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Lundin JI, Peters U, Hu Y, Ammous F, Avery CL, Benjamin EJ, Bis JC, Brody JA, Carlson C, Cushman M, Gignoux C, Guo X, Haessler J, Haiman C, Joehanes R, Kasela S, Kenny E, Lapalainien T, Levy D, Liu C, Liu Y, Loos RJ, Lu A, Matise T, North KE, Park SL, Ratliff SM, Reiner A, Rich SS, Rotter JI, Smith JA, Sotoodehnia N, Tracy R, Van den Berg D, Xu H, Ye T, Zhao W, Raffield LM, Kooperberg C. Methylation patterns associated with C-reactive protein in racially and ethnically diverse populations. Epigenetics 2024; 19:2333668. [PMID: 38571307 PMCID: PMC10996836 DOI: 10.1080/15592294.2024.2333668] [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: 11/30/2023] [Accepted: 03/17/2024] [Indexed: 04/05/2024] Open
Abstract
Systemic low-grade inflammation is a feature of chronic disease. C-reactive protein (CRP) is a common biomarker of inflammation and used as an indicator of disease risk; however, the role of inflammation in disease is not completely understood. Methylation is an epigenetic modification in the DNA which plays a pivotal role in gene expression. In this study we evaluated differential DNA methylation patterns associated with blood CRP level to elucidate biological pathways and genetic regulatory mechanisms to improve the understanding of chronic inflammation. The racially and ethnically diverse participants in this study were included as 50% White, 41% Black or African American, 7% Hispanic or Latino/a, and 2% Native Hawaiian, Asian American, American Indian, or Alaska Native (total n = 13,433) individuals. We replicated 113 CpG sites from 87 unique loci, of which five were novel (CADM3, NALCN, NLRC5, ZNF792, and cg03282312), across a discovery set of 1,150 CpG sites associated with CRP level (p < 1.2E-7). The downstream pathways affected by DNA methylation included the identification of IFI16 and IRF7 CpG-gene transcript pairs which contributed to the innate immune response gene enrichment pathway along with NLRC5, NOD2, and AIM2. Gene enrichment analysis also identified the nuclear factor-kappaB transcription pathway. Using two-sample Mendelian randomization (MR) we inferred methylation at three CpG sites as causal for CRP levels using both White and Black or African American MR instrument variables. Overall, we identified novel CpG sites and gene transcripts that could be valuable in understanding the specific cellular processes and pathogenic mechanisms involved in inflammation.
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Affiliation(s)
- Jessica I. Lundin
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Yao Hu
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Farah Ammous
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Christy L. Avery
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Emelia J. Benjamin
- Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston University School of Public Health, Boston, MA, USA
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jennifer A. Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Chris Carlson
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Mary Cushman
- Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, VT, USA
| | - Chris Gignoux
- Interdisciplinary Quantitative Biology, University of Colorado, Boulder, CO, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jeff Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Chris Haiman
- Department of Environmental Medicine and Public Health, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Roby Joehanes
- Population Sciences Branch, National Heart, Lung, and Blood Institute of the National Institutes of Health, Bethesda, MD, USA
| | | | - Eimear Kenny
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute of the National Institutes of Health, Bethesda, MD, USA
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Yongmei Liu
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA
| | - Ruth J.F. Loos
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ake Lu
- Department of Human Genetics, University of California LA, Los Angeles, CA, USA
| | - Tara Matise
- Department of Genetics, Rutgers University, New Brunswick, NJ, USA
| | - Kari E. North
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Sungshim L. Park
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Scott M. Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Alex Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, and Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Harborview Medical Center, Seattle, WA, USA
| | - Russell Tracy
- Department of Biochemistry, University of Vermont, Burlington, VT, USA
| | - David Van den Berg
- Department of Environmental Medicine and Public Health, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Huichun Xu
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Ting Ye
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Wei Zhao
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - On Behalf of the PAGE Study
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
- Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston University School of Public Health, Boston, MA, USA
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, VT, USA
- Interdisciplinary Quantitative Biology, University of Colorado, Boulder, CO, USA
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
- Department of Environmental Medicine and Public Health, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute of the National Institutes of Health, Bethesda, MD, USA
- New York Genome Center, New York, NY
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA
- Department of Human Genetics, University of California LA, Los Angeles, CA, USA
- Department of Genetics, Rutgers University, New Brunswick, NJ, USA
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Epidemiology, School of Public Health, and Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
- Cardiovascular Health Research Unit, Harborview Medical Center, Seattle, WA, USA
- Department of Biochemistry, University of Vermont, Burlington, VT, USA
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
