950 West 28th Avenue, Vancouver, BC, V5Z 4H4, Canada
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - Marcia Smiti Jude
- BC Children's Hospital Research Institute, 950 West 28th Avenue, Vancouver, BC, V5Z 4H4, Canada
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - Chaini Konwar
- BC Children's Hospital Research Institute, 950 West 28th Avenue, Vancouver, BC, V5Z 4H4, Canada
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - Calen P Ryan
- Robert N. Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Joanne Whitehead
- BC Children's Hospital Research Institute, 950 West 28th Avenue, Vancouver, BC, V5Z 4H4, Canada
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - Hannah-Ruth Engelbrecht
- BC Children's Hospital Research Institute, 950 West 28th Avenue, Vancouver, BC, V5Z 4H4, Canada
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - Julia L MacIsaac
- BC Children's Hospital Research Institute, 950 West 28th Avenue, Vancouver, BC, V5Z 4H4, Canada
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - Kristy Dever
- BC Children's Hospital Research Institute, 950 West 28th Avenue, Vancouver, BC, V5Z 4H4, Canada
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - Tran Khanh Toan
- Family Medicine Department, Hanoi Medical University, Hanoi, Vietnam
| | - Kim Korinek
- Department of Sociology, University of Utah, Salt Lake City, USA
| | - Zachary Zimmer
- Department of Family Studies and Gerontology, Mount Saint Vincent University, Halifax, Canada
- Canada Research Chair, Global Aging and Community Initiative
| | - Kim M Huffman
- Duke University School of Medicine, Durham, NC, 27701, USA
| | - Nanette R Lee
- USC-Office of Population Studies Foundation, Inc., University of San Carlos, Cebu City, Philippines
| | - Thomas W McDade
- Department of Anthropology, Northwestern University, Evanston, Illinois, USA
- Program in Child and Brain Development, CIFAR, Toronto, Ontario, Canada
| | - Christopher W Kuzawa
- Department of Anthropology and Institute for Policy Research, Northwestern University, Evanston, IL 60208, USA
| | - Daniel W Belsky
- Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, NY, USA
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Michael S Kobor
- BC Children's Hospital Research Institute, 950 West 28th Avenue, Vancouver, BC, V5Z 4H4, Canada
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
- Program in Child and Brain Development, CIFAR, Toronto, Ontario, Canada
- The Edwin S.H. Leong UBC Healthy Aging Chair-A UBC President's Excellence Chair, University of British Columbia, Canada
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Hogan CM, Merrill SM, Hernandez Valencia E, McHayle AA, Sisitsky MD, McDermott JM, Parent J. The Impact of Early Life Adversity on Peripubertal Accelerated Epigenetic Aging and Psychopathology. J Am Acad Child Adolesc Psychiatry 2024:S0890-8567(24)00352-6. [PMID: 38969335 DOI: 10.1016/j.jaac.2024.04.019] [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: 10/17/2023] [Revised: 04/24/2024] [Accepted: 06/26/2024] [Indexed: 07/07/2024]
Abstract
OBJECTIVE To examine longitudinal associations between early life threat and deprivation on epigenetic age acceleration at ages 9 and 15 years, and to examine associations of age acceleration on later internalizing and externalizing symptoms. METHOD The study examines a large (n = 2,039) and racially diverse (Black/African American = 44%, Latino = 18%, White = 5%) sample from a national dataset. Epigenetic age acceleration was estimated using the pediatric buccal epigenetic clock. Early life threat and deprivation were measured using composites from the Parent-Child Conflict Tactics Scale and county-level violent and property crime rate data. Internalizing and externalizing symptoms came from parent-reported Child Behavior Checklist. Path analysis models examined associations of threat and deprivation at age 3 years on epigenetic age acceleration at ages 9 and 15. Experiences of threat were further broken down into threat experienced in the home and in the community. RESULTS Home threat experienced at age 3 years predicted age acceleration at 9 and 15, and community threat experienced at 3 predicted age acceleration at 15, but not at 9. Deprivation was not a significant predictor of accelerated aging. Age acceleration at age 9 predicted externalizing, but not internalizing, symptoms at age 15. Community threat had a direct effect on externalizing. No association emerged with internalizing. CONCLUSION Findings revealed that threat, not deprivation, was predictive of age acceleration, demonstrating support for this pattern longitudinally, using an epigenetic clock that is accurate in children. The findings provide critical nuance to the examination of threat, and highlight associated risks and possible intervention points for externalizing symptoms.
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Affiliation(s)
| | - Sarah M Merrill
- Warren Alpert Medical School at Brown University, Providence, Rhode Island
| | | | - Allison A McHayle
- Warren Alpert Medical School at Brown University, Providence, Rhode Island
| | | | | | - Justin Parent
- Warren Alpert Medical School at Brown University, Providence, Rhode Island; University of Rhode Island, Kingston, Rhode Island; Emma Pendleton Bradley Hospital, East Providence, Rhode Island
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5
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Mukherjee N, Bolin EH, Qasim A, Orloff MS, Lupo PJ, Nembhard WN. DNA methylation of the Lamin A/C gene is associated with congenital heart disease. Birth Defects Res 2024; 116:e2381. [PMID: 39073036 DOI: 10.1002/bdr2.2381] [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: 02/05/2024] [Revised: 05/24/2024] [Accepted: 06/18/2024] [Indexed: 07/30/2024]
Abstract
BACKGROUND Prior studies report associations of maternal serum Lamin A, encoded by the LMNA gene, with fetal congenital heart disease (CHD). It is unknown whether DNA methylation (DNAm) of cytosine-phosphate-guanine (CpG) sites in LMNA impacts the CHD susceptibility. METHODS We investigated the associations of LMNA DNAm with CHD using publicly available data of CHD cases (n = 197) and controls (n = 134) from the Gene Expression Omnibus repository. Peripheral blood DNAm was measured using Illumina 850 K BeadChip for cases and 450 K BeadChip for controls. We tested 31 LMNA CpGs to identify differences in DNAm between cases and controls using linear regression correcting for multiple testing with false discovery rate (FDR). In a case-only analysis, we tested the variations in LMNA DNAm between CHD subtypes. To identify the consistency of DNAm across tissue types we compared peripheral blood (n = 197) and heart tissue DNAm (n = 20) in CHD cases. RESULTS After adjusting for age, sex, and cell types there were significant differences in 17 of the 31 LMNA CpGs between CHD cases and controls (FDR p ≤ .05). We identified lower DNAm of cg09820673 at 3' UTR for hypoplastic left heart syndrome compared to other CHD subtypes. Three CpGs exhibited uniform DNAm in blood and heart tissues in cases. Eleven CpGs showed changes in the same direction in blood and heart tissues in cases compared to controls. CONCLUSION We identify statistically significant differences in LMNA DNAm between CHD cases and controls. Future studies should investigate the role of maternal LMNA DNAm in CHD development.
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Affiliation(s)
- Nandini Mukherjee
- Department of Epidemiology, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - Elijah H Bolin
- Department of Pediatrics, Section of Cardiology, University of Arkansas for Medical Sciences and Arkansas Children's Research Institute, Little Rock, Arkansas, USA
| | - Amna Qasim
- Department of Pediatrics, Section of Cardiology, University of Arkansas for Medical Sciences and Arkansas Children's Research Institute, Little Rock, Arkansas, USA
| | - Mohammed S Orloff
- Department of Epidemiology, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
- Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - Philip J Lupo
- Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
| | - Wendy N Nembhard
- Department of Epidemiology, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
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Schuurmans IK, Mulder RH, Baltramonaityte V, Lahtinen A, Qiuyu F, Rothmann LM, Staginnus M, Tuulari J, Burt SA, Buss C, Craig JM, Donald KA, Felix JF, Freeman TP, Grassi-Oliveira R, Huels A, Hyde LW, Jones SA, Karlsson H, Karlsson L, Koen N, Lawn W, Mitchell C, Monk CS, Mooney MA, Muetzel R, Nigg JT, Belangero SIN, Notterman D, O'Connor T, O'Donnell KJ, Pan PM, Paunio T, Ryabinin P, Saffery R, Salum GA, Seal M, Silk TJ, Stein DJ, Zar H, Walton E, Cecil CAM. Consortium Profile: The Methylation, Imaging and NeuroDevelopment (MIND) Consortium. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.06.23.24309353. [PMID: 38978656 PMCID: PMC11230303 DOI: 10.1101/2024.06.23.24309353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Epigenetic processes, such as DNA methylation, show potential as biological markers and mechanisms underlying gene-environment interplay in the prediction of mental health and other brain-based phenotypes. However, little is known about how peripheral epigenetic patterns relate to individual differences in the brain itself. An increasingly popular approach to address this is by combining epigenetic and neuroimaging data; yet, research in this area is almost entirely comprised of cross-sectional studies in adults. To bridge this gap, we established the Methylation, Imaging and NeuroDevelopment (MIND) Consortium, which aims to bring a developmental focus to the emerging field of Neuroimaging Epigenetics by (i) promoting collaborative, adequately powered developmental research via multi-cohort analyses; (ii) increasing scientific rigor through the establishment of shared pipelines and open science practices; and (iii) advancing our understanding of DNA methylation-brain dynamics at different developmental periods (from birth to emerging adulthood), by leveraging data from prospective, longitudinal pediatric studies. MIND currently integrates 15 cohorts worldwide, comprising (repeated) measures of DNA methylation in peripheral tissues (blood, buccal cells, and saliva) and neuroimaging by magnetic resonance imaging across up to five time points over a period of up to 21 years (Npooled DNAm = 11,299; Npooled neuroimaging = 10,133; Npooled combined = 4,914). By triangulating associations across multiple developmental time points and study types, we hope to generate new insights into the dynamic relationships between peripheral DNA methylation and the brain, and how these ultimately relate to neurodevelopmental and psychiatric phenotypes.
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7
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Davydova E, Perenkov A, Vedunova M. Building Minimized Epigenetic Clock by iPlex MassARRAY Platform. Genes (Basel) 2024; 15:425. [PMID: 38674360 PMCID: PMC11049545 DOI: 10.3390/genes15040425] [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: 02/26/2024] [Revised: 03/25/2024] [Accepted: 03/26/2024] [Indexed: 04/28/2024] Open
Abstract
Epigenetic clocks are valuable tools for estimating both chronological and biological age by assessing DNA methylation levels at specific CpG dinucleotides. While conventional epigenetic clocks rely on genome-wide methylation data, targeted approaches offer a more efficient alternative. In this study, we explored the feasibility of constructing a minimized epigenetic clock utilizing data acquired through the iPlex MassARRAY technology. The study enrolled a cohort of relatively healthy individuals, and their methylation levels of eight specific CpG dinucleotides in genes SLC12A5, LDB2, FIGN, ACSS3, FHL2, and EPHX3 were evaluated using the iPlex MassARRAY system and the Illumina EPIC array. The methylation level of five studied CpG sites demonstrated significant correlations with chronological age and an acceptable convergence of data obtained by the iPlex MassARRAY and Illumina EPIC array. At the same time, the methylation level of three CpG sites showed a weak relationship with age and exhibited a low concordance between the data obtained from the two technologies. The construction of the epigenetic clock involved the utilization of different machine-learning models, including linear models, deep neural networks (DNN), and gradient-boosted decision trees (GBDT). The results obtained from these models were compared with each other and with the outcomes generated by other well-established epigenetic clocks. In our study, the TabNet architecture (deep tabular data learning architecture) exhibited the best performance (best MAE = 5.99). Although our minimized epigenetic clock yielded slightly higher age prediction errors compared to other epigenetic clocks, it still represents a viable alternative to the genome-wide epigenotyping array.
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Affiliation(s)
- Ekaterina Davydova
- Institute of Biology and Biomedicine, Lobachevsky State University, 23 Gagarin Ave., Nizhny Novgorod 603022, Russia (M.V.)
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Moqri M, Herzog C, Poganik JR, Ying K, Justice JN, Belsky DW, Higgins-Chen AT, Chen BH, Cohen AA, Fuellen G, Hägg S, Marioni RE, Widschwendter M, Fortney K, Fedichev PO, Zhavoronkov A, Barzilai N, Lasky-Su J, Kiel DP, Kennedy BK, Cummings S, Slagboom PE, Verdin E, Maier AB, Sebastiano V, Snyder MP, Gladyshev VN, Horvath S, Ferrucci L. Validation of biomarkers of aging. Nat Med 2024; 30:360-372. [PMID: 38355974 PMCID: PMC11090477 DOI: 10.1038/s41591-023-02784-9] [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: 09/07/2023] [Accepted: 12/19/2023] [Indexed: 02/16/2024]
Abstract
The search for biomarkers that quantify biological aging (particularly 'omic'-based biomarkers) has intensified in recent years. Such biomarkers could predict aging-related outcomes and could serve as surrogate endpoints for the evaluation of interventions promoting healthy aging and longevity. However, no consensus exists on how biomarkers of aging should be validated before their translation to the clinic. Here, we review current efforts to evaluate the predictive validity of omic biomarkers of aging in population studies, discuss challenges in comparability and generalizability and provide recommendations to facilitate future validation of biomarkers of aging. Finally, we discuss how systematic validation can accelerate clinical translation of biomarkers of aging and their use in gerotherapeutic clinical trials.
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Affiliation(s)
- Mahdi Moqri
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, USA
- Department of Obstetrics and Gynecology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Chiara Herzog
- European Translational Oncology Prevention and Screening Institute, Universität Innsbruck, Innsbruck, Austria
| | - Jesse R Poganik
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Kejun Ying
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Jamie N Justice
- Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Daniel W Belsky
- Department of Epidemiology, Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, NY, USA
| | | | - Brian H Chen
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, USA
| | - Alan A Cohen
- Department of Environmental Health Sciences, Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Georg Fuellen
- Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock University Medical Center, Rostock, Germany
- School of Medicine, University College Dublin, Dublin, Ireland
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Martin Widschwendter
- European Translational Oncology Prevention and Screening Institute, Universität Innsbruck, Innsbruck, Austria
- Department of Women's Cancer, EGA Institute for Women's Health, University College London, London, UK
- Department of Women's and Children's Health, Division of Obstetrics and Gynaecology, Karolinska Institutet, Stockholm, Sweden
| | | | | | | | - Nir Barzilai
- Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Jessica Lasky-Su
- Department of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Douglas P Kiel
- Musculoskeletal Research Center, Hinda and Arthur Marcus Institute for Aging Research and Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Brian K Kennedy
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Centre for Healthy Longevity, @AgeSingapore, National University Health System, Singapore, Singapore
| | - Steven Cummings
- San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, CA, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - P Eline Slagboom
- Section of Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Eric Verdin
- Buck Institute for Research on Aging, Novato, CA, USA
| | - Andrea B Maier
- Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Centre for Healthy Longevity, @AgeSingapore, National University Health System, Singapore, Singapore
- Department of Human Movement Sciences, @AgeAmsterdam, Amsterdam Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Vittorio Sebastiano
- Department of Obstetrics and Gynecology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Michael P Snyder
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, USA
| | - Vadim N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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Kocher K, Bhattacharya S, Niforatos-Andescavage N, Almalvez M, Henderson D, Vilain E, Limperopoulos C, Délot EC. Genome-wide neonatal epigenetic changes associated with maternal exposure to the COVID-19 pandemic. BMC Med Genomics 2023; 16:268. [PMID: 37899449 PMCID: PMC10614377 DOI: 10.1186/s12920-023-01707-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 10/17/2023] [Indexed: 10/31/2023] Open
Abstract
BACKGROUND During gestation, stressors to the fetus, including viral exposure or maternal psychological distress, can fundamentally alter the neonatal epigenome, and may be associated with long-term impaired developmental outcomes. The impact of in utero exposure to the COVID-19 pandemic on the newborn epigenome has yet to be described. METHODS This study aimed to determine whether there are unique epigenetic signatures in newborns who experienced otherwise healthy pregnancies that occurred during the COVID-19 pandemic (Project RESCUE). The pre-pandemic control and pandemic cohorts (Project RESCUE) included in this study are part of a prospective observational and longitudinal cohort study that evaluates the impact of elevated prenatal maternal stress during the COVID-19 pandemic on early childhood neurodevelopment. Using buccal swabs collected at birth, differential DNA methylation analysis was performed using the Infinium MethylationEPIC arrays and linear regression analysis. Pathway analysis and gene ontology enrichment were performed on resultant gene lists. RESULTS Widespread differential methylation was found between neonates exposed in utero to the pandemic and pre-pandemic neonates. In contrast, there were no apparent epigenetic differences associated with maternal COVID-19 infection during pregnancy. Differential methylation was observed among genomic sites that underpin important neurological pathways that have been previously reported in the literature to be differentially methylated because of prenatal stress, such as NR3C1. CONCLUSIONS The present study reveals potential associations between exposure to the COVID-19 pandemic during pregnancy and subsequent changes in the newborn epigenome. While this finding warrants further investigation, it is a point that should be considered in any study assessing newborn DNA methylation studies obtained during this period, even in otherwise healthy pregnancies.
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Affiliation(s)
- Kristen Kocher
- Center for Genetic Medicine Research, Children's National Research & Innovation Campus, Washington, DC, USA
- Department of Genomics & Precision Medicine, George Washington University, Washington, DC, USA
| | - Surajit Bhattacharya
- Center for Genetic Medicine Research, Children's National Research & Innovation Campus, Washington, DC, USA
| | | | - Miguel Almalvez
- Institute for Clinical and Translational Science, University of California, Irvine, CA, USA
| | - Diedtra Henderson
- Developing Brain Institute, Children's National Hospital, Washington, DC, USA
| | - Eric Vilain
- Institute for Clinical and Translational Science, University of California, Irvine, CA, USA.
| | | | - Emmanuèle C Délot
- Center for Genetic Medicine Research, Children's National Research & Innovation Campus, Washington, DC, USA.
- Department of Genomics & Precision Medicine, George Washington University, Washington, DC, USA.
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10
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Zhang W, Young JI, Gomez L, Schmidt MA, Lukacsovich D, Varma A, Chen XS, Kunkle B, Martin ER, Wang L. Critical evaluation of the reliability of DNA methylation probes on the Illumina MethylationEPIC BeadChip microarrays. RESEARCH SQUARE 2023:rs.3.rs-3068938. [PMID: 37461726 PMCID: PMC10350239 DOI: 10.21203/rs.3.rs-3068938/v2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
DNA methylation (DNAm) plays a crucial role in a number of complex diseases. However, the reliability of DNAm levels measured using Illumina arrays varies across different probes. Previous research primarily assessed probe reliability by comparing duplicate samples between the 450k-450k or 450k-EPIC platforms, with limited investigations on Illumina EPIC arrays. We conducted a comprehensive assessment of the EPIC array probe reliability using 138 duplicated blood DNAm samples generated by the Alzheimer's Disease Neuroimaging Initiative study. We introduced a novel statistical measure, the modified intraclass correlation, to better account for the disagreement in duplicate measurements. We observed higher reliability in probes with average methylation beta values of 0.2 to 0.8, and lower reliability in type I probes or those within the promoter and CpG island regions. Importantly, we found that probe reliability has significant implications in the analyses of Epigenome-wide Association Studies (EWAS). Higher reliability is associated with more consistent effect sizes in different studies, the identification of differentially methylated regions (DMRs) and methylation quantitative trait locus (mQTLs), and significant correlations with downstream gene expression. Moreover, blood DNAm measurements obtained from probes with higher reliability are more likely to show concordance with brain DNAm measurements. Our findings, which provide crucial reliable information for probes on the EPIC array, will serve as a valuable resource for future DNAm studies.
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Affiliation(s)
- Wei Zhang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Juan I. Young
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Lissette Gomez
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Michael A. Schmidt
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - David Lukacsovich
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Achintya Varma
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - X. Steven Chen
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Brian Kunkle
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Eden R. Martin
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Lily Wang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
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11
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Zhang W, Young JI, Gomez L, Schmidt MA, Lukacsovich D, Varma A, Chen XS, Kunkle B, Martin ER, Wang L. Critical evaluation of the reliability of DNA methylation probes on the Illumina MethylationEPIC BeadChip microarrays. RESEARCH SQUARE 2023:rs.3.rs-3068938. [PMID: 37461726 PMCID: PMC10350239 DOI: 10.21203/rs.3.rs-3068938/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/24/2023]
Abstract
DNA methylation (DNAm) plays a crucial role in a number of complex diseases. However, the reliability of DNAm levels measured using Illumina arrays varies across different probes. Previous research primarily assessed probe reliability by comparing duplicate samples between the 450k-450k or 450k-EPIC platforms, with limited investigations on Illumina EPIC arrays. We conducted a comprehensive assessment of the EPIC array probe reliability using 138 duplicated blood DNAm samples generated by the Alzheimer's Disease Neuroimaging Initiative study. We introduced a novel statistical measure, the modified intraclass correlation, to better account for the disagreement in duplicate measurements. We observed higher reliability in probes with average methylation beta values of 0.2 to 0.8, and lower reliability in type I probes or those within the promoter and CpG island regions. Importantly, we found that probe reliability has significant implications in the analyses of Epigenome-wide Association Studies (EWAS). Higher reliability is associated with more consistent effect sizes in different studies, the identification of differentially methylated regions (DMRs) and methylation quantitative trait locus (mQTLs), and significant correlations with downstream gene expression. Moreover, blood DNAm measurements obtained from probes with higher reliability are more likely to show concordance with brain DNAm measurements. Our findings, which provide crucial reliable information for probes on the EPIC array, will serve as a valuable resource for future DNAm studies.
