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Ziemann M, Abeysooriya M, Bora A, Lamon S, Kasu MS, Norris MW, Wong YT, Craig JM. Direction-aware functional class scoring enrichment analysis of infinium DNA methylation data. Epigenetics 2024; 19:2375022. [PMID: 38967555 PMCID: PMC11229754 DOI: 10.1080/15592294.2024.2375022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Accepted: 06/26/2024] [Indexed: 07/06/2024] Open
Abstract
Infinium Methylation BeadChip arrays remain one of the most popular platforms for epigenome-wide association studies, but tools for downstream pathway analysis have their limitations. Functional class scoring (FCS) is a group of pathway enrichment techniques that involve the ranking of genes and evaluation of their collective regulation in biological systems, but the implementations described for Infinium methylation array data do not retain direction information, which is important for mechanistic understanding of genomic regulation. Here, we evaluate several candidate FCS methods that retain directional information. According to simulation results, the best-performing method involves the mean aggregation of probe limma t-statistics by gene followed by a rank-ANOVA enrichment test using the mitch package. This method, which we call 'LAM,' outperformed an existing over-representation analysis method in simulations, and showed higher sensitivity and robustness in an analysis of real lung tumour-normal paired datasets. Using matched RNA-seq data, we examine the relationship of methylation differences at promoters and gene bodies with RNA expression at the level of pathways in lung cancer. To demonstrate the utility of our approach, we apply it to three other contexts where public data were available. First, we examine the differential pathway methylation associated with chronological age. Second, we investigate pathway methylation differences in infants conceived with in vitro fertilization. Lastly, we analyse differential pathway methylation in 19 disease states, identifying hundreds of novel associations. These results show LAM is a powerful method for the detection of differential pathway methylation complementing existing methods. A reproducible vignette is provided to illustrate how to implement this method.
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Affiliation(s)
- Mark Ziemann
- Bioinformatics Working Group, Burnet Institute, Melbourne, Australia
- School of Life and Environmental Sciences, Deakin University, Geelong, Australia
| | - Mandhri Abeysooriya
- School of Life and Environmental Sciences, Deakin University, Geelong, Australia
- School of Exercise and Nutrition Sciences, Institute for Physical Activity and Nutrition, Deakin University, Geelong, Australia
| | - Anusuiya Bora
- Bioinformatics Working Group, Burnet Institute, Melbourne, Australia
- School of Life and Environmental Sciences, Deakin University, Geelong, Australia
| | - Séverine Lamon
- School of Exercise and Nutrition Sciences, Institute for Physical Activity and Nutrition, Deakin University, Geelong, Australia
| | - Mary Sravya Kasu
- School of Life and Environmental Sciences, Deakin University, Geelong, Australia
| | - Mitchell W. Norris
- School of Life and Environmental Sciences, Deakin University, Geelong, Australia
| | - Yen Ting Wong
- School of Medicine, Deakin University, Geelong, Australia
- Murdoch Children’s Research Institute, Melbourne, Australia
| | - Jeffrey M. Craig
- School of Medicine, Deakin University, Geelong, Australia
- Murdoch Children’s Research Institute, Melbourne, Australia
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2
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Ma S, Pan X, Gan J, Guo X, He J, Hu H, Wang Y, Ning S, Zhi H. DNA methylation heterogeneity attributable to a complex tumor immune microenvironment prompts prognostic risk in glioma. Epigenetics 2024; 19:2318506. [PMID: 38439715 PMCID: PMC10936651 DOI: 10.1080/15592294.2024.2318506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 02/07/2024] [Indexed: 03/06/2024] Open
Abstract
Gliomas are malignant tumours of the human nervous system with different World Health Organization (WHO) classifications, glioblastoma (GBM) with higher grade and are more malignant than lower-grade glioma (LGG). To dissect how the DNA methylation heterogeneity in gliomas is influenced by the complex cellular composition of the tumour immune microenvironment, we first compared the DNA methylation profiles of purified human immune cells and bulk glioma tissue, stratifying three tumour immune microenvironmental subtypes for GBM and LGG samples from The Cancer Genome Atlas (TCGA). We found that more intermediate methylation sites were enriched in glioma tumour tissues, and used the Proportion of sites with Intermediate Methylation (PIM) to compare intertumoral DNA methylation heterogeneity. A larger PIM score reflected stronger DNA methylation heterogeneity. Enhanced DNA methylation heterogeneity was associated with stronger immune cell infiltration, better survival rates, and slower tumour progression in glioma patients. We then created a Cell-type-associated DNA Methylation Heterogeneity Contribution (CMHC) score to explore the impact of different immune cell types on heterogeneous CpG site (CpGct) in glioma tissues. We identified eight prognosis-related CpGct to construct a risk score: the Cell-type-associated DNA Methylation Heterogeneity Risk (CMHR) score. CMHR was positively correlated with cytotoxic T-lymphocyte infiltration (CTL), and showed better predictive performance for IDH status (AUC = 0.96) and glioma histological phenotype (AUC = 0.81). Furthermore, DNA methylation alterations of eight CpGct might be related to drug treatments of gliomas. In conclusion, we indicated that DNA methylation heterogeneity is associated with a complex tumour immune microenvironment, glioma phenotype, and patient's prognosis.
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Affiliation(s)
- Shuangyue Ma
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- Liangzhu Laboratory, Zhejiang University, Hangzhou, China
| | - Xu Pan
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Jing Gan
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Xiaxin Guo
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Jiaheng He
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Haoyu Hu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Yuncong Wang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Shangwei Ning
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Hui Zhi
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
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3
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Diez-Ahijado L, Cilleros-Portet A, Fernández-Jimenez N, Fernández MF, Guxens M, Julvez J, Llop S, Lopez-Espinosa MJ, Subiza-Pérez M, Lozano M, Ibarluzea J, Sunyer J, Bustamante M, Cosin-Tomas M. Evaluating the association between placenta DNA methylation and cognitive functions in the offspring. Transl Psychiatry 2024; 14:383. [PMID: 39304652 DOI: 10.1038/s41398-024-03094-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 08/31/2024] [Accepted: 09/04/2024] [Indexed: 09/22/2024] Open
Abstract
The placenta plays a crucial role in protecting the fetus from environmental harm and supports the development of its brain. In fact, compromised placental function could predispose an individual to neurodevelopmental disorders. Placental epigenetic modifications, including DNA methylation, could be considered a proxy of placental function and thus plausible mediators of the association between intrauterine environmental exposures and genetics, and childhood and adult mental health. Although neurodevelopmental disorders such as autism spectrum disorder have been investigated in relation to placenta DNA methylation, no studies have addressed the association between placenta DNA methylation and child's cognitive functions. Thus, our goal here was to investigate whether the placental DNA methylation profile measured using the Illumina EPIC array is associated with three different cognitive domains (namely verbal score, perceptive performance score, and general cognitive score) assessed by the McCarthy Scales of Children's functions in childhood at age 4. To this end, we conducted epigenome-wide association analyses, including data from 255 mother-child pairs within the INMA project, and performed a follow-up functional analysis to help the interpretation of the findings. After multiple-testing correction, we found that methylation at 4 CpGs (cg1548200, cg02986379, cg00866476, and cg14113931) was significantly associated with the general cognitive score, and 2 distinct differentially methylated regions (DMRs) (including 27 CpGs) were significantly associated with each cognitive dimension. Interestingly, the genes annotated to these CpGs, such as DAB2, CEP76, PSMG2, or MECOM, are involved in placenta, fetal, and brain development. Moreover, functional enrichment analyses of suggestive CpGs (p < 1 × 10-4) revealed gene sets involved in placenta development, fetus formation, and brain growth. These findings suggest that placental DNA methylation could be a mechanism contributing to the alteration of important pathways in the placenta that have a consequence on the offspring's brain development and cognitive function.
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Affiliation(s)
- Laia Diez-Ahijado
- ISGlobal, Institute for Global Health, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública, Madrid, Spain
| | - Ariadna Cilleros-Portet
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country (UPV/EHU) and Biocruces-Bizkaia Health Research Institute, Basque Country, Spain
| | - Nora Fernández-Jimenez
- Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country (UPV/EHU) and Biocruces-Bizkaia Health Research Institute, Basque Country, Spain
| | - Mariana F Fernández
- CIBER Epidemiología y Salud Pública, Madrid, Spain
- University of Granada, Biomedical Research Centre, Instituto de Investigación Biosanitaria (ibs.GRANADA), Granada, Spain
| | - Monica Guxens
- ISGlobal, Institute for Global Health, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública, Madrid, Spain
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Jordi Julvez
- ISGlobal, Institute for Global Health, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública, Madrid, Spain
- Clinical and Epidemiological Neuroscience, Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
| | - Sabrina Llop
- CIBER Epidemiología y Salud Pública, Madrid, Spain
- Epidemiology and Environmental Health Joint Research Unit, FISABIO-Public Health, FISABIO-Universitat Jaume I-Universitat de València, Valencia, Spain
| | - Maria-Jose Lopez-Espinosa
- CIBER Epidemiología y Salud Pública, Madrid, Spain
- Epidemiology and Environmental Health Joint Research Unit, FISABIO-Public Health, FISABIO-Universitat Jaume I-Universitat de València, Valencia, Spain
- Faculty of Nursing and Chiropody, University of Valencia, Valencia, Spain
| | - Mikel Subiza-Pérez
- CIBER Epidemiología y Salud Pública, Madrid, Spain
- Department of Clinical and Health Psychology and Research Methods, University of the Basque Country UPV/EHU, Avenida Tolosa 70, 20018, Donostia-San Sebastián, Spain
- Bradford Institute for Health Research, Temple Bank House, Bradford Royal Infirmary, Duckworth Lane, BD9 6RJ, Bradford, UK
- Biodonostia Health Research Institute, Group of Environmental Epidemiology and Child Development, Paseo Doctor Begiristain s/n, 20014, Donostia- San Sebastián, Spain
| | - Manuel Lozano
- Epidemiology and Environmental Health Joint Research Unit, FISABIO-Public Health, FISABIO-Universitat Jaume I-Universitat de València, Valencia, Spain
- Preventive Medicine and Public Health, Food Sciences, Toxicology and Forensic Medicine Department, Universitat de València, Valencia, Spain
| | - Jesus Ibarluzea
- CIBER Epidemiología y Salud Pública, Madrid, Spain
- Biodonostia Health Research Institute, Group of Environmental Epidemiology and Child Development, Paseo Doctor Begiristain s/n, 20014, Donostia- San Sebastián, Spain
- Ministry of Health of the Basque Government, Sub-Directorate for Public Health and Addictions of Gipuzkoa, San Sebastian, Spain
| | - Jordi Sunyer
- ISGlobal, Institute for Global Health, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública, Madrid, Spain
| | - Mariona Bustamante
- ISGlobal, Institute for Global Health, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública, Madrid, Spain
| | - Marta Cosin-Tomas
- ISGlobal, Institute for Global Health, Barcelona, Spain.
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.
- CIBER Epidemiología y Salud Pública, Madrid, Spain.
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Shore CJ, Villicaña S, El-Sayed Moustafa JS, Roberts AL, Gunn DA, Bataille V, Deloukas P, Spector TD, Small KS, Bell JT. Genetic effects on the skin methylome in healthy older twins. Am J Hum Genet 2024; 111:1932-1952. [PMID: 39137780 PMCID: PMC11393713 DOI: 10.1016/j.ajhg.2024.07.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 05/22/2024] [Accepted: 07/15/2024] [Indexed: 08/15/2024] Open
Abstract
Whole-skin DNA methylation variation has been implicated in several diseases, including melanoma, but its genetic basis has not yet been fully characterized. Using bulk skin tissue samples from 414 healthy female UK twins, we performed twin-based heritability and methylation quantitative trait loci (meQTL) analyses for >400,000 DNA methylation sites. We find that the human skin DNA methylome is on average less heritable than previously estimated in blood and other tissues (mean heritability: 10.02%). meQTL analysis identified local genetic effects influencing DNA methylation at 18.8% (76,442) of tested CpG sites, as well as 1,775 CpG sites associated with at least one distal genetic variant. As a functional follow-up, we performed skin expression QTL (eQTL) analyses in a partially overlapping sample of 604 female twins. Colocalization analysis identified over 3,500 shared genetic effects affecting thousands of CpG sites (10,067) and genes (4,475). Mediation analysis of putative colocalized gene-CpG pairs identified 114 genes with evidence for eQTL effects being mediated by DNA methylation in skin, including in genes implicating skin disease such as ALOX12 and CSPG4. We further explored the relevance of skin meQTLs to skin disease and found that skin meQTLs and CpGs under genetic influence were enriched for multiple skin-related genome-wide and epigenome-wide association signals, including for melanoma and psoriasis. Our findings give insights into the regulatory landscape of epigenomic variation in skin.
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Affiliation(s)
- Christopher J Shore
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
| | - Sergio Villicaña
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | | | - Amy L Roberts
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | | | - Veronique Bataille
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Panos Deloukas
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Kerrin S Small
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
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5
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Petersen RM, Vockley CM, Lea AJ. Uncovering methylation-dependent genetic effects on regulatory element function in diverse genomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.23.609412. [PMID: 39229133 PMCID: PMC11370585 DOI: 10.1101/2024.08.23.609412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
A major goal in evolutionary biology and biomedicine is to understand the complex interactions between genetic variants, the epigenome, and gene expression. However, the causal relationships between these factors remain poorly understood. mSTARR-seq, a methylation-sensitive massively parallel reporter assay, is capable of identifying methylation-dependent regulatory activity at many thousands of genomic regions simultaneously, and allows for the testing of causal relationships between DNA methylation and gene expression on a region-by-region basis. Here, we developed a multiplexed mSTARR-seq protocol to assay naturally occurring human genetic variation from 25 individuals sampled from 10 localities in Europe and Africa. We identified 6,957 regulatory elements in either the unmethylated or methylated state, and this set was enriched for enhancer and promoter annotations, as expected. The expression of 58% of these regulatory elements was modulated by methylation, which was generally associated with decreased RNA expression. Within our set of regulatory elements, we used allele-specific expression analyses to identify 8,020 sites with genetic effects on gene regulation; further, we found that 42.3% of these genetic effects varied between methylated and unmethylated states. Sites exhibiting methylation-dependent genetic effects were enriched for GWAS and EWAS annotations, implicating them in human disease. Compared to datasets that assay DNA from a single European individual, our multiplexed assay uncovers dramatically more genetic effects and methylation-dependent genetic effects, highlighting the importance of including diverse individuals in assays which aim to understand gene regulatory processes.
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6
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van Hilten A, van Rooij J, Ikram MA, Niessen WJ, van Meurs JBJ, Roshchupkin GV. Phenotype prediction using biologically interpretable neural networks on multi-cohort multi-omics data. NPJ Syst Biol Appl 2024; 10:81. [PMID: 39095438 PMCID: PMC11297229 DOI: 10.1038/s41540-024-00405-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 07/12/2024] [Indexed: 08/04/2024] Open
Abstract
Integrating multi-omics data into predictive models has the potential to enhance accuracy, which is essential for precision medicine. In this study, we developed interpretable predictive models for multi-omics data by employing neural networks informed by prior biological knowledge, referred to as visible networks. These neural networks offer insights into the decision-making process and can unveil novel perspectives on the underlying biological mechanisms associated with traits and complex diseases. We tested the performance, interpretability and generalizability for inferring smoking status, subject age and LDL levels using genome-wide RNA expression and CpG methylation data from the blood of the BIOS consortium (four population cohorts, Ntotal = 2940). In a cohort-wise cross-validation setting, the consistency of the diagnostic performance and interpretation was assessed. Performance was consistently high for predicting smoking status with an overall mean AUC of 0.95 (95% CI: 0.90-1.00) and interpretation revealed the involvement of well-replicated genes such as AHRR, GPR15 and LRRN3. LDL-level predictions were only generalized in a single cohort with an R2 of 0.07 (95% CI: 0.05-0.08). Age was inferred with a mean error of 5.16 (95% CI: 3.97-6.35) years with the genes COL11A2, AFAP1, OTUD7A, PTPRN2, ADARB2 and CD34 consistently predictive. For both regression tasks, we found that using multi-omics networks improved performance, stability and generalizability compared to interpretable single omic networks. We believe that visible neural networks have great potential for multi-omics analysis; they combine multi-omic data elegantly, are interpretable, and generalize well to data from different cohorts.
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Affiliation(s)
- Arno van Hilten
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
| | - Jeroen van Rooij
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - M Arfan Ikram
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - Wiro J Niessen
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Orthopaedics and Sports Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Gennady V Roshchupkin
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
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7
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Yeung E, Biedrzycki RJ, Gómez Herrera LC, Issarapu P, Dou J, Marques IF, Mansuri SR, Page CM, Harbs J, Khodasevich D, Poisel E, Niu Z, Allard C, Casey E, Berstein FM, Mancano G, Elliott HR, Richmond R, He Y, Ronkainen J, Sebert S, Bell EM, Sharp G, Mumford SL, Schisterman EF, Chandak GR, Fall CHD, Sahariah SA, Silver MJ, Prentice AM, Bouchard L, Domellof M, West C, Holland N, Cardenas A, Eskenazi B, Zillich L, Witt SH, Send T, Breton C, Bakulski KM, Fallin MD, Schmidt RJ, Stein DJ, Zar HJ, Jaddoe VWV, Wright J, Grazuleviciene R, Gutzkow KB, Sunyer J, Huels A, Vrijheid M, Harlid S, London S, Hivert M, Felix J, Bustamante M, Guan W. Maternal age is related to offspring DNA methylation: A meta-analysis of results from the PACE consortium. Aging Cell 2024; 23:e14194. [PMID: 38808605 PMCID: PMC11320347 DOI: 10.1111/acel.14194] [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: 10/24/2023] [Revised: 04/16/2024] [Accepted: 04/19/2024] [Indexed: 05/30/2024] Open
Abstract
Worldwide trends to delay childbearing have increased parental ages at birth. Older parental age may harm offspring health, but mechanisms remain unclear. Alterations in offspring DNA methylation (DNAm) patterns could play a role as aging has been associated with methylation changes in gametes of older individuals. We meta-analyzed epigenome-wide associations of parental age with offspring blood DNAm of over 9500 newborns and 2000 children (5-10 years old) from the Pregnancy and Childhood Epigenetics consortium. In newborns, we identified 33 CpG sites in 13 loci with DNAm associated with maternal age (PFDR < 0.05). Eight of these CpGs were located near/in the MTNR1B gene, coding for a melatonin receptor. Regional analysis identified them together as a differentially methylated region consisting of 9 CpGs in/near MTNR1B, at which higher DNAm was associated with greater maternal age (PFDR = 6.92 × 10-8) in newborns. In childhood blood samples, these differences in blood DNAm of MTNR1B CpGs were nominally significant (p < 0.05) and retained the same positive direction, suggesting persistence of associations. Maternal age was also positively associated with higher DNA methylation at three CpGs in RTEL1-TNFRSF6B at birth (PFDR < 0.05) and nominally in childhood (p < 0.0001). Of the remaining 10 CpGs also persistent in childhood, methylation at cg26709300 in YPEL3/BOLA2B in external data was associated with expression of ITGAL, an immune regulator. While further study is needed to establish causality, particularly due to the small effect sizes observed, our results potentially support offspring DNAm as a mechanism underlying associations of maternal age with child health.