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2
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Aroke EN, Srinivasasainagendra V, Kottae P, Quinn TL, Wiggins AM, Hobson J, Kinnie K, Stoudmire T, Tiwari HK, Goodin BR. The Pace of Biological Aging Predicts Nonspecific Chronic Low Back Pain Severity. THE JOURNAL OF PAIN 2024; 25:974-983. [PMID: 37907115 PMCID: PMC10960701 DOI: 10.1016/j.jpain.2023.10.018] [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: 06/24/2023] [Revised: 10/15/2023] [Accepted: 10/21/2023] [Indexed: 11/02/2023]
Abstract
This study aimed to determine if and how the pace of biological aging was associated with nonspecific chronic low back pain (cLBP) and compare what measure of epigenetic age acceleration most strongly predicts cLBP outcomes. We used the Dunedin Pace of Aging from the Epigenome (DunedinPACE), Horvath's, Hannum's, and PhenoAge clocks to determine the pace of biological aging in 69 cLBP, and 49 pain-free controls (PFCs) adults, ages 18 to 85 years. On average, participants with cLBP had higher DunedinPACE (P < .001) but lower Horvath (P = .04) and Hannum (P = .02) accelerated epigenetic age than PFCs. There was no significant difference in PhenoAge acceleration between the cLBP and PFC groups (P = .97). DunedinPACE had the largest effect size (Cohen's d = .78) on group differences. In univariate regressions, a unit increase in DunedinPACE score was associated with 265.98 times higher odds of cLBP than the PFC group (P < .001). After controlling for sex, race, and body mass index (BMI), the odds ratio of cLBP to PFC group was 149.62 (P < .001). Furthermore, among participants with cLBP, DunedinPACE scores positively correlated with pain severity (rs = .385, P = .001) and interference (rs = .338, P = .005). Epigenetic age acceleration from Horvath, Hannum, and PhenoAge clocks were not significant predictors of cLBP. The odds of a faster pace of biological aging are higher among adults with cLBP, and this was associated with greater pain severity and disability. Future interventions to slow the pace of biological aging may improve cLBP outcomes. PERSPECTIVE: Accelerated epigenetic aging is common among adults with nonspecific cLBP. Higher DunedinPACE scores positively correlate with pain severity and interference, and better predict cLBP than other DNA methylation clocks. Interventions to slow the pace of biological aging may be viable targets for improving pain outcomes.
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Affiliation(s)
- Edwin N. Aroke
- School of Nursing, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Vinodh Srinivasasainagendra
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Pooja Kottae
- Department of Computer Science, College of Arts and Sciences, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Tammie L. Quinn
- Department of Psychology, College of Arts and Sciences, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Asia M. Wiggins
- Department of Psychology, College of Arts and Sciences, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Joanna Hobson
- Department of Psychology, College of Arts and Sciences, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Kiari Kinnie
- School of Nursing, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Tonya Stoudmire
- School of Nursing, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Hemant K. Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Burel R. Goodin
- Department of Anesthesiology, School of Medicine, Washington University, St Louis, USA
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3
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Stols-Gonçalves D, Mak AL, Madsen MS, van der Vossen EWJ, Bruinstroop E, Henneman P, Mol F, Scheithauer TPM, Smits L, Witjes J, Meijnikman AS, Verheij J, Nieuwdorp M, Holleboom AG, Levin E. Faecal Microbiota transplantation affects liver DNA methylation in Non-alcoholic fatty liver disease: a multi-omics approach. Gut Microbes 2023; 15:2223330. [PMID: 37317027 DOI: 10.1080/19490976.2023.2223330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 05/31/2023] [Accepted: 06/05/2023] [Indexed: 06/16/2023] Open
Abstract
Individuals with nonalcoholic fatty liver disease (NAFLD) have an altered gut microbiota composition. Moreover, hepatic DNA methylation may be altered in the state of NAFLD. Using a fecal microbiota transplantation (FMT) intervention, we aimed to investigate whether a change in gut microbiota composition relates to altered liver DNA methylation in NAFLD. Moreover, we assessed whether plasma metabolite profiles altered by FMT relate to changes in liver DNA methylation. Twenty-one individuals with NAFLD underwent three 8-weekly vegan allogenic donor (n = 10) or autologous (n = 11) FMTs. We obtained hepatic DNA methylation profiles from paired liver biopsies of study participants before and after FMTs. We applied a multi-omics machine learning approach to identify changes in the gut microbiome, peripheral blood metabolome and liver DNA methylome, and analyzed cross-omics correlations. Vegan allogenic donor FMT compared to autologous FMT induced distinct differential changes in I) gut microbiota profiles, including increased abundance of Eubacterium siraeum and potential probiotic Blautia wexlerae; II) plasma metabolites, including altered levels of phenylacetylcarnitine (PAC) and phenylacetylglutamine (PAG) both from gut-derived phenylacetic acid, and of several choline-derived long-chain acylcholines; and III) hepatic DNA methylation profiles, most importantly in Threonyl-TRNA Synthetase 1 (TARS) and Zinc finger protein 57 (ZFP57). Multi-omics analysis showed that Gemmiger formicillis and Firmicutes bacterium_CAG_170 positively correlated with both PAC and PAG. E siraeum negatively correlated with DNA methylation of cg16885113 in ZFP57. Alterations in gut microbiota composition by FMT caused widespread changes in plasma metabolites (e.g. PAC, PAG, and choline-derived metabolites) and liver DNA methylation profiles in individuals with NAFLD. These results indicate that FMTs might induce metaorganismal pathway changes, from the gut bacteria to the liver.