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Affiliation(s)
- Wei Zhang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Juan I. Young
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Lissette Gomez
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Michael A. Schmidt
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - David Lukacsovich
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Achintya Varma
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - X. Steven Chen
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Brian Kunkle
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Eden R. Martin
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Lily Wang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
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12
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Jedynak P, Broséus L, Tost J, Busato F, Gabet S, Thomsen C, Sakhi AK, Pin I, Slama R, Lepeule J, Philippat C. Prenatal exposure to triclosan assessed in multiple urine samples and placental DNA methylation. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 335:122197. [PMID: 37481027 DOI: 10.1016/j.envpol.2023.122197] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Revised: 07/11/2023] [Accepted: 07/12/2023] [Indexed: 07/24/2023]
Abstract
A previous study reported positive associations of maternal urinary concentrations of triclosan, a synthetic phenol with widespread exposure in the general population, with placental DNA methylation of male fetuses. Given the high number of comparisons performed in -omic research, further studies were needed to validate and extend on these findings. Using a cohort of male and female fetuses with repeated maternal urine samples to assess exposure, we studied the associations between triclosan and placental DNA methylation. We assessed triclosan concentrations in two pools of 21 urine samples collected among 395 women from the SEPAGES cohort. We used Infinium Methylation EPIC arrays to measure DNA methylation in placental biopsies collected at delivery. We performed a candidate study restricted to a set of candidate CpGs (n = 500) identified in a previous work as well as an exploratory epigenome-wide association study to investigate the associations between triclosan and differentially methylated probes and regions. Analyses were conducted on the whole population and stratified by child's sex. Mediation analysis was performed to test whether heterogeneity of placental tissue may mediate the observed associations. In the candidate approach, we confirmed 18 triclosan-associated genes when both sexes were considered. After stratification for child's sex, triclosan was associated with 72 genes in females and three in males. Most of the associations were positive and several CpGs mapped to imprinted genes: FBRSL1, KCNQ1, RHOBTB3, and SMOC1. A mediation effect by placental tissue heterogeneity was identified for most of the observed associations. In the exploratory analysis, we identified a few isolated associations in the sex-stratified analysis. In line with a previous study on male placentas, our approach revealed several positive associations between triclosan exposure and placental DNA methylation. Several identified loci mapped to imprinted genes.
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Affiliation(s)
- Paulina Jedynak
- University Grenoble Alpes, Inserm U 1209, CNRS UMR 5309, Team of Environmental Epidemiology applied to Development and Respiratory Health, Institute for Advanced Biosciences, Grenoble, France
| | - Lucile Broséus
- University Grenoble Alpes, Inserm U 1209, CNRS UMR 5309, Team of Environmental Epidemiology applied to Development and Respiratory Health, Institute for Advanced Biosciences, Grenoble, France
| | - Jörg Tost
- Laboratory for Epigenetics and Environment, Centre National de Recherche en Génomique Humaine, CEA - Institut de Biologie François Jacob, University Paris Saclay, Evry, France
| | - Florence Busato
- Laboratory for Epigenetics and Environment, Centre National de Recherche en Génomique Humaine, CEA - Institut de Biologie François Jacob, University Paris Saclay, Evry, France
| | - Stephan Gabet
- University Grenoble Alpes, Inserm U 1209, CNRS UMR 5309, Team of Environmental Epidemiology applied to Development and Respiratory Health, Institute for Advanced Biosciences, Grenoble, France; University Lille, CHU Lille, Institut Pasteur de Lille, ULR 4483-IMPacts de L'Environnement Chimique sur La Santé (IMPECS), Lille, France
| | - Cathrine Thomsen
- Division of Climate and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Amrit K Sakhi
- Division of Climate and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Isabelle Pin
- University Grenoble Alpes, Inserm U 1209, CNRS UMR 5309, Team of Environmental Epidemiology applied to Development and Respiratory Health, Institute for Advanced Biosciences, Grenoble, France; Pediatric Department, Grenoble Alpes University Hospital, La Tronche, France
| | - Rémy Slama
- University Grenoble Alpes, Inserm U 1209, CNRS UMR 5309, Team of Environmental Epidemiology applied to Development and Respiratory Health, Institute for Advanced Biosciences, Grenoble, France
| | - Johanna Lepeule
- University Grenoble Alpes, Inserm U 1209, CNRS UMR 5309, Team of Environmental Epidemiology applied to Development and Respiratory Health, Institute for Advanced Biosciences, Grenoble, France.
| | - Claire Philippat
- University Grenoble Alpes, Inserm U 1209, CNRS UMR 5309, Team of Environmental Epidemiology applied to Development and Respiratory Health, Institute for Advanced Biosciences, Grenoble, France
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13
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Gupta MK, Peng H, Li Y, Xu CJ. The role of DNA methylation in personalized medicine for immune-related diseases. Pharmacol Ther 2023; 250:108508. [PMID: 37567513 DOI: 10.1016/j.pharmthera.2023.108508] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 08/03/2023] [Accepted: 08/08/2023] [Indexed: 08/13/2023]
Abstract
Epigenetics functions as a bridge between host genetic & environmental factors, aiding in human health and diseases. Many immune-related diseases, including infectious and allergic diseases, have been linked to epigenetic mechanisms, particularly DNA methylation. In this review, we summarized an updated overview of DNA methylation and its importance in personalized medicine, and demonstrated that DNA methylation has excellent potential for disease prevention, diagnosis, and treatment in a personalized manner. The future implications and limitations of the DNA methylation study have also been well-discussed.
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Affiliation(s)
- Manoj Kumar Gupta
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany; TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - He Peng
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany; TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - Yang Li
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany; TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany; Department of Internal Medicine and Radboud Institute for Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Cheng-Jian Xu
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany; TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany; Department of Internal Medicine and Radboud Institute for Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.
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14
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Kadalayil L, Alam MZ, White CH, Ghantous A, Walton E, Gruzieva O, Merid SK, Kumar A, Roy RP, Solomon O, Huen K, Eskenazi B, Rzehak P, Grote V, Langhendries JP, Verduci E, Ferre N, Gruszfeld D, Gao L, Guan W, Zeng X, Schisterman EF, Dou JF, Bakulski KM, Feinberg JI, Soomro MH, Pesce G, Baiz N, Isaevska E, Plusquin M, Vafeiadi M, Roumeliotaki T, Langie SAS, Standaert A, Allard C, Perron P, Bouchard L, van Meel ER, Felix JF, Jaddoe VWV, Yousefi PD, Ramlau-Hansen CH, Relton CL, Tobi EW, Starling AP, Yang IV, Llambrich M, Santorelli G, Lepeule J, Salas LA, Bustamante M, Ewart SL, Zhang H, Karmaus W, Röder S, Zenclussen AC, Jin J, Nystad W, Page CM, Magnus M, Jima DD, Hoyo C, Maguire RL, Kvist T, Czamara D, Räikkönen K, Gong T, Ullemar V, Rifas-Shiman SL, Oken E, Almqvist C, Karlsson R, Lahti J, Murphy SK, Håberg SE, London S, Herberth G, Arshad H, Sunyer J, Grazuleviciene R, Dabelea D, Steegers-Theunissen RPM, Nohr EA, Sørensen TIA, Duijts L, Hivert MF, Nelen V, Popovic M, Kogevinas M, Nawrot TS, Herceg Z, Annesi-Maesano I, Fallin MD, Yeung E, Breton CV, Koletzko B, Holland N, Wiemels JL, Melén E, Sharp GC, Silver MJ, Rezwan FI, Holloway JW. Analysis of DNA methylation at birth and in childhood reveals changes associated with season of birth and latitude. Clin Epigenetics 2023; 15:148. [PMID: 37697338 PMCID: PMC10496224 DOI: 10.1186/s13148-023-01542-5] [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: 02/13/2023] [Accepted: 07/27/2023] [Indexed: 09/13/2023] Open
Abstract
BACKGROUND Seasonal variations in environmental exposures at birth or during gestation are associated with numerous adult traits and health outcomes later in life. Whether DNA methylation (DNAm) plays a role in the molecular mechanisms underlying the associations between birth season and lifelong phenotypes remains unclear. METHODS We carried out epigenome-wide meta-analyses within the Pregnancy And Childhood Epigenetic Consortium to identify associations of DNAm with birth season, both at differentially methylated probes (DMPs) and regions (DMRs). Associations were examined at two time points: at birth (21 cohorts, N = 9358) and in children aged 1-11 years (12 cohorts, N = 3610). We conducted meta-analyses to assess the impact of latitude on birth season-specific associations at both time points. RESULTS We identified associations between birth season and DNAm (False Discovery Rate-adjusted p values < 0.05) at two CpGs at birth (winter-born) and four in the childhood (summer-born) analyses when compared to children born in autumn. Furthermore, we identified twenty-six differentially methylated regions (DMR) at birth (winter-born: 8, spring-born: 15, summer-born: 3) and thirty-two in childhood (winter-born: 12, spring and summer: 10 each) meta-analyses with few overlapping DMRs between the birth seasons or the two time points. The DMRs were associated with genes of known functions in tumorigenesis, psychiatric/neurological disorders, inflammation, or immunity, amongst others. Latitude-stratified meta-analyses [higher (≥ 50°N), lower (< 50°N, northern hemisphere only)] revealed differences in associations between birth season and DNAm by birth latitude. DMR analysis implicated genes with previously reported links to schizophrenia (LAX1), skin disorders (PSORS1C, LTB4R), and airway inflammation including asthma (LTB4R), present only at birth in the higher latitudes (≥ 50°N). CONCLUSIONS In this large epigenome-wide meta-analysis study, we provide evidence for (i) associations between DNAm and season of birth that are unique for the seasons of the year (temporal effect) and (ii) latitude-dependent variations in the seasonal associations (spatial effect). DNAm could play a role in the molecular mechanisms underlying the effect of birth season on adult health outcomes.
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Affiliation(s)
- Latha Kadalayil
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton General Hospital, Southampton, UK
| | - Md Zahangir Alam
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton General Hospital, Southampton, UK
- Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
| | - Cory Haley White
- Merck Exploratory Science Center in Cambridge MA, Merck Research Laboratories, Cambridge, MA, 02141, USA
| | - Akram Ghantous
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer, Lyon, France
| | - Esther Walton
- Department of Psychology, University of Bath, Bath, UK
| | - Olena Gruzieva
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Centre for Occupational and Environmental Medicine, Region Stockholm, Sweden
| | - Simon Kebede Merid
- Centre for Occupational and Environmental Medicine, Region Stockholm, Sweden
| | - Ashish Kumar
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
| | - Ritu P Roy
- Helen Diller Family Comprehensive Cancer Center University of California, San Francisco, CA, 94143, USA
- Computational Biology and Informatics Core, University of California, San Francisco, CA, 94143, USA
| | - Olivia Solomon
- Children's Environmental Health Laboratory, University of California, Berkeley, CA, USA
| | - Karen Huen
- Children's Environmental Health Laboratory, University of California, Berkeley, CA, USA
| | - Brenda Eskenazi
- Children's Environmental Health Laboratory, University of California, Berkeley, CA, USA
| | - Peter Rzehak
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - Veit Grote
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | | | - Elvira Verduci
- Department of Pediatrics, Vittore Buzzi Children Hospital, University of Milan, Milan, Italy
| | - Natalia Ferre
- Pediatric Nutrition and Human Development Research Unit, Universitat Rovira i Virgili, IISPV, Reus, Spain
| | - Darek Gruszfeld
- Neonatal Department, Children's Memorial Health Institute, Warsaw, Poland
| | - Lu Gao
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA
| | - Weihua Guan
- Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, MMC 303, 420 Delaware St. SE, Minneapolis, MN, 55455, USA
| | | | - Enrique F Schisterman
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Drive, Philadelphia, PA, 19104, USA
| | - John F Dou
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, USA
| | - Kelly M Bakulski
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, USA
| | - Jason I Feinberg
- Wendy Klag Center for Autism and Developmental Disabilities Johns Hopkins University, Baltimore, MD, USA
- Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Munawar Hussain Soomro
- Sorbonne Université and INSERM, Epidemiology of Allergic and Respiratory Diseases Department, Pierre Louis Institute of Epidemiology and Public Health (IPLESP UMRS 1136), Saint-Antoine Medical School, Paris Cedex 12, France
- Department of Community Medicine and Public Health, SMBB Medical University, Larkana, Pakistan
| | - Giancarlo Pesce
- Sorbonne Université and INSERM, Epidemiology of Allergic and Respiratory Diseases Department, Pierre Louis Institute of Epidemiology and Public Health (IPLESP UMRS 1136), Saint-Antoine Medical School, Paris Cedex 12, France
| | - Nour Baiz
- Institut Desbrest de Santé Publique (IDESP), INSERM and Montpellier University, Montpellier, France
| | - Elena Isaevska
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, CPO Piemonte, Italy
| | - Michelle Plusquin
- Center for Environmental Sciences, University of Hasselt, 3590, Diepenbeek, Belgium
| | - Marina Vafeiadi
- Department of Social Medicine, School of Medicine, University of Crete, Heraklion, Greece
| | - Theano Roumeliotaki
- Department of Social Medicine, School of Medicine, University of Crete, Heraklion, Greece
| | - Sabine A S Langie
- Unit Health, Flemish Institute for Technological Research (VITO), Mol, Belgium
- Faculty of Sciences, Hasselt University, Diepenbeek, Belgium
- Department of Pharmacology and Toxicology, School for Nutrition and Translational Research in Metabolism (NUTRIM), Maastricht University, Limburg, The Netherlands
| | - Arnout Standaert
- Unit Health, Flemish Institute for Technological Research (VITO), Mol, Belgium
| | - Catherine Allard
- Centre de Recherche du Centre Hospitalier de l'Universite de Sherbrooke, Sherbrooke, Canada
| | - Patrice Perron
- Department of Medicine, Universite de Sherbrooke, Sherbrooke, Canada
| | - Luigi Bouchard
- Department of Biochemistry and Functional Genomics, Universite de Sherbrooke, Sherbrooke, Canada
- Clinical Department of Laboratory Medicine, Centre intégré universitaire de santé et de services sociaux (CIUSSS) du Saguenay-Lac-Saint-Jean - Hôpital de Chicoutimi, Chicoutimi, Canada
| | - Evelien R van Meel
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Division of Respiratory Medicine and Allergology, Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Janine F Felix
- The 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
| | - Vincent W V Jaddoe
- The 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
| | - Paul D Yousefi
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | | | - Caroline L Relton
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Elmar W Tobi
- Periconceptional Epidemiology, Department of Obstetrics and Gynecology, Erasmus MC, University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Anne P Starling
- Life Course Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ivana V Yang
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Center for Genes, Environment and Health, National Jewish Health, Denver, CO, USA
| | - Maria Llambrich
- Institute for Global Health (ISGlobal), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | | | - Johanna Lepeule
- Institute for Advanced Biosciences, University Grenoble-Alpes, INSERM, CNRS, Grenoble, France
| | - Lucas A Salas
- Institute for Global Health (ISGlobal), Barcelona, Spain
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA
- Center for Molecular Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA
- Children's Environmental Health and Disease Prevention Research Center at Dartmouth, Lebanon, NH, USA
| | - Mariona Bustamante
- Institute for Global Health (ISGlobal), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Susan L Ewart
- Department of Large Animal Clinical Sciences, College of Veterinary Medicine, Michigan State University, East Lansing, MI, USA
| | - Hongmei Zhang
- Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, USA
| | - Wilfried Karmaus
- Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, USA
| | - Stefan Röder
- Department of Environmental Immunology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Ana Claudia Zenclussen
- Department of Environmental Immunology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Jianping Jin
- 2530 Meridian Pkwy, Suite 200, Durham, NC 27713, USA
| | - Wenche Nystad
- Department of Chronic Diseases and Ageing, Norwegian Institute of Public Health, Oslo, Norway
| | - Christian M Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Section for Statistics and Data Science, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
| | - Maria Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Dereje D Jima
- Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, USA
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA
| | - Cathrine Hoyo
- Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, USA
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
| | - Rachel L Maguire
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
- Department of Obstetrics and Gynaecology, Duke University Medical Center, Durham, NC, USA
| | - Tuomas Kvist
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Darina Czamara
- Department of Translational Research in Psychiatry, Max-Planck-Institute of Psychiatry, 80804, Munich, Germany
| | - Katri Räikkönen
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Tong Gong
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Vilhelmina Ullemar
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sheryl L Rifas-Shiman
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, USA
| | - Emily Oken
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, USA
| | - Catarina Almqvist
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Pediatric Allergy and Pulmonology Unit at Astrid Lindgren Children's Hospital, Karolinska University Hospital, Stockholm, Sweden
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jari Lahti
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Susan K Murphy
- Department of Obstetrics and Gynaecology, Duke University Medical Center, Durham, NC, USA
| | - Siri E Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Stephanie London
- Department of Health and Human Services, National Institute of Environmental Health Sciences, National Institutes of Health, RTP, NC, 27709, USA
| | - Gunda Herberth
- Department of Environmental Immunology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Hasan Arshad
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
- David Hide Asthma and Allergy Research Centre, Isle of Wight, UK
- NIHR Southampton Biomedical Research Centre, Southampton General Hospital, Southampton, UK
| | - Jordi Sunyer
- Institute for Global Health (ISGlobal), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Regina Grazuleviciene
- Department of Environmental Science, Vytautas Magnus University, 44248, Kaunas, Lithuania
| | - Dana Dabelea
- Life Course Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Pediatrics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Régine P M Steegers-Theunissen
- Periconceptional Epidemiology, Department of Obstetrics and Gynecology, Erasmus MC, University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Ellen A Nohr
- Department of Clinical Research, Odense Universitetshospital, Odense, Denmark
| | - Thorkild I A Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Liesbeth Duijts
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Division of Respiratory Medicine and Allergology, Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Division of Neonatology, Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Vera Nelen
- Provincial Institute for Hygiene, Antwerp, Belgium
| | - Maja Popovic
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, CPO Piemonte, Italy
| | | | - Tim S Nawrot
- Center for Environmental Sciences, University of Hasselt, 3590, Diepenbeek, Belgium
- Department of Public Health and Primary Care, Leuven University, Louvain, Belgium
| | - Zdenko Herceg
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer, Lyon, France
| | - Isabella Annesi-Maesano
- Institut Desbrest de Santé Publique (IDESP), INSERM and Montpellier University, Montpellier, France
| | - M Daniele Fallin
- Wendy Klag Center for Autism and Developmental Disabilities Johns Hopkins University, Baltimore, MD, USA
- Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Edwina Yeung
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, 6710B Rockledge Dr, MSC 7004, Bethesda, MD, USA
| | - Carrie V Breton
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA
| | - Berthold Koletzko
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - Nina Holland
- Children's Environmental Health Laboratory, CERCH, Berkeley Public Health, University of California, 2121 Berkeley Way #5216, Berkeley, CA, 94720, USA
| | - Joseph L Wiemels
- Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, 90033, USA
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, 90033, USA
| | - Erik Melén
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
- Sachs' Children and Youth Hospital, Södersjukhuset, Stockholm, Sweden
| | - Gemma C Sharp
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Psychology, University of Exeter, Exeter, UK
| | - Matt J Silver
- Medical Research Council Unit, The Gambia at the London School of Hygiene and Tropical Medicine, Fajara, The Gambia
- Medical Research Council Unit, The Gambia at the London School of Hygiene and Tropical Medicine, London, UK
| | - Faisal I Rezwan
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton General Hospital, Southampton, UK
- Department of Computer Science, Aberystwyth University, Aberystwyth, Ceredigion, UK
| | - John W Holloway
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton General Hospital, Southampton, UK.
- NIHR Southampton Biomedical Research Centre, Southampton General Hospital, Southampton, UK.
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15
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Recto K, Kachroo P, Huan T, Van Den Berg D, Lee GY, Bui H, Lee DH, Gereige J, Yao C, Hwang SJ, Joehanes R, Weiss ST, O'Connor GT, Levy D, DeMeo DL. Epigenome-wide DNA methylation association study of circulating IgE levels identifies novel targets for asthma. EBioMedicine 2023; 95:104758. [PMID: 37598461 PMCID: PMC10462855 DOI: 10.1016/j.ebiom.2023.104758] [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: 03/14/2023] [Revised: 08/01/2023] [Accepted: 08/02/2023] [Indexed: 08/22/2023] Open
Abstract
BACKGROUND Identifying novel epigenetic signatures associated with serum immunoglobulin E (IgE) may improve our understanding of molecular mechanisms underlying asthma and IgE-mediated diseases. METHODS We performed an epigenome-wide association study using whole blood from Framingham Heart Study (FHS; n = 3,471, 46% females) participants and validated results using the Childhood Asthma Management Program (CAMP; n = 674, 39% females) and the Genetic Epidemiology of Asthma in Costa Rica Study (CRA; n = 787, 41% females). Using the closest gene to each IgE-associated CpG, we highlighted biologically plausible pathways underlying IgE regulation and analyzed the transcription patterns linked to IgE-associated CpGs (expression quantitative trait methylation loci; eQTMs). Using prior UK Biobank summary data from genome-wide association studies of asthma and allergy, we performed Mendelian randomization (MR) for causal inference testing using the IgE-associated CpGs from FHS with methylation quantitative trait loci (mQTLs) as instrumental variables. FINDINGS We identified 490 statistically significant differentially methylated CpGs associated with IgE in FHS, of which 193 (39.3%) replicated in CAMP and CRA (FDR < 0.05). Gene ontology analysis revealed enrichment in pathways related to transcription factor binding, asthma, and other immunological processes. eQTM analysis identified 124 cis-eQTMs for 106 expressed genes (FDR < 0.05). MR in combination with drug-target analysis revealed CTSB and USP20 as putatively causal regulators of IgE levels (Bonferroni adjusted P < 7.94E-04) that can be explored as potential therapeutic targets. INTERPRETATION By integrating eQTM and MR analyses in general and clinical asthma populations, our findings provide a deeper understanding of the multidimensional inter-relations of DNA methylation, gene expression, and IgE levels. FUNDING US NIH/NHLBI grants: P01HL132825, K99HL159234. N01-HC-25195 and HHSN268201500001I.