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Affiliation(s)
- Edwina Yeung
- Epidemiology Branch, Division of Population Health Research, Division of Intramural ResearchEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentBethesdaMarylandUSA
| | - Richard J. Biedrzycki
- Division of Intramural ResearchGlotech Inc., Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of HealthBethesdaMarylandUSA
| | - Laura C. Gómez Herrera
- ISGlobal, Institute for Global HealthBarcelonaSpain
- Universitat Pompeu Fabra (UPF)BarcelonaSpain
- CIBER Epidemiología y Salud Pública (CIBERESP)MadridSpain
| | - Prachand Issarapu
- MRC Unit the Gambia at the London School of Hygiene and Tropical Medicine (LSHTM)BanjulThe Gambia
| | - John Dou
- Department of Epidemiology, School of Public HealthUniversity of MichiganAnn ArborMichiganUSA
| | - Irene Fontes Marques
- Generation R Study Group, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
- Department of Pediatrics, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
| | - Sohail Rafik Mansuri
- Genomic Research on Complex Diseases (GRC‐Group)CSIR‐Centre for Cellular and Molecular BiologyHyderabadTelanganaIndia
| | | | - Justin Harbs
- Department of Diagnostics and Intervention, OncologyUmeå UniversityUmeåSweden
| | - Dennis Khodasevich
- Environmental Health Sciences, Berkeley Public HealthCERCH, University of CaliforniaBerkeleyCaliforniaUSA
| | - Eric Poisel
- Department of Genetic Epidemiology in PsychiatryCentral Institute of Mental Health, Medical Faculty Mannheim, University of HeidelbergMannheimGermany
| | - Zhongzheng Niu
- Department of Population and Public Health Science, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Catherine Allard
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke (CHUS)SherbrookeQuebecCanada
| | - Emma Casey
- Department of Epidemiology, Rollins School of Public HealthEmory UniversityAtlantaGeorgiaUSA
| | - Fernanda Morales Berstein
- Medical Research Council Integrative Epidemiology UnitUniversity of BristolBristolUK
- Bristol Medical School Population Health SciencesUniversity of BristolBristolUK
| | - Giulia Mancano
- Medical Research Council Integrative Epidemiology UnitUniversity of BristolBristolUK
- Bristol Medical School Population Health SciencesUniversity of BristolBristolUK
| | - Hannah R. Elliott
- Medical Research Council Integrative Epidemiology UnitUniversity of BristolBristolUK
- Bristol Medical School Population Health SciencesUniversity of BristolBristolUK
| | - Rebecca Richmond
- Medical Research Council Integrative Epidemiology UnitUniversity of BristolBristolUK
- Bristol Medical School Population Health SciencesUniversity of BristolBristolUK
| | - Yiyan He
- Research Unit of Population HealthUniversity of OuluOuluFinland
| | | | - Sylvain Sebert
- Research Unit of Population HealthUniversity of OuluOuluFinland
| | - Erin M. Bell
- Department of Environmental Health Sciences and Epidemiology and BiostatisticsUniversity at Albany School of Public HealthAlbanyNew YorkUSA
| | - Gemma Sharp
- Department of PsychologyUniversity of ExeterExeterUK
| | - Sunni L. Mumford
- Department of Biostatistics, Epidemiology and Informatics and Department of Obstetrics and Gynecology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Enrique F. Schisterman
- Department of Biostatistics, Epidemiology and Informatics and Department of Obstetrics and Gynecology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Giriraj R. Chandak
- Genomic Research on Complex Diseases (GRC‐Group)CSIR‐Centre for Cellular and Molecular BiologyHyderabadTelanganaIndia
| | | | | | - Matt J. Silver
- MRC Unit the Gambia at the London School of Hygiene and Tropical Medicine (LSHTM)BanjulThe Gambia
| | - Andrew M. Prentice
- MRC Unit the Gambia at the London School of Hygiene and Tropical Medicine (LSHTM)BanjulThe Gambia
| | - Luigi Bouchard
- Department of Biochemistry and Functional GenomicsCentre intégré Universitaire de santé et de Services Sociaux (CIUSSS) du Saguenay‐Lac‐St‐Jean, Université de SherbrookeSherbrookeQuebecCanada
- Department of Laboratory MedicineCIUSSS du Saguenay‐Lac‐Saint‐Jean – Hôpital de ChicoutimiChicoutimiQuebecCanada
| | - Magnus Domellof
- Department of Clinical Sciences, PediatricsUmeå UniversityUmeåSweden
| | - Christina West
- Department of Clinical Sciences, PediatricsUmeå UniversityUmeåSweden
| | - Nina Holland
- Environmental Health Sciences, Berkeley Public HealthCERCH, University of CaliforniaBerkeleyCaliforniaUSA
| | - Andres Cardenas
- Department of Epidemiology and Population HealthStanford UniversityStanfordCaliforniaUSA
| | - Brenda Eskenazi
- Environmental Health Sciences, Berkeley Public HealthCERCH, University of CaliforniaBerkeleyCaliforniaUSA
| | - Lea Zillich
- Department of Genetic Epidemiology in PsychiatryCentral Institute of Mental Health, Medical Faculty Mannheim, University of HeidelbergMannheimGermany
| | - Stephanie H. Witt
- Department of Genetic Epidemiology in PsychiatryCentral Institute of Mental Health, Medical Faculty Mannheim, University of HeidelbergMannheimGermany
| | - Tabea Send
- Department of Psychiatry and PsychotherapyCentral Institute of Mental Health, Medical Faculty Mannheim, University of HeidelbergMannheimGermany
| | - Carrie Breton
- Department of Population and Public Health Science, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Kelly M. Bakulski
- Department of Epidemiology, School of Public HealthUniversity of MichiganAnn ArborMichiganUSA
| | - M. Daniele Fallin
- Dean's Office, Rollins School of Public HealthEmory UniversityAtlantaGeorgiaUSA
| | - Rebecca J. Schmidt
- Department of Public Health Sciences and the M.I.N.D. Institute, School of MedicineUniversity of CaliforniaDavisCaliforniaUSA
| | - Dan J. Stein
- Neuroscience Institute, University of Cape TownCape TownSouth Africa
- Department of Psychiatry and Mental HealthUniversity of Cape TownCape TownSouth Africa
- South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental DisordersUniversity of Cape TownCape TownSouth Africa
| | - Heather J. Zar
- South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental DisordersUniversity of Cape TownCape TownSouth Africa
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's HospitalUniversity of Cape TownCape TownSouth Africa
| | - Vincent W. V. Jaddoe
- Generation R Study Group, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
- Department of Pediatrics, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
| | - John Wright
- Bradford Institute for Health Research, Temple Bank House, Bradford Royal InfirmaryBradfordUK
| | | | | | - Jordi Sunyer
- ISGlobal, Institute for Global HealthBarcelonaSpain
- Universitat Pompeu Fabra (UPF)BarcelonaSpain
- CIBER Epidemiología y Salud Pública (CIBERESP)MadridSpain
- IMIM‐Parc Salut MarBarcelonaSpain
| | - Anke Huels
- Department of Epidemiology, Rollins School of Public HealthEmory UniversityAtlantaGeorgiaUSA
- Gangarosa Department of Environmental Health, Rollins School of Public HealthEmory UniversityAtlantaGeorgiaUSA
| | - Martine Vrijheid
- ISGlobal, Institute for Global HealthBarcelonaSpain
- Universitat Pompeu Fabra (UPF)BarcelonaSpain
- CIBER Epidemiología y Salud Pública (CIBERESP)MadridSpain
| | - Sophia Harlid
- Department of Diagnostics and Intervention, OncologyUmeå UniversityUmeåSweden
| | - Stephanie London
- Epidemiology BranchNational Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle ParkDurhamNorth CarolinaUSA
| | - Marie‐France Hivert
- Division of Chronic Disease Research across the Lifecourse (CoRAL); Department of Population Medicine, Harvard Medical SchoolHarvard Pilgrim Health Care InstituteBostonMassachusettsUSA
- Diabetes Unit, Massachusetts General HospitalBostonMassachusettsUSA
| | - Janine Felix
- Generation R Study Group, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
- Department of Pediatrics, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
| | - Mariona Bustamante
- ISGlobal, Institute for Global HealthBarcelonaSpain
- Universitat Pompeu Fabra (UPF)BarcelonaSpain
- CIBER Epidemiología y Salud Pública (CIBERESP)MadridSpain
| | - Weihua Guan
- Division of Biostatistics, School of Public HealthUniversity of MinnesotaMinneapolisMinnesotaUSA
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8
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Nikpay M. Multiomics Screening Identified CpG Sites and Genes That Mediate the Impact of Exposure to Environmental Chemicals on Cardiometabolic Traits. EPIGENOMES 2024; 8:29. [PMID: 39189255 PMCID: PMC11348123 DOI: 10.3390/epigenomes8030029] [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: 06/17/2024] [Revised: 07/19/2024] [Accepted: 07/24/2024] [Indexed: 08/28/2024] Open
Abstract
An understanding of the molecular mechanism whereby an environmental chemical causes a disease is important for the purposes of future applications. In this study, a multiomics workflow was designed to combine several publicly available datasets in order to identify CpG sites and genes that mediate the impact of exposure to environmental chemicals on cardiometabolic traits. Organophosphate and prenatal lead exposure were previously reported to change methylation level at the cg23627948 site. The outcome of the analyses conducted in this study revealed that, as the cg23627948 site becomes methylated, the expression of the GNA12 gene decreases, which leads to a higher body fat percentage. Prenatal perfluorooctane sulfonate exposure was reported to increase the methylation level at the cg21153102 site. Findings of this study revealed that higher methylation at this site contributes to higher diastolic blood pressure by changing the expression of CHP1 and GCHFR genes. Moreover, HKR1 mediates the impact of B12 supplementation → cg05280698 hypermethylation on higher kidney function, while CTDNEP1 mediates the impact of air pollution → cg03186999 hypomethylation on higher systolic blood pressure. This study investigates CpG sites and genes that mediate the impact of environmental chemicals on cardiometabolic traits. Furthermore, the multiomics approach described in this study provides a convenient workflow with which to investigate the impact of an environmental factor on the body's biomarkers, and, consequently, on health conditions, using publicly available data.
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Affiliation(s)
- Majid Nikpay
- Omics and Biomedical Analysis Core Facility, University of Ottawa Heart Institute, Ottawa, ON K1Y 4W7, Canada
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9
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Watowich MM, Costa CE, Chiou KL, Goldman EA, Petersen RM, Patterson S, Martínez MI, Sterner KN, Horvath JE, Montague MJ, Platt ML, Brent LJN, Higham JP, Lea AJ, Snyder-Mackler N. Immune gene regulation is associated with age and environmental adversity in a nonhuman primate. Mol Ecol 2024:e17445. [PMID: 39032090 DOI: 10.1111/mec.17445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 04/27/2024] [Accepted: 06/14/2024] [Indexed: 07/22/2024]
Abstract
Phenotypic aging is ubiquitous across mammalian species, suggesting shared underlying mechanisms of aging. Aging is linked to molecular changes to DNA methylation and gene expression, and environmental factors, such as severe external challenges or adversities, can moderate these age-related changes. Yet, it remains unclear whether environmental adversities affect gene regulation via the same molecular pathways as chronological, or 'primary', aging. Investigating molecular aging in naturalistic animal populations can fill this gap by providing insight into shared molecular mechanisms of aging and the effects of a greater diversity of environmental adversities - particularly those that can be challenging to study in humans or laboratory organisms. Here, we characterised molecular aging - specifically, CpG methylation - in a sample of free-ranging rhesus macaques living off the coast of Puerto Rico (n samples = 571, n individuals = 499), which endured a major hurricane during our study. Age was associated with methylation at 78,661 sites (31% of all sites tested). Age-associated hypermethylation occurred more frequently in areas of active gene regulation, while hypomethylation was enriched in regions that show less activity in immune cells, suggesting these regions may become de-repressed in older individuals. Age-associated hypomethylation also co-occurred with increased chromatin accessibility while hypermethylation showed the opposite trend, hinting at a coordinated, multi-level loss of epigenetic stability during aging. We detected 32,048 CpG sites significantly associated with exposure to a hurricane, and these sites overlapped age-associated sites, most strongly in regulatory regions and most weakly in quiescent regions. Together, our results suggest that environmental adversity may contribute to aging-related molecular phenotypes in regions of active gene transcription, but that primary aging has specific signatures in non-regulatory regions.
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Affiliation(s)
- Marina M Watowich
- Department of Biology, University of Washington, Seattle, Washington, USA
- Center for Evolution and Medicine, Arizona State University, Tempe, Arizona, USA
- School of Life Sciences, Arizona State University, Tempe, Arizona, USA
- Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee, USA
| | - Christina E Costa
- Department of Anthropology, New York University, New York, New York, USA
- New York Consortium in Evolutionary Primatology, New York, New York, USA
| | - Kenneth L Chiou
- Center for Evolution and Medicine, Arizona State University, Tempe, Arizona, USA
- School of Life Sciences, Arizona State University, Tempe, Arizona, USA
| | - Elisabeth A Goldman
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
| | - Rachel M Petersen
- Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee, USA
| | - Sam Patterson
- Department of Anthropology, New York University, New York, New York, USA
| | - Melween I Martínez
- Caribbean Primate Research Center, Unit of Comparative Medicine, University of Puerto Rico, San Juan, Puerto Rico, USA
| | - Kirstin N Sterner
- Department of Anthropology, University of Oregon, Eugene, Oregon, USA
| | - Julie E Horvath
- Research and Collections Section, North Carolina Museum of Natural Sciences, Raleigh, North Carolina, USA
- Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina, USA
- Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Michael J Montague
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Michael L Platt
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Psychology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Marketing Department, Wharton School of Business, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Lauren J N Brent
- Centre for Research in Animal Behaviour, University of Exeter, Exeter, UK
| | - James P Higham
- Department of Anthropology, New York University, New York, New York, USA
- New York Consortium in Evolutionary Primatology, New York, New York, USA
| | - Amanda J Lea
- Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee, USA
| | - Noah Snyder-Mackler
- Center for Evolution and Medicine, Arizona State University, Tempe, Arizona, USA
- School of Life Sciences, Arizona State University, Tempe, Arizona, USA
- School of Human Evolution and Social Change, Arizona State University, Tempe, Arizona, USA
- Neurodegenerative Disease Research Center, Arizona State University, Tempe, Arizona, USA
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10
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Lukacsovich D, O’Shea D, Huang H, Zhang W, Young J, Chen XS, Dietrich ST, Kunkle B, Martin E, Wang L. MIAMI-AD (Methylation in Aging and Methylation in AD): an integrative knowledgebase that facilitates explorations of DNA methylation across sex, aging, and Alzheimer's disease. Database (Oxford) 2024; 2024:baae061. [PMID: 39028752 PMCID: PMC11259044 DOI: 10.1093/database/baae061] [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: 01/19/2024] [Revised: 05/08/2024] [Accepted: 07/03/2024] [Indexed: 07/21/2024]
Abstract
Alzheimer's disease (AD) is a common neurodegenerative disorder with a significant impact on aging populations. DNA methylation (DNAm) alterations have been implicated in both the aging processes and the development of AD. Given that AD affects more women than men, it is also important to explore DNAm changes that occur specifically in each sex. We created MIAMI-AD, a comprehensive knowledgebase containing manually curated summary statistics from 98 published tables in 38 studies, all of which included at least 100 participants. MIAMI-AD enables easy browsing, querying, and downloading DNAm associations at multiple levels-at individual CpG, gene, genomic regions, or genome-wide, in one or multiple studies. Moreover, it also offers tools to perform integrative analyses, such as comparing DNAm associations across different phenotypes or tissues, as well as interactive visualizations. Using several use case examples, we demonstrated that MIAMI-AD facilitates our understanding of age-associated CpGs in AD and the sex-specific roles of DNAm in AD. This open-access resource is freely available to the research community, and all the underlying data can be downloaded. MIAMI-AD facilitates integrative explorations to better understand the interplay between DNAm across aging, sex, and AD. Database URL: https://miami-ad.org/.
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Affiliation(s)
- David Lukacsovich
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136, USA
| | - Deirdre O’Shea
- Department of Neurology, Comprehensive Center for Brain Health, University of Miami, Miller School of Medicine, 7700 W Camino Real, Boca Raton, FL 33433, USA
| | - Hanchen Huang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136, USA
| | - Wei Zhang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136, USA
| | - Juan Young
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
| | - X Steven Chen
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, 1475 NW 12th Ave, Miami, FL 33136, USA
| | - Sven-Thorsten Dietrich
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
| | - Brian Kunkle
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
| | - Eden Martin
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
| | - Lily Wang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136, USA
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, 1475 NW 12th Ave, Miami, FL 33136, USA
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11
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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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12
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Chen BH, Zhou W. mLiftOver: harmonizing data across Infinium DNA methylation platforms. Bioinformatics 2024; 40:btae423. [PMID: 38963309 PMCID: PMC11233119 DOI: 10.1093/bioinformatics/btae423] [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: 03/19/2024] [Revised: 06/07/2024] [Accepted: 07/03/2024] [Indexed: 07/05/2024] Open
Abstract
MOTIVATION Infinium DNA methylation BeadChips are widely used for genome-wide DNA methylation profiling at the population scale. Recent updates to probe content and naming conventions in the EPIC version 2 (EPICv2) arrays have complicated integrating new data with previous Infinium array platforms, such as the MethylationEPIC (EPIC) and the HumanMethylation450 (HM450) BeadChip. RESULTS We present mLiftOver, a user-friendly tool that harmonizes probe ID, methylation level, and signal intensity data across different Infinium platforms. It manages probe replicates, missing data imputation, and platform-specific bias for accurate data conversion. We validated the tool by applying HM450-based cancer classifiers to EPICv2 cancer data, achieving high accuracy. Additionally, we successfully integrated EPICv2 healthy tissue data with legacy HM450 data for tissue identity analysis and produced consistent copy number profiles in cancer cells. AVAILABILITY AND IMPLEMENTATION mLiftOver is implemented R and available in the Bioconductor package SeSAMe (version 1.21.13+): https://bioconductor.org/packages/release/bioc/html/sesame.html. Analysis of EPIC and EPICv2 platform-specific bias and high-confidence mapping is available at https://github.com/zhou-lab/InfiniumAnnotationV1/raw/main/Anno/EPICv2/EPICv2ToEPIC_conversion.tsv.gz. The source code is available at https://github.com/zwdzwd/sesame/blob/devel/R/mLiftOver.R under the MIT license.
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Affiliation(s)
- Brian H Chen
- California Pacific Medical Center Research Institute, Sutter Health, San Francisco, CA 94143, United States
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, Philadelphia, PA, 19104, United States
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
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13
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Shorey-Kendrick LE, Davis B, Gao L, Park B, Vu A, Morris CD, Breton CV, Fry R, Garcia E, Schmidt RJ, O’Shea TM, Tepper RS, McEvoy CT, Spindel ER. Development and Validation of a Novel Placental DNA Methylation Biomarker of Maternal Smoking during Pregnancy in the ECHO Program. ENVIRONMENTAL HEALTH PERSPECTIVES 2024; 132:67005. [PMID: 38885141 PMCID: PMC11218700 DOI: 10.1289/ehp13838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 02/27/2024] [Accepted: 05/22/2024] [Indexed: 06/20/2024]
Abstract
BACKGROUND Maternal cigarette smoking during pregnancy (MSDP) is associated with numerous adverse health outcomes in infants and children with potential lifelong consequences. Negative effects of MSDP on placental DNA methylation (DNAm), placental structure, and function are well established. OBJECTIVE Our aim was to develop biomarkers of MSDP using DNAm measured in placentas (N = 96 ), collected as part of the Vitamin C to Decrease the Effects of Smoking in Pregnancy on Infant Lung Function double-blind, placebo-controlled randomized clinical trial conducted between 2012 and 2016. We also aimed to develop a digital polymerase chain reaction (PCR) assay for the top ranking cytosine-guanine dinucleotide (CpG) so that large numbers of samples can be screened for exposure at low cost. METHODS We compared the ability of four machine learning methods [logistic least absolute shrinkage and selection operator (LASSO) regression, logistic elastic net regression, random forest, and gradient boosting machine] to classify MSDP based on placental DNAm signatures. We developed separate models using the complete EPIC array dataset and on the subset of probes also found on the 450K array so that models exist for both platforms. For comparison, we developed a model using CpGs previously associated with MSDP in placenta. For each final model, we used model coefficients and normalized beta values to calculate placental smoking index (PSI) scores for each sample. Final models were validated in two external datasets: the Extremely Low Gestational Age Newborn observational study, N = 426 ; and the Rhode Island Children's Health Study, N = 237 . RESULTS Logistic LASSO regression demonstrated the highest performance in cross-validation testing with the lowest number of input CpGs. Accuracy was greatest in external datasets when using models developed for the same platform. PSI scores in smokers only (n = 72 ) were moderately correlated with maternal plasma cotinine levels. One CpG (cg27402634), with the largest coefficient in two models, was measured accurately by digital PCR compared with measurement by EPIC array (R 2 = 0.98 ). DISCUSSION To our knowledge, we have developed the first placental DNAm-based biomarkers of MSDP with broad utility to studies of prenatal disease origins. https://doi.org/10.1289/EHP13838.