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Affiliation(s)
- Daniela Stols-Gonçalves
- Department of Vascular Medicine, Amsterdam University Medical Centre, Amsterdam, The Netherlands
| | - Anne Linde Mak
- Department of Vascular Medicine, Amsterdam University Medical Centre, Amsterdam, The Netherlands
- Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Mette S Madsen
- Gubra, Hørsholm, Denmark
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kongens Lyngby, Denmark
| | | | - Eveline Bruinstroop
- Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Department of Endocrinology, Amsterdam University Medical Centre, Amsterdam, The Netherlands
| | - Peter Henneman
- Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Department of Human Genetics, Amsterdam University Medical Centre, Amsterdam, The Netherlands
| | - Femke Mol
- Department of Vascular Medicine, Amsterdam University Medical Centre, Amsterdam, The Netherlands
| | - Torsten P M Scheithauer
- Department of Vascular Medicine, Amsterdam University Medical Centre, Amsterdam, The Netherlands
- Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Department of Internal Medicine, Amsterdam University Medical Centre (UMC), Vrije Universiteit (VU) University Medical Centre, Amsterdam, Netherlands
| | - Loek Smits
- Department of Vascular Medicine, Amsterdam University Medical Centre, Amsterdam, The Netherlands
| | - Julia Witjes
- Department of Vascular Medicine, Amsterdam University Medical Centre, Amsterdam, The Netherlands
- Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Abraham Stijn Meijnikman
- Department of Vascular Medicine, Amsterdam University Medical Centre, Amsterdam, The Netherlands
- Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Joanne Verheij
- Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Department of Pathology, Amsterdam University Medical Centre, Amsterdam, The Netherlands
| | - Max Nieuwdorp
- Department of Vascular Medicine, Amsterdam University Medical Centre, Amsterdam, The Netherlands
- Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Adriaan G Holleboom
- Department of Vascular Medicine, Amsterdam University Medical Centre, Amsterdam, The Netherlands
- Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Evgeni Levin
- Department of Vascular Medicine, Amsterdam University Medical Centre, Amsterdam, The Netherlands
- Amsterdam Gastroenterology Endocrinology Metabolism (AGEM) Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Horaizon BV, Delft, The Netherlands
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4
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Hageman I, Mol F, Atiqi S, Joustra V, Sengul H, Henneman P, Visman I, Hakvoort T, Nurmohamed M, Wolbink G, Levin E, Li Yim AY, D’Haens G, de Jonge WJ. Novel DNA methylome biomarkers associated with adalimumab response in rheumatoid arthritis patients. Front Immunol 2023; 14:1303231. [PMID: 38187379 PMCID: PMC10771853 DOI: 10.3389/fimmu.2023.1303231] [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: 09/27/2023] [Accepted: 12/04/2023] [Indexed: 01/09/2024] Open
Abstract
Background and aims Rheumatoid arthritis (RA) patients are currently treated with biological agents mostly aimed at cytokine blockade, such as tumor necrosis factor-alpha (TNFα). Currently, there are no biomarkers to predict therapy response to these agents. Here, we aimed to predict response to adalimumab (ADA) treatment in RA patients using DNA methylation in peripheral blood (PBL). Methods DNA methylation profiling on whole peripheral blood from 92 RA patients before the start of ADA treatment was determined using Illumina HumanMethylationEPIC BeadChip array. After 6 months, treatment response was assessed according to the European Alliance of Associations for Rheumatology (EULAR) criteria for disease activity. Patients were classified as responders (Disease Activity Score in 28 Joints (DAS28) < 3.2 or decrease of 1.2 points) or as non-responders (DAS28 > 5.1 or decrease of less than 0.6 points). Machine learning models were built through stability-selected gradient boosting to predict response prior to ADA treatment with predictor DNA methylation markers. Results Of the 94 RA patients, we classified 49 and 43 patients as responders and non-responders, respectively. We were capable of differentiating responders from non-responders with a high performance (area under the curve (AUC) 0.76) using a panel of 27 CpGs. These classifier CpGs are annotated to genes involved in immunological and pathophysiological pathways related to RA such as T-cell signaling, B-cell pathology, and angiogenesis. Conclusion Our findings indicate that the DNA methylome of PBL provides discriminative capabilities in discerning responders and non-responders to ADA treatment and may therefore serve as a tool for therapy prediction.