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Affiliation(s)
- Kathryn Recto
- The Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA; The Framingham Heart Study, Framingham, MA 01702, USA
| | - Priyadarshini Kachroo
- Brigham and Women's Hospital, Channing Division of Network Medicine, Boston, MA 02115, USA
| | - Tianxiao Huan
- The Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA; The Framingham Heart Study, Framingham, MA 01702, USA
| | - David Van Den Berg
- University of Southern California Methylation Characterization Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Gha Young Lee
- The Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA; The Framingham Heart Study, Framingham, MA 01702, USA
| | - Helena Bui
- The Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA; The Framingham Heart Study, Framingham, MA 01702, USA
| | - Dong Heon Lee
- The Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA; The Framingham Heart Study, Framingham, MA 01702, USA
| | - Jessica Gereige
- Boston University School of Medicine, Pulmonary Center, Boston, MA 02118, USA
| | - Chen Yao
- The Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA; The Framingham Heart Study, Framingham, MA 01702, USA
| | - Shih-Jen Hwang
- The Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA; The Framingham Heart Study, Framingham, MA 01702, USA
| | - Roby Joehanes
- The Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA; The Framingham Heart Study, Framingham, MA 01702, USA
| | - Scott T Weiss
- Brigham and Women's Hospital, Channing Division of Network Medicine, Boston, MA 02115, USA
| | - George T O'Connor
- The Framingham Heart Study, Framingham, MA 01702, USA; Boston University School of Medicine, Pulmonary Center, Boston, MA 02118, USA
| | - Daniel Levy
- The Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA; The Framingham Heart Study, Framingham, MA 01702, USA.
| | - Dawn L DeMeo
- Brigham and Women's Hospital, Channing Division of Network Medicine, Boston, MA 02115, USA.
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16
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Khodasevich D, Holland N, Hubbard A, Harley K, Deardorff J, Eskenazi B, Cardenas A. Associations between prenatal phthalate exposure and childhood epigenetic age acceleration. ENVIRONMENTAL RESEARCH 2023; 231:116067. [PMID: 37149020 PMCID: PMC10330458 DOI: 10.1016/j.envres.2023.116067] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 03/06/2023] [Accepted: 05/04/2023] [Indexed: 05/08/2023]
Abstract
BACKGROUND Phthalates, a group of pervasive endocrine-disrupting chemicals found in plastics and personal care products, have been associated with a wide range of developmental and health outcomes. However, their impact on biomarkers of aging has not been characterized. We tested associations between prenatal exposure to 11 phthalate metabolites on epigenetic aging in children at birth, 7, 9, and 14 years of age. We hypothesized that prenatal phthalate exposure will be associated with epigenetic age acceleration measures at birth and in early childhood, with patterns dependent on sex and timing of DNAm measurement. METHODS Among 385 mother-child pairs from the CHAMACOS cohort, we measured DNAm at birth, 7, 9, and 14 years of age, and utilized adjusted linear regression to assess the association between prenatal phthalate exposure and Bohlin's Gestational Age Acceleration (GAA) at birth and Intrinsic Epigenetic Age Acceleration (IEAA) throughout childhood. Additionally, quantile g-computation was utilized to assess the effect of the phthalate mixture on GAA at birth and IEAA throughout childhood. RESULTS We found a negative association between prenatal di (2-ethylhexyl) phthalate (DEHP) exposure and IEAA among males at age 7 (-0.62 years; 95% CI:-1.06 to -0.18), and a marginal negative association between the whole phthalate mixture and GAA among males at birth (-1.54 days, 95% CI: -2.79 to -0.28), while most other associations were nonsignificant. CONCLUSIONS Our results suggest that prenatal exposure to certain phthalates is associated with epigenetic aging in children. Additionally, our findings suggest that the influence of prenatal exposures on epigenetic age may only manifest during specific periods of child development, and studies relying on DNAm measurements solely from cord blood or single time points may overlook potential relationships.
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Affiliation(s)
- Dennis Khodasevich
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA; Center for Computational Biology, University of California, Berkeley, CA, USA
| | - Nina Holland
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA; Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California, Berkeley, Berkeley, CA, USA
| | - Alan Hubbard
- Division of Biostatistics, School of Public Health, University of California, Berkeley, CA, USA
| | - Kim Harley
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California, Berkeley, Berkeley, CA, USA
| | - Julianna Deardorff
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California, Berkeley, Berkeley, CA, USA; Division of Community Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
| | - Brenda Eskenazi
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California, Berkeley, Berkeley, CA, USA
| | - Andres Cardenas
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA.
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17
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Wang SS, Lewis MJ, Pitzalis C. DNA Methylation Signatures of Response to Conventional Synthetic and Biologic Disease-Modifying Antirheumatic Drugs (DMARDs) in Rheumatoid Arthritis. Biomedicines 2023; 11:1987. [PMID: 37509625 PMCID: PMC10377185 DOI: 10.3390/biomedicines11071987] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 07/03/2023] [Accepted: 07/11/2023] [Indexed: 07/30/2023] Open
Abstract
Rheumatoid arthritis (RA) is a complex condition that displays heterogeneity in disease severity and response to standard treatments between patients. Failure rates for conventional, target synthetic, and biologic disease-modifying rheumatic drugs (DMARDs) are significant. Although there are models for predicting patient response, they have limited accuracy, require replication/validation, or for samples to be obtained through a synovial biopsy. Thus, currently, there are no prediction methods approved for routine clinical use. Previous research has shown that genetics and environmental factors alone cannot explain the differences in response between patients. Recent studies have demonstrated that deoxyribonucleic acid (DNA) methylation plays an important role in the pathogenesis and disease progression of RA. Importantly, specific DNA methylation profiles associated with response to conventional, target synthetic, and biologic DMARDs have been found in the blood of RA patients and could potentially function as predictive biomarkers. This review will summarize and evaluate the evidence for DNA methylation signatures in treatment response mainly in blood but also learn from the progress made in the diseased tissue in cancer in comparison to RA and autoimmune diseases. We will discuss the benefits and challenges of using DNA methylation signatures as predictive markers and the potential for future progress in this area.
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Affiliation(s)
- Susan Siyu Wang
- Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Queen Mary University of London and Barts Health NIHR BRC & NHS Trust, London EC1M 6BQ, UK
| | - Myles J Lewis
- Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Queen Mary University of London and Barts Health NIHR BRC & NHS Trust, London EC1M 6BQ, UK
| | - Costantino Pitzalis
- Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Queen Mary University of London and Barts Health NIHR BRC & NHS Trust, London EC1M 6BQ, UK
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18
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Schneider L, Wies C, Krieghoff-Henning EI, Bucher TC, Utikal JS, Schadendorf D, Brinker TJ. Multimodal integration of image, epigenetic and clinical data to predict BRAF mutation status in melanoma. Eur J Cancer 2023; 183:131-138. [PMID: 36854237 DOI: 10.1016/j.ejca.2023.01.021] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 01/20/2023] [Accepted: 01/25/2023] [Indexed: 02/05/2023]
Abstract
BACKGROUND In machine learning, multimodal classifiers can provide more generalised performance than unimodal classifiers. In clinical practice, physicians usually also rely on a range of information from different examinations for diagnosis. In this study, we used BRAF mutation status prediction in melanoma as a model system to analyse the contribution of different data types in a combined classifier because BRAF status can be determined accurately by sequencing as the current gold standard, thus nearly eliminating label noise. METHODS We trained a deep learning-based classifier by combining individually trained random forests of image, clinical and methylation data to predict BRAF-V600 mutation status in primary and metastatic melanomas of The Cancer Genome Atlas cohort. RESULTS With our multimodal approach, we achieved an area under the receiver operating characteristic curve of 0.80, whereas the individual classifiers yielded areas under the receiver operating characteristic curve of 0.63 (histopathologic image data), 0.66 (clinical data) and 0.66 (methylation data) on an independent data set. CONCLUSIONS Our combined approach can predict BRAF status to some extent by identifying BRAF-V600 specific patterns at the histologic, clinical and epigenetic levels. The multimodal classifiers have improved generalisability in predicting BRAF mutation status.
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Affiliation(s)
- Lucas Schneider
- Digital Biomarkers for Oncology Group, German Cancer Research Centre (DKFZ), Heidelberg, Germany
| | - Christoph Wies
- Digital Biomarkers for Oncology Group, German Cancer Research Centre (DKFZ), Heidelberg, Germany
| | - Eva I Krieghoff-Henning
- Digital Biomarkers for Oncology Group, German Cancer Research Centre (DKFZ), Heidelberg, Germany
| | - Tabea-Clara Bucher
- Digital Biomarkers for Oncology Group, German Cancer Research Centre (DKFZ), Heidelberg, Germany
| | - Jochen S Utikal
- Skin Cancer Unit, German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Dermatology, Venereology and Allergology, University Medical Center Mannheim, Ruprecht-Karl University of Heidelberg, Mannheim, Germany; DKFZ Hector Cancer Institute at the University Medical Center Mannheim, Mannheim, Germany
| | - Dirk Schadendorf
- Department of Dermatology, University Hospital Essen, Essen, Germany
| | - Titus J Brinker
- Digital Biomarkers for Oncology Group, German Cancer Research Centre (DKFZ), Heidelberg, Germany.
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Welsh H, Batalha CMPF, Li W, Mpye KL, Souza-Pinto NC, Naslavsky MS, Parra EJ. A systematic evaluation of normalization methods and probe replicability using infinium EPIC methylation data. Clin Epigenetics 2023; 15:41. [PMID: 36906598 PMCID: PMC10008016 DOI: 10.1186/s13148-023-01459-z] [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: 10/10/2022] [Accepted: 02/24/2023] [Indexed: 03/13/2023] Open
Abstract
BACKGROUND The Infinium EPIC array measures the methylation status of > 850,000 CpG sites. The EPIC BeadChip uses a two-array design: Infinium Type I and Type II probes. These probe types exhibit different technical characteristics which may confound analyses. Numerous normalization and pre-processing methods have been developed to reduce probe type bias as well as other issues such as background and dye bias. METHODS This study evaluates the performance of various normalization methods using 16 replicated samples and three metrics: absolute beta-value difference, overlap of non-replicated CpGs between replicate pairs, and effect on beta-value distributions. Additionally, we carried out Pearson's correlation and intraclass correlation coefficient (ICC) analyses using both raw and SeSAMe 2 normalized data. RESULTS The method we define as SeSAMe 2, which consists of the application of the regular SeSAMe pipeline with an additional round of QC, pOOBAH masking, was found to be the best performing normalization method, while quantile-based methods were found to be the worst performing methods. Whole-array Pearson's correlations were found to be high. However, in agreement with previous studies, a substantial proportion of the probes on the EPIC array showed poor reproducibility (ICC < 0.50). The majority of poor performing probes have beta values close to either 0 or 1, and relatively low standard deviations. These results suggest that probe reliability is largely the result of limited biological variation rather than technical measurement variation. Importantly, normalizing the data with SeSAMe 2 dramatically improved ICC estimates, with the proportion of probes with ICC values > 0.50 increasing from 45.18% (raw data) to 61.35% (SeSAMe 2).
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Affiliation(s)
- H Welsh
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, Canada.
| | - C M P F Batalha
- Department of Biochemistry, University of São Paulo, São Paulo, Brazil
| | - W Li
- The Centre for Applied Genomics, Hospital for Sick Children, Toronto, Canada
| | - K L Mpye
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, Canada
| | - N C Souza-Pinto
- Department of Biochemistry, University of São Paulo, São Paulo, Brazil
| | - M S Naslavsky
- Department of Genetics and Evolutionary Biology, University of São Paulo, São Paulo, Brazil
| | - E J Parra
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, Canada
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20
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Rijlaarsdam J, Cosin-Tomas M, Schellhas L, Abrishamcar S, Malmberg A, Neumann A, Felix JF, Sunyer J, Gutzkow KB, Grazuleviciene R, Wright J, Kampouri M, Zar HJ, Stein DJ, Heinonen K, Räikkönen K, Lahti J, Hüls A, Caramaschi D, Alemany S, Cecil CAM. DNA methylation and general psychopathology in childhood: an epigenome-wide meta-analysis from the PACE consortium. Mol Psychiatry 2023; 28:1128-1136. [PMID: 36385171 PMCID: PMC7614743 DOI: 10.1038/s41380-022-01871-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 10/25/2022] [Accepted: 11/02/2022] [Indexed: 11/17/2022]
Abstract
The general psychopathology factor (GPF) has been proposed as a way to capture variance shared between psychiatric symptoms. Despite a growing body of evidence showing both genetic and environmental influences on GPF, the biological mechanisms underlying these influences remain unclear. In the current study, we conducted epigenome-wide meta-analyses to identify both probe- and region-level associations of DNA methylation (DNAm) with school-age general psychopathology in six cohorts from the Pregnancy And Childhood Epigenetics (PACE) Consortium. DNAm was examined both at birth (cord blood; prospective analysis) and during school-age (peripheral whole blood; cross-sectional analysis) in total samples of N = 2178 and N = 2190, respectively. At school-age, we identified one probe (cg11945228) located in the Bromodomain-containing protein 2 gene (BRD2) that negatively associated with GPF (p = 8.58 × 10-8). We also identified a significant differentially methylated region (DMR) at school-age (p = 1.63 × 10-8), implicating the SHC Adaptor Protein 4 (SHC4) gene and the EP300-interacting inhibitor of differentiation 1 (EID1) gene that have been previously implicated in multiple types of psychiatric disorders in adulthood, including obsessive compulsive disorder, schizophrenia, and major depressive disorder. In contrast, no prospective associations were identified with DNAm at birth. Taken together, results of this study revealed some evidence of an association between DNAm at school-age and GPF. Future research with larger samples is needed to further assess DNAm variation associated with GPF.
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Affiliation(s)
- Jolien Rijlaarsdam
- Department of Child and Adolescent Psychiatry/ Psychology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Marta Cosin-Tomas
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain.
- Universitat Pompeu Fabra, Barcelona, Spain.
- Centro de investigación biomédica en red en epidemiología y salud pública (ciberesp), Madrid, Spain.
| | - Laura Schellhas
- School of Psychological Science, MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Institute for Sex Research, Sexual Medicine and Forensic Psychiatry, University Medical Center Hamburg, Eppendorf, Germany
| | - Sarina Abrishamcar
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Anni Malmberg
- Department of Psychology & Logopedics, University of Helsinki, Helsinki, Finland
| | | | - Janine F Felix
- The 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
| | - Jordi Sunyer
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- Centro de investigación biomédica en red en epidemiología y salud pública (ciberesp), Madrid, Spain
| | - Kristine B Gutzkow
- Division of Climate and Environmental Health, Norwegian Institute of Public Health (NIPH), Oslo, Norway
| | - Regina Grazuleviciene
- Department of Environmental Science, Vytautas Magnus University, 44248, Kaunas, Lithuania
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Mariza Kampouri
- Department of Social Medicine, University of Crete, Crete, Greece
| | - Heather J Zar
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa
- South African Medical Research Council (SAMRC) Unit on Child and Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - Dan J Stein
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
- South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Kati Heinonen
- Department of Psychology & Logopedics, University of Helsinki, Helsinki, Finland
- Psychology/ Welfare Sciences, Faculty of Social Sciences, Tampere University, Tampere, Finland
| | - Katri Räikkönen
- Department of Psychology & Logopedics, University of Helsinki, Helsinki, Finland
| | - Jari Lahti
- Department of Psychology & Logopedics, University of Helsinki, Helsinki, Finland
| | - Anke Hüls
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Doretta Caramaschi
- Medical Research Council Integrative Epidemiology Unit, Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
- Department of Psychology, , University of Exeter, Exeter, UK
| | - Silvia Alemany
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Spain
| | - Charlotte A M Cecil
- Department of Child and Adolescent Psychiatry/ Psychology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.
- 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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21
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Martin EM, Grimm SA, Xu Z, Taylor JA, Wade PA. Beadchip technology to detect DNA methylation in mouse faithfully recapitulates whole-genome bisulfite sequencing. Epigenomics 2023; 15:115-129. [PMID: 37020391 PMCID: PMC10131490 DOI: 10.2217/epi-2023-0034] [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: 02/01/2023] [Accepted: 03/15/2023] [Indexed: 04/07/2023] Open
Abstract
Aim: To facilitate wide-scale implementation of Illumina Mouse Methylation BeadChip (MMB) technology, array-based measurement of cytosine methylation was compared with the gold-standard assessment of DNA methylation by whole-genome bisulfite sequencing (WGBS). Methods: DNA methylation across two mouse strains (C57B6 and C3H) and both sexes was assessed using the MMB and compared with previously existing deep-coverage WGBS of mice of the same strain and sex. Results & conclusion: The findings demonstrated that 93.3-99.2% of sites had similar measurements of methylation across technologies and that differentially methylated cytosines and regions identified by each technology overlap and enrich for similar biological functions, suggesting that the MMB faithfully recapitulates the findings of WGBS.
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Affiliation(s)
- Elizabeth M Martin
- Epigenetics & Stem Cell Biology Laboratory, National Institute of Environmental Health Science, Research Triangle Park, NC 27713, USA
| | - Sara A Grimm
- Integrative Bioinformatics, Biostatistics & Computational Biology Branch, National Institute of Environmental Health Science, Research Triangle Park, NC 27713, USA
| | - Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Science, Research Triangle Park, NC 27713, USA
| | - Jack A Taylor
- Epigenetics & Stem Cell Biology Laboratory, National Institute of Environmental Health Science, Research Triangle Park, NC 27713, USA
- Epidemiology Branch, National Institute of Environmental Health Science, Research Triangle Park, NC 27713, USA
| | - Paul A Wade
- Epigenetics & Stem Cell Biology Laboratory, National Institute of Environmental Health Science, Research Triangle Park, NC 27713, USA
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22
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Alfano R, Bijnens E, Langie SAS, Nawrot TS, Reimann B, Vanbrabant K, Wang C, Plusquin M. Epigenome-wide analysis of maternal exposure to green space during gestation and cord blood DNA methylation in the ENVIRONAGE cohort. ENVIRONMENTAL RESEARCH 2023; 216:114828. [PMID: 36400229 PMCID: PMC9760568 DOI: 10.1016/j.envres.2022.114828] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 11/10/2022] [Accepted: 11/14/2022] [Indexed: 06/05/2023]
Abstract
BACKGROUND DNA methylation programming is sensitive to prenatal life environmental influences, but the impact of maternal exposure to green space on newborns DNA methylation has not been studied yet. METHODS We conducted a meta-epigenome-wide association study (EWAS) of maternal exposure to green space during gestation with cord blood DNA methylation in two subsets of the ENVIRONAGE cohort (N = 538). Cord blood DNA methylation was measured by Illumina HumanMethylation 450K in one subset (N = 189) and EPICarray in another (N = 349). High (vegetation height>3 m (m)), low (vegetation height<3 m) and total (including both) high-resolution green space exposures during pregnancy were estimated within 100 m and 1000 m distance around maternal residence. In each subset, we sought cytosine-phosphate-guanine (CpG) sites via linear mixed models adjusted on newborns' sex, ethnicity, gestational age, season at delivery, sampling day, maternal parity, age, smoking, education, and estimated blood cell proportions. EWASs results were meta-analysed via fixed-effects meta-analyses. Differentially methylated regions (DMRs) were identified via ENmix-combp and DMRcate algorithms. Sensitivity analyses were additionally adjusted on PM2.5, distance to major roads, urbanicity and neighborhood income. In the 450K subset, cord blood expression of differentially methylated genes was measured by Agilent microarrays and associated with green space. RESULTS 147 DMRs were identified, 85 of which were still significant upon adjustment for PM2.5, distance to major roads, urbanicity and neighborhood income, including HLA-DRB5, RPTOR, KCNQ1DN, A1BG-AS1, HTR2A, ZNF274, COL11A1 and PRSS36 DMRs. One CpG reached genome-wide significance, while 54 CpGs were suggestive significant (p-values<1e-05). Among them, a CpG, hypermethylated with 100 m buffer total green space, was annotated to PAQR9, whose expression decreased with 1000 m buffer low green space (p-value = 1.45e-05). CONCLUSIONS Our results demonstrate that maternal exposure to green space during pregnancy is associated with cord blood DNA methylation, mainly at loci organized in regions, in genes playing important roles in neurological development (e.g., HTR2A).
