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      A meta-analysis of pre-pregnancy maternal body mass index and placental DNA methylation identifies 27 CpG sites with implications for mother-child health

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      Communications Biology
      Nature Publishing Group UK
      Epigenomics, Genetics research

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          Abstract

          Higher maternal pre-pregnancy body mass index (ppBMI) is associated with increased neonatal morbidity, as well as with pregnancy complications and metabolic outcomes in offspring later in life. The placenta is a key organ in fetal development and has been proposed to act as a mediator between the mother and different health outcomes in children. The overall aim of the present work is to investigate the association of ppBMI with epigenome-wide placental DNA methylation (DNAm) in 10 studies from the PACE consortium, amounting to 2631 mother-child pairs. We identify 27 CpG sites at which we observe placental DNAm variations of up to 2.0% per 10 ppBMI-unit. The CpGs that are differentially methylated in placenta do not overlap with CpGs identified in previous studies in cord blood DNAm related to ppBMI. Many of the identified CpGs are located in open sea regions, are often close to obesity-related genes such as GPX1 and LGR4 and altogether, are enriched in cancer and oxidative stress pathways. Our findings suggest that placental DNAm could be one of the mechanisms by which maternal obesity is associated with metabolic health outcomes in newborns and children, although further studies will be needed in order to corroborate these findings.

          Abstract

          A meta-analysis of pre-pregnancy maternal body mass index (ppBMI) and placental DNA methylation from 2631 mother-child pairs identifies 27 CpG sites associated with ppBMI, providing insight into how maternal obesity could be associated with metabolic health outcomes in offspring.

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          Integrative analysis of 111 reference human epigenomes

          The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but a similar reference has lacked for epigenomic studies. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection to-date of human epigenomes for primary cells and tissues. Here, we describe the integrative analysis of 111 reference human epigenomes generated as part of the program, profiled for histone modification patterns, DNA accessibility, DNA methylation, and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically-relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation, and human disease.
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            Software for Computing and Annotating Genomic Ranges

            We describe Bioconductor infrastructure for representing and computing on annotated genomic ranges and integrating genomic data with the statistical computing features of R and its extensions. At the core of the infrastructure are three packages: IRanges, GenomicRanges, and GenomicFeatures. These packages provide scalable data structures for representing annotated ranges on the genome, with special support for transcript structures, read alignments and coverage vectors. Computational facilities include efficient algorithms for overlap and nearest neighbor detection, coverage calculation and other range operations. This infrastructure directly supports more than 80 other Bioconductor packages, including those for sequence analysis, differential expression analysis and visualization.
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                Author and article information