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Affiliation(s)
- Ishtu Hageman
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Centers (UMC), University of Amsterdam, Amsterdam, Netherlands
- Tytgat Institute for Liver and Intestinal Research, Amsterdam University Medical Centers (UMC), University of Amsterdam, Amsterdam, Netherlands
| | - Femke Mol
- Tytgat Institute for Liver and Intestinal Research, Amsterdam University Medical Centers (UMC), University of Amsterdam, Amsterdam, Netherlands
| | - Sadaf Atiqi
- Department of Rheumatology, Amsterdam Rheumatology and Immunology Center, Vrije Universiteit (VU) University Medical Center, Amsterdam, Netherlands
| | - Vincent Joustra
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Centers (UMC), University of Amsterdam, Amsterdam, Netherlands
| | - Hilal Sengul
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Centers (UMC), University of Amsterdam, Amsterdam, Netherlands
| | - Peter Henneman
- Genome Diagnostics Laboratory, Department of Human Genetics, Amsterdam University Medical Centers (UMC), University of Amsterdam, Amsterdam, Netherlands
| | - Ingrid Visman
- Department of Rheumatology, Amsterdam Rheumatology and Immunology Center, Vrije Universiteit (VU) University Medical Center, Amsterdam, Netherlands
| | - Theodorus Hakvoort
- Tytgat Institute for Liver and Intestinal Research, Amsterdam University Medical Centers (UMC), University of Amsterdam, Amsterdam, Netherlands
| | - Mike Nurmohamed
- Department of Rheumatology, Amsterdam Rheumatology and Immunology Center, Vrije Universiteit (VU) University Medical Center, Amsterdam, Netherlands
| | - Gertjan Wolbink
- Department of Rheumatology, Amsterdam Rheumatology and Immunology Center, Vrije Universiteit (VU) University Medical Center, Amsterdam, Netherlands
| | - Evgeni Levin
- Department of Vascular Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
- Horaizon BV, Delft, Netherlands
| | - Andrew Y.F. Li Yim
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Centers (UMC), University of Amsterdam, Amsterdam, Netherlands
- Tytgat Institute for Liver and Intestinal Research, Amsterdam University Medical Centers (UMC), University of Amsterdam, Amsterdam, Netherlands
- Genome Diagnostics Laboratory, Department of Human Genetics, Amsterdam University Medical Centers (UMC), University of Amsterdam, Amsterdam, Netherlands
| | - Geert D’Haens
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Centers (UMC), University of Amsterdam, Amsterdam, Netherlands
| | - Wouter J. de Jonge
- Tytgat Institute for Liver and Intestinal Research, Amsterdam University Medical Centers (UMC), University of Amsterdam, Amsterdam, Netherlands
- Department of Surgery, University of Bonn, Bonn, Germany
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5
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Bhat B, Jones GT. Gaps in current methods to detect polymorphic CpGs from Illumina Infinium human methylation microarrays and exploring their potential impact in multi-EWAS analyses. Epigenetics 2023; 18:2281153. [PMID: 37983305 PMCID: PMC10732615 DOI: 10.1080/15592294.2023.2281153] [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: 07/14/2023] [Accepted: 10/27/2023] [Indexed: 11/22/2023] Open
Abstract
DNA methylation (DNAm) epigenome-wide association studies (EWAS) have been performed on diverse ethnicities to discover novel biomarkers associated with various diseases, such as cancers, autoimmune diseases, and neurological disorders. However, genetic polymorphisms can influence DNAm levels resulting in methylation quantitative trait loci (meQTL). These can be either direct effects, by altering the sequence of the methylation (CpG) site itself, or, in the case of array-based measures, indirectly altering the detection probe-binding site interaction. Given that genetic variant frequencies associated with meQTL can differ between population groups, these have the potential to confound EWAS observations, particularly in multi-ethnic populations. In this study, we analysed publicly available DNA methylation profiles (450K array), consisting of 1342 individuals from 6 distinct ancestral groups. We investigate two distinct tools (GapHunter and MethylToSNP) specifically designed to identify CpG sites that may be influenced by genetic variation. Results from this aggregated trans-ancestral epigenome-wide dataset suggest that both tools fail to consistently identify not only rarer (MAF < 0.05) genetic variant effects but also more than half of sites predicted to be associated with variants with much higher allele frequencies (MAF >0.2). In addition, there is a relatively low concordance in the detection of polymorphic CpGs between GapHunter and MethylToSNP. Screening of CpG site associations from EWAS using either of these tools is unlikely to be a robust or comprehensive means of identifying all genetic variant confounding effects.