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Affiliation(s)
- Rossella Alfano
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium.
| | - Esmée Bijnens
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium
| | - Sabine A S Langie
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium; Department of Pharmacology & Toxicology, School for Nutrition and Translational Research in Metabolism (NUTRIM), Maastricht University, Maastricht, the Netherlands
| | - Tim S Nawrot
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium; Department of Public Health, Leuven University (KU Leuven), Leuven, Belgium
| | - Brigitte Reimann
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium
| | - Kenneth Vanbrabant
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium
| | - Congrong Wang
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium
| | - Michelle Plusquin
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium
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23
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Li S, Mancuso N, Metayer C, Ma X, de Smith AJ, Wiemels JL. Incorporation of DNA methylation quantitative trait loci (mQTLs) in epigenome-wide association analysis: application to birthweight effects in neonatal whole blood. Clin Epigenetics 2022; 14:158. [PMID: 36457128 PMCID: PMC9714153 DOI: 10.1186/s13148-022-01385-6] [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: 05/05/2022] [Accepted: 11/22/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Epigenome-wide association studies (EWAS) have helped to define the associations between DNA methylation and many clinicopathologic and developmental traits. Since DNA methylation is affected by genetic variation at certain loci, EWAS associations may be potentially influenced by genetic effects. However, a formal assessment of the value of incorporating genetic variation in EWAS evaluations is lacking especially for multiethnic populations. METHODS Using single nucleotide polymorphism (SNP) from Illumina Omni Express or Affymetrix PMDA arrays and DNA methylation data from the Illumina 450 K or EPIC array from 1638 newborns of diverse genetic ancestries, we generated DNA methylation quantitative trait loci (mQTL) databases for both array types. We then investigated associations between neonatal DNA methylation and birthweight (incorporating gestational age) using EWAS modeling, and reported how EWAS results were influenced by controlling for mQTLs. RESULTS For CpGs on the 450 K array, an average of 15.4% CpGs were assigned as mQTLs, while on the EPIC array, 23.0% CpGs were matched to mQTLs (adjusted P value < 0.05). The CpGs associated with SNPs were enriched in the CpG island shore regions. Correcting for mQTLs in the EWAS model for birthweight helped to increase significance levels for top hits. For CpGs overlapping genes associated with birthweight-related pathways (nutrition metabolism, biosynthesis, for example), accounting for mQTLs changed their regression coefficients more dramatically (> 20%) than for other random CpGs. CONCLUSION DNA methylation levels at circa 20% CpGs in the genome were affected by common SNP genotypes. EWAS model fit significantly improved when taking these genetic effects into consideration. Genetic effects were stronger on CpGs overlapping genetic elements associated with control of gene expression.
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Affiliation(s)
- Shaobo Li
- grid.42505.360000 0001 2156 6853Department of Population and Public Health Sciences, Center for Genetic Epidemiology, University of Southern California, USC Health Sciences Campus, 1520 San Pablo St., Los Angeles, CA USA
| | - Nicholas Mancuso
- grid.42505.360000 0001 2156 6853Department of Population and Public Health Sciences, Center for Genetic Epidemiology, University of Southern California, USC Health Sciences Campus, 1520 San Pablo St., Los Angeles, CA USA
| | - Catherine Metayer
- grid.47840.3f0000 0001 2181 7878School of Public Health, University of California Berkeley, Berkeley, CA USA
| | - Xiaomei Ma
- grid.47100.320000000419368710Department of Chronic Disease Epidemiology, Yale School of Public Health, Yale University, New Haven, CT USA
| | - Adam J. de Smith
- grid.42505.360000 0001 2156 6853Department of Population and Public Health Sciences, Center for Genetic Epidemiology, University of Southern California, USC Health Sciences Campus, 1520 San Pablo St., Los Angeles, CA USA
| | - Joseph L. Wiemels
- grid.42505.360000 0001 2156 6853Department of Population and Public Health Sciences, Center for Genetic Epidemiology, University of Southern California, USC Health Sciences Campus, 1520 San Pablo St., Los Angeles, CA USA
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24
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Titanji BK, Lee M, Wang Z, Chen J, Hui Q, Lo Re III V, So-Armah K, Justice AC, Xu K, Freiberg M, Gwinn M, Marconi VC, Sun YV. Epigenome-wide association study of biomarkers of liver function identifies albumin-associated DNA methylation sites among male veterans with HIV. Front Genet 2022; 13:1020871. [PMID: 36303554 PMCID: PMC9592923 DOI: 10.3389/fgene.2022.1020871] [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: 08/16/2022] [Accepted: 09/22/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Liver disease (LD) is an important cause of morbidity and mortality for people with HIV (PWH). The molecular factors linked with LD in PWH are varied and incompletely characterized. We performed an epigenome-wide association study (EWAS) to identify associations between DNA methylation (DNAm) and biomarkers of liver function-aspartate transaminase, alanine transaminase, albumin, total bilirubin, platelet count, FIB-4 score, and APRI score-in male United States veterans with HIV. Methods: Blood samples and clinical data were obtained from 960 HIV-infected male PWH from the Veterans Aging Cohort Study. DNAm was assessed using the Illumina 450K or the EPIC 850K array in two mutually exclusive subsets. We performed a meta-analysis for each DNAm site measured by either platform. We also examined the associations between four measures of DNAm age acceleration (AA) and liver biomarkers. Results: Nine DNAm sites were positively associated with serum albumin in the meta-analysis of the EPIC and 450K EWAS after correcting for multiple testing. Four DNAm sites (cg16936953, cg18942579, cg01409343, and cg12054453), annotated within the TMEM49 and four of the remaining five sites (cg18181703, cg03546163, cg20995564, and cg23966214) annotated to SOCS3, FKBP5, ZEB2, and SAMD14 genes, respectively. The DNAm site, cg12992827, was not annotated to any known coding sequence. No significant associations were detected for the other six liver biomarkers. Higher PhenoAA was significantly associated with lower level of serum albumin (β = -0.007, p-value = 8.6 × 10-4, CI: -0.011116, -0.002884). Conclusion: We identified epigenetic associations of both individual DNAm sites and DNAm AA with liver function through serum albumin in men with HIV. Further replication analyses in independent cohorts are warranted to confirm the epigenetic mechanisms underlying liver function and LD in PWH.
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Affiliation(s)
- Boghuma K. Titanji
- Division of Infectious Disease, Emory School of Medicine, Atlanta, GA, United States
| | - Mitch Lee
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Zeyuan Wang
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Junyu Chen
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Qin Hui
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Vincent Lo Re III
- Division of Infectious Diseases Department of Medicine and Center for Clinical Epidemiology and Biostatistics Perelman School of Medicine University of Pennsylvania, Philadelphia, PA, United States
| | - Kaku So-Armah
- Boston University Medical School, Boston, MA, United States
| | - Amy C. Justice
- Connecticut Veteran Health System, West Haven, CT, United States,Yale University School of Medicine, New Haven, CT, United States
| | - Ke Xu
- Connecticut Veteran Health System, West Haven, CT, United States,Yale University School of Medicine, New Haven, CT, United States
| | - Matthew Freiberg
- Cardiovascular Medicine Division and Tennessee Valley Healthcare System, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Marta Gwinn
- Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Vincent C. Marconi
- Division of Infectious Disease, Emory School of Medicine, Atlanta, GA, United States,Atlanta Veterans Affairs Health Care System, Decatur, GA, United States,Hubert Department of Global Health, Rollins School of Public Health, Atlanta, GA, United States,Emory Vaccine Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States
| | - Yan V. Sun
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States,Atlanta Veterans Affairs Health Care System, Decatur, GA, United States,*Correspondence: Yan V. Sun,
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25
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Carratto TMT, Moraes VMS, Recalde TSF, Oliveira MLGD, Teixeira Mendes-Junior C. Applications of massively parallel sequencing in forensic genetics. Genet Mol Biol 2022; 45:e20220077. [PMID: 36121926 PMCID: PMC9514793 DOI: 10.1590/1678-4685-gmb-2022-0077] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 07/15/2022] [Indexed: 11/22/2022] Open
Abstract
Massively parallel sequencing, also referred to as next-generation sequencing, has positively changed DNA analysis, allowing further advances in genetics. Its capability of dealing with low quantity/damaged samples makes it an interesting instrument for forensics. The main advantage of MPS is the possibility of analyzing simultaneously thousands of genetic markers, generating high-resolution data. Its detailed sequence information allowed the discovery of variations in core forensic short tandem repeat loci, as well as the identification of previous unknown polymorphisms. Furthermore, different types of markers can be sequenced in a single run, enabling the emergence of DIP-STRs, SNP-STR haplotypes, and microhaplotypes, which can be very useful in mixture deconvolution cases. In addition, the multiplex analysis of different single nucleotide polymorphisms can provide valuable information about identity, biogeographic ancestry, paternity, or phenotype. DNA methylation patterns, mitochondrial DNA, mRNA, and microRNA profiling can also be analyzed for different purposes, such as age inference, maternal lineage analysis, body-fluid identification, and monozygotic twin discrimination. MPS technology also empowers the study of metagenomics, which analyzes genetic material from a microbial community to obtain information about individual identification, post-mortem interval estimation, geolocation inference, and substrate analysis. This review aims to discuss the main applications of MPS in forensic genetics.
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Affiliation(s)
- Thássia Mayra Telles Carratto
- Universidade de São Paulo, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Departamento de Química, Laboratório de Pesquisas Forenses e Genômicas, Ribeirão Preto, SP, Brazil
| | - Vitor Matheus Soares Moraes
- Universidade de São Paulo, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Departamento de Química, Laboratório de Pesquisas Forenses e Genômicas, Ribeirão Preto, SP, Brazil
| | | | | | - Celso Teixeira Mendes-Junior
- Universidade de São Paulo, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Departamento de Química, Laboratório de Pesquisas Forenses e Genômicas, Ribeirão Preto, SP, Brazil
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26
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Titanji BK, Wang Z, Chen J, Hui Q, So-Armah K, Freiberg M, Justice AC, Ke X, Marconi VC, Sun YV. Soluble CD14-associated DNA methylation sites predict mortality among men with HIV infection. AIDS 2022; 36:1563-1571. [PMID: 35979830 PMCID: PMC9394925 DOI: 10.1097/qad.0000000000003279] [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] [Indexed: 02/04/2023]
Abstract
OBJECTIVES Elevated plasma levels of sCD14 predict all-cause mortality in people with HIV (PWH). Epigenetic regulation plays a key role in infection and inflammation. To reveal the epigenetic relationships between sCD14, immune function and disease progression among PWH, we conducted an epigenome-wide association study (EWAS) of sCD14 and investigated the relationship with mortality. DESIGN AND METHODS DNA methylation (DNAm) levels of peripheral blood samples from PWH in the Veterans Aging Cohort Study (VACS) were measured using the Illumina Infinium Methylation 450K (n = 549) and EPIC (850K) BeadChip (n = 526). Adjusted for covariates and multiple testing, we conducted an epigenome-wide discovery, replication, and meta-analysis to identify significant associations with sCD14. We then examined and replicated the relationship between the principal epigenetic sites and survival using Cox regression models. FINDINGS We identified 118 DNAm sites significantly associated with sCD14 in the meta-analysis of 1075 PWH. The principal associated DNAm sites mapped to genes (e.g. STAT1, PARP9, IFITM1, MX1, and IFIT1) related to inflammation and antiviral response. Adjusting for multiple testing, 10 of 118 sCD14-associated DNAm sites significantly predicted survival time conditional on sCD14 levels. CONCLUSION The identification of DNAm sites independently predicting survival may improve our understanding of prognosis and potential therapeutic targets among PWH.
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Affiliation(s)
- Boghuma K Titanji
- Division of Infectious Diseases, Emory University School of Medicine
| | - Zeyuan Wang
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA
| | - Junyu Chen
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA
| | - Qin Hui
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA
| | | | - Matthew Freiberg
- Cardiovascular Medicine Division and Tennessee Valley Healthcare System, Vanderbilt University Medical Center, Nashville, TN
| | - Amy C Justice
- Yale University School of Medicine, New Haven
- Connecticut Veteran Health System, West Haven, CT
| | - Xu Ke
- Yale University School of Medicine, New Haven
- Connecticut Veteran Health System, West Haven, CT
| | - Vincent C Marconi
- Division of Infectious Diseases, Emory University School of Medicine
- Atlanta Veterans Affairs Healthcare System, Decatur
- Hubert Department of Global Health, Rollins School of Public Health
- Emory Vaccine Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, USA
| | - Yan V Sun
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA
- Atlanta Veterans Affairs Healthcare System, Decatur
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27
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Daredia S, Huen K, Van Der Laan L, Collender PA, Nwanaji-Enwerem JC, Harley K, Deardorff J, Eskenazi B, Holland N, Cardenas A. Prenatal and birth associations of epigenetic gestational age acceleration in the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) cohort. Epigenetics 2022; 17:2006-2021. [PMID: 35912433 DOI: 10.1080/15592294.2022.2102846] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
Gestational age (GA) is an important determinant of child health and disease risk. Two epigenetic GA clocks have been developed using DNA methylation (DNAm) patterns in cord blood. We investigate the accuracy of GA clocks and determinants of epigenetic GA acceleration (GAA), a biomarker of biological ageing. We hypothesize that prenatal and birth characteristics are associated with altered GAA, thereby disrupting foetal biological ageing. We examined 372 mother-child pairs from the Center for the Health Assessment of Mothers and Children of Salinas study of primarily Latino farmworkers in California. Chronological GA was robustly correlated with epigenetic GA (DNAm GA) estimated by the Knight (r = 0.48, p < 2.2x10-16) and Bohlin clocks (r = 0.67, p < 2.2x10-16) using the Illumina 450K array in cord blood samples collected at birth. GA clock performance was robust, though slightly lower, using DNAm profiles from the Illumina EPIC array in a smaller subsample (Knight: r = 0.39, p < 3.5x10-5; Bohlin: r = 0.60, p < 7.7x10-12). After adjusting for confounders, high maternal serum triglyceride levels (Bohlin: β = -0.01 days per mg/dL, p = 0.03), high maternal serum lipid levels (Bohlin: β = -4.31x10-3 days per mg/dL, p = 0.04), preterm delivery (Bohlin: β = -4.03 days, p = 9.64x10-4), greater maternal parity (Knight: β = -4.07 days, p = 0.01; Bohlin: β = -2.43 days, p = 0.01), and male infant sex (Knight: β = -3.15 days, p = 3.10x10-3) were associated with decreased GAA.Prenatal and birth characteristics affect GAA in newborns. Understanding factors that accelerate or delay biological ageing at birth may identify early-life targets for disease prevention and improve ageing across the life-course. Future research should test the impact of altered GAA on the long-term burden of age-related diseases.
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Affiliation(s)
- Saher Daredia
- Division of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, CA, USA
| | - Karen Huen
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA.,Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California, Berkeley, CA, USA
| | - Lars Van Der Laan
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
| | - Philip A Collender
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
| | - Jamaji C Nwanaji-Enwerem
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
| | - Kim Harley
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California, Berkeley, CA, USA.,Division of Community Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
| | - Julianna Deardorff
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California, Berkeley, CA, USA.,Division of Community Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
| | - Brenda Eskenazi
- Division of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, CA, USA.,Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA.,Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California, Berkeley, CA, USA
| | - Nina Holland
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA.,Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California, Berkeley, CA, USA
| | - Andres Cardenas
- Division of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, CA, USA.,Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA.,Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California, Berkeley, CA, USA.,Center for Computational Biology, University of California, Berkeley, CA, USA
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28
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Sammallahti S, Koopman-Verhoeff ME, Binter AC, Mulder RH, Cabré-Riera A, Kvist T, Malmberg ALK, Pesce G, Plancoulaine S, Heiss JA, Rifas-Shiman SL, Röder SW, Starling AP, Wilson R, Guerlich K, Haftorn KL, Page CM, Luik AI, Tiemeier H, Felix JF, Raikkonen K, Lahti J, Relton CL, Sharp GC, Waldenberger M, Grote V, Heude B, Annesi-Maesano I, Hivert MF, Zenclussen AC, Herberth G, Dabelea D, Grazuleviciene R, Vafeiadi M, Håberg SE, London SJ, Guxens M, Richmond RC, Cecil CAM. Longitudinal associations of DNA methylation and sleep in children: a meta-analysis. Clin Epigenetics 2022; 14:83. [PMID: 35790973 PMCID: PMC9258202 DOI: 10.1186/s13148-022-01298-4] [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: 02/25/2022] [Accepted: 06/04/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Sleep is important for healthy functioning in children. Numerous genetic and environmental factors, from conception onwards, may influence this phenotype. Epigenetic mechanisms such as DNA methylation have been proposed to underlie variation in sleep or may be an early-life marker of sleep disturbances. We examined if DNA methylation at birth or in school age is associated with parent-reported and actigraphy-estimated sleep outcomes in children. METHODS We meta-analysed epigenome-wide association study results. DNA methylation was measured from cord blood at birth in 11 cohorts and from peripheral blood in children (4-13 years) in 8 cohorts. Outcomes included parent-reported sleep duration, sleep initiation and fragmentation problems, and actigraphy-estimated sleep duration, sleep onset latency and wake-after-sleep-onset duration. RESULTS We found no associations between DNA methylation at birth and parent-reported sleep duration (n = 3658), initiation problems (n = 2504), or fragmentation (n = 1681) (p values above cut-off 4.0 × 10-8). Lower methylation at cg24815001 and cg02753354 at birth was associated with longer actigraphy-estimated sleep duration (p = 3.31 × 10-8, n = 577) and sleep onset latency (p = 8.8 × 10-9, n = 580), respectively. DNA methylation in childhood was not cross-sectionally associated with any sleep outcomes (n = 716-2539). CONCLUSION DNA methylation, at birth or in childhood, was not associated with parent-reported sleep. Associations observed with objectively measured sleep outcomes could be studied further if additional data sets become available.
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Affiliation(s)
- Sara Sammallahti
- grid.5645.2000000040459992XDepartment of Adolescent and Child Psychiatry, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.7737.40000 0004 0410 2071Department of Obstetrics and Gynaecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - M. Elisabeth Koopman-Verhoeff
- grid.5645.2000000040459992XDepartment of Adolescent and Child Psychiatry, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.5645.2000000040459992XGeneration R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.5132.50000 0001 2312 1970Institute of Education and Child Studies, Leiden University, Leiden, The Netherlands
| | - Anne-Claire Binter
- Barcelona Institute for Global Health, ISGlobal, Campus Mar, Doctor Aiguader, 88, 08003, Barcelona, Spain. .,Universitat Pompeu Fabra, Barcelona, Spain. .,Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain.
| | - Rosa H. Mulder
- grid.5645.2000000040459992XDepartment of Adolescent and Child Psychiatry, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.5645.2000000040459992XGeneration R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Alba Cabré-Riera
- grid.434607.20000 0004 1763 3517Barcelona Institute for Global Health, ISGlobal, Campus Mar, Doctor Aiguader, 88, 08003 Barcelona, Spain ,grid.5612.00000 0001 2172 2676Universitat Pompeu Fabra, Barcelona, Spain ,grid.413448.e0000 0000 9314 1427Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
| | - Tuomas Kvist
- grid.7737.40000 0004 0410 2071Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Anni L. K. Malmberg
- grid.7737.40000 0004 0410 2071Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Giancarlo Pesce
- grid.462844.80000 0001 2308 1657INSERM UMR-S 1136, Team of Epidemiology of Allergic and Respiratory Diseases (EPAR), Institute Pierre Louis of Epidemiology and Public Health (IPLESP), Sorbonne University, Paris, France
| | - Sabine Plancoulaine
- grid.508487.60000 0004 7885 7602CRESS, Inserm, INRAE, Université de Paris Cité, Paris, France
| | - Jonathan A. Heiss
- grid.59734.3c0000 0001 0670 2351Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Sheryl L. Rifas-Shiman
- grid.67104.340000 0004 0415 0102Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA USA
| | - Stefan W. Röder
- grid.7492.80000 0004 0492 3830Department of Environmental Immunology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Anne P. Starling
- grid.430503.10000 0001 0703 675XDepartment of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO USA ,grid.430503.10000 0001 0703 675XCenter for Lifecourse Epidemiology of Adiposity and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO USA ,grid.10698.360000000122483208Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Rory Wilson
- grid.4567.00000 0004 0483 2525Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria Germany
| | - Kathrin Guerlich
- grid.411095.80000 0004 0477 2585Division of Metabolic and Nutritional Medicine, Department of Pediatrics, Dr. Von Hauner Children’s Hospital, LMU University Hospital Munich, Munich, Germany
| | - Kristine L. Haftorn
- grid.418193.60000 0001 1541 4204Department of Genetics and Bioinformatics, Norwegian Institute of Public Health, Oslo, Norway ,grid.418193.60000 0001 1541 4204Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway ,grid.5510.10000 0004 1936 8921Institute of Health and Society, University of Oslo, Oslo, Norway
| | - Christian M. Page
- grid.418193.60000 0001 1541 4204Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway ,grid.5510.10000 0004 1936 8921Department of Mathematics, University of Oslo, Oslo, Norway
| | - Annemarie I. Luik
- grid.5645.2000000040459992XDepartment of Adolescent and Child Psychiatry, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Henning Tiemeier
- grid.5645.2000000040459992XDepartment of Adolescent and Child Psychiatry, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.5645.2000000040459992XGeneration R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.38142.3c000000041936754XDepartment of Social and Behavioral Science, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Janine F. Felix
- grid.5645.2000000040459992XGeneration R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.5645.2000000040459992XDepartment of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Katri Raikkonen
- grid.7737.40000 0004 0410 2071Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Jari Lahti
- grid.7737.40000 0004 0410 2071Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Caroline L. Relton
- grid.5337.20000 0004 1936 7603MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK ,grid.5337.20000 0004 1936 7603Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Gemma C. Sharp
- grid.5337.20000 0004 1936 7603MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK ,grid.5337.20000 0004 1936 7603Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Melanie Waldenberger
- grid.4567.00000 0004 0483 2525Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria Germany
| | - Veit Grote
- grid.411095.80000 0004 0477 2585Division of Metabolic and Nutritional Medicine, Department of Pediatrics, Dr. Von Hauner Children’s Hospital, LMU University Hospital Munich, Munich, Germany
| | - Barbara Heude
- grid.508487.60000 0004 7885 7602CRESS, Inserm, INRAE, Université de Paris Cité, Paris, France
| | - Isabella Annesi-Maesano
- grid.121334.60000 0001 2097 0141IDESP, University of Montpellier and INSERM, Montpellier, France
| | - Marie-France Hivert
- grid.67104.340000 0004 0415 0102Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA USA
| | - Ana C. Zenclussen
- grid.7492.80000 0004 0492 3830Department of Environmental Immunology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany ,grid.9647.c0000 0004 7669 9786Perinatal Immunology Group, Saxonian Incubator for Clinical Translation - SIKT, Leipzig University, Leipzig, Germany
| | - Gunda Herberth
- grid.7492.80000 0004 0492 3830Department of Environmental Immunology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Dana Dabelea
- grid.430503.10000 0001 0703 675XDepartment of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO USA ,grid.430503.10000 0001 0703 675XCenter for Lifecourse Epidemiology of Adiposity and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO USA ,grid.430503.10000 0001 0703 675XDepartment of Pediatrics, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Regina Grazuleviciene
- grid.19190.300000 0001 2325 0545Department of Environmental Science, Vytautas Magnus University, Kaunas, Lithuania
| | - Marina Vafeiadi
- grid.8127.c0000 0004 0576 3437Department of Social Medicine, Faculty of Medicine, University of Crete, Heraklion, Crete Greece
| | - Siri E. Håberg
- grid.418193.60000 0001 1541 4204Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Stephanie J. London
- grid.280664.e0000 0001 2110 5790Epidemiology Branch, Department of Health and Human Services, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC USA
| | - Mònica Guxens
- grid.5645.2000000040459992XDepartment of Adolescent and Child Psychiatry, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.434607.20000 0004 1763 3517Barcelona Institute for Global Health, ISGlobal, Campus Mar, Doctor Aiguader, 88, 08003 Barcelona, Spain ,grid.5612.00000 0001 2172 2676Universitat Pompeu Fabra, Barcelona, Spain ,grid.413448.e0000 0000 9314 1427Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
| | - Rebecca C. Richmond
- grid.5337.20000 0004 1936 7603MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK ,grid.5337.20000 0004 1936 7603Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Charlotte A. M. Cecil
- grid.5645.2000000040459992XDepartment of Adolescent and Child Psychiatry, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.5645.2000000040459992XGeneration R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.10419.3d0000000089452978Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands ,grid.13097.3c0000 0001 2322 6764Department of Psychology, Institute of Psychology, Psychiatry and Neuroscience, King’s College London, London, UK
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29
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Khodasevich D, Smith AR, Huen K, Eskenazi B, Cardenas A, Holland N. Comparison of DNA methylation measurements from EPIC BeadChip and SeqCap targeted bisulphite sequencing in PON1 and nine additional candidate genes. Epigenetics 2022; 17:1944-1955. [PMID: 35786310 DOI: 10.1080/15592294.2022.2091818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
Epigenome-wide association studies (EWAS) are widely implemented in epidemiology, and the Illumina HumanMethylationEPIC BeadChip (EPIC) DNA microarray is the most-used technology. Recently, next-generation sequencing (NGS)-based methods, which assess DNA methylation at single-base resolution, have become more affordable and technically feasible. While the content of microarray technology is fixed, NGS-based approaches, such as the Roche Nimblegen, SeqCap Epi Enrichment System (SeqCap), offer the flexibility of targeting most CpGs in a gene. With the current usage of microarrays and emerging NGS-based technologies, it is important to establish whether data generated from the two platforms are comparable. We harnessed 112 samples from the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) birth cohort study and compared DNA methylation between the EPIC microarray and SeqCap for PON1 and nine additional candidate genes, by evaluating epigenomic coverage and correlations. We conducted multivariable linear regression and principal component analyses to assess the ability of the EPIC array and SeqCap to detect biological differences in gene methylation by the PON1-108 single nucleotide polymorphism. We found an overall high concordance (r = 0.84) between SeqCap and EPIC DNA methylation, among highly methylated and minimally methylated regions. However, substantial disagreement was present between the two methods in moderately methylated regions, with SeqCap measurements exhibiting greater within-site variation. Additionally, SeqCap did not capture PON1 SNP associated differences in DNA methylation that were evident with the EPIC array. Our findings indicate that microarrays perform well for analysing DNA methylation in large cohort studies but with limited coverage.