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Affiliation(s)
- Lyndsey E. Shorey-Kendrick
- Division of Neuroscience, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton, Oregon, USA
| | - Brett Davis
- Department of Medicine, Knight Cardiovascular Institute, Oregon Health & Science University, Portland, Oregon, USA
| | - Lina Gao
- Biostatistics Shared Resources, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
- Bioinformatics & Biostatistics Core, Oregon National Primate Research Center, Oregon Health & Science University, Portland, Oregon, USA
| | - Byung Park
- Biostatistics Shared Resources, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
- Bioinformatics & Biostatistics Core, Oregon National Primate Research Center, Oregon Health & Science University, Portland, Oregon, USA
- Oregon Health & Science University–Portland State University School of Public Health, Portland, Oregon, USA
| | - Annette Vu
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon, USA
| | - Cynthia D. Morris
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon, USA
- Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, Oregon, USA
| | - Carrie V. Breton
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, USA
| | - Rebecca Fry
- Department of Environmental Sciences and Engineering, UNC Gillings School of Public Health, Chapel Hill, North Carolina, USA
| | - Erika Garcia
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, USA
| | - Rebecca J. Schmidt
- Department of Public Health Sciences, School of Medicine, University of California, Davis, Davis, California, USA
- MIND Institute, School of Medicine, University of California Davis, Davis, California, USA
| | - T. Michael O’Shea
- Department of Pediatrics, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Robert S. Tepper
- Department of Pediatrics, Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Cindy T. McEvoy
- Department of Pediatrics, Oregon Health & Science University, Portland, Oregon, USA
| | - Eliot R. Spindel
- Division of Neuroscience, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton, Oregon, USA
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14
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Li W, Xia M, Zeng H, Lin H, Teschendorff AE, Gao X, Wang S. Longitudinal analysis of epigenome-wide DNA methylation reveals novel loci associated with BMI change in East Asians. Clin Epigenetics 2024; 16:70. [PMID: 38802969 PMCID: PMC11131215 DOI: 10.1186/s13148-024-01679-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 05/11/2024] [Indexed: 05/29/2024] Open
Abstract
BACKGROUND Obesity is a global public health concern linked to chronic diseases such as cardiovascular disease and type 2 diabetes (T2D). Emerging evidence suggests that epigenetic modifications, particularly DNA methylation, may contribute to obesity. However, the molecular mechanism underlying the longitudinal change of BMI has not been well-explored, especially in East Asian populations. METHODS This study performed a longitudinal epigenome-wide association analysis of DNA methylation to uncover novel loci associated with BMI change in 533 individuals across two Chinese cohorts with repeated DNA methylation and BMI measurements over four years. RESULTS We identified three novel CpG sites (cg14671384, cg25540824, and cg10848724) significantly associated with BMI change. Two of the identified CpG sites were located in regions previously associated with body shape and basal metabolic rate. Annotation of the top 20 BMI change-associated CpGs revealed strong connections to obesity and T2D. Notably, these CpGs exhibited active regulatory roles and located in genes with high expression in the liver and digestive tract, suggesting a potential regulatory pathway from genome to phenotypes of energy metabolism and absorption via DNA methylation. Cross-sectional and longitudinal EWAS comparisons indicated different mechanisms between CpGs related to BMI and BMI change. CONCLUSION This study enhances our understanding of the epigenetic dynamics underlying BMI change and emphasizes the value of longitudinal analyses in deciphering the complex interplay between epigenetics and obesity.
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Affiliation(s)
- Wenran Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Mingfeng Xia
- Department of Endocrinology and Metabolism, Zhongshan Hospital and Fudan Institute for Metabolic Diseases, Fudan University, Shanghai, China
- Department of Endocrinology and Metabolism, Wusong Branch of Zhongshan Hospital, Fudan University, Shanghai, China
| | - Hailuan Zeng
- Department of Endocrinology and Metabolism, Zhongshan Hospital and Fudan Institute for Metabolic Diseases, Fudan University, Shanghai, China
- Human Phenome Institute, Fudan University, Shanghai, China
| | - Huandong Lin
- Department of Endocrinology and Metabolism, Zhongshan Hospital and Fudan Institute for Metabolic Diseases, Fudan University, Shanghai, China
| | - Andrew E Teschendorff
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Xin Gao
- Department of Endocrinology and Metabolism, Zhongshan Hospital and Fudan Institute for Metabolic Diseases, Fudan University, Shanghai, China.
- Human Phenome Institute, Fudan University, Shanghai, China.
| | - Sijia Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
- Taizhou Institute of Health Sciences, Fudan University, Taizhou, Jiangsu, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.
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15
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Goldberg DC, Cloud C, Lee SM, Barnes B, Gruber S, Kim E, Pottekat A, Westphal M, McAuliffe L, Majournie E, KalayilManian M, Zhu Q, Tran C, Hansen M, Parker JB, Kohli RM, Porecha R, Renke N, Zhou W. MSA: scalable DNA methylation screening BeadChip for high-throughput trait association studies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.17.594606. [PMID: 38826316 PMCID: PMC11142114 DOI: 10.1101/2024.05.17.594606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
The Infinium DNA Methylation BeadChips have significantly contributed to population-scale epigenetics research by enabling epigenome-wide trait association discoveries. Here, we design, describe, and experimentally verify a new iteration of this technology, the Methylation Screening Array (MSA), to focus on human trait screening and discovery. This array utilizes extensive data from previous Infinium platform-based epigenome-wide association studies (EWAS). It incorporates knowledge from the latest single-cell and cell type-resolution whole genome methylome profiles. The MSA is engineered to achieve scalable screening of epigenetics-trait association in an ultra-high sample throughput. Our design encompassed diverse human trait associations, including those with genetic, cellular, environmental, and demographical variables and human diseases such as genetic, neurodegenerative, cardiovascular, infectious, and immune diseases. We comprehensively evaluated this array's reproducibility, accuracy, and capacity for cell-type deconvolution and supporting 5-hydroxymethylation profiling in diverse human tissues. Our first atlas data using this platform uncovered the complex chromatin and tissue contexts of DNA modification variations and genetic variants linked to human phenotypes.
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Affiliation(s)
- David C Goldberg
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, PA, 19104, USA
| | - Cameron Cloud
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, PA, 19104, USA
| | - Sol Moe Lee
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, PA, 19104, USA
| | | | | | - Elliot Kim
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, PA, 19104, USA
| | | | | | | | | | | | | | | | | | - Jared B Parker
- Department of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Rahul M Kohli
- Department of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | | | | | - Wanding Zhou
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, PA, 19104, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
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16
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Salama OE, Hizon N, Del Vecchio M, Kolsun K, Fonseca MA, Lin DTS, Urtatiz O, MacIsaac JL, Kobor MS, Sellers EAC, Dolinsky VW, Dart AB, Jones MJ, Wicklow BA. DNA methylation signatures of youth-onset type 2 diabetes and exposure to maternal diabetes. Clin Epigenetics 2024; 16:65. [PMID: 38741114 DOI: 10.1186/s13148-024-01675-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 04/29/2024] [Indexed: 05/16/2024] Open
Abstract
OBJECTIVE Youth-onset type 2 diabetes (T2D) is physiologically distinct from adult-onset, but it is not clear how the two diseases differ at a molecular level. In utero exposure to maternal type 2 diabetes (T2D) is known to be a specific risk factor for youth-onset T2D. DNA methylation (DNAm) changes associated with T2D but which differ between youth- and adult-onset might delineate the impacts of T2D development at different ages and could also determine the contribution of exposure to in utero diabetes. METHODS We performed an epigenome-wide analysis of DNAm on whole blood from 218 youth with T2D and 77 normoglycemic controls from the iCARE (improving renal Complications in Adolescents with type 2 diabetes through REsearch) cohort. Associations were tested using multiple linear regression models while adjusting for maternal diabetes, sex, age, BMI, smoking status, second-hand smoking exposure, cell-type proportions and genetic ancestry. RESULTS We identified 3830 differentially methylated sites associated with youth T2D onset, of which 3794 were moderately (adjusted p-value < 0.05 and effect size estimate > 0.01) associated and 36 were strongly (adjusted p-value < 0.05 and effect size estimate > 0.05) associated. A total of 3725 of these sites were not previously reported in the EWAS Atlas as associated with T2D, adult obesity or youth obesity. Moreover, three CpGs associated with youth-onset T2D in the PFKFB3 gene were also associated with maternal T2D exposure (FDR < 0.05 and effect size > 0.01). This is the first study to link PFKFB3 and T2D in youth. CONCLUSION Our findings support that T2D in youth has different impacts on DNAm than adult-onset, and suggests that changes in DNAm could provide an important link between in utero exposure to maternal diabetes and the onset of T2D.
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Affiliation(s)
- Ola E Salama
- Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, MB, Canada
- Diabetes Research Envision and Accomplished in Manitoba (DREAM) Theme of the Children's Hospital Research Institute of Manitoba, Winnipeg, MB, Canada
| | - Nikho Hizon
- Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, MB, Canada
- Diabetes Research Envision and Accomplished in Manitoba (DREAM) Theme of the Children's Hospital Research Institute of Manitoba, Winnipeg, MB, Canada
| | - Melissa Del Vecchio
- Diabetes Research Envision and Accomplished in Manitoba (DREAM) Theme of the Children's Hospital Research Institute of Manitoba, Winnipeg, MB, Canada
- Department of Pediatrics and Child Health, University of Manitoba, Winnipeg, MB, Canada
| | - Kurt Kolsun
- Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, MB, Canada
- Diabetes Research Envision and Accomplished in Manitoba (DREAM) Theme of the Children's Hospital Research Institute of Manitoba, Winnipeg, MB, Canada
| | - Mario A Fonseca
- Diabetes Research Envision and Accomplished in Manitoba (DREAM) Theme of the Children's Hospital Research Institute of Manitoba, Winnipeg, MB, Canada
- Department of Pharmacology and Therapeutics, University of Manitoba, Winnipeg, MB, Canada
| | - David T S Lin
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Centre for Molecular Medicine and Therapeutics, Vancouver, BC, Canada
| | - Oscar Urtatiz
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Centre for Molecular Medicine and Therapeutics, Vancouver, BC, Canada
| | - Julia L MacIsaac
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Centre for Molecular Medicine and Therapeutics, Vancouver, BC, Canada
| | - Michael S Kobor
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Centre for Molecular Medicine and Therapeutics, Vancouver, BC, Canada
- Edwin S.H. Leong Centre for Healthy Aging, University of British Columbia, Vancouver, BC, Canada
| | - Elizabeth A C Sellers
- Diabetes Research Envision and Accomplished in Manitoba (DREAM) Theme of the Children's Hospital Research Institute of Manitoba, Winnipeg, MB, Canada
- Department of Pediatrics and Child Health, University of Manitoba, Winnipeg, MB, Canada
| | - Vernon W Dolinsky
- Diabetes Research Envision and Accomplished in Manitoba (DREAM) Theme of the Children's Hospital Research Institute of Manitoba, Winnipeg, MB, Canada
- Department of Pharmacology and Therapeutics, University of Manitoba, Winnipeg, MB, Canada
| | - Allison B Dart
- Diabetes Research Envision and Accomplished in Manitoba (DREAM) Theme of the Children's Hospital Research Institute of Manitoba, Winnipeg, MB, Canada
- Department of Pediatrics and Child Health, University of Manitoba, Winnipeg, MB, Canada
| | - Meaghan J Jones
- Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, MB, Canada.
- Diabetes Research Envision and Accomplished in Manitoba (DREAM) Theme of the Children's Hospital Research Institute of Manitoba, Winnipeg, MB, Canada.
| | - Brandy A Wicklow
- Diabetes Research Envision and Accomplished in Manitoba (DREAM) Theme of the Children's Hospital Research Institute of Manitoba, Winnipeg, MB, Canada.
- Department of Pediatrics and Child Health, University of Manitoba, Winnipeg, MB, Canada.
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17
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Peng Q, Liu X, Li W, Jing H, Li J, Gao X, Luo Q, Breeze CE, Pan S, Zheng Q, Li G, Qian J, Yuan L, Yuan N, You C, Du S, Zheng Y, Yuan Z, Tan J, Jia P, Wang J, Zhang G, Lu X, Shi L, Guo S, Liu Y, Ni T, Wen B, Zeng C, Jin L, Teschendorff AE, Liu F, Wang S. Analysis of blood methylation quantitative trait loci in East Asians reveals ancestry-specific impacts on complex traits. Nat Genet 2024; 56:846-860. [PMID: 38641644 DOI: 10.1038/s41588-023-01494-9] [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: 11/17/2021] [Accepted: 08/02/2023] [Indexed: 04/21/2024]
Abstract
Methylation quantitative trait loci (mQTLs) are essential for understanding the role of DNA methylation changes in genetic predisposition, yet they have not been fully characterized in East Asians (EAs). Here we identified mQTLs in whole blood from 3,523 Chinese individuals and replicated them in additional 1,858 Chinese individuals from two cohorts. Over 9% of mQTLs displayed specificity to EAs, facilitating the fine-mapping of EA-specific genetic associations, as shown for variants associated with height. Trans-mQTL hotspots revealed biological pathways contributing to EA-specific genetic associations, including an ERG-mediated 233 trans-mCpG network, implicated in hematopoietic cell differentiation, which likely reflects binding efficiency modulation of the ERG protein complex. More than 90% of mQTLs were shared between different blood cell lineages, with a smaller fraction of lineage-specific mQTLs displaying preferential hypomethylation in the respective lineages. Our study provides new insights into the mQTL landscape across genetic ancestries and their downstream effects on cellular processes and diseases/traits.
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Affiliation(s)
- Qianqian Peng
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Xinxuan Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Wenran Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Han Jing
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Jiarui Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Xingjian Gao
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Qi Luo
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | | | - Siyu Pan
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Qiwen Zheng
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Guochao Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Jiaqiang Qian
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Liyun Yuan
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Na Yuan
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Chenglong You
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Siyuan Du
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yuanting Zheng
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, and Human Phenome Institute, Fudan University, Shanghai, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China
| | - Ziyu Yuan
- Taizhou Institute of Health Sciences, Fudan University, Taizhou, China
| | - Jingze Tan
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China
| | - Peilin Jia
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Jiucun Wang
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, and Human Phenome Institute, Fudan University, Shanghai, China
- Taizhou Institute of Health Sciences, Fudan University, Taizhou, China
- Research Unit of Dissecting the Population Genetics and Developing New Technologies for Treatment and Prevention of Skin Phenotypes and Dermatological Diseases (2019RU058), Chinese Academy of Medical Sciences, Shanghai, China
| | - Guoqing Zhang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
- Taizhou Institute of Health Sciences, Fudan University, Taizhou, China
| | - Xianping Lu
- Shenzhen Chipscreen Biosciences Co. Ltd., Shenzhen, China
| | - Leming Shi
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, and Human Phenome Institute, Fudan University, Shanghai, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China
- Taizhou Institute of Health Sciences, Fudan University, Taizhou, China
| | - Shicheng Guo
- Department of Medical Genetics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- Center for Precision Medicine Research, Marshfield Clinic Research Institute, Marshfield, WI, USA
| | - Yun Liu
- MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Ting Ni
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Human Phenome Institute, School of Life Sciences and Huashan Hospital, Fudan University, Shanghai, China
| | - Bo Wen
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, and Human Phenome Institute, Fudan University, Shanghai, China
- The Fifth People's Hospital of Shanghai and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Changqing Zeng
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, and Human Phenome Institute, Fudan University, Shanghai, China
- Taizhou Institute of Health Sciences, Fudan University, Taizhou, China
- Research Unit of Dissecting the Population Genetics and Developing New Technologies for Treatment and Prevention of Skin Phenotypes and Dermatological Diseases (2019RU058), Chinese Academy of Medical Sciences, Shanghai, China
| | - Andrew E Teschendorff
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
| | - Fan Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China.
- School of Future Technology, University of Chinese Academy of Sciences, Beijing, China.
- Department of Forensic Sciences, College of Criminal Justice, Naif Arab University of Security Sciences, Riyadh, Kingdom of Saudi Arabia.
| | - Sijia Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
- Taizhou Institute of Health Sciences, Fudan University, Taizhou, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.
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18
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Lee SM, Loo C, Prasasya R, Bartolomei M, Kohli R, Zhou W. Low-input and single-cell methods for Infinium DNA methylation BeadChips. Nucleic Acids Res 2024; 52:e38. [PMID: 38407446 PMCID: PMC11040145 DOI: 10.1093/nar/gkae127] [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: 09/11/2023] [Revised: 01/29/2024] [Accepted: 02/10/2024] [Indexed: 02/27/2024] Open
Abstract
The Infinium BeadChip is the most widely used DNA methylome assay technology for population-scale epigenome profiling. However, the standard workflow requires over 200 ng of input DNA, hindering its application to small cell-number samples, such as primordial germ cells. We developed experimental and analysis workflows to extend this technology to suboptimal input DNA conditions, including ultra-low input down to single cells. DNA preamplification significantly enhanced detection rates to over 50% in five-cell samples and ∼25% in single cells. Enzymatic conversion also substantially improved data quality. Computationally, we developed a method to model the background signal's influence on the DNA methylation level readings. The modified detection P-value calculation achieved higher sensitivities for low-input datasets and was validated in over 100 000 public diverse methylome profiles. We employed the optimized workflow to query the demethylation dynamics in mouse primordial germ cells available at low cell numbers. Our data revealed nuanced chromatin states, sex disparities, and the role of DNA methylation in transposable element regulation during germ cell development. Collectively, we present comprehensive experimental and computational solutions to extend this widely used methylation assay technology to applications with limited DNA.
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Affiliation(s)
- Sol Moe Lee
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA 19104, USA
| | - Christian E Loo
- Graduate Group in Biochemistry and Biophysics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Rexxi D Prasasya
- Department of Cell and Developmental Biology, Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Marisa S Bartolomei
- Department of Cell and Developmental Biology, Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Rahul M Kohli
- Department of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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19
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Aguilar-Lacasaña S, Fontes Marques I, de Castro M, Dadvand P, Escribà X, Fossati S, González JR, Nieuwenhuijsen M, Alfano R, Annesi-Maesano I, Brescianini S, Burrows K, Calas L, Elhakeem A, Heude B, Hough A, Isaevska E, W V Jaddoe V, Lawlor DA, Monaghan G, Nawrot T, Plusquin M, Richiardi L, Watmuff A, Yang TC, Vrijheid M, F Felix J, Bustamante M. Green space exposure and blood DNA methylation at birth and in childhood - A multi-cohort study. ENVIRONMENT INTERNATIONAL 2024; 188:108684. [PMID: 38776651 DOI: 10.1016/j.envint.2024.108684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 03/21/2024] [Accepted: 04/21/2024] [Indexed: 05/25/2024]
Abstract
Green space exposure has been associated with improved mental, physical and general health. However, the underlying biological mechanisms remain largely unknown. The aim of this study was to investigate the association between green space exposure and cord and child blood DNA methylation. Data from eight European birth cohorts with a total of 2,988 newborns and 1,849 children were used. Two indicators of residential green space exposure were assessed: (i) surrounding greenness (satellite-based Normalized Difference Vegetation Index (NDVI) in buffers of 100 m and 300 m) and (ii) proximity to green space (having a green space ≥ 5,000 m2 within a distance of 300 m). For these indicators we assessed two exposure windows: (i) pregnancy, and (ii) the period from pregnancy to child blood DNA methylation assessment, named as cumulative exposure. DNA methylation was measured with the Illumina 450K or EPIC arrays. To identify differentially methylated positions (DMPs) we fitted robust linear regression models between pregnancy green space exposure and cord blood DNA methylation and between cumulative green space exposure and child blood DNA methylation. Two sensitivity analyses were conducted: (i) without adjusting for cellular composition, and (ii) adjusting for air pollution. Cohort results were combined through fixed-effect inverse variance weighted meta-analyses. Differentially methylated regions (DMRs) were identified from meta-analysed results using the Enmix-combp and DMRcate methods. There was no statistical evidence of pregnancy or cumulative exposures associating with any DMP (False Discovery Rate, FDR, p-value < 0.05). However, surrounding greenness exposure was inversely associated with four DMRs (three in cord blood and one in child blood) annotated to ADAMTS2, KCNQ1DN, SLC6A12 and SDK1 genes. Results did not change substantially in the sensitivity analyses. Overall, we found little evidence of the association between green space exposure and blood DNA methylation. Although we identified associations between surrounding greenness exposure with four DMRs, these findings require replication.