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Affiliation(s)
- Basharat Bhat
- Departments of Surgical Sciences, University of Otago, Dunedin, New Zealand
| | - Gregory T Jones
- Departments of Surgical Sciences, University of Otago, Dunedin, New Zealand
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6
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Hu X, Logan JG, Kwon Y, Lima JAC, Jacobs DR, Duprez D, Brumback L, Taylor KD, Durda P, Johnson WC, Cornell E, Guo X, Liu Y, Tracy RP, Blackwell TW, Papanicolaou G, Mitchell GF, Rich SS, Rotter JI, Van Den Berg DJ, Chirinos JA, Hughes TM, Garrett-Bakelman FE, Manichaikul A. Multi-ancestry epigenome-wide analyses identify methylated sites associated with aortic augmentation index in TOPMed MESA. Sci Rep 2023; 13:17680. [PMID: 37848499 PMCID: PMC10582077 DOI: 10.1038/s41598-023-44806-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 10/12/2023] [Indexed: 10/19/2023] Open
Abstract
Despite the prognostic value of arterial stiffness (AS) and pulsatile hemodynamics (PH) for cardiovascular morbidity and mortality, epigenetic modifications that contribute to AS/PH remain unknown. To gain a better understanding of the link between epigenetics (DNA methylation) and AS/PH, we examined the relationship of eight measures of AS/PH with CpG sites and co-methylated regions using multi-ancestry participants from Trans-Omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA) with sample sizes ranging from 438 to 874. Epigenome-wide association analysis identified one genome-wide significant CpG (cg20711926-CYP1B1) associated with aortic augmentation index (AIx). Follow-up analyses, including gene set enrichment analysis, expression quantitative trait methylation analysis, and functional enrichment analysis on differentially methylated positions and regions, further prioritized three CpGs and their annotated genes (cg23800023-ETS1, cg08426368-TGFB3, and cg17350632-HLA-DPB1) for AIx. Among these, ETS1 and TGFB3 have been previously prioritized as candidate genes. Furthermore, both ETS1 and HLA-DPB1 have significant tissue correlations between Whole Blood and Aorta in GTEx, which suggests ETS1 and HLA-DPB1 could be potential biomarkers in understanding pathophysiology of AS/PH. Overall, our findings support the possible role of epigenetic regulation via DNA methylation of specific genes associated with AIx as well as identifying potential targets for regulation of AS/PH.
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Affiliation(s)
- Xiaowei Hu
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22908, USA
| | - Jeongok G Logan
- School of Nursing, University of Virginia, Charlottesville, VA, USA
| | - Younghoon Kwon
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Joao A C Lima
- Department of Internal Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - David R Jacobs
- Division of Epidemiology, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Daniel Duprez
- Cardiovascular Division, University of Minnesota, Minneapolis, MN, USA
| | - Lyndia Brumback
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Peter Durda
- Laboratory for Clinical Biochemistry Research, University of Vermont, Burlington, VT, USA
| | - W Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Elaine Cornell
- Laboratory for Clinical Biochemistry Research, University of Vermont, Burlington, VT, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Yongmei Liu
- Division of Cardiology, Department of Medicine, Duke University, Durham, NC, USA
| | - Russell P Tracy
- Laboratory for Clinical Biochemistry Research, University of Vermont, Burlington, VT, USA
| | - Thomas W Blackwell
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - George Papanicolaou
- Epidemiology Branch, National Heart, Lung and Blood Institute, Bethesda, MD, USA
| | | | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22908, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - David J Van Den Berg
- Department of Preventive Medicine and Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Julio A Chirinos
- Division of Cardiovascular Medicine, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Timothy M Hughes
- Department of Internal Medicine - Section of Gerontology and Geriatric Medicine, and Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Francine E Garrett-Bakelman
- Department of Biochemistry and Molecular Genetics, Department of Medicine, University of Virginia, 1340 Jefferson Park Ave., Pinn hall 6054, Charlottesville, VA, 22908, USA.
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22908, USA.
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7
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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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8
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Niemiec SS, Kechris K, Pattee J, Yang IV, Adgate JL, Calafat AM, Dabelea D, Starling AP. Prenatal exposures to per- and polyfluoroalkyl substances and epigenetic aging in umbilical cord blood: The Healthy Start study. ENVIRONMENTAL RESEARCH 2023; 231:116215. [PMID: 37224946 PMCID: PMC10330919 DOI: 10.1016/j.envres.2023.116215] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 05/19/2023] [Accepted: 05/20/2023] [Indexed: 05/26/2023]
Abstract
BACKGROUND Per- and polyfluoroalkyl substances (PFAS) are ubiquitous, environmentally persistent chemicals, and prenatal exposures have been associated with adverse child health outcomes. Prenatal PFAS exposure may lead to epigenetic age acceleration (EAA), defined as the discrepancy between an individual's chronologic and epigenetic or biological age. OBJECTIVES We estimated associations of maternal serum PFAS concentrations with EAA in umbilical cord blood DNA methylation using linear regression, and a multivariable exposure-response function of the PFAS mixture using Bayesian kernel machine regression. METHODS Five PFAS were quantified in maternal serum (median: 27 weeks of gestation) among 577 mother-infant dyads from a prospective cohort. Cord blood DNA methylation data were assessed with the Illumina HumanMethylation450 array. EAA was calculated as the residuals from regressing gestational age on epigenetic age, calculated using a cord-blood specific epigenetic clock. Linear regression tested for associations between each maternal PFAS concentration with EAA. Bayesian kernel machine regression with hierarchical selection estimated an exposure-response function for the PFAS mixture. RESULTS In single pollutant models we observed an inverse relationship between perfluorodecanoate (PFDA) and EAA (-0.148 weeks per log-unit increase, 95% CI: -0.283, -0.013). Mixture analysis with hierarchical selection between perfluoroalkyl carboxylates and sulfonates indicated the carboxylates had the highest group posterior inclusion probability (PIP), or relative importance. Within this group, PFDA had the highest conditional PIP. Univariate predictor-response functions indicated PFDA and perfluorononanoate were inversely associated with EAA, while perfluorohexane sulfonate had a positive association with EAA. CONCLUSIONS Maternal mid-pregnancy serum concentrations of PFDA were negatively associated with EAA in cord blood, suggesting a pathway by which prenatal PFAS exposures may affect infant development. No significant associations were observed with other PFAS. Mixture models suggested opposite directions of association between perfluoroalkyl sulfonates and carboxylates. Future studies are needed to determine the importance of neonatal EAA for later child health outcomes.