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Affiliation(s)
- Dennis Khodasevich
- Division of Environmental Health Sciences, Children's Environmental Health Laboratory, School of Public Health, University of California, Berkeley, CA, USA
| | - Anna R Smith
- Division of Environmental Health Sciences, Children's Environmental Health Laboratory, School of Public Health, University of California, Berkeley, CA, USA.,Center for Computational Biology, University of California, Berkeley, CA, USA
| | - Karen Huen
- Division of Environmental Health Sciences, Children's Environmental Health Laboratory, School of Public Health, University of California, Berkeley, CA, USA
| | - Brenda Eskenazi
- Center for Children's Environmental Health, School of Public Health, University of California, Berkeley, CA, USA
| | - Andres Cardenas
- Division of Environmental Health Sciences, Children's Environmental Health Laboratory, School of Public Health, University of California, Berkeley, CA, USA.,Center for Computational Biology, University of California, Berkeley, CA, USA
| | - Nina Holland
- Division of Environmental Health Sciences, Children's Environmental Health Laboratory, School of Public Health, University of California, Berkeley, CA, USA
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30
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Olstad EW, Nordeng HME, Sandve GK, Lyle R, Gervin K. Low reliability of DNA methylation across Illumina Infinium platforms in cord blood: implications for replication studies and meta-analyses of prenatal exposures. Clin Epigenetics 2022; 14:80. [PMID: 35765087 PMCID: PMC9238140 DOI: 10.1186/s13148-022-01299-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Accepted: 06/12/2022] [Indexed: 11/20/2022] Open
Abstract
Background There is an increasing interest in the role of epigenetics in epidemiology, but the emerging research field faces several critical biological and technical challenges. In particular, recent studies have shown poor correlation of measured DNA methylation (DNAm) levels within and across Illumina Infinium platforms in various tissues. In this study, we have investigated concordance between 450 k and EPIC Infinium platforms in cord blood. We could not replicate our previous findings on the association of prenatal paracetamol exposure with cord blood DNAm, which prompted an investigation of cross-platform DNAm differences. Results This study is based on two DNAm data sets from cord blood samples selected from the Norwegian Mother, Father and Child Cohort Study (MoBa). DNAm of one data set was measured using the 450 k platform and the other data set was measured using the EPIC platform. Initial analyses of the EPIC data could not replicate any of our previous significant findings in the 450 k data on associations between prenatal paracetamol exposure and cord blood DNAm. A subset of the samples (n = 17) was included in both data sets, which enabled analyses of technical sources potentially contributing to the negative replication. Analyses of these 17 samples with repeated measurements revealed high per-sample correlations (\documentclass[12pt]{minimal}
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\begin{document}$$\stackrel{\mathrm{-}}{\text{R}}\hspace{0.17em}\approx$$\end{document}R-≈ 0.99), but low per-CpG correlations (\documentclass[12pt]{minimal}
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\begin{document}$$\stackrel{\mathrm{-}}{\text{R}}$$\end{document}R- ≈ 0.24) between the platforms. 1.7% of the CpGs exhibited a mean DNAm difference across platforms > 0.1. Furthermore, only 26.7% of the CpGs exhibited a moderate or better cross-platform reliability (intra-class correlation coefficient ≥ 0.5). Conclusion The observations of low cross-platform probe correlation and reliability corroborate previous reports in other tissues. Our study cannot determine the origin of the differences between platforms. Nevertheless, it emulates the setting in studies using data from multiple Infinium platforms, often analysed several years apart. Therefore, the findings may have important implications for future epigenome-wide association studies (EWASs), in replication, meta-analyses and longitudinal studies. Cognisance and transparency of the challenges related to cross-platform studies may enhance the interpretation, replicability and validity of EWAS results both in cord blood and other tissues, ultimately improving the clinical relevance of epigenetic epidemiology. Supplementary Information The online version contains supplementary material available at 10.1186/s13148-022-01299-3.
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31
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Kumagai H, Miyamoto‐Mikami E, Someya Y, Kidokoro T, Miller B, Kumagai ME, Yoshioka M, Choi Y, Tagawa K, Maeda S, Kohmura Y, Suzuki K, Machida S, Naito H, Fuku N. Sports activities at a young age decrease hypertension risk-The J-Fit + study. Physiol Rep 2022; 10:e15364. [PMID: 35757903 PMCID: PMC9234749 DOI: 10.14814/phy2.15364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 06/01/2022] [Accepted: 06/07/2022] [Indexed: 11/24/2022] Open
Abstract
This study aimed to assess (1) blood pressure between young, current athletes, and non-athletes early in life; (2) hypertension prevalence between former athletes and the general population later in life; and (3) understand the mechanisms between exercise training and hypertension risks in the form of DNA methylation. Study 1: A total of 354 young male participants, including current athletes, underwent blood pressure assessment. Study 2: The prevalence of hypertension in 1269 male former athletes was compared with that in the Japanese general population. Current and former athletes were divided into three groups: endurance-, mixed-, and sprint/power-group. Study 3: We analyzed the effect of aerobic- or resistance-training on DNA methylation patterns using publicly available datasets to explore the possible underlying mechanisms. In young, current athletes, the mixed- and sprint/power-group exhibited higher systolic blood pressure, and all groups exhibited higher pulse pressure than non-athletes. In contrast, the prevalence of hypertension in former athletes was significantly lower in all groups than in the general population. Compared to endurance-group (reference), adjusted-hazard ratios for the incidence of hypertension among mixed- and sprint/power-group were 1.24 (0.87-1.84) and 1.50 (1.04-2.23), respectively. Moreover, aerobic- and resistance-training commonly modified over 3000 DNA methylation sites in skeletal muscle, and these were suggested to be associated with cardiovascular function-related pathways. These findings suggest that the high blood pressure induced by exercise training at a young age does not influence the development of future hypertension. Furthermore, previous exercise training experiences at a young age could decrease the risk of future hypertension.
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Affiliation(s)
- Hiroshi Kumagai
- Graduate School of Health and Sports ScienceJuntendo UniversityChibaJapan
- The Leonard Davis School of GerontologyUniversity of Southern California, CaliforniaLos AngelesCaliforniaUSA
| | | | - Yuki Someya
- Graduate School of Health and Sports ScienceJuntendo UniversityChibaJapan
| | | | - Brendan Miller
- The Leonard Davis School of GerontologyUniversity of Southern California, CaliforniaLos AngelesCaliforniaUSA
| | - Michi Emma Kumagai
- The Leonard Davis School of GerontologyUniversity of Southern California, CaliforniaLos AngelesCaliforniaUSA
- Department of PsychiatryDavid Geffen School of Medicine, University of CaliforniaLos AngelesCaliforniaUSA
| | - Masaki Yoshioka
- Graduate School of Comprehensive Human SciencesUniversity of TsukubaTsukubaJapan
- Japan Society for the Promotion of ScienceTokyoJapan
| | - Youngju Choi
- Institute of Sports & Arts ConvergenceInha UniversityIncheonSouth Korea
| | - Kaname Tagawa
- Graduate School of Comprehensive Human SciencesUniversity of TsukubaTsukubaJapan
| | - Seiji Maeda
- Faculty of Sport SciencesWaseda UniversitySaitamaJapan
| | - Yoshimitsu Kohmura
- Graduate School of Health and Sports ScienceJuntendo UniversityChibaJapan
| | - Koya Suzuki
- Graduate School of Health and Sports ScienceJuntendo UniversityChibaJapan
| | - Shuichi Machida
- Graduate School of Health and Sports ScienceJuntendo UniversityChibaJapan
| | - Hisashi Naito
- Graduate School of Health and Sports ScienceJuntendo UniversityChibaJapan
| | - Noriyuki Fuku
- Graduate School of Health and Sports ScienceJuntendo UniversityChibaJapan
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32
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Wang KZ, Chaudhary Z, Qian J, Adanty C, Graff-Guerrero A, Gerretsen P, Zai CC, De Luca V. Differential Methylation Analysis of Suicidal Ideation Severity in Schizophrenia with the Illumina MethylationEPIC Array. Healthcare (Basel) 2022; 10:809. [PMID: 35627945 PMCID: PMC9141768 DOI: 10.3390/healthcare10050809] [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: 04/05/2022] [Accepted: 04/22/2022] [Indexed: 02/04/2023] Open
Abstract
There is a multitude of factors that makes difficult to identify those at risk for suicide, especially among schizophrenia patients. Suicide cannot be explained by genetics alone, therefore epigenetic mechanisms including DNA methylation are thought to play a role. DNA methylation could be a valuable tool in helping predict those at-risk individuals. This cross-sectional study comprised 112 subjects diagnosed with schizophrenia spectrum disorders, and were grouped according to the current suicidal ideation severity. DNA methylation across the genome was measured with the Infinium® MethylationEPIC BeadChip. We utilized the dmpFinder and bumphunter functions within the Bioconductor minfi package to identify differentially methylated positions (DMPs) and differentially methylated regions (DMRs), respectively. Following quality control, we removed one sample from the analysis and reported the most significant DMPs and DMRs associated with suicidal ideation severity. All positions and regions identified in this analysis were only found to have suggestive levels of significance at the genome-wide level. The present study was one of the first to investigate genome-wide methylation and suicidal ideation severity. While there were many strengths of our study, including investigating both differentially methylated positions and regions, further larger-scale studies are necessary to replicate, support, and validate our findings presented here.
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Affiliation(s)
| | | | | | | | | | | | | | - Vincenzo De Luca
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada; (K.Z.W.); (Z.C.); (J.Q.); (C.A.); (A.G.-G.); (P.G.); (C.C.Z.)
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33
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Wu YL, Jiang T, Huang W, Wu XY, Zhang PJ, Tian YP. Genome-wide methylation profiling of early colorectal cancer using an Illumina Infinium Methylation EPIC BeadChip. World J Gastrointest Oncol 2022; 14:935-946. [PMID: 35582104 PMCID: PMC9048525 DOI: 10.4251/wjgo.v14.i4.935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Revised: 02/21/2022] [Accepted: 04/04/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND DNA methylation is a part of epigenetic modification, that is closely related to the growth and development of colorectal cancer (CRC). Specific methylated genes and methylated diagnostic models of tumors have become current research focuses. The methylation status of circulating DNA in plasma might serve as a potential biomarker for CRC.
AIM To investigate genome-wide methylation pattern in early CRC using the Illumina Infinium Human Methylation 850K BeadChip.
METHODS The 850K Methylation BeadChip was used to analyze the genome-wide methylation status of early CRC patients (n = 5) and colorectal adenoma patients (n = 5). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analyses were performed on the selected differentially methylated sites to further discover candidate methylation biomarkers in plasma.
RESULTS A total of 1865 methylated CpG sites with significant differences were detected, including 676 hypermethylated sites and 1189 hypomethylated sites. The distribution of these sites covered from the 1st to 22nd chromosomes and are mainly distributed on the gene body and gene promoter region. GO and KEGG enrichment analysis showed that the functions of these genes were related to biological regulation, molecular binding, transcription factor activity and signal transduction pathway.
CONCLUSION The study demonstrated that the Illumina Infinium Human Methylation 850K BeadChip can be used to investigate genome-wide methylation status of plasma DNA in early CRC and colorectal adenoma patients.
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Affiliation(s)
- Yu-Ling Wu
- Medical School of Chinese PLA, Beijing 100853, China
| | - Tao Jiang
- Medical Innovation Research Division, Chinese PLA General Hospital, Beijing 100853, China
| | - Wei Huang
- Medical School of Chinese PLA, Beijing 100853, China
| | - Xing-Yu Wu
- Nankai University School of Medicine, Tianjin 300071, China
| | - Peng-Jun Zhang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Interventional Therapy Department, Peking University Cancer Hospital and Institute, Beijing 100142, China
| | - Ya-Ping Tian
- Medical Innovation Research Division, Chinese PLA General Hospital, Beijing 100853, China
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34
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Liu Y, Eliot MN, Papandonatos GD, Kelsey KT, Fore R, Langevin S, Buckley J, Chen A, Lanphear BP, Cecil KM, Yolton K, Hivert MF, Sagiv SK, Baccarelli AA, Oken E, Braun JM. Gestational Perfluoroalkyl Substance Exposure and DNA Methylation at Birth and 12 Years of Age: A Longitudinal Epigenome-Wide Association Study. ENVIRONMENTAL HEALTH PERSPECTIVES 2022; 130:37005. [PMID: 35266797 PMCID: PMC8911098 DOI: 10.1289/ehp10118] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 02/21/2022] [Accepted: 02/23/2022] [Indexed: 05/31/2023]
Abstract
BACKGROUND DNA methylation alterations may underlie associations between gestational perfluoroalkyl substances (PFAS) exposure and later-life health outcomes. To the best of our knowledge, no longitudinal studies have examined the associations between gestational PFAS and DNA methylation. OBJECTIVES We examined associations of gestational PFAS exposure with longitudinal DNA methylation measures at birth and in adolescence using the Health Outcomes and Measures of the Environment (HOME) Study (2003-2006; Cincinnati, Ohio). METHODS We quantified serum concentrations of perfluorooctanoate (PFOA), perfluorooctane sulfonate (PFOS), perfluorononanoate (PFNA), and perfluorohexane sulfonate (PFHxS) in mothers during pregnancy. We measured DNA methylation in cord blood (n=266) and peripheral leukocytes at 12 years of age (n=160) using the Illumina HumanMethylation EPIC BeadChip. We analyzed associations between log2-transformed PFAS concentrations and repeated DNA methylation measures using linear regression with generalized estimating equations. We included interaction terms between children's age and gestational PFAS. We performed Gene Ontology enrichment analysis to identify molecular pathways. We used Project Viva (1999-2002; Boston, Massachusetts) to replicate significant associations. RESULTS After adjusting for covariates, 435 cytosine-guanine dinucleotide (CpG) sites were associated with PFAS (false discovery rate, q<0.05). Specifically, we identified 2 CpGs for PFOS, 12 for PFOA, 8 for PFHxS, and 413 for PFNA; none overlapped. Among these, 2 CpGs for PFOA and 4 for PFNA were replicated in Project Viva. Some of the PFAS-associated CpG sites annotated to gene regions related to cancers, cognitive health, cardiovascular disease, and kidney function. We found little evidence that the associations between PFAS and DNA methylation differed by children's age. DISCUSSION In these longitudinal data, PFAS biomarkers were associated with differences in several CpGs at birth and at 12 years of age in or near genes linked to some PFAS-associated health outcomes. Future studies should examine whether DNA methylation mediates associations between gestational PFAS exposure and health. https://doi.org/10.1289/EHP10118.
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Affiliation(s)
- Yun Liu
- Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island, USA
| | - Melissa N. Eliot
- Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island, USA
| | - George D. Papandonatos
- Department of Biostatistics, Brown University School of Public Health, Providence, Rhode Island, USA
| | - Karl T. Kelsey
- Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island, USA
- Department of Laboratory Medicine and Pathology, Brown University, Providence, Rhode Island, USA
| | - Ruby Fore
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, Massachusetts, USA
| | - Scott Langevin
- Department of Environmental & Public Health Sciences, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Jessie Buckley
- Department of Environmental Health and Engineering, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Aimin Chen
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Bruce P. Lanphear
- Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Kim M. Cecil
- Department of Environmental & Public Health Sciences, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
- Department of Radiology, Cincinnati Children’s Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
- Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Kimberly Yolton
- Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, Massachusetts, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Sharon K. Sagiv
- Department of Epidemiology, Berkeley School of Public Health, University of California, Berkeley, California, USA
| | - Andrea A. Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Emily Oken
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, Massachusetts, USA
| | - Joseph M. Braun
- Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island, USA
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Cristoferi I, Giacon TA, Boer K, van Baardwijk M, Neri F, Campisi M, Kimenai HJAN, Clahsen-van Groningen MC, Pavanello S, Furian L, Minnee RC. The applications of DNA methylation as a biomarker in kidney transplantation: a systematic review. Clin Epigenetics 2022; 14:20. [PMID: 35130936 PMCID: PMC8822833 DOI: 10.1186/s13148-022-01241-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 01/27/2022] [Indexed: 12/27/2022] Open
Abstract
Background Although kidney transplantation improves patient survival and quality of life, long-term results are hampered by both immune- and non-immune-mediated complications. Current biomarkers of post-transplant complications, such as allograft rejection, chronic renal allograft dysfunction, and cutaneous squamous cell carcinoma, have a suboptimal predictive value. DNA methylation is an epigenetic modification that directly affects gene expression and plays an important role in processes such as ischemia/reperfusion injury, fibrosis, and alloreactive immune response. Novel techniques can quickly assess the DNA methylation status of multiple loci in different cell types, allowing a deep and interesting study of cells’ activity and function. Therefore, DNA methylation has the potential to become an important biomarker for prediction and monitoring in kidney transplantation.
Purpose of the study The aim of this study was to evaluate the role of DNA methylation as a potential biomarker of graft survival and complications development in kidney transplantation. Material and Methods A systematic review of several databases has been conducted. The Newcastle–Ottawa scale and the Jadad scale have been used to assess the risk of bias for observational and randomized studies, respectively.
Results Twenty articles reporting on DNA methylation as a biomarker for kidney transplantation were included, all using DNA methylation for prediction and monitoring. DNA methylation pattern alterations in cells isolated from different tissues, such as kidney biopsies, urine, and blood, have been associated with ischemia–reperfusion injury and chronic renal allograft dysfunction. These alterations occurred in different and specific loci. DNA methylation status has also proved to be important for immune response modulation, having a crucial role in regulatory T cell definition and activity. Research also focused on a better understanding of the role of this epigenetic modification assessment for regulatory T cells isolation and expansion for future tolerance induction-oriented therapies. Conclusions Studies included in this review are heterogeneous in study design, biological samples, and outcome. More coordinated investigations are needed to affirm DNA methylation as a clinically relevant biomarker important for prevention, monitoring, and intervention. Supplementary Information The online version contains supplementary material available at 10.1186/s13148-022-01241-7.