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Affiliation(s)
- Sofia Aguilar-Lacasaña
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública, Spain; Universitat de Barcelona, Barcelona, Spain.
| | - Irene Fontes Marques
- 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
| | - Montserrat de Castro
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública, Spain
| | - Payam Dadvand
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública, Spain
| | - Xavier Escribà
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública, Spain
| | - Serena Fossati
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública, Spain
| | - Juan R González
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública, Spain
| | - Mark Nieuwenhuijsen
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública, Spain
| | - Rossella Alfano
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium
| | - Isabella Annesi-Maesano
- Desbrest Institute of Epidemiology and Public Health (IDESP), Montpellier University and Inserm, Montpellier, Service des Maladies Allergiques et Respiratoires, CHU, Montpellier, France
| | - Sonia Brescianini
- Centre for Behavioural Science and Mental Health, Istituto Superiore di Sanità, Rome, Italy
| | - Kimberley Burrows
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Lucinda Calas
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004 Paris, France
| | - Ahmed Elhakeem
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Barbara Heude
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004 Paris, France
| | - Amy Hough
- Born in Bradford, Wolfson Centre for Applied Health Research, Bradford Royal Infirmary, Bradford, UK
| | - Elena Isaevska
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Medical Sciences, University of Turin, CPO-Piemonte, Turin, Italy
| | - Vincent W V Jaddoe
- 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
| | - Deborah A Lawlor
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Genevieve Monaghan
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tim Nawrot
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium; Department of Public Health, Leuven University (KU Leuven), Leuven, Belgium
| | - Michelle Plusquin
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium
| | - Lorenzo Richiardi
- Department of Medical Sciences, University of Turin, CPO-Piemonte, Turin, Italy
| | - Aidan Watmuff
- Born in Bradford, Wolfson Centre for Applied Health Research, Bradford Royal Infirmary, Bradford, UK
| | - Tiffany C Yang
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, UK
| | - Martine Vrijheid
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública, Spain
| | - Janine F Felix
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Mariona Bustamante
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública, Spain
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20
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Bell CG. Epigenomic insights into common human disease pathology. Cell Mol Life Sci 2024; 81:178. [PMID: 38602535 PMCID: PMC11008083 DOI: 10.1007/s00018-024-05206-2] [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: 01/19/2024] [Revised: 03/11/2024] [Accepted: 03/13/2024] [Indexed: 04/12/2024]
Abstract
The epigenome-the chemical modifications and chromatin-related packaging of the genome-enables the same genetic template to be activated or repressed in different cellular settings. This multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan. The causal role of the epigenome in human pathology, beyond imprinting disorders and specific tumour suppressor genes, was further brought into the spotlight by large-scale sequencing projects identifying that mutations in epigenomic machinery genes could be critical drivers in both cancer and developmental disorders. Abrogation of this cellular mechanism is providing new molecular insights into pathogenesis. However, deciphering the full breadth and implications of these epigenomic changes remains challenging. Knowledge is accruing regarding disease mechanisms and clinical biomarkers, through pathogenically relevant and surrogate tissue analyses, respectively. Advances include consortia generated cell-type specific reference epigenomes, high-throughput DNA methylome association studies, as well as insights into ageing-related diseases from biological 'clocks' constructed by machine learning algorithms. Also, 3rd-generation sequencing is beginning to disentangle the complexity of genetic and DNA modification haplotypes. Cell-free DNA methylation as a cancer biomarker has clear clinical utility and further potential to assess organ damage across many disorders. Finally, molecular understanding of disease aetiology brings with it the opportunity for exact therapeutic alteration of the epigenome through CRISPR-activation or inhibition.
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Affiliation(s)
- Christopher G Bell
- William Harvey Research Institute, Barts & The London Faculty of Medicine, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.
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21
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Bunyavanich S, Becker PM, Altman MC, Lasky-Su J, Ober C, Zengler K, Berdyshev E, Bonneau R, Chatila T, Chatterjee N, Chung KF, Cutcliffe C, Davidson W, Dong G, Fang G, Fulkerson P, Himes BE, Liang L, Mathias RA, Ogino S, Petrosino J, Price ND, Schadt E, Schofield J, Seibold MA, Steen H, Wheatley L, Zhang H, Togias A, Hasegawa K. Analytical challenges in omics research on asthma and allergy: A National Institute of Allergy and Infectious Diseases workshop. J Allergy Clin Immunol 2024; 153:954-968. [PMID: 38295882 PMCID: PMC10999353 DOI: 10.1016/j.jaci.2024.01.014] [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: 12/13/2023] [Revised: 01/19/2024] [Accepted: 01/24/2024] [Indexed: 02/29/2024]
Abstract
Studies of asthma and allergy are generating increasing volumes of omics data for analysis and interpretation. The National Institute of Allergy and Infectious Diseases (NIAID) assembled a workshop comprising investigators studying asthma and allergic diseases using omics approaches, omics investigators from outside the field, and NIAID medical and scientific officers to discuss the following areas in asthma and allergy research: genomics, epigenomics, transcriptomics, microbiomics, metabolomics, proteomics, lipidomics, integrative omics, systems biology, and causal inference. Current states of the art, present challenges, novel and emerging strategies, and priorities for progress were presented and discussed for each area. This workshop report summarizes the major points and conclusions from this NIAID workshop. As a group, the investigators underscored the imperatives for rigorous analytic frameworks, integration of different omics data types, cross-disciplinary interaction, strategies for overcoming current limitations, and the overarching goal to improve scientific understanding and care of asthma and allergic diseases.
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Affiliation(s)
| | - Patrice M Becker
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, Md
| | | | - Jessica Lasky-Su
- Brigham & Women's Hospital and Harvard Medical School, Boston, Mass
| | | | | | | | | | - Talal Chatila
- Boston Children's Hospital and Harvard Medical School, Boston, Mass
| | | | | | | | - Wendy Davidson
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, Md
| | - Gang Dong
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, Md
| | - Gang Fang
- Icahn School of Medicine at Mount Sinai, New York, NY
| | - Patricia Fulkerson
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, Md
| | | | - Liming Liang
- Harvard T. H. Chan School of Public Health, Boston, Mass
| | | | - Shuji Ogino
- Brigham & Women's Hospital and Harvard Medical School, Boston, Mass; Harvard T. H. Chan School of Public Health, Boston, Mass; Broad Institute of MIT and Harvard, Boston, Mass
| | | | | | - Eric Schadt
- Icahn School of Medicine at Mount Sinai, New York, NY
| | | | - Max A Seibold
- National Jewish Health, Denver, Colo; University of Colorado School of Medicine, Aurora, Colo
| | - Hanno Steen
- Boston Children's Hospital and Harvard Medical School, Boston, Mass
| | - Lisa Wheatley
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, Md
| | - Hongmei Zhang
- School of Public Health, University of Memphis, Memphis, Tenn
| | - Alkis Togias
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, Md
| | - Kohei Hasegawa
- Massachusetts General Hospital and Harvard Medical School, Boston, Mass
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22
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Yang M, Wang M, Zhao X, Xu F, Liang S, Wang Y, Wang N, Sambou ML, Jiang Y, Dai J. DNA methylation marker identification and poly-methylation risk score in prediction of healthspan termination. Epigenomics 2024; 16:461-472. [PMID: 38482663 DOI: 10.2217/epi-2023-0343] [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: 03/23/2024] Open
Abstract
Aim: To elucidate the epigenetic consequences of DNA methylation in healthspan termination (HST), considering the current limited understanding. Materials & methods: Genetically predicted DNA methylation models were established (n = 2478). These models were applied to genome-wide association study data on HST. Then, a poly-methylation risk score (PMRS) was established in 241,008 individuals from the UK Biobank. Results: Of the 63,046 CpGs from the prediction models, 13 novel CpGs were associated with HST. Furthermore, people with high PMRSs showed higher HST risk (hazard ratio: 1.18; 95% CI: 1.13-1.25). Conclusion: The study indicates that DNA methylation may influence HST by regulating the expression of genes (e.g., PRMT6, CTSK). PMRSs have a promising application in discriminating subpopulations to facilitate early prevention.
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Affiliation(s)
- Meiqi Yang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Mei Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Xiaoyu Zhao
- Department of Statistics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Feifei Xu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Shuang Liang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Yifan Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Nanxi Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Muhammed Lamin Sambou
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Yue Jiang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention & Treatment, Collaborative Innovation Center for Cancer Personalized Medicine & China International Cooperation Center for Environment & Human Health, Gusu School, Nanjing Medical University, Nanjing, 211166, China
| | - Juncheng Dai
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention & Treatment, Collaborative Innovation Center for Cancer Personalized Medicine & China International Cooperation Center for Environment & Human Health, Gusu School, Nanjing Medical University, Nanjing, 211166, China
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23
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Liu D, Aziz NA, Imtiaz MA, Pehlivan G, Breteler MMB. Associations of measured and genetically predicted leukocyte telomere length with vascular phenotypes: a population-based study. GeroScience 2024; 46:1947-1970. [PMID: 37782440 PMCID: PMC10828293 DOI: 10.1007/s11357-023-00914-2] [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: 06/07/2023] [Accepted: 08/15/2023] [Indexed: 10/03/2023] Open
Abstract
Shorter leukocyte telomere length (LTL) is associated with cardiovascular dysfunction. Whether this association differs between measured and genetically predicted LTL is still unclear. Moreover, the molecular processes underlying the association remain largely unknown. We used baseline data of the Rhineland Study, an ongoing population-based cohort study in Bonn, Germany [56.2% women, age: 55.5 ± 14.0 years (range 30 - 95 years)]. We calculated genetically predicted LTL in 4180 participants and measured LTL in a subset of 1828 participants with qPCR. Using multivariable regression, we examined the association of measured and genetically predicted LTL, and the difference between measured and genetically predicted LTL (ΔLTL), with four vascular functional domains and the overall vascular health. Moreover, we performed epigenome-wide association studies of three LTL measures. Longer measured LTL was associated with better microvascular and cardiac function. Longer predicted LTL was associated with better cardiac function. Larger ΔLTL was associated with better microvascular and cardiac function and overall vascular health, independent of genetically predicted LTL. Several CpGs were associated (p < 1e-05) with measured LTL (n = 5), genetically predicted LTL (n = 8), and ΔLTL (n = 27). Genes whose methylation status was associated with ΔLTL were enriched in vascular endothelial signaling pathways and have been linked to environmental exposures, cardiovascular diseases, and mortality. Our findings suggest that non-genetic causes of LTL contribute to microvascular and cardiac function and overall vascular health, through an effect on the vascular endothelial signaling pathway. Interventions that counteract LTL may thus improve vascular function.
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Affiliation(s)
- Dan Liu
- German Center for Neurodegenerative Diseases (DZNE), Population Health Sciences, Bonn, Germany
| | - N Ahmad Aziz
- German Center for Neurodegenerative Diseases (DZNE), Population Health Sciences, Bonn, Germany
- Department of Neurology, Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Mohammed Aslam Imtiaz
- German Center for Neurodegenerative Diseases (DZNE), Population Health Sciences, Bonn, Germany
| | - Gökhan Pehlivan
- German Center for Neurodegenerative Diseases (DZNE), Population Health Sciences, Bonn, Germany
| | - Monique M B Breteler
- German Center for Neurodegenerative Diseases (DZNE), Population Health Sciences, Bonn, Germany.
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany.
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24
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Zhao X, Yang M, Fan J, Wang M, Wang Y, Qin N, Zhu M, Jiang Y, Gorlova OY, Gorlov IP, Albanes D, Lam S, Tardón A, Chen C, Goodman GE, Bojesen SE, Landi MT, Johansson M, Risch A, Wichmann HE, Bickeböller H, Christiani DC, Rennert G, Arnold SM, Brennan P, Field JK, Shete S, Le Marchand L, Liu G, Hung RJ, Andrew AS, Kiemeney LA, Zienolddiny S, Grankvist K, Johansson M, Caporaso NE, Woll PJ, Lazarus P, Schabath MB, Aldrich MC, Patel AV, Davies MPA, Ma H, Jin G, Hu Z, Amos CI, Shen H, Dai J. Identification of genetically predicted DNA methylation markers associated with non-small cell lung cancer risk among 34,964 cases and 448,579 controls. Cancer 2024; 130:913-926. [PMID: 38055287 PMCID: PMC11327897 DOI: 10.1002/cncr.35130] [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: 12/07/2022] [Revised: 05/05/2023] [Accepted: 05/22/2023] [Indexed: 12/07/2023]
Abstract
BACKGROUND Although the associations between genetic variations and lung cancer risk have been explored, the epigenetic consequences of DNA methylation in lung cancer development are largely unknown. Here, the genetically predicted DNA methylation markers associated with non-small cell lung cancer (NSCLC) risk by a two-stage case-control design were investigated. METHODS The genetic prediction models for methylation levels based on genetic and methylation data of 1595 subjects from the Framingham Heart Study were established. The prediction models were applied to a fixed-effect meta-analysis of screening data sets with 27,120 NSCLC cases and 27,355 controls to identify the methylation markers, which were then replicated in independent data sets with 7844 lung cancer cases and 421,224 controls. Also performed was a multi-omics functional annotation for the identified CpGs by integrating genomics, epigenomics, and transcriptomics and investigation of the potential regulation pathways. RESULTS Of the 29,894 CpG sites passing the quality control, 39 CpGs associated with NSCLC risk (Bonferroni-corrected p ≤ 1.67 × 10-6 ) were originally identified. Of these, 16 CpGs remained significant in the validation stage (Bonferroni-corrected p ≤ 1.28 × 10-3 ), including four novel CpGs. Multi-omics functional annotation showed nine of 16 CpGs were potentially functional biomarkers for NSCLC risk. Thirty-five genes within a 1-Mb window of 12 CpGs that might be involved in regulatory pathways of NSCLC risk were identified. CONCLUSIONS Sixteen promising DNA methylation markers associated with NSCLC were identified. Changes of the methylation level at these CpGs might influence the development of NSCLC by regulating the expression of genes nearby. PLAIN LANGUAGE SUMMARY The epigenetic consequences of DNA methylation in lung cancer development are still largely unknown. This study used summary data of large-scale genome-wide association studies to investigate the associations between genetically predicted levels of methylation biomarkers and non-small cell lung cancer risk at the first time. This study looked at how well larotrectinib worked in adult patients with sarcomas caused by TRK fusion proteins. These findings will provide a unique insight into the epigenetic susceptibility mechanisms of lung cancer.
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Affiliation(s)
- Xiaoyu Zhao
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Department of Statistics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Meiqi Yang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Jingyi Fan
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
- Health Management Center, Gusu School, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Mei Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yifan Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Na Qin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
- Department of Thoracic Surgery, Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Yue Jiang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
| | - Olga Y Gorlova
- Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire, USA
- Department of Medicine, Epidemiology Section, Institute for Clinical and Translational Research, Baylor Medical College, Houston, Texas, USA
| | - Ivan P Gorlov
- Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire, USA
- Department of Medicine, Epidemiology Section, Institute for Clinical and Translational Research, Baylor Medical College, Houston, Texas, USA
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Stephen Lam
- Department of Integrative Oncology, British Columbia Cancer Agency, Vancouver, British Columbia, Canada
| | - Adonina Tardón
- Department of Public Health IUOPA, University of Oviedo, ISPA and CIBERESP, Oviedo, Spain
| | - Chu Chen
- Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Gary E Goodman
- Public Health Sciences Division, Swedish Cancer Institute, Seattle, Washington, USA
| | - Stig E Bojesen
- Department of Clinical Biochemistry, Copenhagen University Hospital, Copenhagen, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Mattias Johansson
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Angela Risch
- Department of Biosciences, Allergy-Cancer-BioNano Research Centre, University of Salzburg, Salzburg, Austria
- Division of Epigenomics and Cancer Risk Factors, DKFZ-German Cancer Research Center, Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC-H), German Center for Lung Research (DZL), Heidelberg, Germany
| | - H-Erich Wichmann
- Institute of Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
| | - Heike Bickeböller
- Department of Genetic Epidemiology, University Medical Center Goettingen, Goettingen, Germany
| | - David C Christiani
- Departments of Environmental Health and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Gad Rennert
- Technion Faculty of Medicine, Carmel Medical Center, Haifa, Israel
| | - Susanne M Arnold
- Markey Cancer Center, University of Kentucky, Lexington, Kentucky, USA
| | - Paul Brennan
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - John K Field
- Molecular and Clinical Cancer Medicine, Roy Castle Lung Cancer Research Programme, The University of Liverpool Institute of Translational Medicine, Liverpool, UK
| | - Sanjay Shete
- Department of Epidemiology, The University of Texas, MD Anderson Cancer Center, Houston, Texas, USA
| | - Loïc Le Marchand
- Epidemiology Program, University of Hawai'i Cancer Center, Honolulu, Hawaii, USA
| | - Geoffrey Liu
- Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Rayjean J Hung
- Prosseman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada
| | - Angeline S Andrew
- Department of Neurology, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire, USA
| | - Lambertus A Kiemeney
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, the Netherlands
| | | | - Kjell Grankvist
- Department of Medical Biosciences, Umeå University, Umea, Sweden
| | | | - Neil E Caporaso
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA
| | - Penella J Woll
- Academic Unit of Clinical Oncology, University of Sheffield, Sheffield, UK
| | - Philip Lazarus
- Department of Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, Washington, USA
| | - Matthew B Schabath
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA
| | - Melinda C Aldrich
- Department of Medicine (Division of Genetic Medicine), Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Alpa V Patel
- Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta, Georgia, USA
| | - Michael P A Davies
- Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - Hongxia Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
| | - Guangfu Jin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
| | - Zhibin Hu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
| | - Christopher I Amos
- Baylor College of Medicine, Institute for Clinical and Translational Research, Houston, Texas, USA
| | - Hongbing Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
| | - Juncheng Dai
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
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25
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Huang BZ, Binder AM, Quon B, Patel YM, Lum-Jones A, Tiirikainen M, Murphy SE, Loo L, Maunakea AK, Haiman CA, Wilkens LR, Koh WP, Cai Q, Aldrich MC, Siegmund KD, Hecht SS, Yuan JM, Blot WJ, Stram DO, Le Marchand L, Park SL. Epigenome-wide association study of total nicotine equivalents in multiethnic current smokers from three prospective cohorts. Am J Hum Genet 2024; 111:456-472. [PMID: 38367619 PMCID: PMC10940014 DOI: 10.1016/j.ajhg.2024.01.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 01/22/2024] [Accepted: 01/25/2024] [Indexed: 02/19/2024] Open
Abstract
The impact of tobacco exposure on health varies by race and ethnicity and is closely tied to internal nicotine dose, a marker of carcinogen uptake. DNA methylation is strongly responsive to smoking status and may mediate health effects, but study of associations with internal dose is limited. We performed a blood leukocyte epigenome-wide association study (EWAS) of urinary total nicotine equivalents (TNEs; a measure of nicotine uptake) and DNA methylation measured using the MethylationEPIC v1.0 BeadChip (EPIC) in six racial and ethnic groups across three cohort studies. In the Multiethnic Cohort Study (discovery, n = 1994), TNEs were associated with differential methylation at 408 CpG sites across >250 genomic regions (p < 9 × 10-8). The top significant sites were annotated to AHRR, F2RL3, RARA, GPR15, PRSS23, and 2q37.1, all of which had decreasing methylation with increasing TNEs. We identified 45 novel CpG sites, of which 42 were unique to the EPIC array and eight annotated to genes not previously linked with smoking-related DNA methylation. The most significant signal in a novel gene was cg03748458 in MIR383;SGCZ. Fifty-one of the 408 discovery sites were validated in the Singapore Chinese Health Study (n = 340) and the Southern Community Cohort Study (n = 394) (Bonferroni corrected p < 1.23 × 10-4). Significant heterogeneity by race and ethnicity was detected for CpG sites in MYO1G and CYTH1. Furthermore, TNEs significantly mediated the association between cigarettes per day and DNA methylation at 15 sites (average 22.5%-44.3% proportion mediated). Our multiethnic study highlights the transethnic and ethnic-specific methylation associations with internal nicotine dose, a strong predictor of smoking-related morbidities.