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Affiliation(s)
- Sierra S Niemiec
- Center for Innovative Design and Analysis, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
| | - Katerina Kechris
- Center for Innovative Design and Analysis, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Jack Pattee
- Center for Innovative Design and Analysis, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Ivana V Yang
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA; Center for Genes, Environment and Health, National Jewish Health, Denver, CO, USA; Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - John L Adgate
- Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado, Aurora, CO, USA
| | - Antonia M Calafat
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Dana Dabelea
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Pediatrics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Anne P Starling
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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9
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Manichaikul A, Hu X, Logan J, Kwon Y, Lima J, Jacobs D, Duprez D, Brumback L, Taylor K, Durda P, Johnson C, Cornell E, Guo X, Liu Y, Tracy R, Blackwell T, Papanicolaou G, Mitchell G, Rich S, Rotter J, Van Den Berg D, Chirinos J, Hughes T, Garrett-Bakelman F. Multi-ancestry epigenome-wide analyses identify methylated sites associated with aortic augmentation index in TOPMed MESA. RESEARCH SQUARE 2023:rs.3.rs-3125948. [PMID: 37502922 PMCID: PMC10371087 DOI: 10.21203/rs.3.rs-3125948/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Despite the prognostic value of arterial stiffness (AS) and pulsatile hemodynamics (PH) for cardiovascular morbidity and mortality, epigenetic modifications that contribute to AS/PH remain unknown. To gain a better understanding of the link between epigenetics (DNA methylation) and AS/PH, we examined the relationship of eight measures of AS/PH with CpG sites and co-methylated regions using multi-ancestry participants from Trans-Omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA) with sample sizes ranging from 438 to 874. Epigenome-wide association analysis identified one genome-wide significant CpG (cg20711926-CYP1B1) associated with aortic augmentation index (AIx). Follow-up analyses, including gene set enrichment analysis, expression quantitative trait methylation analysis, and functional enrichment analysis on differentially methylated positions and regions, further prioritized three CpGs and their annotated genes (cg23800023-ETS1, cg08426368-TGFB3, and cg17350632-HLA-DPB1) for AIx. Among these, ETS1 and TGFB3 have been previously prioritized as candidate genes. Furthermore, both ETS1 and HLA-DPB1 have significant tissue correlations between Whole Blood and Aorta in GTEx, which suggests ETS1 and HLA-DPB1 could be potential biomarkers in understanding pathophysiology of AS/PH. Overall, our findings support the possible role of epigenetic regulation via DNA methylation of specific genes associated with AIx as well as identifying potential targets for regulation of AS/PH.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Kent Taylor
- The Institute for Translational Genomics and Population Sciences
| | | | | | | | | | | | | | | | | | | | - Stephen Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia
| | - Jerome Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center
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10
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McAllan L, Baranasic D, Villicaña S, Brown S, Zhang W, Lehne B, Adamo M, Jenkinson A, Elkalaawy M, Mohammadi B, Hashemi M, Fernandes N, Lambie N, Williams R, Christiansen C, Yang Y, Zudina L, Lagou V, Tan S, Castillo-Fernandez J, King JWD, Soong R, Elliott P, Scott J, Prokopenko I, Cebola I, Loh M, Lenhard B, Batterham RL, Bell JT, Chambers JC, Kooner JS, Scott WR. Integrative genomic analyses in adipocytes implicate DNA methylation in human obesity and diabetes. Nat Commun 2023; 14:2784. [PMID: 37188674 PMCID: PMC10185556 DOI: 10.1038/s41467-023-38439-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 05/03/2023] [Indexed: 05/17/2023] Open
Abstract
DNA methylation variations are prevalent in human obesity but evidence of a causative role in disease pathogenesis is limited. Here, we combine epigenome-wide association and integrative genomics to investigate the impact of adipocyte DNA methylation variations in human obesity. We discover extensive DNA methylation changes that are robustly associated with obesity (N = 190 samples, 691 loci in subcutaneous and 173 loci in visceral adipocytes, P < 1 × 10-7). We connect obesity-associated methylation variations to transcriptomic changes at >500 target genes, and identify putative methylation-transcription factor interactions. Through Mendelian Randomisation, we infer causal effects of methylation on obesity and obesity-induced metabolic disturbances at 59 independent loci. Targeted methylation sequencing, CRISPR-activation and gene silencing in adipocytes, further identifies regional methylation variations, underlying regulatory elements and novel cellular metabolic effects. Our results indicate DNA methylation is an important determinant of human obesity and its metabolic complications, and reveal mechanisms through which altered methylation may impact adipocyte functions.