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Affiliation(s)
- Iacopo Cristoferi
- Division of HPB and Transplant Surgery, Department of Surgery, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands. .,Department of Pathology and Clinical Bioinformatics, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands. .,Erasmus MC Transplant Institute, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands.
| | - Tommaso Antonio Giacon
- Kidney and Pancreas Transplantation Unit, Department of Surgical, Oncological and Gastroenterological Sciences, Padua University Hospital, Via Giustiniani 2, 35128, Padua, Italy.,Occupational Medicine, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, Padua University, Via Giustiniani 2, 35128, Padua, Italy.,Environmental and Respiratory Physiology Laboratory, Department of Biomedical Sciences, Padua University, Via Marzolo 3, 35131, Padua, Italy.,Institute of Anaesthesia and Intensive Care, Department of Medicine - DIMED, Padua University Hospital, Via Cesare Battisti 267, 35128, Padua, Italy
| | - Karin Boer
- Erasmus MC Transplant Institute, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands.,Division of Nephrology and Transplantation, Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - Myrthe van Baardwijk
- Division of HPB and Transplant Surgery, Department of Surgery, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands.,Department of Pathology and Clinical Bioinformatics, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands.,Erasmus MC Transplant Institute, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands
| | - Flavia Neri
- Kidney and Pancreas Transplantation Unit, Department of Surgical, Oncological and Gastroenterological Sciences, Padua University Hospital, Via Giustiniani 2, 35128, Padua, Italy
| | - Manuela Campisi
- Occupational Medicine, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, Padua University, Via Giustiniani 2, 35128, Padua, Italy
| | - Hendrikus J A N Kimenai
- Division of HPB and Transplant Surgery, Department of Surgery, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands.,Erasmus MC Transplant Institute, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands
| | - Marian C Clahsen-van Groningen
- Department of Pathology and Clinical Bioinformatics, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands.,Erasmus MC Transplant Institute, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands.,Institute of Experimental Medicine and Systems Biology, RWTH Aachen University, Pauwelsstraße 30, 52074, Aachen, Germany
| | - Sofia Pavanello
- Occupational Medicine, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, Padua University, Via Giustiniani 2, 35128, Padua, Italy
| | - Lucrezia Furian
- Kidney and Pancreas Transplantation Unit, Department of Surgical, Oncological and Gastroenterological Sciences, Padua University Hospital, Via Giustiniani 2, 35128, Padua, Italy
| | - Robert C Minnee
- Division of HPB and Transplant Surgery, Department of Surgery, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands.,Erasmus MC Transplant Institute, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands
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Vanderlinden LA, Johnson RK, Carry PM, Dong F, DeMeo DL, Yang IV, Norris JM, Kechris K. An effective processing pipeline for harmonizing DNA methylation data from Illumina's 450K and EPIC platforms for epidemiological studies. BMC Res Notes 2021; 14:352. [PMID: 34496950 PMCID: PMC8424820 DOI: 10.1186/s13104-021-05741-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Accepted: 08/16/2021] [Indexed: 02/06/2023] Open
Abstract
OBJECTIVE Illumina BeadChip arrays are commonly used to generate DNA methylation data for large epidemiological studies. Updates in technology over time create challenges for data harmonization within and between studies, many of which obtained data from the older 450K and newer EPIC platforms. The pre-processing pipeline for DNA methylation is not trivial, and influences the downstream analyses. Incorporating different platforms adds a new level of technical variability that has not yet been taken into account by recommended pipelines. Our study evaluated the performance of various tools on different versions of platform data harmonization at each step of pre-processing pipeline, including quality control (QC), normalization, batch effect adjustment, and genomic inflation. We illustrate our novel approach using 450K and EPIC data from the Diabetes Autoimmunity Study in the Young (DAISY) prospective cohort. RESULTS We found normalization and probe filtering had the biggest effect on data harmonization. Employing a meta-analysis was an effective and easily executable method for accounting for platform variability. Correcting for genomic inflation also helped with harmonization. We present guidelines for studies seeking to harmonize data from the 450K and EPIC platforms, which includes the use of technical replicates for evaluating numerous pre-processing steps, and employing a meta-analysis.
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Affiliation(s)
- Lauren A Vanderlinden
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Randi K Johnson
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Patrick M Carry
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Fran Dong
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Ivana V Yang
- School of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Jill M Norris
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Katerina Kechris
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
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Penova-Veselinovic B, Melton PE, Huang RC, Yovich JL, Burton P, Wijs LA, Hart RJ. DNA methylation patterns within whole blood of adolescents born from assisted reproductive technology are not different from adolescents born from natural conception. Hum Reprod 2021; 36:2035-2049. [PMID: 33890633 DOI: 10.1093/humrep/deab078] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2020] [Revised: 03/04/2021] [Indexed: 12/18/2022] Open
Abstract
STUDY QUESTION Do the epigenome-wide DNA methylation profiles of adolescents born from ART differ from the epigenome of naturally conceived counterparts? SUMMARY ANSWER No significant differences in the DNA methylation profiles of adolescents born from ART [IVF or ICSI] were observed when compared to their naturally conceived, similar aged counterparts. WHAT IS KNOWN ALREADY Short-term and longer-term studies have investigated the general health outcomes of children born from IVF treatment, albeit without common agreement as to the cause and underlying mechanisms of these adverse health findings. Growing evidence suggests that the reported adverse health outcomes in IVF-born offspring might have underlying epigenetic mechanisms. STUDY DESIGN, SIZE, DURATION The Growing Up Healthy Study (GUHS) is a prospective study that recruited 303 adolescents and young adults, conceived through ART, to compare various long-term health outcomes and DNA methylation profiles with similar aged counterparts from Generation 2 from the Raine Study. GUHS assessments were conducted between 2013 and 2017. The effect of ART on DNA methylation levels of 231 adolescents mean age 15.96 ± 1.59 years (52.8% male) was compared to 1188 naturally conceived counterparts, 17.25 ± 0.58 years (50.9% male) from the Raine Study. PARTICIPANTS/MATERIALS, SETTING, METHODS DNA methylation profiles from a subset of 231 adolescents (13-19.9 years) from the GUHS, generated using the Infinium Methylation Epic Bead Chip (EPIC) array were compared to 1188 profiles from the Raine Study previously measured using the Illumina 450K array. We conducted epigenome-wide association approach (EWAS) and tested for an association between the cohorts applying Firth's bias reduced logistic regression against the outcome of ART versus naturally conceived offspring. Additionally, within the GUHS cohort, we investigated differences in methylation status in fresh versus frozen embryo transfers, cause of infertility as well as IVF versus ICSI conceived offspring. Following the EWAS analysis we investigated nominally significant probes using Gene Set Enrichment Analysis (GSEA) to identify enriched biological pathways. Finally, within GUHS we compared four estimates (Horvath, Hanuum, PhenoAge [Levine], and skin Horvath) of epigenetic age and their correlation with chronological age. MAIN RESULTS AND THE ROLE OF CHANCE Between the two cohorts, we did not identify any DNA methylation probes that reached a Bonferroni corrected P-value < 1.24E-0.7. When comparing IVF versus ICSI conceived adolescents within the GUHS cohort, after adjustment for participant age, sex, maternal smoking, multiple births, and batch effect, three methylation probes (cg15016734, cg26744878 and cg20233073) reached a Bonferroni correction of 6.31E-08. After correcting for cell count heterogeneity, two of the aforementioned probes remained significant and an additional two probes (cg 0331628 and cg 20235051) were identified. A general trend towards hypomethylation in the ICSI offspring was observed. All four measures of epigenetic age were highly correlated with chronological age and showed no evidence of accelerated epigenetic aging within their whole blood. LIMITATIONS, REASONS FOR CAUTION The small sample size coupled with the use of whole blood, where epigenetic differences may occur in other tissue. This was corrected by the utilized statistical method that accounts for imbalanced sample size between groups and adjusting for cell count heterogeneity. Only a small portion of the methylome was analysed and rare individual differences may be missed. WIDER IMPLICATIONS OF THE FINDINGS Our findings provide further reassurance that the effects of the ART manipulations occurring during early embryogenesis, existing in the neonatal period are indeed of a transient nature and do not persist into adolescence. However, we have not excluded that alternative epigenetic mechanisms may be at play. STUDY FUNDING/COMPETING INTEREST(S) This project was supported by NHMRC project Grant no. 1042269 and R.J.H. received funding support from Ferring Pharmaceuticals Pty Ltd. R.J.H. is the Medical Director of Fertility Specialists of Western Australia and a shareholder in Western IVF. He has received educational sponsorship from Merck Sharp & Dohme Corp.- Australia, Merck-Serono Australia Pty Ltd and Ferring Pharmaceuticals Pty Ltd. P.B. is the Scientific Director of Concept Fertility Centre, Subiaco, Western Australia. J.L.Y. is the Medical Director of PIVET Medical Centre, Perth, Western Australia. The remaining authors have no conflicts of interest.
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Affiliation(s)
- B Penova-Veselinovic
- Division of Obstetrics and Gynaecology, Faculty of Health and Medical Sciences, University of Western Australia, Perth, WA, Australia
| | - P E Melton
- School of Population and Global Health, University of Western Australia, Perth, WA, Australia.,School of Pharmacy and Biomedical Science, Curtin University, Perth, WA, Australia.,Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
| | - R C Huang
- Faculty of Health and Medical Sciences, Centre for Child Health Research, University of Western Australia, Perth, WA, Australia.,Telethon Kids Institute, Nedlands, WA, Australia
| | - J L Yovich
- School of Pharmacy and Biomedical Science, Curtin University, Perth, WA, Australia.,PIVET Medical Centre, Perth, WA, Australia
| | - P Burton
- Concept Fertility Centre, Subiaco, WA, Australia.,School of Health and Medical Sciences, Faculty of Health Science, Edith Cowan University, Perth, WA, Australia
| | - L A Wijs
- Division of Obstetrics and Gynaecology, Faculty of Health and Medical Sciences, University of Western Australia, Perth, WA, Australia
| | - R J Hart
- Division of Obstetrics and Gynaecology, Faculty of Health and Medical Sciences, University of Western Australia, Perth, WA, Australia.,Fertility Specialists of Western Australia, Bethesda Hospital, Claremont, WA, Australia
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Saadatmand F, Gurdziel K, Jackson L, Kwabi-Addo B, Ruden DM. DNA methylation and exposure to violence among African American young adult males. Brain Behav Immun Health 2021; 14:100247. [PMID: 34589758 PMCID: PMC8474503 DOI: 10.1016/j.bbih.2021.100247] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 03/18/2021] [Accepted: 03/22/2021] [Indexed: 02/02/2023] Open
Abstract
Exposure to violence (ETV) has been linked to epigenomics mechanisms such as DNA methylation (DNAm). We used epigenetic profiling of blood collected from 32 African American young adult males who lived in Washington DC to determine if changes in DNAm at CpG sites affiliated with nervous and immune system were associated with exposure to violence. Pathway analysis of differentially methylated regions comparing high and low ETV groups revealed an enrichment of gene sets annotated to nervous system and immune ontologies. Many of these genes are known to interact with each other which suggests DNAm alters gene function in the nervous and immune system in response to ETV. Using data from a unique age group, young African American adult males, we provide evidence that lifetime ETV could impact DNA methylation in genes impacted at Central Nervous System and Immune Function sites. METHOD Methylation analysis was performed on DNA collected from the blood of participants classified with either high or low lifetime ETV. Illumina®MethylationEPIC Beadchips (~850k CpG sites) were processed on the iScan System to examine whole-genome methylation differences. Differentially methylated CpG-sites between high (n = 19) and low (n = 13) groups were identified using linear regression with violence and substance abuse as model covariates. Gene ontology analysis was used to identify enrichment categories from probes annotated to the nearest gene. RESULTS A total of 595 probes (279 hypermethylated; 316 hypomethylated) annotated to 383 genes were considered differentially methylated in association with ETV. Males with high ETV showed elevated methylation in several signaling pathways but were most impacted at Central Nervous System and Immune Function affiliated sites. Eight candidate genes were identified that play important biological roles in stress response to violence with HDAC4 (10%), NR4A3 (11%), NR4A2 (12%), DSCAML1(12%), and ELAVL3 (13%) exhibiting higher levels in the low ETV group and DLGAP1 (10%), SHANK2 (10%), and NRG1(11%) having increased methylation in the high ETV group. These findings suggest that individuals subjected to high ETV may be at risk for poor health outcomes that have not been reported previously.
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Affiliation(s)
- Forough Saadatmand
- Department of Pediatrics, College of Medicine, Howard University, Washington, DC, USA
| | - Katherine Gurdziel
- Office of the Vice President of Research, Wayne State University, Detroit, MI, USA
| | - Latifa Jackson
- Department of Pediatrics, College of Medicine, Howard University, Washington, DC, USA
- W. Montague Cobb Research Laboratory, College of Arts and Sciences, Howard University, Washington, DC, USA
| | - Bernard Kwabi-Addo
- Department of Biochemistry and Molecular Biology, College of Medicine, Howard University, Washington, DC, USA
| | - Douglas M. Ruden
- Department of Ob/Gyn, CS Mott Center for Human Growth and Development, Wayne State University School of Medicine, Detroit, MI, USA
- Institutes for Environmental Health Science, Wayne State University School of Medicine, Detroit, MI, USA
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39
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Combined prenatal Lactobacillus reuteri and ω-3 supplementation synergistically modulates DNA methylation in neonatal T helper cells. Clin Epigenetics 2021; 13:135. [PMID: 34193262 PMCID: PMC8247185 DOI: 10.1186/s13148-021-01115-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 06/15/2021] [Indexed: 02/08/2023] Open
Abstract
Background Environmental exposures may alter DNA methylation patterns of T helper cells. As T helper cells are instrumental for allergy development, changes in methylation patterns may constitute a mechanism of action for allergy preventive interventions. While epigenetic effects of separate perinatal probiotic or ω-3 fatty acid supplementation have been studied previously, the combined treatment has not been assessed. We aimed to investigate epigenome-wide DNA methylation patterns from a sub-group of children in an on-going randomised double-blind placebo-controlled allergy prevention trial using pre- and postnatal combined Lactobacillus reuteri and ω-3 fatty acid treatment. To this end, > 866000 CpG sites (MethylationEPIC 850K array) in cord blood CD4+ T cells were examined in samples from all four study arms (double-treatment: n = 18, single treatments: probiotics n = 16, ω-3 n = 15, and double placebo: n = 14). Statistical and bioinformatic analyses identified treatment-associated differentially methylated CpGs and genes, which were used to identify putatively treatment-induced network modules. Pathway analyses inferred biological relevance, and comparisons were made to an independent allergy data set. Results Comparing the active treatments to the double placebo group, most differentially methylated CpGs and genes were hypermethylated, possibly suggesting induction of transcriptional inhibition. The double-treated group showed the largest number of differentially methylated CpGs, of which many were unique, suggesting synergy between interventions. Clusters within the double-treated network module consisted of immune-related pathways, including T cell receptor signalling, and antigen processing and presentation, with similar pathways revealed for the single-treatment modules. CpGs derived from differential methylation and network module analyses were enriched in an independent allergy data set, particularly in the double-treatment group, proposing treatment-induced DNA methylation changes as relevant for allergy development. Conclusion Prenatal L. reuteri and/or ω-3 fatty acid treatment results in hypermethylation and affects immune- and allergy-related pathways in neonatal T helper cells, with potentially synergistic effects between the interventions and relevance for allergic disease. Further studies need to address these findings on a transcriptional level, and whether the results associate to allergy development in the children. Understanding the role of DNA methylation in regulating effects of perinatal probiotic and ω-3 interventions may provide essential knowledge in the development of efficacious allergy preventive strategies. Trial registration ClinicalTrials.gov, ClinicalTrials.gov-ID: NCT01542970. Registered 27th of February 2012—Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT01542970. Supplementary Information The online version contains supplementary material available at 10.1186/s13148-021-01115-4.
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Sammallahti S, Cortes Hidalgo AP, Tuominen S, Malmberg A, Mulder RH, Brunst KJ, Alemany S, McBride NS, Yousefi P, Heiss JA, McRae N, Page CM, Jin J, Pesce G, Caramaschi D, Rifas-Shiman SL, Koen N, Adams CD, Magnus MC, Baïz N, Ratanatharathorn A, Czamara D, Håberg SE, Colicino E, Baccarelli AA, Cardenas A, DeMeo DL, Lawlor DA, Relton CL, Felix JF, van IJzendoorn MH, Bakermans-Kranenburg MJ, Kajantie E, Räikkönen K, Sunyer J, Sharp GC, Houtepen LC, Nohr EA, Sørensen TIA, Téllez-Rojo MM, Wright RO, Annesi-Maesano I, Wright J, Hivert MF, Wright RJ, Zar HJ, Stein DJ, London SJ, Cecil CAM, Tiemeier H, Lahti J. Maternal anxiety during pregnancy and newborn epigenome-wide DNA methylation. Mol Psychiatry 2021; 26:1832-1845. [PMID: 33414500 PMCID: PMC8595870 DOI: 10.1038/s41380-020-00976-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 10/31/2020] [Accepted: 11/30/2020] [Indexed: 01/29/2023]
Abstract
Maternal anxiety during pregnancy is associated with adverse foetal, neonatal, and child outcomes, but biological mechanisms remain unclear. Altered foetal DNA methylation (DNAm) has been proposed as a potential underlying mechanism. In the current study, we performed a meta-analysis to examine the associations between maternal anxiety, measured prospectively during pregnancy, and genome-wide DNAm from umbilical cord blood. Sixteen non-overlapping cohorts from 12 independent longitudinal studies of the Pregnancy And Childhood Epigenetics Consortium participated, resulting in a combined dataset of 7243 mother-child dyads. We examined prenatal anxiety in relation to genome-wide DNAm and differentially methylated regions. We observed no association between the general symptoms of anxiety during pregnancy or pregnancy-related anxiety, and DNAm at any of the CpG sites, after multiple-testing correction. Furthermore, we identify no differentially methylated regions associated with maternal anxiety. At the cohort-level, of the 21 associations observed in individual cohorts, none replicated consistently in the other cohorts. In conclusion, contrary to some previous studies proposing cord blood DNAm as a promising potential mechanism explaining the link between maternal anxiety during pregnancy and adverse outcomes in offspring, we found no consistent evidence for any robust associations between maternal anxiety and DNAm in cord blood. Larger studies and analysis of DNAm in other tissues may be needed to establish subtle or subgroup-specific associations between maternal anxiety and the foetal epigenome.