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Affiliation(s)
- Brian Z Huang
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA.
| | - Alexandra M Binder
- Population Sciences of the Pacific Program-Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA; Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - Brandon Quon
- Population Sciences of the Pacific Program-Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Yesha M Patel
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Annette Lum-Jones
- Population Sciences of the Pacific Program-Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Maarit Tiirikainen
- Population Sciences of the Pacific Program-Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Sharon E Murphy
- Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA
| | - Lenora Loo
- Population Sciences of the Pacific Program-Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Alika K Maunakea
- Department of Anatomy, Biochemistry and Physiology, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, USA
| | - Christopher A Haiman
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Lynne R Wilkens
- Population Sciences of the Pacific Program-Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Woon-Puay Koh
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Melinda C Aldrich
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kimberly D Siegmund
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Stephen S Hecht
- Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA; Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - William J Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Daniel O Stram
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Loïc Le Marchand
- Population Sciences of the Pacific Program-Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Sungshim L Park
- Population Sciences of the Pacific Program-Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA.
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26
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Creasey N, Leijten P, Tollenaar MS, Boks MP, Overbeek G. DNA methylation variation after a parenting program for child conduct problems: Findings from a randomized controlled trial. Child Dev 2024. [PMID: 38436454 DOI: 10.1111/cdev.14090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2024]
Abstract
This study investigated associations of the Incredible Years (IY) parenting program with children's DNA methylation. Participants were 289 Dutch children aged 3-9 years (75% European ancestry, 48% female) with above-average conduct problems. Saliva was collected 2.5 years after families were randomized to IY or care as usual (CAU). Using an intention-to-treat approach, confirmatory multiple-regression analyses revealed no significant differences between the IY and CAU groups in children's methylation levels at the NR3C1 and FKBP5 genes. However, exploratory epigenome-wide analyses revealed nine differentially methylated regions between groups, coinciding with SLAMF1, MITF, FAM200B, PSD3, SNX31, and CELSR1. The study provides preliminary evidence for associations of IY with children's salivary methylation levels and highlights the need for further research into biological outcomes of parenting programs.
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Affiliation(s)
- Nicole Creasey
- Research Institute of Child Development and Education, University of Amsterdam, Amsterdam, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Patty Leijten
- Research Institute of Child Development and Education, University of Amsterdam, Amsterdam, The Netherlands
| | - Marieke S Tollenaar
- Institute of Psychology & Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands
| | - Marco P Boks
- Institute of Psychology & Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands
- Department of Psychiatry, Brain Center University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Geertjan Overbeek
- Research Institute of Child Development and Education, University of Amsterdam, Amsterdam, The Netherlands
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27
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Lange de Luna J, Nounu A, Neumeyer S, Sinke L, Wilson R, Hellbach F, Matías-García PR, Delerue T, Winkelmann J, Peters A, Thorand B, Beekman M, Heijmans BT, Slagboom E, Gieger C, Linseisen J, Waldenberger M. Epigenome-wide association study of dietary fatty acid intake. Clin Epigenetics 2024; 16:29. [PMID: 38365790 PMCID: PMC10874013 DOI: 10.1186/s13148-024-01643-9] [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: 06/14/2023] [Accepted: 02/09/2024] [Indexed: 02/18/2024] Open
Abstract
BACKGROUND Dietary intake of n-3 polyunsaturated fatty acids (PUFA) may have a protective effect on the development of cardiovascular diseases, diabetes, depression and cancer, while a high intake of n-6 PUFA was often reported to be associated with inflammation-related traits. The effect of PUFAs on health outcomes might be mediated by DNA methylation (DNAm). The aim of our study is to identify the impact of PUFA intake on DNAm in the Cooperative Health Research in the Region of Augsburg (KORA) FF4 cohort and the Leiden Longevity Study (LLS). RESULTS DNA methylation levels were measured in whole blood from the population-based KORA FF4 study (N = 1354) and LLS (N = 448), using the Illumina MethylationEPIC BeadChip and Illumina HumanMethylation450 array, respectively. We assessed associations between DNAm and intake of eight and four PUFAs in KORA and LLS, respectively. Where possible, results were meta-analyzed. Below the Bonferroni correction threshold (p < 7.17 × 10-8), we identified two differentially methylated positions (DMPs) associated with PUFA intake in the KORA study. The DMP cg19937480, annotated to gene PRDX1, was positively associated with docosahexaenoic acid (DHA) in model 1 (beta: 2.00 × 10-5, 95%CI: 1.28 × 10-5-2.73 × 10-5, P value: 6.98 × 10-8), while cg05041783, annotated to gene MARK2, was positively associated with docosapentaenoic acid (DPA) in our fully adjusted model (beta: 9.80 × 10-5, 95%CI: 6.25 × 10-5-1.33 × 10-4, P value: 6.75 × 10-8). In the meta-analysis, we identified the CpG site (cg15951061), annotated to gene CDCA7L below Bonferroni correction (1.23 × 10-7) associated with eicosapentaenoic acid (EPA) intake in model 1 (beta: 2.00 × 10-5, 95% CI: 1.27 × 10-5-2.73 × 10-5, P value = 5.99 × 10-8) and we confirmed the association of cg19937480 with DHA in both models 1 and 2 (beta: 2.07 × 10-5, 95% CI: 1.31 × 10-5-2.83 × 10-5, P value = 1.00 × 10-7 and beta: 2.19 × 10-5, 95% CI: 1.41 × 10-5-2.97 × 10-5, P value = 5.91 × 10-8 respectively). CONCLUSIONS Our study identified three CpG sites associated with PUFA intake. The mechanisms of these sites remain largely unexplored, highlighting the novelty of our findings. Further research is essential to understand the links between CpG site methylation and PUFA outcomes.
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Affiliation(s)
- Julia Lange de Luna
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology-IBE, LMU Munich, 80539, Munich, Germany
| | - Aayah Nounu
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Sonja Neumeyer
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Lucy Sinke
- Molecular Epidemiology, Department of Biomedical Data Science, Leiden University Medical Center, 2333 ZC, Leiden, The Netherlands
| | - Rory Wilson
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Fabian Hellbach
- Epidemiology, Faculty of Medicine, University of Augsburg, University Hospital of Augsburg, 86156, Augsburg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology-IBE, LMU Munich, 80539, Munich, Germany
| | - Pamela R Matías-García
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Thomas Delerue
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Juliane Winkelmann
- Institute of Neurogenomics, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Klinikum Rechts Der Isar, Chair Neurogenetics, Technical University of Munich, Munich, Germany
- Klinikum Rechts Der Isar, Institute of Human Genetics, Technical University of Munich, Munich, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology-IBE, LMU Munich, 80539, Munich, Germany
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology-IBE, LMU Munich, 80539, Munich, Germany
| | - Marian Beekman
- Molecular Epidemiology, Department of Biomedical Data Science, Leiden University Medical Center, 2333 ZC, Leiden, The Netherlands
| | - Bastiaan T Heijmans
- Molecular Epidemiology, Department of Biomedical Data Science, Leiden University Medical Center, 2333 ZC, Leiden, The Netherlands
| | - Eline Slagboom
- Molecular Epidemiology, Department of Biomedical Data Science, Leiden University Medical Center, 2333 ZC, Leiden, The Netherlands
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Jakob Linseisen
- Epidemiology, Faculty of Medicine, University of Augsburg, University Hospital of Augsburg, 86156, Augsburg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology-IBE, LMU Munich, 80539, Munich, Germany
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany.
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany.
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da Silva Rodrigues G, Noronha NY, Noma IHY, de Lima JGR, da Silva Sobrinho AC, de Souza Pinhel MA, de Almeida ML, Watanabe LM, Nonino CB, Júnior CRB. 14-Week exercise training modifies the DNA methylation levels at gene sites in non-Alzheimer's disease women aged 50 to 70 years. Exp Gerontol 2024; 186:112362. [PMID: 38232788 DOI: 10.1016/j.exger.2024.112362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 01/08/2024] [Accepted: 01/11/2024] [Indexed: 01/19/2024]
Abstract
Exercise training emerges as a key strategy in lifestyle modification, capable of reducing the risk of developing Alzheimer's disease (AD) due to risk factors such as age, family history, genetics and low level of education associated with AD. We aim to analyze the effect of a 14-week combined exercise training (CT) on the methylation of genes associated with AD in non-alzheimer's disease women. CT sessions lasted 60 min, occurring three times a week for 14 weeks. Forty non-Alzheimer's disease women aged 50 to 70 years (60.7 ± 4.1 years) with a mean height of 1.6 ± 0.1 m, mean weight of 73.12 ± 9.0 kg and a mean body mass index of 29.69 ± 3.5 kg/m2, underwent two physical assessments: pre and post the 14 weeks. DNA methylation assays utilized the EPIC Infinium Methylation BeadChip from Illumina. We observed that 14 weeks of CT led to reductions in systolic (p = 0.001) and diastolic (p = 0.017) blood pressure and improved motor skills post-intervention. Among 25 genes linked to AD, CT induced differentially methylated sites in 12 genes, predominantly showing hypomethylated sites (negative β values). Interestingly, despite hypomethylated sites, some genes exhibited hypermethylated sites (positive β values), such as ABCA7, BDNF, and WWOX. A 14-week CT regimen was adequate to induce differential methylation in 12 CE-related genes in healthy older women, alongside improvements in motor skills and blood pressure. In conclusion, this study suggest that combined training can be a strategy to improve physical fitness in older individuals, especially able to induce methylation alterations in genes sites related to development of AD. It is important to highlight that training should act as protective factor in older adults.
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Affiliation(s)
- Guilherme da Silva Rodrigues
- Department of Internal Medicine, School of Medicine of Ribeirão Preto, University of São Paulo, Ribeirão Preto, São Paulo, Brazil
| | - Natália Yumi Noronha
- Department of Gynecology and Obstetrics, University Medical Center Groningen, Groningen, the Netherlands.
| | - Isabella Harumi Yonehara Noma
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil
| | - João Gabriel Ribeiro de Lima
- Department of Internal Medicine, School of Medicine of Ribeirão Preto, University of São Paulo, Ribeirão Preto, São Paulo, Brazil
| | | | - Marcela Augusta de Souza Pinhel
- Department of Internal Medicine, School of Medicine of Ribeirão Preto, University of São Paulo, Ribeirão Preto, São Paulo, Brazil
| | | | | | - Carla Barbosa Nonino
- Department of Health Sciences, Ribeirão Preto Medical School, Ribeirão Preto, São Paulo, Brazil
| | - Carlos Roberto Bueno Júnior
- Department of Internal Medicine, School of Medicine of Ribeirão Preto, University of São Paulo, Ribeirão Preto, São Paulo, Brazil; School of Physical Education of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
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29
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Ouni M, Kovac L, Gancheva S, Jähnert M, Zuljan E, Gottmann P, Kahl S, de Angelis MH, Roden M, Schürmann A. Novel markers and networks related to restored skeletal muscle transcriptome after bariatric surgery. Obesity (Silver Spring) 2024; 32:363-375. [PMID: 38086776 DOI: 10.1002/oby.23954] [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: 07/11/2023] [Revised: 10/16/2023] [Accepted: 10/19/2023] [Indexed: 01/26/2024]
Abstract
OBJECTIVE The aim of this study was to discover novel markers underlying the improvement of skeletal muscle metabolism after bariatric surgery. METHODS Skeletal muscle transcriptome data of lean people and people with obesity, before and 1 year after bariatric surgery, were subjected to weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) regression. Results of LASSO were confirmed in a replication cohort. RESULTS The expression levels of 440 genes differing between individuals with and without obesity were no longer different 1 year after surgery, indicating restoration. WGCNA clustered 116 genes with normalized expression in one major module, particularly correlating to weight loss and decreased plasma free fatty acids (FFA), 44 of which showed an obesity-related phenotype upon deletion in mice. Among the genes of the major module, 105 represented prominent markers for reduced FFA concentration, including 55 marker genes for decreased BMI in both the discovery and replication cohorts. CONCLUSIONS Previously unknown gene networks and marker genes underlined the important role of FFA in restoring muscle gene expression after bariatric surgery and further suggest novel therapeutic targets for obesity.
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Affiliation(s)
- Meriem Ouni
- German Institute of Human Nutrition, Department of Experimental Diabetology, Potsdam, Germany
- German Center for Diabetes Research (DZD), Munich, Germany
| | - Leona Kovac
- German Institute of Human Nutrition, Department of Experimental Diabetology, Potsdam, Germany
- German Center for Diabetes Research (DZD), Munich, Germany
| | - Sofiya Gancheva
- German Center for Diabetes Research (DZD), Munich, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich Heine University, Düsseldorf, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research, Heinrich Heine University, Düsseldorf, Germany
| | - Markus Jähnert
- German Institute of Human Nutrition, Department of Experimental Diabetology, Potsdam, Germany
- German Center for Diabetes Research (DZD), Munich, Germany
| | - Erika Zuljan
- German Institute of Human Nutrition, Department of Experimental Diabetology, Potsdam, Germany
- German Center for Diabetes Research (DZD), Munich, Germany
| | - Pascal Gottmann
- German Institute of Human Nutrition, Department of Experimental Diabetology, Potsdam, Germany
- German Center for Diabetes Research (DZD), Munich, Germany
| | - Sabine Kahl
- German Center for Diabetes Research (DZD), Munich, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich Heine University, Düsseldorf, Germany
| | - Martin Hrabĕ de Angelis
- German Center for Diabetes Research (DZD), Munich, Germany
- Institute of Experimental Genetics, German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- School of Life Sciences, Technical University Munich, Freising, Germany
| | - Michael Roden
- German Center for Diabetes Research (DZD), Munich, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich Heine University, Düsseldorf, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research, Heinrich Heine University, Düsseldorf, Germany
| | - Annette Schürmann
- German Institute of Human Nutrition, Department of Experimental Diabetology, Potsdam, Germany
- German Center for Diabetes Research (DZD), Munich, Germany
- Institute of Nutritional Sciences, University of Potsdam, Nuthetal, Germany
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30
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Hoang TT, Lee Y, McCartney DL, Kersten ETG, Page CM, Hulls PM, Lee M, Walker RM, Breeze CE, Bennett BD, Burkholder AB, Ward J, Brantsæter AL, Caspersen IH, Motsinger-Reif AA, Richards M, White JD, Zhao S, Richmond RC, Magnus MC, Koppelman GH, Evans KL, Marioni RE, Håberg SE, London SJ. Comprehensive evaluation of smoking exposures and their interactions on DNA methylation. EBioMedicine 2024; 100:104956. [PMID: 38199042 PMCID: PMC10825325 DOI: 10.1016/j.ebiom.2023.104956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 12/19/2023] [Accepted: 12/20/2023] [Indexed: 01/12/2024] Open
Abstract
BACKGROUND Smoking impacts DNA methylation, but data are lacking on smoking-related differential methylation by sex or dietary intake, recent smoking cessation (<1 year), persistence of differential methylation from in utero smoking exposure, and effects of environmental tobacco smoke (ETS). METHODS We meta-analysed data from up to 15,014 adults across 5 cohorts with DNA methylation measured in blood using Illumina's EPIC array for current smoking (2560 exposed), quit < 1 year (500 exposed), in utero (286 exposed), and ETS exposure (676 exposed). We also evaluated the interaction of current smoking with sex or diet (fibre, folate, and vitamin C). FINDINGS Using false discovery rate (FDR < 0.05), 65,857 CpGs were differentially methylated in relation to current smoking, 4025 with recent quitting, 594 with in utero exposure, and 6 with ETS. Most current smoking CpGs attenuated within a year of quitting. CpGs related to in utero exposure in adults were enriched for those previously observed in newborns. Differential methylation by current smoking at 4-71 CpGs may be modified by sex or dietary intake. Nearly half (35-50%) of differentially methylated CpGs on the 450 K array were associated with blood gene expression. Current smoking and in utero smoking CpGs implicated 3049 and 1067 druggable targets, including chemotherapy drugs. INTERPRETATION Many smoking-related methylation sites were identified with Illumina's EPIC array. Most signals revert to levels observed in never smokers within a year of cessation. Many in utero smoking CpGs persist into adulthood. Smoking-related druggable targets may provide insights into cancer treatment response and shared mechanisms across smoking-related diseases. FUNDING Intramural Research Program of the National Institutes of Health, Norwegian Ministry of Health and Care Services and the Ministry of Education and Research, Chief Scientist Office of the Scottish Government Health Directorates and the Scottish Funding Council, Medical Research Council UK and the Wellcome Trust.
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Affiliation(s)
- Thanh T Hoang
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA; Department of Pediatrics, Division of Hematology-Oncology, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA; Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA; Cancer and Hematology Center, Texas Children's Hospital, Houston, TX, USA
| | - Yunsung Lee
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Elin T G Kersten
- University of Groningen, University Medical Center Groningen, Beatrix Children's Hospital, Dept. of Pediatric Pulmonology and Pediatric Allergy, Groningen, the Netherlands; University of Groningen, University Medical Center Groningen, GRIAC Research Institute, Groningen, the Netherlands
| | - Christian M Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway; Department of Physical Health and Ageing, Division for Physical and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Paige M Hulls
- Population Health Sciences, Bristol Medical School, University of Bristol, BS8 2BN, UK; MRC Integrative Epidemiology Unit at University of Bristol, BS8 2BN, UK
| | - Mikyeong Lee
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh EH4 2XU, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; School of Psychology, University of Exeter, Perry Road, Exeter, UK
| | - Charles E Breeze
- UCL Cancer Institute, University College London, Paul O'Gorman Building, London, UK; Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Brian D Bennett
- Department of Health and Human Services, Integrative Bioinformatics Support Group, National Institutes of Health, Research Triangle Park, NC, USA
| | - Adam B Burkholder
- Department of Health and Human Services, Office of Environmental Science Cyberinfrastructure, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - James Ward
- Department of Health and Human Services, Integrative Bioinformatics Support Group, National Institutes of Health, Research Triangle Park, NC, USA
| | - Anne Lise Brantsæter
- Department of Food Safety, Division of Climate and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Ida H Caspersen
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Alison A Motsinger-Reif
- Department of Health and Human Services, Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | | | - Julie D White
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA; GenOmics and Translational Research Center, Analytics Practice Area, RTI International, Research Triangle Park, NC, USA
| | - Shanshan Zhao
- Department of Health and Human Services, Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Rebecca C Richmond
- Population Health Sciences, Bristol Medical School, University of Bristol, BS8 2BN, UK; MRC Integrative Epidemiology Unit at University of Bristol, BS8 2BN, UK
| | - Maria C Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Gerard H Koppelman
- University of Groningen, University Medical Center Groningen, Beatrix Children's Hospital, Dept. of Pediatric Pulmonology and Pediatric Allergy, Groningen, the Netherlands; University of Groningen, University Medical Center Groningen, GRIAC Research Institute, Groningen, the Netherlands
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Siri E Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Stephanie J London
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA.