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Affiliation(s)
- Liam McAllan
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, W12 0NN, UK
- MRC London Institute of Medical Sciences, London, W12 0NN, UK
| | - Damir Baranasic
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, W12 0NN, UK
- MRC London Institute of Medical Sciences, London, W12 0NN, UK
| | - Sergio Villicaña
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Scarlett Brown
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, W12 0NN, UK
- MRC London Institute of Medical Sciences, London, W12 0NN, UK
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UB1 3HW, UK
| | - Benjamin Lehne
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
| | - Marco Adamo
- UCLH Bariatric Centre for Weight Loss, Weight Management and Metabolic and Endocrine Surgery, University College London Hospitals, Ground Floor West Wing, 250 Euston Road, London, NW1 2PG, UK
| | - Andrew Jenkinson
- UCLH Bariatric Centre for Weight Loss, Weight Management and Metabolic and Endocrine Surgery, University College London Hospitals, Ground Floor West Wing, 250 Euston Road, London, NW1 2PG, UK
| | - Mohamed Elkalaawy
- UCLH Bariatric Centre for Weight Loss, Weight Management and Metabolic and Endocrine Surgery, University College London Hospitals, Ground Floor West Wing, 250 Euston Road, London, NW1 2PG, UK
| | - Borzoueh Mohammadi
- UCLH Bariatric Centre for Weight Loss, Weight Management and Metabolic and Endocrine Surgery, University College London Hospitals, Ground Floor West Wing, 250 Euston Road, London, NW1 2PG, UK
| | - Majid Hashemi
- UCLH Bariatric Centre for Weight Loss, Weight Management and Metabolic and Endocrine Surgery, University College London Hospitals, Ground Floor West Wing, 250 Euston Road, London, NW1 2PG, UK
| | - Nadia Fernandes
- Imperial BRC Genomics Facility, Faculty of Medicine, Imperial College London, London, W12 0NN, UK
| | - Nathalie Lambie
- Imperial BRC Genomics Facility, Faculty of Medicine, Imperial College London, London, W12 0NN, UK
| | - Richard Williams
- Imperial BRC Genomics Facility, Faculty of Medicine, Imperial College London, London, W12 0NN, UK
| | - Colette Christiansen
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, UK
| | - Youwen Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
- School of Cardiovascular and Metabolic Medicine and Sciences, James Black Centre, King's College London British Heart Foundation Centre of Excellence, 125 Coldharbour Lane, London, SE5 9NU, UK
| | - Liudmila Zudina
- Department of Clinical & Experimental Medicine, University of Surrey, Guildford, UK
| | - Vasiliki Lagou
- Department of Microbiology and Immunology, Laboratory of Adaptive Immunity, KU Leuven, Leuven, Belgium
- VIB-KU Leuven Center for Brain and Disease Research, Leuven, Belgium
| | - Sili Tan
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | | | - James W D King
- MRC London Institute of Medical Sciences, London, W12 0NN, UK
| | - Richie Soong
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
- Department of Pathology, National University Hospital, Singapore, Singapore
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- National Institute for Health Research Biomedical Research Centre, Imperial College London, London, UK
| | - James Scott
- National Heart and Lung Institute, Imperial College London, London, W12 0NN, UK
- Imperial College Healthcare NHS Trust, London, W12 0HS, UK
| | - Inga Prokopenko
- Department of Clinical & Experimental Medicine, University of Surrey, Guildford, UK
- People-Centred Artificial Intelligence Institute, University of Surrey, Guildford, UK
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre Russian Academy of Sciences, Ufa, Russian Federation
| | - Inês Cebola
- Section of Genetics and Genomics, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Marie Loh
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
- Translational Laboratory in Genetic Medicine (TLGM), Agency for Science, Technology and Research (A*STAR), 8A Biomedical Grove, Immunos, Level 5, Singapore, 138648, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Boris Lenhard
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, W12 0NN, UK
- MRC London Institute of Medical Sciences, London, W12 0NN, UK
| | - Rachel L Batterham
- UCLH Bariatric Centre for Weight Loss, Weight Management and Metabolic and Endocrine Surgery, University College London Hospitals, Ground Floor West Wing, 250 Euston Road, London, NW1 2PG, UK
- Centre for Obesity Research, Rayne Institute, Department of Medicine, University College, London, WC1E 6JJ, UK
- National Institute of Health Research University College London Hospitals Biomedical Research Centre, London, W1T 7DN, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - John C Chambers
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UB1 3HW, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Imperial College Healthcare NHS Trust, London, W12 0HS, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UB1 3HW, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- National Heart and Lung Institute, Imperial College London, London, W12 0NN, UK
- Imperial College Healthcare NHS Trust, London, W12 0HS, UK
| | - William R Scott
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, W12 0NN, UK.
- MRC London Institute of Medical Sciences, London, W12 0NN, UK.
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK.
- Imperial College Healthcare NHS Trust, London, W12 0HS, UK.