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Affiliation(s)
- Sara Sammallahti
- Erasmus MC, University Medical Center Rotterdam, Department of Adolescent and Child Psychiatry and Psychology, Rotterdam, The Netherlands
- Erasmus MC, University Medical Center Rotterdam, Generation R Study Group, Rotterdam, The Netherlands
- Harvard T.H. Chan School of Public Health, Department of Social and Behavioral Science, Boston, MA, USA
- University of Helsinki, Department of Psychology and Logopedics, Helsinki, Finland
| | - Andrea P Cortes Hidalgo
- Erasmus MC, University Medical Center Rotterdam, Department of Adolescent and Child Psychiatry and Psychology, Rotterdam, The Netherlands
- Erasmus MC, University Medical Center Rotterdam, Generation R Study Group, Rotterdam, The Netherlands
| | - Samuli Tuominen
- University of Helsinki, Department of Psychology and Logopedics, Helsinki, Finland
| | - Anni Malmberg
- University of Helsinki, Department of Psychology and Logopedics, Helsinki, Finland
| | - Rosa H Mulder
- Erasmus MC, University Medical Center Rotterdam, Department of Adolescent and Child Psychiatry and Psychology, Rotterdam, The Netherlands
- Erasmus MC, University Medical Center Rotterdam, Generation R Study Group, Rotterdam, The Netherlands
- Leiden University, Institute of Education and Child Studies, Leiden, The Netherlands
| | - Kelly J Brunst
- University of Cincinnati, College of Medicine, Department of Environmental Health, Cincinnati, OH, USA
| | - Silvia Alemany
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Nancy S McBride
- University of Bristol, MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, Bristol, UK
| | - Paul Yousefi
- University of Bristol, MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, Bristol, UK
| | - Jonathan A Heiss
- Icahn School of Medicine at Mount Sinai, Department of Environmental Medicine and Public Health, New York, NY, USA
| | - Nia McRae
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Christian M Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Oslo Centre for Biostatistics and Epidemiology, Oslo University Hospital, Oslo, Norway
| | | | - Giancarlo Pesce
- INSERM UMR-S 1136, EPAR, Saint-Antoine Medical School, Paris, France
- Sorbonne Université, Epidemiology of Allergic and Respiratory Diseases Department (EPAR), Pierre Louis Institute of Epidemiology and Public Health (IPLESP), Paris, France
| | - Doretta Caramaschi
- University of Bristol, MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, Bristol, UK
| | - Sheryl L Rifas-Shiman
- Harvard Medical School, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Nastassja Koen
- University of Cape Town, Department of Psychiatry and Mental Health, Cape Town, South Africa
- South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders, Cape Town, South Africa
- University of Cape Town, Neuroscience Institute, Cape Town, South Africa
| | - Charleen D Adams
- Beckman Research Institute of City of Hope, Department of Population Sciences, Duarte, CA, USA
| | - Maria C Magnus
- University of Bristol, MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, Bristol, UK
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Nour Baïz
- INSERM UMR-S 1136, EPAR, Saint-Antoine Medical School, Paris, France
- Sorbonne Université, Epidemiology of Allergic and Respiratory Diseases Department (EPAR), Pierre Louis Institute of Epidemiology and Public Health (IPLESP), Paris, France
| | - Andrew Ratanatharathorn
- Columbia University, Department of Epidemiology, New York City, NY, USA
- Harvard T.H. Chan School of Public Health, Department of Epidemiology, Boston, MA, USA
| | - Darina Czamara
- Max-Planck-Institute of Psychiatry, Department of Translational Research in Psychiatry, Munich, Germany
| | - Siri E Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Elena Colicino
- Icahn School of Medicine at Mount Sinai, Department of Environmental Medicine and Public Health, New York, NY, USA
| | - Andrea A Baccarelli
- Columbia University Mailman School of Public Health, Precision Environmental Health Lab, New York, NY, USA
| | - Andres Cardenas
- University of California, Division of Environmental Health Sciences, School of Public Health, Berkeley, CA, USA
| | - Dawn L DeMeo
- Brigham and Women's Hospital, Channing Division of Network Medicine, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Deborah A Lawlor
- University of Bristol, MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, Bristol, UK
| | - Caroline L Relton
- University of Bristol, MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, Bristol, UK
| | - Janine F Felix
- Erasmus MC, University Medical Center Rotterdam, Generation R Study Group, Rotterdam, The Netherlands
- Erasmus MC, University Medical Center Rotterdam, Department of Pediatrics, Rotterdam, The Netherlands
| | - Marinus H van IJzendoorn
- Erasmus University Rotterdam, Department of Psychology, Education, and Child Studies, Rotterdam, The Netherlands
- University of Cambridge, School of Clinical Medicine, Cambridge, UK
| | - Marian J Bakermans-Kranenburg
- Leiden University, Leiden Institute for Brain and Cognition, Leiden, The Netherlands
- Vrije Universiteit Amsterdam, Clinical Child & Family Studies, Amsterdam, The Netherlands
| | - Eero Kajantie
- Finnish Institute for Health and Welfare, Helsinki, Finland
- Oulu University Hospital and University of Oulu, PEDEGO Research Unit, MRC Oulu, Oulu, Finland
- Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
- Norwegian University of Science and Technology, Department of Clinical and Molecular Medicine, Trondheim, Norway
| | - Katri Räikkönen
- University of Helsinki, Department of Psychology and Logopedics, Helsinki, Finland
| | - Jordi Sunyer
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Gemma C Sharp
- University of Bristol, MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, Bristol, UK
| | - Lotte C Houtepen
- University of Bristol, MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, Bristol, UK
| | - Ellen A Nohr
- University of Southern Denmark, Institute of Clinical Research and Department of Gynaecology and Obstetrics, Odense, Denmark
| | - Thorkild I A Sørensen
- University of Bristol, MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, Bristol, UK
- University of Copenhagen, Faculty of Health and Medical Sciences, Department of Public Health, Copenhagen, Denmark
- University of Copenhagen, Faculty of Medical and Health Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, Copenhagen, Denmark
| | - Martha M Téllez-Rojo
- National Institute of Public Health, Center for Nutrition and Health Research, Cuernavaca, Mor, Mexico
| | | | - Isabella Annesi-Maesano
- INSERM UMR-S 1136, EPAR, Saint-Antoine Medical School, Paris, France
- Sorbonne Université, Epidemiology of Allergic and Respiratory Diseases Department (EPAR), Pierre Louis Institute of Epidemiology and Public Health (IPLESP), Paris, France
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals, NHS Foundation Trust, Bradford, UK
| | - Marie-France Hivert
- Harvard Medical School, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Massachusetts General Hospital, Diabetes Unit, Boston, MA, USA
| | - Rosalind J Wright
- Icahn School of Medicine at Mount Sinai, Environmental Medicine & Public Health, Institute for Exposomic Research, New York, NY, USA
| | - Heather J Zar
- University of Cape Town, Department of Paediatrics and Child Health, Cape Town, South Africa
- South African Medical Research Council (SAMRC) Unit on Child and Adolescent Health, Cape Town, Cape Town, South Africa
| | - Dan J Stein
- University of Cape Town, Department of Psychiatry and Mental Health, Cape Town, South Africa
- South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders, Cape Town, South Africa
- University of Cape Town, Neuroscience Institute, Cape Town, South Africa
| | - Stephanie J London
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Charlotte A M Cecil
- Erasmus MC, University Medical Center Rotterdam, Department of Adolescent and Child Psychiatry and Psychology, Rotterdam, The Netherlands
- Erasmus MC, University Medical Center Rotterdam, Generation R Study Group, Rotterdam, The Netherlands
- Erasmus MC, University Medical Center Rotterdam, Department of Epidemiology, Rotterdam, The Netherlands
- Leiden University Medical Center, Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden, The Netherlands
| | - Henning Tiemeier
- Erasmus MC, University Medical Center Rotterdam, Department of Adolescent and Child Psychiatry and Psychology, Rotterdam, The Netherlands.
- Erasmus MC, University Medical Center Rotterdam, Generation R Study Group, Rotterdam, The Netherlands.
- Harvard T.H. Chan School of Public Health, Department of Social and Behavioral Science, Boston, MA, USA.
| | - Jari Lahti
- University of Helsinki, Department of Psychology and Logopedics, Helsinki, Finland
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Liang X, Justice AC, So-Armah K, Krystal JH, Sinha R, Xu K. DNA methylation signature on phosphatidylethanol, not on self-reported alcohol consumption, predicts hazardous alcohol consumption in two distinct populations. Mol Psychiatry 2021; 26:2238-2253. [PMID: 32034291 PMCID: PMC8440221 DOI: 10.1038/s41380-020-0668-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2019] [Revised: 12/20/2019] [Accepted: 01/28/2020] [Indexed: 12/28/2022]
Abstract
The process of diagnosing hazardous alcohol drinking (HAD) is based on self-reported data and is thereby vulnerable to bias. There has been an interest in developing epigenetic biomarkers for HAD that might complement clinical assessment. Because alcohol consumption has been previously linked to DNA methylation (DNAm), we aimed to select DNAm signatures in blood to predict HAD from two demographically and clinically distinct populations (Ntotal = 1,549). We first separately conducted an epigenome-wide association study (EWAS) for phosphatidylethanol (PEth), an objective measure of alcohol consumption, and for self-reported alcohol consumption in Cohort 1. We identified 83 PEth-associated CpGs, including 23 CpGs previously associated with alcohol consumption or alcohol use disorder. In contrast, no CpG reached epigenome-wide significance on self-reported alcohol consumption. Using a machine learning approach, two CpG subsets from EWAS on PEth and on self-reported alcohol consumption from Cohort 1 were separately tested for the prediction of HAD in Cohort 2. We found that a subset of 143 CpGs selected from the EWAS on PEth showed an excellent prediction of HAD with the area under the receiver operating characteristic curve (AUC) of 89.4% in training set and 73.9% in validation set of Cohort 2. However, CpGs preselected from the EWAS on self-reported alcohol consumption showed a poor prediction of HAD with AUC 75.2% in training set and 57.6% in validation set. Our results demonstrate that an objective measure for alcohol consumption is a more informative phenotype than self-reported data for revealing epigenetic mechanisms. The PEth-associated DNAm signature in blood could serve as a robust biomarker for alcohol consumption.
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Affiliation(s)
- Xiaoyu Liang
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare System, West Haven, CT, USA
| | - Amy C Justice
- VA Connecticut Healthcare System, West Haven, CT, USA
- Yale School of Medicine, New Haven, CT, USA
| | - Kaku So-Armah
- Boston University School of Medicine, Boston, MA, USA
| | - John H Krystal
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare System, West Haven, CT, USA
| | - Rajita Sinha
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Child Study Center, Yale School of Medicine, New Haven, CT, USA
- Stress Center, Yale School of Medicine, New Haven, CT, USA
| | - Ke Xu
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
- VA Connecticut Healthcare System, West Haven, CT, USA.
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42
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Söderhäll C, Reinius LE, Salmenperä P, Gentile M, Acevedo N, Konradsen JR, Nordlund B, Hedlin G, Scheynius A, Myllykangas S, Kere J. High-resolution targeted bisulfite sequencing reveals blood cell type-specific DNA methylation patterns in IL13 and ORMDL3. Clin Epigenetics 2021; 13:106. [PMID: 33971943 PMCID: PMC8111952 DOI: 10.1186/s13148-021-01093-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 04/26/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Methylation of DNA at CpG sites is an epigenetic modification and a potential modifier of disease risk, possibly mediating environmental effects. Currently, DNA methylation is commonly assessed using specific microarrays that sample methylation at a few % of all methylated sites. METHODS To understand if significant information on methylation can be added by a more comprehensive analysis of methylation, we set up a quantitative method, bisulfite oligonucleotide-selective sequencing (Bs-OS-seq), and compared the data with microarray-derived methylation data. We assessed methylation at two asthma-associated genes, IL13 and ORMDL3, in blood samples collected from children with and without asthma and fractionated white blood cell types from healthy adult controls. RESULTS Our results show that Bs-OS-seq can uncover vast amounts of methylation variation not detected by commonly used array methods. We found that high-density methylation information from even one gene can delineate the main white blood cell lineages. CONCLUSIONS We conclude that high-resolution methylation studies can yield clinically important information at selected specific loci missed by array-based methods, with potential implications for future studies of methylation-disease associations.
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Affiliation(s)
- Cilla Söderhäll
- Department of Biosciences and Nutrition, Karolinska Institutet, Stockholm, Sweden. .,Department of Women's and Children's Health, Karolinska Institutet, Bioclinicum J9:30, Visionsgatan 4, 171 64, Stockholm, Sweden. .,Department of Pediatric Allergy and Pulmonology, Astrid Lindgren Children's Hospital, Karolinska University Hospital, Stockholm, Sweden.
| | - Lovisa E Reinius
- Department of Biosciences and Nutrition, Karolinska Institutet, Stockholm, Sweden
| | | | | | - Nathalie Acevedo
- Department of Clinical Science and Education, Karolinska Institutet, and Sachs' Children and Youth Hospital, Södersjukhuset, 118 83, Stockholm, Sweden.,Institute for Immunological Research, University of Cartagena, Cartagena, Colombia
| | - Jon R Konradsen
- Department of Women's and Children's Health, Karolinska Institutet, Bioclinicum J9:30, Visionsgatan 4, 171 64, Stockholm, Sweden.,Department of Pediatric Allergy and Pulmonology, Astrid Lindgren Children's Hospital, Karolinska University Hospital, Stockholm, Sweden
| | - Björn Nordlund
- Department of Women's and Children's Health, Karolinska Institutet, Bioclinicum J9:30, Visionsgatan 4, 171 64, Stockholm, Sweden.,Department of Pediatric Allergy and Pulmonology, Astrid Lindgren Children's Hospital, Karolinska University Hospital, Stockholm, Sweden
| | - Gunilla Hedlin
- Department of Women's and Children's Health, Karolinska Institutet, Bioclinicum J9:30, Visionsgatan 4, 171 64, Stockholm, Sweden.,Department of Pediatric Allergy and Pulmonology, Astrid Lindgren Children's Hospital, Karolinska University Hospital, Stockholm, Sweden
| | - Annika Scheynius
- Department of Clinical Science and Education, Karolinska Institutet, and Sachs' Children and Youth Hospital, Södersjukhuset, 118 83, Stockholm, Sweden.,Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden
| | | | - Juha Kere
- Department of Biosciences and Nutrition, Karolinska Institutet, Stockholm, Sweden.,Folkhälsan Research Center, Helsinki, Finland.,Stem Cells and Metabolism Research Program, University of Helsinki, Helsinki, Finland
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Xu Z, Taylor JA. Reliability of DNA methylation measures using Illumina methylation BeadChip. Epigenetics 2021; 16:495-502. [PMID: 32749174 PMCID: PMC8078668 DOI: 10.1080/15592294.2020.1805692] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 07/07/2020] [Accepted: 07/24/2020] [Indexed: 12/22/2022] Open
Abstract
Illumina BeadChips are widely utilized in epigenome-wide association studies (EWAS). Several studies have reported that many probes on these arrays have poor reliability. Here, we compare different pre-processing methods to improve intra-class correlation coefficients (ICC). We describe the characteristics of ICC across the genome, within and between studies, and across different array platforms. Using technical duplicates from 128 subjects, we find that with raw data only 22.5% of the CpGs on 450 K array have 'acceptable' ICCs (>0.5). Data preprocessing steps, such as background correction and dye bias correction, can reduce technical noise and improve the percentage to 38.5%. Similar to previous studies, we found that ICC is associated with CpG methylation level such that 83% of CpGs with intermediate methylation (0.1< beta-value <0.9) have acceptable ICCs, whereas only 21% of CpGs with low or high methylation (beta-value <0.1 or >0.9) have acceptable ICCs. ICC is also correlated with CpG methylation variance; after mutual adjustment for beta-value and variance, only variance remains correlated. Many CpGs with poor ICCs (<0.5) are located in biologically important regulatory regions, including gene promoters and CpG islands. Poor ICC at these sites appears to be a consequence of low biologic variation among individuals rather than increased technical measurement variation. ICCs quality classifications are highly concordant across different array platforms and across different studies. We find that ICC can be reliably estimated with 30 pairs of duplicate samples. CpGs with acceptable ICC have higher study power and are more commonly reported in published epigenome-wide studies.
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Affiliation(s)
- Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Jack A. Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
- Epigenetics & Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
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Whalley C, Payne K, Domingo E, Blake A, Richman S, Brooks J, Batis N, Spruce R, Mehanna H, Nankivell P, Beggs AD. Ultra-Low DNA Input into Whole Genome Methylation Assays and Detection of Oncogenic Methylation and Copy Number Variants in Circulating Tumour DNA. EPIGENOMES 2021; 5:6. [PMID: 33777442 PMCID: PMC7610445 DOI: 10.3390/epigenomes5010006] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 02/06/2021] [Accepted: 02/12/2021] [Indexed: 11/28/2022] Open
Abstract
Abnormal CpG methylation in cancer is ubiquitous and generally detected in tumour specimens using a variety of techniques at a resolution encompassing single CpG loci to genome wide coverage. Analysis of samples with very low DNA inputs, such as formalin fixed (FFPE) biopsy specimens from clinical trials or circulating tumour DNA is challenging at the genome-wide level because of lack of available input. We present the results of low input experiments into the Illumina Infinium HD methylation assay on FFPE specimens and ctDNA samples. METHODS For all experiments, the Infinium HD assay for methylation was used. In total, forty-eight FFPE specimens were used at varying concentrations (lowest input 50 ng); eighteen blood derived specimens (lowest input 10 ng) and six matched ctDNA input (lowest input 10 ng)/fresh tumour specimens (lowest input 250 ng) were processed. Downstream analysis was performed in R/Bioconductor for quality control metrics and differential methylation analysis as well as copy number calls. RESULTS Correlation coefficients for CpG methylation were high at the probe level averaged R2 = 0.99 for blood derived samples and R2 > 0.96 for the FFPE samples. When matched ctDNA/fresh tumour samples were compared, R2 > 0.91 between the two. Results of differential methylation analysis did not vary significantly by DNA input in either the blood or FFPE groups. There were differences seen in the ctDNA group as compared to their paired tumour sample, possibly because of enrichment for tumour material without contaminating normal. Copy number variants observed in the tumour were generally also seen in the paired ctDNA sample with good concordance via DQ plot. CONCLUSIONS The Illumina Infinium HD methylation assay can robustly detect methylation across a range of sample types, including ctDNA, down to an input of 10 ng. It can also reliably detect oncogenic methylation changes and copy number variants in ctDNA. These findings demonstrate that these samples can now be accessed by methylation array technology, allowing analysis of these important sample types.
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Affiliation(s)
- Celina Whalley
- Institute of Cancer & Genomic Sciences, University of Birmingham, Vincent Drive, Birmingham B15 2TT, UK; (C.W.); (K.P.); (J.B.); (N.B.); (R.S.); (H.M.); (P.N.)
| | - Karl Payne
- Institute of Cancer & Genomic Sciences, University of Birmingham, Vincent Drive, Birmingham B15 2TT, UK; (C.W.); (K.P.); (J.B.); (N.B.); (R.S.); (H.M.); (P.N.)
| | - Enric Domingo
- Department of Oncology, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, UK; (E.D.); (A.B.)
| | - Andrew Blake
- Department of Oncology, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, UK; (E.D.); (A.B.)
| | - Susan Richman
- Pathology and Data Analytics, Leeds Institute of Medical Research, St James University Hospital, Leeds LS2 9JT, UK;
| | - Jill Brooks
- Institute of Cancer & Genomic Sciences, University of Birmingham, Vincent Drive, Birmingham B15 2TT, UK; (C.W.); (K.P.); (J.B.); (N.B.); (R.S.); (H.M.); (P.N.)
| | - Nikolaos Batis
- Institute of Cancer & Genomic Sciences, University of Birmingham, Vincent Drive, Birmingham B15 2TT, UK; (C.W.); (K.P.); (J.B.); (N.B.); (R.S.); (H.M.); (P.N.)
| | - Rachel Spruce
- Institute of Cancer & Genomic Sciences, University of Birmingham, Vincent Drive, Birmingham B15 2TT, UK; (C.W.); (K.P.); (J.B.); (N.B.); (R.S.); (H.M.); (P.N.)
| | | | - Hisham Mehanna
- Institute of Cancer & Genomic Sciences, University of Birmingham, Vincent Drive, Birmingham B15 2TT, UK; (C.W.); (K.P.); (J.B.); (N.B.); (R.S.); (H.M.); (P.N.)
| | - Paul Nankivell
- Institute of Cancer & Genomic Sciences, University of Birmingham, Vincent Drive, Birmingham B15 2TT, UK; (C.W.); (K.P.); (J.B.); (N.B.); (R.S.); (H.M.); (P.N.)
| | - Andrew D. Beggs
- Institute of Cancer & Genomic Sciences, University of Birmingham, Vincent Drive, Birmingham B15 2TT, UK; (C.W.); (K.P.); (J.B.); (N.B.); (R.S.); (H.M.); (P.N.)
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Abstract
PURPOSE OF REVIEW Osteoarthritis is a heterogeneous, multifactorial condition regulated by complex biological interactions at multiple levels. Comprehensive understanding of these regulatory interactions is required to develop feasible advances to improve patient outcomes. Improvements in technology have made extensive genomic, transcriptomic, epigenomic, proteomic, and metabolomic profiling possible. This review summarizes findings over the past 20 months related to omics technologies in osteoarthritis and examines how using a multiomics approach is necessary for advancing our understanding of osteoarthritis as a disease to improve precision osteoarthritis treatments. RECENT FINDINGS Using the search terms 'genomics' or 'transcriptomics' or 'epigenomics' or 'proteomics' or 'metabolomics' and 'osteoarthritis' from January 1, 2018 to August 31, 2019, we identified advances in omics approaches applied to osteoarthritis. Trends include untargeted whole genome, transcriptome, proteome, and metabolome analyses leading to identification of novel molecular signatures, cell subpopulations and multiomics validation approaches. SUMMARY To address the complexity of osteoarthritis, integration of multitissue analyses by multiomics approaches with the inclusion of longitudinal clinical data is necessary for a comprehensive understanding of the disease process, and for appropriate development of efficacious diagnostics, prognostics, and biotherapeutics.
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Kandaswamy R, Hannon E, Arseneault L, Mansell G, Sugden K, Williams B, Burrage J, Staley JR, Pishva E, Dahir A, Roberts S, Danese A, Mill J, Fisher HL, Wong CCY. DNA methylation signatures of adolescent victimization: analysis of a longitudinal monozygotic twin sample. Epigenetics 2020; 16:1169-1186. [PMID: 33371772 PMCID: PMC8813077 DOI: 10.1080/15592294.2020.1853317] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Accumulating evidence suggests that individuals exposed to victimization at key developmental stages may have different epigenetic fingerprints compared to those exposed to no/minimal stressful events, however results are inconclusive. This study aimed to strengthen causal inference regarding the impact of adolescent victimization on the epigenome by controlling for genetic variation, age, gender, and shared environmental exposures. We conducted longitudinal epigenome-wide association analyses (EWAS) on DNA methylation (DNAm) profiles of 118 monozygotic (MZ) twin pairs from the Environmental Risk study with and without severe adolescent victimization generated using buccal DNA collected at ages 5, 10 and 18, and the Illumina EPIC array. Additionally, we performed cross-sectional EWAS on age-18 blood and buccal DNA from the same individuals to elucidate tissue-specific signatures of severe adolescent victimization. Our analyses identified 20 suggestive differentially methylated positions (DMPs) (P < 5e-05), with altered DNAm trajectories between ages 10–18 associated with severe adolescent victimization (∆Beta range = −5.5%−5.3%). Age-18 cross-sectional analyses revealed 72 blood (∆Beta range = −2.2%−3.4%) and 42 buccal (∆Beta range = −3.6%−4.6%) suggestive severe adolescent victimization-associated DMPs, with some evidence of convergent signals between these two tissue types. Downstream regional analysis identified significant differentially methylated regions (DMRs) in LGR6 and ANK3 (Šidák P = 5e-09 and 4.07e-06), and one upstream of CCL27 (Šidák P = 2.80e-06) in age-18 blood and buccal EWAS, respectively. Our study represents the first longitudinal MZ twin analysis of DNAm and severe adolescent victimization, providing initial evidence for altered DNA methylomic signatures in individuals exposed to adolescent victimization.