                Contributors
                joseramon.bilbao@ehu.eus
                Journal
                Commun Biol
                Commun Biol
                Communications Biology
                Nature Publishing Group UK (London )
                2399-3642
                30 November 2022
                30 November 2022
                2022
                : 5
                : 1313
                Affiliations
                [1 ]GRID grid.11480.3c, ISNI 0000000121671098, Department of Genetics, Physical Anthropology and Animal Physiology, , University of the Basque Country (UPV/EHU) and Biocruces-Bizkaia Health Research Institute, ; Leioa, Basque Country Spain
                [2 ]GRID grid.38142.3c, ISNI 000000041936754X, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, ; Boston, MA USA
                [3 ]GRID grid.418110.d, ISNI 0000 0004 0642 0153, University Grenoble Alpes, Inserm, CNRS, Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, IAB, ; Grenoble, France
                [4 ]GRID grid.411172.0, ISNI 0000 0001 0081 2808, Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke (CHUS), ; Sherbrooke, QC Canada
                [5 ]GRID grid.7737.4, ISNI 0000 0004 0410 2071, Department of Psychology and Logopedics, , University of Helsinki, ; Helsinki, Finland
                [6 ]GRID grid.189967.8, ISNI 0000 0001 0941 6502, Gangarosa Department of Environmental Health, , Rollins School of Public Health at Emory University, ; Atlanta, GA USA
                [7 ]GRID grid.59734.3c, ISNI 0000 0001 0670 2351, Department of Environmental Medicine and Public Health, , Icahn School of Medicine at Mount Sinai, ; New York, NY USA
                [8 ]GRID grid.410445.0, ISNI 0000 0001 2188 0957, Cancer Epidemiology Program, , University of Hawaii Cancer Center, ; Honolulu, HI USA
                [9 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, Department of Epidemiology, Fielding School of Public Health, , University of California, ; Los Angeles, CA USA
                [10 ]GRID grid.5338.d, ISNI 0000 0001 2173 938X, Epidemiology and Environmental Health Joint Research Unit, , FISABIO-Universitat Jaume I-Universitat de València, ; Valencia, Spain
                [11 ]GRID grid.5338.d, ISNI 0000 0001 2173 938X, Preventive Medicine and Public Health, Food Sciences, Toxicology and Forensic Medicine Department, , Universitat de València, ; Valencia, Spain
                [12 ]GRID grid.4489.1, ISNI 0000000121678994, Department of Statistics and Operations Research, , University of Granada, ; Granada, Spain
                [13 ]GRID grid.4489.1, ISNI 0000000121678994, Bioinformatics Unit. GENYO, , Centre for Genomics and Oncological Research: Pfizer, University of Granada, Andalusian Regional Government, PTS Granada, ; Granada, Spain
                [14 ]GRID grid.1058.c, ISNI 0000 0000 9442 535X, Murdoch Children’s Research Institute, ; Parkville, VIC Australia
                [15 ]GRID grid.1008.9, ISNI 0000 0001 2179 088X, Department of Paediatrics, , University of Melbourne, ; Parkville, VIC Australia
                [16 ]GRID grid.214458.e, ISNI 0000000086837370, Department of Epidemiology, School of Public Health, , University of Michigan, ; Ann Arbor, MI USA
                [17 ]GRID grid.27860.3b, ISNI 0000 0004 1936 9684, Department of Medical Microbiology and Immunology, MIND Institute, Genome Center, , University of California, ; Davis, CA USA
                [18 ]GRID grid.508487.6, ISNI 0000 0004 7885 7602, Université de Paris, Centre for Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, ; Paris, France
                [19 ]GRID grid.5645.2, ISNI 000000040459992X, Department of Child and Adolescent Psychiatry and Psychology, ; Erasmus MC Rotterdam, The Netherlands
                [20 ]GRID grid.189967.8, ISNI 0000 0001 0941 6502, Department of Epidemiology, , Rollins School of Public health at Emory University, ; Atlanta, GA USA
                [21 ]GRID grid.5963.9, Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, , University of Freiburg, ; Freiburg, Germany
                [22 ]GRID grid.411342.1, ISNI 0000 0004 1771 1175, Health Research Institute of Asturias, ISPA and Biomedical Research and Innovation Institute of Cadiz (INiBICA), , Research Unit, Puerta del Mar University Hospital, ; Cadiz, Spain
                [23 ]GRID grid.21107.35, ISNI 0000 0001 2171 9311, Wendy Klag Center for Autism and Developmental Disabilities, Bloomberg School of Public Health, , Johns Hopkins University, ; Baltimore, MD USA