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31
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Li S, Spitz N, Ghantous A, Abrishamcar S, Reimann B, Marques I, Silver MJ, Aguilar-Lacasaña S, Kitaba N, Rezwan FI, Röder S, Sirignano L, Tuhkanen J, Mancano G, Sharp GC, Metayer C, Morimoto L, Stein DJ, Zar HJ, Alfano R, Nawrot T, Wang C, Kajantie E, Keikkala E, Mustaniemi S, Ronkainen J, Sebert S, Silva W, Vääräsmäki M, Jaddoe VWV, Bernstein RM, Prentice AM, Cosin-Tomas M, Dwyer T, Håberg SE, Herceg Z, Magnus MC, Munthe-Kaas MC, Page CM, Völker M, Gilles M, Send T, Witt S, Zillich L, Gagliardi L, Richiardi L, Czamara D, Räikkönen K, Chatzi L, Vafeiadi M, Arshad SH, Ewart S, Plusquin M, Felix JF, Moore SE, Vrijheid M, Holloway JW, Karmaus W, Herberth G, Zenclussen A, Streit F, Lahti J, Hüls A, Hoang TT, London SJ, Wiemels JL. A Pregnancy and Childhood Epigenetics Consortium (PACE) meta-analysis highlights potential relationships between birth order and neonatal blood DNA methylation. Commun Biol 2024; 7:66. [PMID: 38195839 PMCID: PMC10776586 DOI: 10.1038/s42003-023-05698-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 12/12/2023] [Indexed: 01/11/2024] Open
Abstract
Higher birth order is associated with altered risk of many disease states. Changes in placentation and exposures to in utero growth factors with successive pregnancies may impact later life disease risk via persistent DNA methylation alterations. We investigated birth order with Illumina DNA methylation array data in each of 16 birth cohorts (8164 newborns) with European, African, and Latino ancestries from the Pregnancy and Childhood Epigenetics Consortium. Meta-analyzed data demonstrated systematic DNA methylation variation in 341 CpGs (FDR adjusted P < 0.05) and 1107 regions. Forty CpGs were located within known quantitative trait loci for gene expression traits in blood, and trait enrichment analysis suggested a strong association with immune-related, transcriptional control, and blood pressure regulation phenotypes. Decreasing fertility rates worldwide with the concomitant increased proportion of first-born children highlights a potential reflection of birth order-related epigenomic states on changing disease incidence trends.
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Affiliation(s)
- Shaobo Li
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, USA
| | - Natalia Spitz
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer, Lyon, France
| | - Akram Ghantous
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer, Lyon, France
| | - Sarina Abrishamcar
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Brigitte Reimann
- Centre for Environmental Sciences, UHasselt, Agoralaan, Building D, 3590, Diepenbeek, Belgium
| | - Irene Marques
- 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
| | - Matt J Silver
- Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, London, UK
| | - Sofía Aguilar-Lacasaña
- ISGlobal, Institute for Global Health, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública, Madrid, Spain
| | - Negusse Kitaba
- Human Development and Health, Faculty of Medicine, Southampton General Hospital, University of Southampton, Southampton, UK
| | - Faisal I Rezwan
- Human Development and Health, Faculty of Medicine, Southampton General Hospital, University of Southampton, Southampton, UK
- Department of Computer Science, Aberystwyth University, Aberystwyth, Ceredigion, SY23 3DB, UK
| | - Stefan Röder
- Department of Environmental Immunology, Helmholtz Centre for Environmental Research -UFZ, Leipzig, Germany
| | - Lea Sirignano
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Johanna Tuhkanen
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Giulia Mancano
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Gemma C Sharp
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- School of Psychology, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Catherine Metayer
- School of Public Health, University of California Berkeley, Berkeley, California, USA
| | - Libby Morimoto
- School of Public Health, University of California Berkeley, Berkeley, California, USA
| | - Dan J Stein
- SAMRC Unit on Risk & Resilience in Mental Disorders, Dept of Psychiatry & Neuroscience Institute, University of Cape Town, Rondebosch, South Africa
| | - Heather J Zar
- SAMRC Unit on Risk & Resilience in Mental Disorders, Dept of Psychiatry & Neuroscience Institute, University of Cape Town, Rondebosch, South Africa
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Rondebosch, South Africa
| | - Rossella Alfano
- Centre for Environmental Sciences, UHasselt, Agoralaan, Building D, 3590, Diepenbeek, Belgium
| | - Tim Nawrot
- Centre for Environmental Sciences, UHasselt, Agoralaan, Building D, 3590, Diepenbeek, Belgium
| | - Congrong Wang
- Centre for Environmental Sciences, UHasselt, Agoralaan, Building D, 3590, Diepenbeek, Belgium
| | - Eero Kajantie
- Clinical Medicine Research Unit, Medical Research Center Oulu, Oulu University, Hospital and University of Oulu, Oulu, Finland
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
- Pediatric Research Centre, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Elina Keikkala
- Clinical Medicine Research Unit, Medical Research Center Oulu, Oulu University, Hospital and University of Oulu, Oulu, Finland
- Population Health Unit, Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Oulu, Finland
| | - Sanna Mustaniemi
- Clinical Medicine Research Unit, Medical Research Center Oulu, Oulu University, Hospital and University of Oulu, Oulu, Finland
- Population Health Unit, Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Oulu, Finland
| | - Justiina Ronkainen
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Sylvain Sebert
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Wnurinham Silva
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Marja Vääräsmäki
- Clinical Medicine Research Unit, Medical Research Center Oulu, Oulu University, Hospital and University of Oulu, Oulu, Finland
- Population Health Unit, Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Oulu, Finland
| | - 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
| | - Robin M Bernstein
- Department of Anthropology and Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO, USA
| | - Andrew M Prentice
- MRC Unit The Gambia at the London School of Hygiene & Tropical Medicine, Fajara, The Gambia
| | - Marta Cosin-Tomas
- ISGlobal, Institute for Global Health, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública, Madrid, Spain
| | - Terence Dwyer
- Nuffield Department of Women's & Reproductive Health, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Siri Eldevik Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Zdenko Herceg
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer, Lyon, France
| | - Maria C Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Monica Cheng Munthe-Kaas
- Department of Pediatric Oncology and Hematology, Oslo University Hospital, Norwegian Institute of Public Health, Oslo, Norway
| | - Christian M Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Physical Health and Aging, Division for Mental and Physical Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Maja Völker
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Maria Gilles
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Tabea Send
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Stephanie Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Lea Zillich
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Luigi Gagliardi
- Woman and Child Health Department, Ospedale Versilia, AUSL Toscana Nord Ovest, Pisa, Italy
| | - Lorenzo Richiardi
- Department of Medical Sciences, University of Turin, CPO Piemonte, Turin, Italy
| | - Darina Czamara
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Katri Räikkönen
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Lida Chatzi
- Department of Population and Public Health Sciences, Keck School of Medicine of USC. University of Southern California, Los Angeles, CA, USA
| | - Marina Vafeiadi
- Department of Social Medicine, Faculty of Medicine, University of Crete, Heraklion, Greece
| | - S 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
| | - Susan Ewart
- College of Veterinary Medicine, Michigan State University, East Lansing, MI, USA
| | - Michelle Plusquin
- Centre for Environmental Sciences, UHasselt, Agoralaan, Building D, 3590, Diepenbeek, Belgium
| | - 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
| | - Sophie E Moore
- Department of Women & Children's Health, King's College London, London, UK
| | - Martine Vrijheid
- ISGlobal, Institute for Global Health, Barcelona, Spain
- CIBER Epidemiología y Salud Pública, Madrid, Spain
| | - 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
| | - Wilfried Karmaus
- Division of Epidemiology, Biostatistics, and Environmental Health, University of Memphis, Memphis, TN, USA
| | - Gunda Herberth
- Department of Environmental Immunology, Helmholtz Centre for Environmental Research -UFZ, Leipzig, Germany
| | - Ana Zenclussen
- Department of Environmental Immunology, Helmholtz Centre for Environmental Research -UFZ, Leipzig, Germany
- Perinatal Immunology, Medical Faculty, Saxonian Incubator for Clinical Translation (SIKT), University of Leipzig, Leipzig, Germany
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Jari Lahti
- Department of Psychology and 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
| | - Thanh T Hoang
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Stephanie J London
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Joseph L Wiemels
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, USA.
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Bai X, Bao Y, Bei S, Bu C, Cao R, Cao Y, Cen H, Chao J, Chen F, Chen H, Chen K, Chen M, Chen M, Chen M, Chen Q, Chen R, Chen S, Chen T, Chen X, Chen X, Cheng Y, Chu Y, Cui Q, Dong L, Du Z, Duan G, Fan S, Fan Z, Fang X, Fang Z, Feng Z, Fu S, Gao F, Gao G, Gao H, Gao W, Gao X, Gao X, Gao X, Gong J, Gong J, Gou Y, Gu S, Guo AY, Guo G, Guo X, Han C, Hao D, Hao L, He Q, He S, He S, Hu W, Huang K, Huang T, Huang X, Huang Y, Jia P, Jia Y, Jiang C, Jiang M, Jiang S, Jiang T, Jiang X, Jin E, Jin W, Kang H, Kang H, Kong D, Lan L, Lei W, Li CY, Li C, Li C, Li H, Li J, Li J, Li L, Li P, Li R, Li X, Li Y, Li Y, Li Z, Liao X, Lin S, Lin Y, Ling Y, Liu B, Liu CJ, Liu D, Liu GH, Liu L, Liu S, Liu W, Liu X, Liu X, Liu Y, Liu Y, Lu M, Lu T, Luo H, Luo H, Luo M, Luo S, Luo X, Ma L, Ma Y, Mai J, Meng J, Meng X, Meng Y, Meng Y, Miao W, Miao YR, Ni L, Nie Z, Niu G, Niu X, Niu Y, Pan R, Pan S, Peng D, Peng J, Qi J, Qi Y, Qian Q, Qin Y, Qu H, Ren J, Ren J, Sang Z, Shang K, Shen WK, Shen Y, Shi Y, Song S, Song T, Su T, Sun J, Sun Y, Sun Y, Sun Y, Tang B, Tang D, Tang Q, Tang Z, Tian D, Tian F, Tian W, Tian Z, Wang A, Wang G, Wang G, Wang J, Wang J, Wang P, Wang P, Wang W, Wang Y, Wang Y, Wang Y, Wang Y, Wang Z, Wei H, Wei Y, Wei Z, Wu D, Wu G, Wu S, Wu S, Wu W, Wu W, Wu Z, Xia Z, Xiao J, Xiao L, Xiao Y, Xie G, Xie GY, Xie J, Xie Y, Xiong J, Xiong Z, Xu D, Xu S, Xu T, Xu T, Xue Y, Xue Y, Yan C, Yang D, Yang F, Yang F, Yang H, Yang J, Yang K, Yang N, Yang QY, Yang S, Yang X, Yang X, Yang X, Yang YG, Ye W, Yu C, Yu F, Yu S, Yuan C, Yuan H, Zeng J, Zhai S, Zhang C, Zhang F, Zhang G, Zhang M, Zhang P, Zhang Q, Zhang R, Zhang S, Zhang W, Zhang W, Zhang W, Zhang X, Zhang X, Zhang Y, Zhang Y, Zhang Y, Zhang YE, Zhang Y, Zhang Z, Zhang Z, Zhao D, Zhao F, Zhao G, Zhao M, Zhao W, Zhao W, Zhao X, Zhao Y, Zhao Y, Zhao Z, Zheng X, Zheng Y, Zhou C, Zhou H, Zhou X, Zhou X, Zhou Y, Zhou Y, Zhu J, Zhu L, Zhu R, Zhu T, Zong W, Zou D, Zuo Z. Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2024. Nucleic Acids Res 2024; 52:D18-D32. [PMID: 38018256 PMCID: PMC10767964 DOI: 10.1093/nar/gkad1078] [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: 09/15/2023] [Revised: 10/12/2023] [Accepted: 10/27/2023] [Indexed: 11/30/2023] Open
Abstract
The National Genomics Data Center (NGDC), which is a part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support the global academic and industrial communities. With the rapid accumulation of multi-omics data at an unprecedented pace, CNCB-NGDC continuously expands and updates core database resources through big data archiving, integrative analysis and value-added curation. Importantly, NGDC collaborates closely with major international databases and initiatives to ensure seamless data exchange and interoperability. Over the past year, significant efforts have been dedicated to integrating diverse omics data, synthesizing expanding knowledge, developing new resources, and upgrading major existing resources. Particularly, several database resources are newly developed for the biodiversity of protists (P10K), bacteria (NTM-DB, MPA) as well as plant (PPGR, SoyOmics, PlantPan) and disease/trait association (CROST, HervD Atlas, HALL, MACdb, BioKA, BioKA, RePoS, PGG.SV, NAFLDkb). All the resources and services are publicly accessible at https://ngdc.cncb.ac.cn.
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Fang F, Quach B, Lawrence KG, van Dongen J, Marks JA, Lundgren S, Lin M, Odintsova VV, Costeira R, Xu Z, Zhou L, Mandal M, Xia Y, Vink JM, Bierut LJ, Ollikainen M, Taylor JA, Bell JT, Kaprio J, Boomsma DI, Xu K, Sandler DP, Hancock DB, Johnson EO. Trans-ancestry epigenome-wide association meta-analysis of DNA methylation with lifetime cannabis use. Mol Psychiatry 2024; 29:124-133. [PMID: 37935791 PMCID: PMC11078760 DOI: 10.1038/s41380-023-02310-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 10/16/2023] [Accepted: 10/23/2023] [Indexed: 11/09/2023]
Abstract
Cannabis is widely used worldwide, yet its links to health outcomes are not fully understood. DNA methylation can serve as a mediator to link environmental exposures to health outcomes. We conducted an epigenome-wide association study (EWAS) of peripheral blood-based DNA methylation and lifetime cannabis use (ever vs. never) in a meta-analysis including 9436 participants (7795 European and 1641 African ancestry) from seven cohorts. Accounting for effects of cigarette smoking, our trans-ancestry EWAS meta-analysis revealed four CpG sites significantly associated with lifetime cannabis use at a false discovery rate of 0.05 ( p < 5.85 × 10 - 7 ) : cg22572071 near gene ADGRF1, cg15280358 in ADAM12, cg00813162 in ACTN1, and cg01101459 near LINC01132. Additionally, our EWAS analysis in participants who never smoked cigarettes identified another epigenome-wide significant CpG site, cg14237301 annotated to APOBR. We used a leave-one-out approach to evaluate methylation scores constructed as a weighted sum of the significant CpGs. The best model can explain 3.79% of the variance in lifetime cannabis use. These findings unravel the DNA methylation changes associated with lifetime cannabis use that are independent of cigarette smoking and may serve as a starting point for further research on the mechanisms through which cannabis exposure impacts health outcomes.
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Affiliation(s)
- Fang Fang
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA.
| | - Bryan Quach
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Kaitlyn G Lawrence
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Jesse A Marks
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Sara Lundgren
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Mingkuan Lin
- Department of Psychiatry, Yale School of Medicine, West Haven, CT, USA
| | - Veronika V Odintsova
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Ricardo Costeira
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Linran Zhou
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Meisha Mandal
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Yujing Xia
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Jacqueline M Vink
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Laura J Bierut
- Department of Psychiatry, Washington University in Saint Louis School of Medicine, St. Louis, MO, USA
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Jordana T Bell
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Ke Xu
- Department of Psychiatry, Yale School of Medicine, West Haven, CT, USA
- VA Connecticut Healthcare System, West Haven, CT, USA
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Dana B Hancock
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Eric O Johnson
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, USA
- Fellow Program, RTI International, Research Triangle Park, NC, USA
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Refn MR, Andersen MM, Kampmann ML, Tfelt-Hansen J, Sørensen E, Larsen MH, Morling N, Børsting C, Pereira V. Longitudinal changes and variation in human DNA methylation analysed with the Illumina MethylationEPIC BeadChip assay and their implications on forensic age prediction. Sci Rep 2023; 13:21658. [PMID: 38066081 PMCID: PMC10709620 DOI: 10.1038/s41598-023-49064-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 12/04/2023] [Indexed: 12/18/2023] Open
Abstract
DNA methylation, a pivotal epigenetic modification, plays a crucial role in regulating gene expression and is known to undergo dynamic changes with age. The present study investigated epigenome-wide methylation profiles in 64 individuals over two time points, 15 years apart, using the Illumina EPIC850k arrays. A mixed-effects model identified 2821 age-associated differentially methylated CpG positions (aDMPs) with a median rate of change of 0.18% per year, consistent with a 10-15% change during a human lifespan. Significant variation in the baseline DNA methylation levels between individuals of similar ages as well as inconsistent direction of change with time across individuals were observed for all the aDMPs. Twenty-three of the 2821 aDMPs were previously incorporated into forensic age prediction models. These markers displayed larger changes in DNA methylation with age compared to all the aDMPs and less variation among individuals. Nevertheless, the forensic aDMPs also showed inter-individual variations in the direction of DNA methylation changes. Only cg16867657 in ELOVL2 exhibited a uniform direction of the age-related change among the investigated individuals, which supports the current knowledge that CpG sites in ELOVL2 are the best markers for age prediction.
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Affiliation(s)
- Mie Rath Refn
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2100, Copenhagen, Denmark.
| | - Mikkel Meyer Andersen
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2100, Copenhagen, Denmark
- The Department of Mathematical Sciences, Aalborg University, 9220, Aalborg, Denmark
| | - Marie-Louise Kampmann
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2100, Copenhagen, Denmark
| | - Jacob Tfelt-Hansen
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2100, Copenhagen, Denmark
- The Department of Cardiology, The Heart Centre, Copenhagen University Hospital, Rigshospitalet, 2100, Copenhagen, Denmark
| | - Erik Sørensen
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, 2100, Copenhagen, Denmark
| | - Margit Hørup Larsen
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, 2100, Copenhagen, Denmark
| | - Niels Morling
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2100, Copenhagen, Denmark
| | - Claus Børsting
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2100, Copenhagen, Denmark
| | - Vania Pereira
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2100, Copenhagen, Denmark
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Lukacsovich D, O’Shea D, Huang H, Zhang W, Young JI, Steven Chen X, Dietrich ST, Kunkle B, Martin ER, Wang L. MIAMI-AD (Methylation in Aging and Methylation in AD): an integrative knowledgebase that facilitates explorations of DNA methylation across sex, aging, and Alzheimer's disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.04.23299412. [PMID: 38105943 PMCID: PMC10723513 DOI: 10.1101/2023.12.04.23299412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Alzheimer's disease (AD) is a common neurodegenerative disorder with a significant impact on aging populations. DNA methylation (DNAm) alterations have been implicated in both the aging processes and the development of AD. Given that AD affects more women than men, it is also important to explore DNAm changes that occur specifically in each sex. We created MIAMI-AD, a comprehensive knowledge base containing manually curated summary statistics from 97 published tables in 37 studies, all of which included at least 100 participants. MIAMI-AD enables easy browsing, querying, and downloading DNAm associations at multiple levels - at individual CpG, gene, genomic regions, or genome-wide, in one or multiple studies. Moreover, it also offers tools to perform integrative analyses, such as comparing DNAm associations across different phenotypes or tissues, as well as interactive visualizations. Using several use case examples, we demonstrated that MIAMI-AD facilitates our understanding of age-associated CpGs in AD and the sex-specific roles of DNAm in AD. This open-access resource is freely available to the research community, and all the underlying data can be downloaded. MIAMI-AD (https://miami-ad.org/) facilitates integrative explorations to better understand the interplay between DNAm across aging, sex, and AD.