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Affiliation(s)
- Radhika Kandaswamy
- King's College London, Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, London, UK
| | - Eilis Hannon
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Louise Arseneault
- King's College London, Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, London, UK.,ESRC Centre for Society & Mental Health, King's College London, London, UK
| | - Georgina Mansell
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Karen Sugden
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Benjamin Williams
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Joe Burrage
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - James R Staley
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ehsan Pishva
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Aisha Dahir
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Susanna Roberts
- King's College London, Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, London UK
| | - Andrea Danese
- King's College London, Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, London, UK.,King's College London, Department of Child & Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, London UK.,National & Specialist CAMHS Clinic for Trauma, Anxiety and Depression, South London & Maudsley NHS Foundation Trust, London, UK
| | - Jonathan Mill
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Helen L Fisher
- King's College London, Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, London, UK.,ESRC Centre for Society & Mental Health, King's College London, London, UK
| | - Chloe C Y Wong
- King's College London, Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, London, UK
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Hop PJ, Zwamborn RAJ, Hannon EJ, Dekker AM, van Eijk K, Walker E, Iacoangeli A, Jones A, Shatunov A, Khleifat AA, Opie-Martin S, Shaw C, Morrison K, Shaw P, McLaughlin R, Hardiman O, Al-Chalabi A, Van Den Berg L, Mill J, Veldink JH. Cross-reactive probes on Illumina DNA methylation arrays: a large study on ALS shows that a cautionary approach is warranted in interpreting epigenome-wide association studies. NAR Genom Bioinform 2020; 2:lqaa105. [PMID: 33554115 PMCID: PMC7745769 DOI: 10.1093/nargab/lqaa105] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 10/27/2020] [Accepted: 11/25/2020] [Indexed: 12/11/2022] Open
Abstract
Illumina DNA methylation arrays are a widely used tool for performing genome-wide DNA methylation analyses. However, measurements obtained from these arrays may be affected by technical artefacts that result in spurious associations if left unchecked. Cross-reactivity represents one of the major challenges, meaning that probes may map to multiple regions in the genome. Although several studies have reported on this issue, few studies have empirically examined the impact of cross-reactivity in an epigenome-wide association study (EWAS). In this paper, we report on cross-reactivity issues that we discovered in a large EWAS on the presence of the C9orf72 repeat expansion in ALS patients. Specifically, we found that that the majority of the significant probes inadvertently cross-hybridized to the C9orf72 locus. Importantly, these probes were not flagged as cross-reactive in previous studies, leading to novel insights into the extent to which cross-reactivity can impact EWAS. Our findings are particularly relevant for epigenetic studies into diseases associated with repeat expansions and other types of structural variation. More generally however, considering that most spurious associations were not excluded based on pre-defined sets of cross-reactive probes, we believe that the presented data-driven flag and consider approach is relevant for any type of EWAS.
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Affiliation(s)
- Paul J Hop
- Department of Neurology, UMC Utrecht Brain Center, 3584 CG, Utrecht, the Netherlands
| | - Ramona A J Zwamborn
- Department of Neurology, UMC Utrecht Brain Center, 3584 CG, Utrecht, the Netherlands
| | - Eilis J Hannon
- University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK
| | - Annelot M Dekker
- Department of Neurology, UMC Utrecht Brain Center, 3584 CG, Utrecht, the Netherlands
| | - Kristel R van Eijk
- Department of Neurology, UMC Utrecht Brain Center, 3584 CG, Utrecht, the Netherlands
| | - Emma M Walker
- University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK
| | - Alfredo Iacoangeli
- Department of Basic and Clinical Neuroscience, King’s College London, Maurice Wohl Clinical Neuroscience Institute, London SE5 9RS, UK
- Department of Biostatistics and Health Informatics, King’s College London, London SE5 8AF, UK
| | - Ashley R Jones
- Department of Basic and Clinical Neuroscience, King’s College London, Maurice Wohl Clinical Neuroscience Institute, London SE5 9RS, UK
| | - Aleksey Shatunov
- Department of Basic and Clinical Neuroscience, King’s College London, Maurice Wohl Clinical Neuroscience Institute, London SE5 9RS, UK
| | - Ahmad Al Khleifat
- Department of Basic and Clinical Neuroscience, King’s College London, Maurice Wohl Clinical Neuroscience Institute, London SE5 9RS, UK
| | - Sarah Opie-Martin
- Department of Basic and Clinical Neuroscience, King’s College London, Maurice Wohl Clinical Neuroscience Institute, London SE5 9RS, UK
| | - Christopher E Shaw
- Department of Basic and Clinical Neuroscience, King’s College London, Maurice Wohl Clinical Neuroscience Institute, London SE5 9RS, UK
- UK Dementia Research Institute, King’s College London, London WC2R 2LS, UK
| | - Karen E Morrison
- Faculty of Medicine, Health & Life Sciences, Queen’s University Belfast, 90 Lisburn Road, Belfast, BT9 6AG, Northern Ireland, UK
| | - Pamela J Shaw
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield S10 2HQ, UK
| | - Russell L McLaughlin
- Complex Trait Genomics Laboratory, Smurfit Institute of Genetics, Trinity College Dublin, Dublin D02 DK07, Republic of Ireland
| | - Orla Hardiman
- Academic Unit of Neurology, Trinity College Dublin, Trinity Biomedical Sciences Institute, Dublin D02 PN40, Republic of Ireland
- Department of Neurology, Beaumont Hospital, Dublin D02 PN40, Republic of Ireland
| | - Ammar Al-Chalabi
- Department of Basic and Clinical Neuroscience, King’s College London, Maurice Wohl Clinical Neuroscience Institute, London SE5 9RS, UK
- Department of Neurology, King’s College Hospital, Bessemer Road, London, SE5 9RX, UK
| | | | - Jonathan Mill
- University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK
| | - Jan H Veldink
- Department of Neurology, UMC Utrecht Brain Center, 3584 CG, Utrecht, the Netherlands
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Vehmeijer FOL, Küpers LK, Sharp GC, Salas LA, Lent S, Jima DD, Tindula G, Reese S, Qi C, Gruzieva O, Page C, Rezwan FI, Melton PE, Nohr E, Escaramís G, Rzehak P, Heiskala A, Gong T, Tuominen ST, Gao L, Ross JP, Starling AP, Holloway JW, Yousefi P, Aasvang GM, Beilin LJ, Bergström A, Binder E, Chatzi L, Corpeleijn E, Czamara D, Eskenazi B, Ewart S, Ferre N, Grote V, Gruszfeld D, Håberg SE, Hoyo C, Huen K, Karlsson R, Kull I, Langhendries JP, Lepeule J, Magnus MC, Maguire RL, Molloy PL, Monnereau C, Mori TA, Oken E, Räikkönen K, Rifas-Shiman S, Ruiz-Arenas C, Sebert S, Ullemar V, Verduci E, Vonk JM, Xu CJ, Yang IV, Zhang H, Zhang W, Karmaus W, Dabelea D, Muhlhausler BS, Breton CV, Lahti J, Almqvist C, Jarvelin MR, Koletzko B, Vrijheid M, Sørensen TIA, Huang RC, Arshad SH, Nystad W, Melén E, Koppelman GH, London SJ, Holland N, Bustamante M, Murphy SK, Hivert MF, Baccarelli A, Relton CL, Snieder H, Jaddoe VWV, Felix JF. DNA methylation and body mass index from birth to adolescence: meta-analyses of epigenome-wide association studies. Genome Med 2020; 12:105. [PMID: 33239103 PMCID: PMC7687793 DOI: 10.1186/s13073-020-00810-w] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Accepted: 11/12/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND DNA methylation has been shown to be associated with adiposity in adulthood. However, whether similar DNA methylation patterns are associated with childhood and adolescent body mass index (BMI) is largely unknown. More insight into this relationship at younger ages may have implications for future prevention of obesity and its related traits. METHODS We examined whether DNA methylation in cord blood and whole blood in childhood and adolescence was associated with BMI in the age range from 2 to 18 years using both cross-sectional and longitudinal models. We performed meta-analyses of epigenome-wide association studies including up to 4133 children from 23 studies. We examined the overlap of findings reported in previous studies in children and adults with those in our analyses and calculated enrichment. RESULTS DNA methylation at three CpGs (cg05937453, cg25212453, and cg10040131), each in a different age range, was associated with BMI at Bonferroni significance, P < 1.06 × 10-7, with a 0.96 standard deviation score (SDS) (standard error (SE) 0.17), 0.32 SDS (SE 0.06), and 0.32 BMI SDS (SE 0.06) higher BMI per 10% increase in methylation, respectively. DNA methylation at nine additional CpGs in the cross-sectional childhood model was associated with BMI at false discovery rate significance. The strength of the associations of DNA methylation at the 187 CpGs previously identified to be associated with adult BMI, increased with advancing age across childhood and adolescence in our analyses. In addition, correlation coefficients between effect estimates for those CpGs in adults and in children and adolescents also increased. Among the top findings for each age range, we observed increasing enrichment for the CpGs that were previously identified in adults (birth Penrichment = 1; childhood Penrichment = 2.00 × 10-4; adolescence Penrichment = 2.10 × 10-7). CONCLUSIONS There were only minimal associations of DNA methylation with childhood and adolescent BMI. With the advancing age of the participants across childhood and adolescence, we observed increasing overlap with altered DNA methylation loci reported in association with adult BMI. These findings may be compatible with the hypothesis that DNA methylation differences are mostly a consequence rather than a cause of obesity.
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Affiliation(s)
- Florianne O L Vehmeijer
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Room Na-2918, Erasmus MC, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Leanne K Küpers
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands
| | - Gemma C Sharp
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Lucas A Salas
- Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Samantha Lent
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Dereje D Jima
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA
- Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, USA
| | - Gwen Tindula
- Children's Environmental Health Laboratory, Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
| | - Sarah Reese
- Department of Health and Human Services, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Cancan Qi
- University of Groningen, University Medical Center Groningen, Department of Pediatric Pulmonology and Pediatric Allergy, Beatrix Children's Hospital, Groningen, The Netherlands
- University Medical Center Groningen GRIAC Research Institute, University of Groningen, Groningen, the Netherlands
| | - Olena Gruzieva
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Centre for Occupational and Environmental Medicine, Region Stockholm, Stockholm, Sweden
| | - Christian Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Oslo Centre for Biostatistics and Epidemiology, Oslo University Hospital, Oslo, Norway
| | - Faisal I Rezwan
- School of Water, Energy and Environment, Cranfield University, Cranfield, Bedfordshire, UK
- Human Development and Health, Faculty of Medicine, Southampton General Hospital, University of Southampton, Southampton, UK
| | - Philip E Melton
- School of Pharmacy and Biomedical Sciences, Curtin University, Bentley, Western Australia, Australia
- School of Biomedical Sciences, The University of Western Australia, Crawley, Western Austalia, Australia
| | - Ellen Nohr
- Centre for Women's, Family and Child Health, University of South-Eastern Norway, Kongsberg, Norway
- Institute of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Geòrgia Escaramís
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
- Research group on Statistics, Econometrics and Health (GRECS), University of Girona, Girona, Spain
| | - Peter Rzehak
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - Anni Heiskala
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Tong Gong
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Samuli T Tuominen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Lu Gao
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jason P Ross
- CSIRO Health and Biosecurity, North Ryde, New South Wales, Australia
| | - Anne P Starling
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - John W Holloway
- Human Development and Health, Faculty of Medicine, Southampton General Hospital, University of Southampton, Southampton, UK
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Paul Yousefi
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Gunn Marit Aasvang
- Department of Air Pollution and Noise, Norwegian Institute of Public Health, Oslo, Norway
| | | | - Anna Bergström
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Centre for Occupational and Environmental Medicine, Region Stockholm, Stockholm, Sweden
| | - Elisabeth Binder
- Department of Translational Research in Psychiatry, Max-Planck-Institute of Psychiatry, Munich, Germany
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Leda Chatzi
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Eva Corpeleijn
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands
| | - Darina Czamara
- Department of Translational Research in Psychiatry, Max-Planck-Institute of Psychiatry, Munich, Germany
| | - Brenda Eskenazi
- Center for Environmental Research and Children's Health, School of Public Health, University of California, Berkeley, CA, USA
| | - Susan Ewart
- College of Veterinary Medicine, Michigan State University, East Lansing, MI, USA
| | - Natalia Ferre
- Pediatrics, Nutrition and Development Research Unit, Universitat Rovira i Virgili, IISPV, Reus, Spain
| | - Veit Grote
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - Dariusz Gruszfeld
- Neonatal Department, Children's Memorial Health Institute, Warsaw, Poland
| | - Siri E Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Cathrine Hoyo
- Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, USA
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
| | - Karen Huen
- Children's Environmental Health Laboratory, Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Inger Kull
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
- Sachs' Children and Youth Hospital, Södersjukhuset, Stockholm, Sweden
| | | | - Johanna Lepeule
- Université Grenoble Alpes, Inserm, CNRS, Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, IAB, Grenoble, France
| | - Maria C Magnus
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Rachel L Maguire
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
- Department of Obstetrics and Gynecology, Duke University Medical Center, Raleigh, NC, USA
| | - Peter L Molloy
- CSIRO Health and Biosecurity, North Ryde, New South Wales, Australia
| | - Claire Monnereau
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Room Na-2918, Erasmus MC, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Trevor A Mori
- Medical School, University of Western Australia, Perth, Australia
| | - Emily Oken
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Katri Räikkönen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Sheryl Rifas-Shiman
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Carlos Ruiz-Arenas
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Sylvain Sebert
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Vilhelmina Ullemar
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Elvira Verduci
- Department of Pediatrics, San Paolo Hospital, University of Milan, Milan, Italy
| | - Judith M Vonk
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands
- University Medical Center Groningen GRIAC Research Institute, University of Groningen, Groningen, the Netherlands
| | - Cheng-Jian Xu
- University of Groningen, University Medical Center Groningen, Department of Pediatric Pulmonology and Pediatric Allergy, Beatrix Children's Hospital, Groningen, The Netherlands
- University Medical Center Groningen GRIAC Research Institute, University of Groningen, Groningen, the Netherlands
- Department of Gastroenterology, Hepatology and Endocrinology, CiiM, Centre for Individualised Infection Medicine, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - Ivana V Yang
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA
- Center for Genes, Environment and Health, National Jewish Health, Denver, CO, USA
| | - Hongmei Zhang
- Division of Epidemiology, Biostatistics, and Environmental Health, University of Memphis, Memphis, TN, USA
| | - Weiming Zhang
- Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO, USA
| | - Wilfried Karmaus
- Division of Epidemiology, Biostatistics, and Environmental Health, University of Memphis, Memphis, TN, USA
| | - Dana Dabelea
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Pediatrics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | | | - Carrie V Breton
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jari Lahti
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Turku Institute for Advanced Studies, University of Turku, Turku, Finland
| | - Catarina Almqvist
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Pediatric Allergy and Pulmonology Unit at Astrid Lindgren Children's Hospital, Karolinska University Hospital, Stockholm, Sweden
| | - Marjo-Riitta Jarvelin
- 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
- Unit of Primary Health Care, Oulu University Hospital, OYS, Oulu, Finland
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
| | - Berthold Koletzko
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - Martine Vrijheid
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Thorkild I A Sørensen
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Department of Public Health, Section of Epidemiology, and The Novo Nordisk Foundation Center for Basic Metabolic Research, Section on Metabolic Genetics, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Rae-Chi Huang
- Telethon Kids Institute, University of Western Australia, Perth, Australia
| | - Syed Hasan Arshad
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
- David Hide Asthma and Allergy Research Centre, Isle of Wight, UK
| | - Wenche Nystad
- Department of Chronic Diseases and Ageing, Norwegian Institute of Public Health, Oslo, Norway
| | - Erik Melén
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
- Sachs' Children and Youth Hospital, Södersjukhuset, Stockholm, Sweden
| | - Gerard H Koppelman
- University of Groningen, University Medical Center Groningen, Department of Pediatric Pulmonology and Pediatric Allergy, Beatrix Children's Hospital, Groningen, The Netherlands
- University Medical Center Groningen GRIAC Research Institute, University of Groningen, Groningen, the Netherlands
| | - Stephanie J London
- Department of Health and Human Services, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Nina Holland
- Children's Environmental Health Laboratory, Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
| | - Mariona Bustamante
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Susan K Murphy
- Department of Obstetrics and Gynecology, Duke University Medical Center, Raleigh, NC, USA
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Universite de Sherbrooke, Sherbrooke, QC, Canada
| | - Andrea Baccarelli
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Harold Snieder
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands
| | - Vincent W V Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Room Na-2918, Erasmus MC, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Janine F Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Room Na-2918, Erasmus MC, PO Box 2040, 3000 CA, Rotterdam, the Netherlands.
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
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Aristizabal MJ, Anreiter I, Halldorsdottir T, Odgers CL, McDade TW, Goldenberg A, Mostafavi S, Kobor MS, Binder EB, Sokolowski MB, O'Donnell KJ. Biological embedding of experience: A primer on epigenetics. Proc Natl Acad Sci U S A 2020; 117:23261-23269. [PMID: 31624126 PMCID: PMC7519272 DOI: 10.1073/pnas.1820838116] [Citation(s) in RCA: 109] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Biological embedding occurs when life experience alters biological processes to affect later life health and well-being. Although extensive correlative data exist supporting the notion that epigenetic mechanisms such as DNA methylation underlie biological embedding, causal data are lacking. We describe specific epigenetic mechanisms and their potential roles in the biological embedding of experience. We also consider the nuanced relationships between the genome, the epigenome, and gene expression. Our ability to connect biological embedding to the epigenetic landscape in its complexity is challenging and complicated by the influence of multiple factors. These include cell type, age, the timing of experience, sex, and DNA sequence. Recent advances in molecular profiling and epigenome editing, combined with the use of comparative animal and human longitudinal studies, should enable this field to transition from correlative to causal analyses.
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Affiliation(s)
- Maria J Aristizabal
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, M5S 3B2, Canada
- Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics, and BC Children's Hospital Research Institute, University of British Columbia, Vancouver, BC, V52 4H4, Canada
- Program in Child and Brain Development, CIFAR, MaRS Centre, Toronto, ON, M5G 1M1, Canada
| | - Ina Anreiter
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, M5S 3B2, Canada
- Program in Child and Brain Development, CIFAR, MaRS Centre, Toronto, ON, M5G 1M1, Canada
| | - Thorhildur Halldorsdottir
- Centre of Public Health Sciences, Faculty of Medicine, University of Iceland, 101, Reykjavik, Iceland
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, 80804, Munich, Germany
| | - Candice L Odgers
- Program in Child and Brain Development, CIFAR, MaRS Centre, Toronto, ON, M5G 1M1, Canada
- Department of Psychological Science, University of California, Irvine, CA 92697
- Sanford School of Public Policy, Duke University, Durham, NC 27708
| | - Thomas W McDade
- Program in Child and Brain Development, CIFAR, MaRS Centre, Toronto, ON, M5G 1M1, Canada
- Department of Anthropology, Northwestern University, Evanston, IL 60208
- Institute for Policy Research, Northwestern University, Evanston, IL 60208
| | - Anna Goldenberg
- Program in Child and Brain Development, CIFAR, MaRS Centre, Toronto, ON, M5G 1M1, Canada
- Department of Computer Science, Hospital for Sick Children, Vector Institute, University of Toronto, Toronto, ON, M5G OA4, Canada
| | - Sara Mostafavi
- Program in Child and Brain Development, CIFAR, MaRS Centre, Toronto, ON, M5G 1M1, Canada
- Department of Statistics, BC Children's Hospital Research Institute, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
| | - Michael S Kobor
- Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics, and BC Children's Hospital Research Institute, University of British Columbia, Vancouver, BC, V52 4H4, Canada
- Program in Child and Brain Development, CIFAR, MaRS Centre, Toronto, ON, M5G 1M1, Canada
| | - Elisabeth B Binder
- Program in Child and Brain Development, CIFAR, MaRS Centre, Toronto, ON, M5G 1M1, Canada
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, 80804, Munich, Germany
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA 30329
| | - Marla B Sokolowski
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, M5S 3B2, Canada;
- Program in Child and Brain Development, CIFAR, MaRS Centre, Toronto, ON, M5G 1M1, Canada
| | - Kieran J O'Donnell
- Program in Child and Brain Development, CIFAR, MaRS Centre, Toronto, ON, M5G 1M1, Canada;
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Hospital Research Centre, Department of Psychiatry, McGill University, Montreal, QC, H4H 1R3, Canada
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50
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Ryan CP. "Epigenetic clocks": Theory and applications in human biology. Am J Hum Biol 2020; 33:e23488. [PMID: 32845048 DOI: 10.1002/ajhb.23488] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2020] [Revised: 07/23/2020] [Accepted: 07/24/2020] [Indexed: 12/20/2022] Open
Abstract
All humans age, but how we age-and how fast-differs considerably from person to person. This deviation between apparent age and chronological age is often referred to as "biological age" (BA) and until recently robust tools for studying BA have been scarce. "Epigenetic clocks" are starting to change this. Epigenetic clocks use predictable changes in the epigenome, usually DNA methylation, to estimate chronological age with unprecedented accuracy. More importantly, deviations between epigenetic age and chronological age predict a broad range of health outcomes and mortality risks better than chronological age alone. Thus, epigenetic clocks appear to capture fundamental molecular processes tied to BA and can serve as powerful tools for studying health, development, and aging across the lifespan. In this article, I review epigenetic clocks, especially as they relate to key theoretical and applied issues in human biology. I first provide an overview of how epigenetic clocks are constructed and what we know about them. I then discuss emerging applications of particular relevance to human biologists-those related to reproduction, life-history, stress, and the environment. I conclude with an overview of the methods necessary for implementing epigenetic clocks, including considerations of study design, sample collection, and technical considerations for processing and interpreting epigenetic clocks. The goal of this review is to highlight some of the ways that epigenetic clocks can inform questions in human biology, and vice versa, and to provide human biologists with the foundational knowledge necessary to successfully incorporate epigenetic clocks into their research.
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Affiliation(s)
- Calen P Ryan
- Department of Anthropology, Northwestern University, Evanston, Illinois, USA
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