                [24 ]GRID grid.418135.a, ISNI 0000 0004 0641 3404, Laboratory for Epigenetics & Environment, Centre National de Recherche en Génomique Humaine, CEA-Institut de Biologie François Jacob, ; Evry, France
                [25 ]GRID grid.419548.5, ISNI 0000 0000 9497 5095, Max-Planck-Institute of Psychiatry, , Department of Translational Research in Psychiatry, ; Munich, Germany
                [26 ]GRID grid.4489.1, ISNI 0000000121678994, University of Granada, Center for Biomedical Research (CIBM), ; Granada, Spain
                [27 ]GRID grid.507088.2, Instituto de Investigación Biosanitaria ibs.GRANADA, ; Granada, Spain
                [28 ]GRID grid.466571.7, ISNI 0000 0004 1756 6246, CIBER of Epidemiology and Public Health (CIBERESP), ; Madrid, Spain
                [29 ]GRID grid.413740.5, ISNI 0000 0001 2186 2871, Andalusian School of Public Health (EASP), ; Granada, Spain
                [30 ]GRID grid.1021.2, ISNI 0000 0001 0526 7079, Deakin University, IMPACT – the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, ; Geelong, Australia
                [31 ]GRID grid.27860.3b, ISNI 0000 0004 1936 9684, Department of Public Health Sciences and the MIND Institute, , University of California Davis School of Medicine, ; Davis, CA USA
                [32 ]GRID grid.434607.2, ISNI 0000 0004 1763 3517, ISGlobal, Barcelona Institute for Global Health, ; Barcelona, Spain
                [33 ]GRID grid.5612.0, ISNI 0000 0001 2172 2676, Universitat Pompeu Fabra (UPF), ; Barcelona, Spain
                [34 ]GRID grid.86715.3d, ISNI 0000 0000 9064 6198, Department of Biochemistry and Functional Genomics, , Universite de Sherbrooke, ; Sherbrooke, QC Canada
                [35 ]GRID grid.459278.5, ISNI 0000 0004 4910 4652, Department of Laboratory Medicine, , CIUSSS du Saguenay–Lac-St-Jean – Hôpital Universitaire de Chicoutimi, ; Chicoutimi, QC Canada
                [36 ]GRID grid.432380.e, Biodonostia, Epidemiology and Public Health Area, , Environmental Epidemiology and Child Development Group, ; 20014 San Sebastian, Basque Country Spain
                [37 ]Health Department of Basque Government, Sub-directorate of Public Health of Gipuzkoa, San Sebastian, Basque Country Spain
                [38 ]GRID grid.32224.35, ISNI 0000 0004 0386 9924, Diabetes Unit, Massachusetts General Hospital, ; Boston, MA USA
                [39 ]GRID grid.512890.7, CIBER of diabetes and associated metabolic disorders (CIBERDEM), ; Madrid, Spain
                Author information
                http://orcid.org/0000-0001-6307-0880
                http://orcid.org/0000-0001-8907-197X
                http://orcid.org/0000-0001-6744-6750
                http://orcid.org/0000-0002-5186-0735
                http://orcid.org/0000-0002-9605-6337
                http://orcid.org/0000-0002-5405-9994
                http://orcid.org/0000-0003-2732-4550
                http://orcid.org/0000-0003-1241-6073
                http://orcid.org/0000-0002-6173-7255
                http://orcid.org/0000-0002-3480-2031
                http://orcid.org/0000-0002-2683-0817
                http://orcid.org/0000-0001-7381-904X
                http://orcid.org/0000-0001-6417-8914
                http://orcid.org/0000-0001-6537-1468
                http://orcid.org/0000-0003-1582-2747
                http://orcid.org/0000-0002-8102-9811
                http://orcid.org/0000-0003-0825-9124
                http://orcid.org/0000-0002-7090-1758
                http://orcid.org/0000-0003-4566-150X
                http://orcid.org/0000-0002-6398-7362
                http://orcid.org/0000-0002-1565-1629
                http://orcid.org/0000-0003-0127-2860
                http://orcid.org/0000-0001-7752-2585
                http://orcid.org/0000-0002-3176-501X
                Article
                4267
                10.1038/s42003-022-04267-y
                9709064
                36446949
                af09ed34-f68a-4149-85ea-75699a06594c
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 5 October 2021
                : 16 November 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100004587, Ministry of Economy and Competitiveness | Instituto de Salud Carlos III (Institute of Health Carlos III);
                Award ID: PI18/01142
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100010585, Osasun Saila, Eusko Jaurlaritzako (Departamento de Salud, Gobierno Vasco);
                Award ID: GVSAN2018111086
                Award Recipient :
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                © The Author(s) 2022

                epigenomics,genetics research
                epigenomics, genetics research

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