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Affiliation(s)
- David Lukacsovich
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Deirdre O’Shea
- Department of Neurology, Comprehensive Center for Brain Health, University of Miami Miller School of Medicine, Boca Raton, FL, 33433
| | - Hanchen Huang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - 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
| | - 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
| | - Sven-Thorsten Dietrich
- John P. Hussman Institute for Human Genomics, the 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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36
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Awada Z, Cahais V, Cuenin C, Akika R, Silva Almeida Vicente AL, Makki M, Tamim H, Herceg Z, Khoueiry Zgheib N, Ghantous A. Waterpipe and cigarette epigenome analysis reveals markers implicated in addiction and smoking type inference. ENVIRONMENT INTERNATIONAL 2023; 182:108260. [PMID: 38006773 PMCID: PMC10716859 DOI: 10.1016/j.envint.2023.108260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 10/02/2023] [Accepted: 10/09/2023] [Indexed: 11/27/2023]
Abstract
Waterpipe smoking is frequent in the Middle East and Africa with emerging prevalence worldwide. The epigenome acts as a molecular sensor to exposures and a crucial driver in several diseases. With the widespread use of waterpipe smoking, it is timely to investigate its epigenomic markers and their role in addiction, as a central player in disease prevention and therapeutic strategies. DNA methylome-wide profiling was performed on an exposure-rich population from the Middle East, constituting of 216 blood samples split equally between never, cigarette-only and waterpipe-only smokers. Waterpipe smokers showed predominantly distinct epigenetic markers from cigarette smokers, even though both smoking forms are tobacco-based. Moreover, each smoking form could be accurately (∼90 %) inferred from the DNA methylome using machine learning. Top markers showed dose-response relationship with extent of smoking and were validated using independent technologies and additional samples (total N = 284). Smoking markers were enriched in regulatory regions and several biological pathways, primarily addiction. The epigenetically altered genes were not associated with genetic etiology of tobacco use, and the methylation levels of addiction genes, in particular, were more likely to reverse after smoking cessation. In contrast, other epigenetic markers continued to feature smoking exposure after cessation, which may explain long-term health effects observed in former smokers. This study reports, for the first time, blood epigenome-wide markers of waterpipe smokers and reveals new markers of cigarette smoking, with implications in mechanisms of addiction and the capacity to discriminate between different smoking types. These markers may offer actionable targets to reverse the epigenetic memory of addiction and can guide future prevention strategies for tobacco smoking as the most preventable cause of illnesses worldwide.
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Affiliation(s)
- Zainab Awada
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer, Lyon, France
| | - Vincent Cahais
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer, Lyon, France
| | - Cyrille Cuenin
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer, Lyon, France
| | - Reem Akika
- Department of Pharmacology and Toxicology, Faculty of Medicine, American University of Beirut, Beirut, Lebanon
| | - Anna Luiza Silva Almeida Vicente
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer, Lyon, France; Molecular Oncology Research Center, Barretos Cancer Hospital, Barretos, São Paulo, Brazil
| | - Maha Makki
- Clinical Research Institute, American University of Beirut Medical Center, Beirut, Lebanon
| | - Hani Tamim
- Clinical Research Institute, American University of Beirut Medical Center, Beirut, Lebanon; College of Medicine, Alfaisal University, Riyadh, Saudi Arabia
| | - Zdenko Herceg
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer, Lyon, France
| | - Nathalie Khoueiry Zgheib
- Department of Pharmacology and Toxicology, Faculty of Medicine, American University of Beirut, Beirut, Lebanon.
| | - Akram Ghantous
- Epigenomics and Mechanisms Branch, International Agency for Research on Cancer, Lyon, France.
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37
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Zhang F, Zhang X, Zhang H, Lin D, Fan H, Guo S, An F, Zhao Y, Li J, Schrodi SJ, Zhang D. Pan-precancer and cancer DNA methylation profiles revealed significant tissue specificity of interrupted biological processes in tumorigenesis. Epigenetics 2023; 18:2231222. [PMID: 37393582 DOI: 10.1080/15592294.2023.2231222] [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: 03/03/2023] [Revised: 06/13/2023] [Accepted: 06/21/2023] [Indexed: 07/04/2023] Open
Abstract
DNA methylation (DNAme) alterations are known to initiate from the precancerous stage of tumorigenesis. Herein, we investigated the global and local patterns of DNAme perturbations in tumorigenesis by analysing the genome-wide DNAme profiles of the cervix, colorectum, stomach, prostate, and liver at precancerous and cancer stages. We observed global hypomethylation in tissues of both two stages, except for the cervix, whose global DNAme level in normal tissue was lower than that of the other four tumour types. For alterations shared by both stages, there were common hyper-methylation (sHyperMethyl) and hypo-methylation (sHypoMethyl) changes, of which the latter type was more frequently identified in all tissues. Biological pathways interrupted by sHyperMethyl and sHypoMethyl alterations demonstrated significant tissue specificity. DNAme bidirectional chaos indicated by the enrichment of both sHyperMethyl and sHypoMethyl changes in the same pathway was observed in most tissues and was a common phenomenon, particularly in liver lesions. Moreover, for the same enriched pathways, different tissues may be affected by distinct DNAme types. For the PI3K-Akt signalling pathway, sHyperMethyl enrichment was observed in the prostate dataset, but sHypoMethyl enrichment was observed in the colorectum and liver datasets. Nevertheless, they did not show an increased possibility in survival prediction of patients in comparison with other DNAme types. Additionally, our study demonstrated that gene-body DNAme changes of tumour suppressor genes and oncogenes may persist from precancerous lesions to the tumour. Overall, we demonstrate the tissue specificity and commonality of cross-stage alterations in DNA methylation profiles in multi-tissue tumorigenesis.
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Affiliation(s)
- Feifan Zhang
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Engineering Medicine, Beihang University, Beijing, China
| | - Xin Zhang
- Department of Urology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Haikun Zhang
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Engineering Medicine, Beihang University, Beijing, China
| | - Dongdong Lin
- Department of Urology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Hailang Fan
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Engineering Medicine, Beihang University, Beijing, China
| | - Shicheng Guo
- Department of Medical Genetics, University of Wisconsin-Madison, Madison, WI, USA
| | - Fang An
- Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, China
| | - Yaqian Zhao
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Engineering Medicine, Beihang University, Beijing, China
| | - Jun Li
- Department of Gastroenterology, Peking University Third Hospital, Beijing, China
| | - Steven J Schrodi
- Department of Medical Genetics, University of Wisconsin-Madison, Madison, WI, USA
- Computation and Informatics in Biology and Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Dake Zhang
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Engineering Medicine, Beihang University, Beijing, China
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Herrera-Luis E, Rosa-Baez C, Huntsman S, Eng C, Beckman KB, LeNoir MA, Rodriguez-Santana JR, Villar J, Laprise C, Borrell LN, Ziv E, Burchard EG, Pino-Yanes M. Novel insights into the whole-blood DNA methylome of asthma in ethnically diverse children and youth. Eur Respir J 2023; 62:2300714. [PMID: 37802634 PMCID: PMC10841414 DOI: 10.1183/13993003.00714-2023] [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: 10/03/2022] [Accepted: 08/20/2023] [Indexed: 10/10/2023]
Abstract
BACKGROUND The epigenetic mechanisms of asthma remain largely understudied in African Americans and Hispanics/Latinos, two populations disproportionately affected by asthma. We aimed to identify markers, regions and processes with differential patterns of DNA methylation (DNAm) in whole blood by asthma status in ethnically diverse children and youth, and to assess their functional consequences. METHODS DNAm levels were profiled with the Infinium MethylationEPIC or HumanMethylation450 BeadChip arrays among 1226 African Americans or Hispanics/Latinos and assessed for differential methylation per asthma status at the CpG and region (differentially methylated region (DMR)) level. Novel associations were validated in blood and/or nasal epithelium from ethnically diverse children and youth. The functional and biological implications of the markers identified were investigated by combining epigenomics with transcriptomics from study participants. RESULTS 128 CpGs and 196 DMRs were differentially methylated after multiple testing corrections, including 92.3% and 92.8% novel associations, respectively. 41 CpGs were replicated in other Hispanics/Latinos, prioritising cg17647904 (NCOR2) and cg16412914 (AXIN1) as asthma DNAm markers. Significant DNAm markers were enriched in previous associations for asthma, fractional exhaled nitric oxide, bacterial infections, immune regulation or eosinophilia. Functional annotation highlighted epigenetically regulated gene networks involved in corticosteroid response, host defence and immune regulation. Several implicated genes are targets for approved or experimental drugs, including TNNC1 and NDUFA12. Many differentially methylated loci previously associated with asthma were validated in our study. CONCLUSIONS We report novel whole-blood DNAm markers for asthma underlying key processes of the disease pathophysiology and confirm the transferability of previous asthma DNAm associations to ethnically diverse populations.
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Affiliation(s)
- Esther Herrera-Luis
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna (ULL), La Laguna, Spain
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Carlos Rosa-Baez
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna (ULL), La Laguna, Spain
| | - Scott Huntsman
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Celeste Eng
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | | | - Michael A LeNoir
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna (ULL), La Laguna, Spain
- Bay Area Pediatrics, Oakland, CA, USA
| | - Jose R Rodriguez-Santana
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna (ULL), La Laguna, Spain
- Centro de Neumología Pediátrica, San Juan, Puerto Rico
| | - Jesús Villar
- Multidisciplinary Organ Dysfunction Evaluation Research Network, Research Unit, Hospital Universitario Dr. Negrín, Las Palmas de Gran Canaria, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Li Ka Shing Knowledge Institute at St Michael's Hospital, Toronto, ON, Canada
| | - Catherine Laprise
- Département des Sciences Fondamentales, Université du Québec à Chicoutimi, Saguenay, QC, Canada
- Centre Intersectoriel en Santé Durable, Université du Québec à Chicoutimi, Saguenay, QC, Canada
| | - Luisa N Borrell
- Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York, NY, USA
| | - Elad Ziv
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Division of General Internal Medicine, Department of Medicine and Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA
| | - Esteban G Burchard
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
- Division of General Internal Medicine, Department of Medicine and Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA
- Instituto de Tecnologías Biomédicas, Universidad de La Laguna (ULL), La Laguna, Spain
| | - Maria Pino-Yanes
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna (ULL), La Laguna, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Instituto de Tecnologías Biomédicas, Universidad de La Laguna (ULL), La Laguna, Spain
- These authors contributed equally as senior authors
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Protti G, Rubbi L, Gören T, Sabirli R, Civlan S, Kurt Ö, Türkçüer İ, Köseler A, Pellegrini M. The methylome of buccal epithelial cells is influenced by age, sex, and physiological properties. Physiol Genomics 2023; 55:618-633. [PMID: 37781740 DOI: 10.1152/physiolgenomics.00063.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 09/05/2023] [Accepted: 09/27/2023] [Indexed: 10/03/2023] Open
Abstract
Epigenetic modifications, particularly DNA methylation, have emerged as regulators of gene expression and are implicated in various biological processes and disease states. Understanding the factors influencing the epigenome is essential for unraveling its complexity. In this study, we aimed to identify how the methylome of buccal epithelial cells, a noninvasive and easily accessible tissue, is associated with demographic and health-related variables commonly used in clinical settings, such as age, sex, blood immune composition, hemoglobin levels, and others. We developed a model to assess the association of multiple factors with the human methylome and identify the genomic loci significantly impacted by each trait. We demonstrated that DNA methylation variation is accurately modeled by several factors. We confirmed the well-known impact of age and sex and unveiled novel clinical factors associated with DNA methylation, such as blood neutrophils, hemoglobin, red blood cell distribution width, high-density lipoprotein cholesterol, and urea. Genomic regions significantly associated with these traits were enriched in relevant transcription factors, drugs, and diseases. Among our findings, we showed that neutrophil-impacted loci were involved in neutrophil functionality and maturation. Similarly, hemoglobin-influenced sites were associated with several diseases, including aplastic anemia, and the genomic loci affected by urea were related to congenital anomalies of the kidney and urinary tract. Our findings contribute to a better understanding of the human methylome plasticity and provide insights into novel factors shaping DNA methylation patterns, highlighting their potential clinical implications as biomarkers and the importance of considering these physiological traits in future medical epigenomic investigations.NEW & NOTEWORTHY We have developed a quantitative model to assess how the human methylome is associated with several factors and to identify the genomic loci significantly impacted by each trait. We reported novel health-related factors driving DNA methylation patterns and new site-specific regulations that further elucidate methylome dynamics. Our study contributes to a better understanding of the plasticity of the human methylome and unveils novel physiological traits with a potential role in future medical epigenomic investigations.
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Affiliation(s)
- Giulia Protti
- Molecular, Cell and Developmental Biology, University of California, Los Angeles, California, United States
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Milan, Italy
| | - Liudmilla Rubbi
- Molecular, Cell and Developmental Biology, University of California, Los Angeles, California, United States
| | - Tarik Gören
- Emergency Department, Pamukkale University Medical Faculty, Denizli, Turkey
| | - Ramazan Sabirli
- Emergency Department, Bakircay University Faculty of Medicine Cigli Training and Research Hospital, Izmir, Turkey
| | - Serkan Civlan
- Department of Neurosurgery, Pamukkale University Faculty of Medicine, Denizli, Turkey
| | - Özgür Kurt
- Department of Microbiology, Acibadem Mehmet Ali Aydinlar University School of Medicine, Istanbul, Turkey
| | - İbrahim Türkçüer
- Emergency Department, Pamukkale University Medical Faculty, Denizli, Turkey
| | - Aylin Köseler
- Department of Biophysics, Pamukkale University Faculty of Medicine, Denizli, Turkey
| | - Matteo Pellegrini
- Molecular, Cell and Developmental Biology, University of California, Los Angeles, California, United States
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Hecker J, Lee S, Kachroo P, Prokopenko D, Maaser-Hecker A, Lutz SM, Hahn G, Irizarry R, Weiss ST, DeMeo DL, Lange C. A consistent pattern of slide effects in Illumina DNA methylation BeadChip array data. Epigenetics 2023; 18:2257437. [PMID: 37731367 PMCID: PMC11062373 DOI: 10.1080/15592294.2023.2257437] [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: 04/18/2023] [Accepted: 09/01/2023] [Indexed: 09/22/2023] Open
Abstract
Background: Recent studies have identified thousands of associations between DNA methylation CpGs and complex diseases/traits, emphasizing the critical role of epigenetics in understanding disease aetiology and identifying biomarkers. However, association analyses based on methylation array data are susceptible to batch/slide effects, which can lead to inflated false positive rates or reduced statistical powerResults: We use multiple DNA methylation datasets based on the popular Illumina Infinium MethylationEPIC BeadChip array to describe consistent patterns and the joint distribution of slide effects across CpGs, confirming and extending previous results. The susceptible CpGs overlap with the Illumina Infinium HumanMethylation450 BeadChip array content.Conclusions: Our findings reveal systematic patterns in slide effects. The observations provide further insights into the characteristics of these effects and can improve existing adjustment approaches.
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Affiliation(s)
- Julian Hecker
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Sanghun Lee
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Medical Consilience, Division of Medicine, Graduate School, Dankook University, Yongin-si, South Korea
| | - Priyadarshini Kachroo
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Dmitry Prokopenko
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Anna Maaser-Hecker
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Sharon M. Lutz
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Population Medicine, PRecisiOn Medicine Translational Research (PROMoTeR) Center, Harvard Pilgrim Health Care and Harvard Medical School, Boston, MA, USA
| | - Georg Hahn
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Rafael Irizarry
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Scott T. Weiss
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Dawn L. DeMeo
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Christoph Lange
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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Allayee H, Farber CR, Seldin MM, Williams EG, James DE, Lusis AJ. Systems genetics approaches for understanding complex traits with relevance for human disease. eLife 2023; 12:e91004. [PMID: 37962168 PMCID: PMC10645424 DOI: 10.7554/elife.91004] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 10/16/2023] [Indexed: 11/15/2023] Open
Abstract
Quantitative traits are often complex because of the contribution of many loci, with further complexity added by environmental factors. In medical research, systems genetics is a powerful approach for the study of complex traits, as it integrates intermediate phenotypes, such as RNA, protein, and metabolite levels, to understand molecular and physiological phenotypes linking discrete DNA sequence variation to complex clinical and physiological traits. The primary purpose of this review is to describe some of the resources and tools of systems genetics in humans and rodent models, so that researchers in many areas of biology and medicine can make use of the data.
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Affiliation(s)
- Hooman Allayee
- Departments of Population & Public Health Sciences, University of Southern CaliforniaLos AngelesUnited States
- Biochemistry & Molecular Medicine, Keck School of Medicine, University of Southern CaliforniaLos AngelesUnited States
| | - Charles R Farber
- Center for Public Health Genomics, University of Virginia School of MedicineCharlottesvilleUnited States
- Departments of Biochemistry & Molecular Genetics, University of Virginia School of MedicineCharlottesvilleUnited States
- Public Health Sciences, University of Virginia School of MedicineCharlottesvilleUnited States
| | - Marcus M Seldin
- Department of Biological Chemistry, University of California, IrvineIrvineUnited States
| | - Evan Graehl Williams
- Luxembourg Centre for Systems Biomedicine, University of LuxembourgLuxembourgLuxembourg
| | - David E James
- School of Life and Environmental Sciences, University of SydneyCamperdownAustralia
- Faculty of Medicine and Health, University of SydneyCamperdownAustralia
- Charles Perkins Centre, University of SydneyCamperdownAustralia
| | - Aldons J Lusis
- Departments of Human Genetics, University of California, Los AngelesLos AngelesUnited States
- Medicine, University of California, Los AngelesLos AngelesUnited States
- Microbiology, Immunology, & Molecular Genetics, David Geffen School of Medicine of UCLALos AngelesUnited States
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42
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Bukowski A, Hoyo C, Vielot NA, Graff M, Kosorok MR, Brewster WR, Maguire RL, Murphy SK, Nedjai B, Ladoukakis E, North KE, Smith JS. Epigenome-wide methylation and progression to high-grade cervical intraepithelial neoplasia (CIN2+): a prospective cohort study in the United States. BMC Cancer 2023; 23:1072. [PMID: 37932662 PMCID: PMC10629205 DOI: 10.1186/s12885-023-11518-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 10/11/2023] [Indexed: 11/08/2023] Open
Abstract
BACKGROUND Methylation levels may be associated with and serve as markers to predict risk of progression of precancerous cervical lesions. We conducted an epigenome-wide association study (EWAS) of CpG methylation and progression to high-grade cervical intraepithelial neoplasia (CIN2 +) following an abnormal screening test. METHODS A prospective US cohort of 289 colposcopy patients with normal or CIN1 enrollment histology was assessed. Baseline cervical sample DNA was analyzed using Illumina HumanMethylation 450K (n = 76) or EPIC 850K (n = 213) arrays. Participants returned at provider-recommended intervals and were followed up to 5 years via medical records. We assessed continuous CpG M values for 9 cervical cancer-associated genes and time-to-progression to CIN2+. We estimated CpG-specific time-to-event ratios (TTER) and hazard ratios using adjusted, interval-censored Weibull accelerated failure time models. We also conducted an exploratory EWAS to identify novel CpGs with false discovery rate (FDR) < 0.05. RESULTS At enrollment, median age was 29.2 years; 64.0% were high-risk HPV-positive, and 54.3% were non-white. During follow-up (median 24.4 months), 15 participants progressed to CIN2+. Greater methylation levels were associated with a shorter time-to-CIN2+ for CADM1 cg03505501 (TTER = 0.28; 95%CI 0.12, 0.63; FDR = 0.03) and RARB Cluster 1 (TTER = 0.46; 95% CI 0.29, 0.71; FDR = 0.01). There was evidence of similar trends for DAPK1 cg14286732, PAX1 cg07213060, and PAX1 Cluster 1. The EWAS detected 336 novel progression-associated CpGs, including those located in CpG islands associated with genes FGF22, TOX, COL18A1, GPM6A, XAB2, TIMP2, GSPT1, NR4A2, and APBB1IP. CONCLUSIONS Using prospective time-to-event data, we detected associations between CADM1-, DAPK1-, PAX1-, and RARB-related CpGs and cervical disease progression, and we identified novel progression-associated CpGs. IMPACT Methylation levels at novel CpG sites may help identify individuals with ≤CIN1 histology at higher risk of progression to CIN2+ and inform risk-based cervical cancer screening guidelines.
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Affiliation(s)
- Alexandra Bukowski
- Department of Epidemiology, University of North Carolina at Chapel Hill, 60 Bondurant Hall, Chapel Hill, NC, 27599, USA.
| | - Cathrine Hoyo
- Department of Biological Sciences, Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, 27695, USA
| | - Nadja A Vielot
- Department of Family Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Misa Graff
- Department of Epidemiology, University of North Carolina at Chapel Hill, 60 Bondurant Hall, Chapel Hill, NC, 27599, USA
| | - Michael R Kosorok
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Wendy R Brewster
- Department of Epidemiology, University of North Carolina at Chapel Hill, 60 Bondurant Hall, Chapel Hill, NC, 27599, USA
- Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Rachel L Maguire
- Department of Biological Sciences, Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, 27695, USA
- Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, NC, 27701, USA
| | - Susan K Murphy
- Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, NC, 27701, USA
| | - Belinda Nedjai
- Centre for Prevention, Detection and Diagnosis, Wolfson Institute of Population Health, Queen Mary University London, London, UK
| | - Efthymios Ladoukakis
- Centre for Prevention, Detection and Diagnosis, Wolfson Institute of Population Health, Queen Mary University London, London, UK
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, 60 Bondurant Hall, Chapel Hill, NC, 27599, USA
| | - Jennifer S Smith
- Department of Epidemiology, University of North Carolina at Chapel Hill, 60 Bondurant Hall, Chapel Hill, NC, 27599, USA
- University of North Carolina Lineberger Comprehensive Cancer Center, Chapel Hill, NC, 27599, USA
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Swart G, Meeks K, Chilunga F, Venema A, Agyemang C, van der Linden E, Henneman P. Associations between epigenome-wide DNA methylation and height-related traits among Sub-Saharan Africans: the RODAM study. J Dev Orig Health Dis 2023; 14:658-669. [PMID: 38044700 DOI: 10.1017/s204017442300034x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Human height and related traits are highly complex, and extensively research has shown that these traits are determined by both genetic and environmental factors. Such factors may partially affect these traits through epigenetic programing. Epigenetic programing is dynamic and plays an important role in controlling gene expression and cell differentiation during (early) development. DNA methylation (DNAm) is the most commonly studied epigenetic feature. In this study we conducted an epigenome-wide DNAm association analysis on height-related traits in a Sub-Saharan African population, in order to detect DNAm biomarkers across four height-related traits. DNAm profiles were acquired in whole blood samples of 704 Ghanaians, sourced from the Research on Obesity and Diabetes among African Migrants study, using the Illumina Infinium HumanMethylation450 BeadChip. Linear models were fitted to detect differentially methylated positions (DMPs) and regions (DMRs) associated with height, leg-to-height ratio (LHR), leg length, and sitting height. No epigenome-wide significant DMPs were recorded. However we did observe among our top DMPs five informative probes associated with the height-related traits: cg26905768 (leg length), cg13268132 (leg length), cg19776793 (height), cg23072383 (LHR), and cg24625894 (sitting height). All five DMPs are annotated to genes whose functions were linked to bone cell regulation and development. DMR analysis identified overlapping DMRs within the gene body of HLA-DPB1 gene, and the HOXA gene cluster. In this first epigenome-wide association studies of these traits, our findings suggest DNAm associations with height-related heights, and might influence development and maintenance of these traits. Further studies are needed to replicate our findings, and to elucidate the molecular mechanism underlying human height-related traits.
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Affiliation(s)
- Galatea Swart
- Department of Human Genetics, Department of Human Genetics, Genome Diagnostic Laboratory, Amsterdam Reproduction and Development, Research Institute, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Karlijn Meeks
- Department of Public and Occupational Health, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institute of Health, Bethesda, MD, USA
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, The John Hopkins University School of Medicine, Baltimore, MD, USA
| | - Felix Chilunga
- Department of Public and Occupational Health, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Andrea Venema
- Department of Human Genetics, Department of Human Genetics, Genome Diagnostic Laboratory, Amsterdam Reproduction and Development, Research Institute, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Charles Agyemang
- Department of Public and Occupational Health, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, The John Hopkins University School of Medicine, Baltimore, MD, USA
| | - Eva van der Linden
- Department of Public and Occupational Health, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Department of Vascular Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands
| | - Peter Henneman
- Department of Human Genetics, Department of Human Genetics, Genome Diagnostic Laboratory, Amsterdam Reproduction and Development, Research Institute, Amsterdam University Medical Centers, Amsterdam, The Netherlands
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Kaur D, Lee SM, Goldberg D, Spix NJ, Hinoue T, Li HT, Dwaraka VB, Smith R, Shen H, Liang G, Renke N, Laird PW, Zhou W. Comprehensive Evaluation of The Infinium Human MethylationEPIC v2 BeadChip. EPIGENETICS COMMUNICATIONS 2023; 3:6. [PMID: 38455390 PMCID: PMC10919401 DOI: 10.1186/s43682-023-00021-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 09/18/2023] [Indexed: 03/09/2024]
Abstract
Infinium Methylation BeadChips are widely used to profile DNA cytosine modifications in large cohort studies for reasons of cost-effectiveness, accurate quantification, and user-friendly data analysis in characterizing these canonical epigenetic marks. In this work, we conducted a comprehensive evaluation of the updated Infinium MethylationEPIC v2 BeadChip (EPICv2). Our evaluation revealed that EPICv2 offers significant improvements over its predecessors, including expanded enhancer coverage, applicability to diverse ancestry groups, support for low-input DNA down to one nanogram, coverage of existing epigenetic clocks, cell type deconvolution panels, and human trait associations, while maintaining accuracy and reproducibility. Using EPICv2, we were able to identify epigenome and sequence signatures in cell line models of DNMT and SETD2 loss and/or hypomorphism. Furthermore, we provided probe-wise evaluation and annotation to facilitate the use of new features on this array for studying the interplay between somatic mutations and epigenetic landscape in cancer genomics. In conclusion, EPICv2 provides researchers with a valuable tool for studying epigenetic modifications and their role in development and disease.
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Affiliation(s)
- Diljeet Kaur
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA, 19104, USA
- These authors contribute equally
| | - Sol Moe Lee
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA, 19104, USA
- These authors contribute equally
| | - David Goldberg
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA, 19104, USA
| | - Nathan J Spix
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Toshinori Hinoue
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Hong-Tao Li
- Department of Urology, University of Southern California, Norris Comprehensive Cancer Center, Los Angeles, CA 90033, USA
| | | | - Ryan Smith
- TruDiagnostic Inc, Lexington, KY 40503, USA
| | - Hui Shen
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Gangning Liang
- Department of Urology, University of Southern California, Norris Comprehensive Cancer Center, Los Angeles, CA 90033, USA
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Nicole Renke
- Illumina, Inc., Product Management Department, San Diego, CA 92122, USA
| | - Peter W Laird
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA, 19104, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
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45
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Van Asselt AJ, Beck JJ, Finnicum CT, Johnson BN, Kallsen N, Hottenga JJ, de Geus EJC, Boomsma DI, Ehli EA, van Dongen J. Genome-Wide DNA Methylation Profiles in Whole-Blood and Buccal Samples-Cross-Sectional, Longitudinal, and across Platforms. Int J Mol Sci 2023; 24:14640. [PMID: 37834090 PMCID: PMC10572275 DOI: 10.3390/ijms241914640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 09/22/2023] [Accepted: 09/24/2023] [Indexed: 10/15/2023] Open
Abstract
The field of DNA methylation research is rapidly evolving, focusing on disease and phenotype changes over time using methylation measurements from diverse tissue sources and multiple array platforms. Consequently, identifying the extent of longitudinal, inter-tissue, and inter-platform variation in DNA methylation is crucial for future advancement. DNA methylation was measured in 375 individuals, with 197 of those having 2 blood sample measurements ~10 years apart. Whole-blood samples were measured on Illumina Infinium 450K and EPIC methylation arrays, and buccal samples from a subset of 58 participants were measured on EPIC array. The data were analyzed with the aims to examine the correlation between methylation levels in longitudinal blood samples in 197 individuals, examine the correlation between methylation levels in the blood and buccal samples in 58 individuals, and examine the correlation between blood methylation profiles assessed on the EPIC and 450K arrays in 83 individuals. We identified 136,833, 7674, and 96,891 CpGs significantly and strongly correlated (>0.50) longitudinally, across blood and buccal samples as well as array platforms, respectively. A total of 3674 of these CpGs were shared across all three sets. Analysis of these shared CpGs identified previously found associations with aging, ancestry, and 7016 mQTLs as well.
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Affiliation(s)
- Austin J. Van Asselt
- Avera McKennan Hospital, University Health Center, Sioux Falls, SD 57105, USA; (A.J.V.A.)
- Department of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
| | - Jeffrey J. Beck
- Avera McKennan Hospital, University Health Center, Sioux Falls, SD 57105, USA; (A.J.V.A.)
| | - Casey T. Finnicum
- Avera McKennan Hospital, University Health Center, Sioux Falls, SD 57105, USA; (A.J.V.A.)
| | - Brandon N. Johnson
- Avera McKennan Hospital, University Health Center, Sioux Falls, SD 57105, USA; (A.J.V.A.)
| | - Noah Kallsen
- Avera McKennan Hospital, University Health Center, Sioux Falls, SD 57105, USA; (A.J.V.A.)
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
| | - Eco J. C. de Geus
- Department of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
| | | | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
| | - Erik A. Ehli
- Avera McKennan Hospital, University Health Center, Sioux Falls, SD 57105, USA; (A.J.V.A.)
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
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Lee SM, Loo CE, Prasasya RD, Bartolomei MS, Kohli RM, Zhou W. Low-input and single-cell methods for Infinium DNA methylation BeadChips. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.18.558252. [PMID: 37786695 PMCID: PMC10541608 DOI: 10.1101/2023.09.18.558252] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
The Infinium BeadChip is the most widely used DNA methylome assay technology for population-scale epigenome profiling. However, the standard workflow requires over 200 ng of input DNA, hindering its application to small cell-number samples, such as primordial germ cells. We developed experimental and analysis workflows to extend this technology to suboptimal input DNA conditions, including ultra-low input down to single cells. DNA preamplification significantly enhanced detection rates to over 50% in five-cell samples and ∼25% in single cells. Enzymatic conversion also substantially improved data quality. Computationally, we developed a method to model the background signal's influence on the DNA methylation level readings. The modified detection p -values calculation achieved higher sensitivities for low-input datasets and was validated in over 100,000 public datasets with diverse methylation profiles. We employed the optimized workflow to query the demethylation dynamics in mouse primordial germ cells available at low cell numbers. Our data revealed nuanced chromatin states, sex disparities, and the role of DNA methylation in transposable element regulation during germ cell development. Collectively, we present comprehensive experimental and computational solutions to extend this widely used methylation assay technology to applications with limited DNA.
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Kim MS, Song M, Kim B, Shim I, Kim DS, Natarajan P, Do R, Won HH. Prioritization of therapeutic targets for dyslipidemia using integrative multi-omics and multi-trait analysis. Cell Rep Med 2023; 4:101112. [PMID: 37582372 PMCID: PMC10518515 DOI: 10.1016/j.xcrm.2023.101112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 12/22/2022] [Accepted: 06/19/2023] [Indexed: 08/17/2023]
Abstract
Drug targets with genetic support are several-fold more likely to succeed in clinical trials. We introduce a genetic-driven approach based on causal inferences that can inform drug target prioritization, repurposing, and adverse effects of using lipid-lowering agents. Given that a multi-trait approach increases the power to detect meaningful variants/genes, we conduct multi-omics and multi-trait analyses, followed by network connectivity investigations, and prioritize 30 potential therapeutic targets for dyslipidemia, including SORT1, PSRC1, CELSR2, PCSK9, HMGCR, APOB, GRN, HFE2, FJX1, C1QTNF1, and SLC5A8. 20% (6/30) of prioritized targets from our hypothesis-free drug target search are either approved or under investigation for dyslipidemia. The prioritized targets are 22-fold higher in likelihood of being approved or under investigation in clinical trials than genome-wide association study (GWAS)-curated targets. Our results demonstrate that the genetic-driven approach used in this study is a promising strategy for prioritizing targets while informing about the potential adverse effects and repurposing opportunities.
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Affiliation(s)
- Min Seo Kim
- Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, Republic of Korea
| | - Minku Song
- Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, Republic of Korea
| | - Beomsu Kim
- Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, Republic of Korea
| | - Injeong Shim
- Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, Republic of Korea
| | - Dan Say Kim
- Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, Republic of Korea
| | - Pradeep Natarajan
- Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Ron Do
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Hong-Hee Won
- Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, Republic of Korea; Samsung Genome Institute, Samsung Medical Center, Seoul, Republic of Korea.
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48
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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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49
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Kitaba NT, Knudsen GTM, Johannessen A, Rezwan FI, Malinovschi A, Oudin A, Benediktsdottir B, Martino D, González FJC, Gómez LP, Holm M, Jõgi NO, Dharmage SC, Skulstad SM, Watkins SH, Suderman M, Gómez-Real F, Schlünssen V, Svanes C, Holloway JW. Fathers' preconception smoking and offspring DNA methylation. Clin Epigenetics 2023; 15:131. [PMID: 37649101 PMCID: PMC10469907 DOI: 10.1186/s13148-023-01540-7] [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: 03/10/2023] [Accepted: 07/24/2023] [Indexed: 09/01/2023] Open
Abstract
BACKGROUND Experimental studies suggest that exposures may impact respiratory health across generations via epigenetic changes transmitted specifically through male germ cells. Studies in humans are, however, limited. We aim to identify epigenetic marks in offspring associated with father's preconception smoking. METHODS We conducted epigenome-wide association studies (EWAS) in the RHINESSA cohort (7-50 years) on father's any preconception smoking (n = 875 offspring) and father's pubertal onset smoking < 15 years (n = 304), using Infinium MethylationEPIC Beadchip arrays, adjusting for offspring age, own smoking and maternal smoking. EWAS of maternal and offspring personal smoking were performed for comparison. Father's smoking-associated dmCpGs were checked in subpopulations of offspring who reported no personal smoking and no maternal smoking exposure. RESULTS Father's smoking commencing preconception was associated with methylation of blood DNA in offspring at two cytosine-phosphate-guanine sites (CpGs) (false discovery rate (FDR) < 0.05) in PRR5 and CENPP. Father's pubertal onset smoking was associated with 19 CpGs (FDR < 0.05) mapped to 14 genes (TLR9, DNTT, FAM53B, NCAPG2, PSTPIP2, MBIP, C2orf39, NTRK2, DNAJC14, CDO1, PRAP1, TPCN1, IRS1 and CSF1R). These differentially methylated sites were hypermethylated and associated with promoter regions capable of gene silencing. Some of these sites were associated with offspring outcomes in this cohort including ever-asthma (NTRK2), ever-wheezing (DNAJC14, TPCN1), weight (FAM53B, NTRK2) and BMI (FAM53B, NTRK2) (p < 0.05). Pathway analysis showed enrichment for gene ontology pathways including regulation of gene expression, inflammation and innate immune responses. Father's smoking-associated sites did not overlap with dmCpGs identified in EWAS of personal and maternal smoking (FDR < 0.05), and all sites remained significant (p < 0.05) in analyses of offspring with no personal smoking and no maternal smoking exposure. CONCLUSION Father's preconception smoking, particularly in puberty, is associated with offspring DNA methylation, providing evidence that epigenetic mechanisms may underlie epidemiological observations that pubertal paternal smoking increases risk of offspring asthma, low lung function and obesity.
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Affiliation(s)
- Negusse Tadesse Kitaba
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, SO16 6YD, UK
| | - Gerd Toril Mørkve Knudsen
- Department of Clinical Sciences, University of Bergen, Bergen, Norway
- Department of Occupational Medicine, Haukeland University Hospital, Bergen, Norway
| | - Ane Johannessen
- Centre for International Health, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | - Faisal I Rezwan
- Department of Computer Science, Aberystwyth University, Aberystwyth, UK
| | - Andrei Malinovschi
- Department of Medical Sciences: Clinical Physiology, Uppsala University, Uppsala, Sweden
| | - Anna Oudin
- Section of Sustainable Health, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Bryndis Benediktsdottir
- Department of Allergy, Respiratory Medicine and Sleep, Landspitali University Hospital, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - David Martino
- Wal-Yan Respiratory Research Centre, Telethon Kids Institute, University of Western Australia, Perth, Australia
| | | | | | - Mathias Holm
- Occupational and Environmental Medicine, School of Public Health and Community Medicine, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Nils Oskar Jõgi
- Department of Clinical Sciences, University of Bergen, Bergen, Norway
- Department of Occupational Medicine, Haukeland University Hospital, Bergen, Norway
| | - Shyamali C Dharmage
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
| | - Svein Magne Skulstad
- Department of Occupational Medicine, Haukeland University Hospital, Bergen, Norway
| | - Sarah H Watkins
- University of Bristol, MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, Bristol, UK
| | - Matthew Suderman
- University of Bristol, MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, Bristol, UK
| | - Francisco Gómez-Real
- Department of Clinical Sciences, University of Bergen, Bergen, Norway
- Department of Gynaecology and Obstetrics, Haukeland University Hospital, Bergen, Norway
| | - Vivi Schlünssen
- Department of Public Health, Work, Environment and Health, Danish Ramazzini Centre, Aarhus University Denmark, Aarhus, Denmark
- National Research Center for the Working Environment, Copenhagen, Denmark
| | - Cecilie Svanes
- Department of Occupational Medicine, Haukeland University Hospital, Bergen, Norway
- Centre for International Health, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | - John W Holloway
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, SO16 6YD, UK.
- NIHR Southampton Biomedical Research Center, University Hospitals Southampton, Southampton, UK.
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Nikpay M. Multiomics Data Analysis Identified CpG Sites That Mediate the Impact of Smoking on Cardiometabolic Traits. EPIGENOMES 2023; 7:19. [PMID: 37754271 PMCID: PMC10528714 DOI: 10.3390/epigenomes7030019] [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: 07/11/2023] [Revised: 08/18/2023] [Accepted: 08/18/2023] [Indexed: 09/28/2023] Open
Abstract
Understanding the epigenome paths through which smoking contributes to cardiometabolic traits is important for downstream applications. In this study, an SNP-based analytical pipeline was used to integrate several publicly available datasets in order to identify CpG sites that mediate the impact of smoking on cardiometabolic traits and to investigate the underlying molecular mechanisms. After applying stringent statistical criteria, 11 CpG sites were detected that showed significant association (p < 5 × 10-8) with cardiometabolic traits at both the discovery and replication stages. By integrating eQTL data, I found genes behind a number of these associations. cg05228408 was hypomethylated in smokers and contributed to higher blood pressure by lowering the expression of the CLCN6 gene. cg08639339 was hypermethylated in smokers and lowered the metabolic rate by increasing the expression of RAB29; furthermore, I noted TMEM120A mediated the impact of smoking-cg17325771 on LDL, and LTBP3 mediated the smoking-cg07029024 effect on heart rate. The pathway analysis identified processes through which the identified genes impact their traits. This study provides a list of CpG sites that mediates the impact of smoking on cardiometabolic traits and a framework to investigate the underlying molecular paths using publicly available data.
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Affiliation(s)
- Majid Nikpay
- Omics and Biomedical Analysis Core Facility, Heart Institute, University of Ottawa, Ottawa, ON K1Y 4W7, Canada
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