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11
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Romanowska J, Nustad HE, Page CM, Denault WRP, Lee Y, Magnus MC, Haftorn KL, Gjerdevik M, Novakovic B, Saffery R, Gjessing HK, Lyle R, Magnus P, Håberg SE, Jugessur A. The X-factor in ART: does the use of assisted reproductive technologies influence DNA methylation on the X chromosome? Hum Genomics 2023; 17:35. [PMID: 37085889 PMCID: PMC10122315 DOI: 10.1186/s40246-023-00484-6] [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: 01/09/2023] [Accepted: 04/10/2023] [Indexed: 04/23/2023] Open
Abstract
BACKGROUND Assisted reproductive technologies (ART) may perturb DNA methylation (DNAm) in early embryonic development. Although a handful of epigenome-wide association studies of ART have been published, none have investigated CpGs on the X chromosome. To bridge this knowledge gap, we leveraged one of the largest collections of mother-father-newborn trios of ART and non-ART (natural) conceptions to date to investigate sex-specific DNAm differences on the X chromosome. The discovery cohort consisted of 982 ART and 963 non-ART trios from the Norwegian Mother, Father, and Child Cohort Study (MoBa). To verify our results from the MoBa cohort, we used an external cohort of 149 ART and 58 non-ART neonates from the Australian 'Clinical review of the Health of adults conceived following Assisted Reproductive Technologies' (CHART) study. The Illumina EPIC array was used to measure DNAm in both datasets. In the MoBa cohort, we performed a set of X-chromosome-wide association studies ('XWASs' hereafter) to search for sex-specific DNAm differences between ART and non-ART newborns. We tested several models to investigate the influence of various confounders, including parental DNAm. We also searched for differentially methylated regions (DMRs) and regions of co-methylation flanking the most significant CpGs. Additionally, we ran an analogous model to our main model on the external CHART dataset. RESULTS In the MoBa cohort, we found more differentially methylated CpGs and DMRs in girls than boys. Most of the associations persisted after controlling for parental DNAm and other confounders. Many of the significant CpGs and DMRs were in gene-promoter regions, and several of the genes linked to these CpGs are expressed in tissues relevant for both ART and sex (testis, placenta, and fallopian tube). We found no support for parental DNAm-dependent features as an explanation for the observed associations in the newborns. The most significant CpG in the boys-only analysis was in UBE2DNL, which is expressed in testes but with unknown function. The most significant CpGs in the girls-only analysis were in EIF2S3 and AMOT. These three loci also displayed differential DNAm in the CHART cohort. CONCLUSIONS Genes that co-localized with the significant CpGs and DMRs associated with ART are implicated in several key biological processes (e.g., neurodevelopment) and disorders (e.g., intellectual disability and autism). These connections are particularly compelling in light of previous findings indicating that neurodevelopmental outcomes differ in ART-conceived children compared to those naturally conceived.
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Affiliation(s)
- Julia Romanowska
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway.
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.
| | - Haakon E Nustad
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- DeepInsight, 0154, Oslo, Norway
| | - Christian M Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
| | - William R P Denault
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Yunsung Lee
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Maria C Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Kristine L Haftorn
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Miriam Gjerdevik
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway
| | - Boris Novakovic
- Murdoch Children's Research Institute, Melbourne, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, Australia
| | - Richard Saffery
- Murdoch Children's Research Institute, Melbourne, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, Australia
| | - Håkon K Gjessing
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | - Robert Lyle
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Per Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Siri E Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Astanand Jugessur
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
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12
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Becerra CY, Wells RK, Kunihiro BP, Lee RH, Umeda L, Allan NP, Rubas NC, McCracken TA, Nunokawa CKL, Lee MH, Pidlaoan FGS, Phankitnirondorn K, Dye CK, Yamamoto BY, Peres R, Juarez R, Maunakea AK. Examining the immunoepigenetic-gut microbiome axis in the context of self-esteem among Native Hawaiians and other Pacific Islanders. Front Genet 2023; 14:1125217. [PMID: 37152987 PMCID: PMC10154580 DOI: 10.3389/fgene.2023.1125217] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 03/21/2023] [Indexed: 05/09/2023] Open
Abstract
Introduction: Native Hawaiian and other Pacific Islander (NHPI) populations experience higher rates of immunometabolic diseases compared to other racial-ethnic groups in Hawaii. As annual NHPI mortality rates for suicide and type 2 diabetes mellitus (T2DM) exceed those of the state as a whole, understanding the social and biological mechanisms underlying these disparities are urgently needed to enable preventive strategies. Methods: A community-based approach was used to investigate the immunoepigenetic-gut microbiome axis in an NHPI-enriched cohort of Oahu residents (N = 68). Self-esteem (SE) data was collected using a modified Rosenberg self-esteem (SE) assessment as a proxy measure for mental wellbeing in consideration for cultural competency. T2DM status was evaluated using point-of-care A1c (%) tests. Stool samples were collected for 16s-based metagenomic sequencing analyses. Plasma from blood samples were isolated by density-gradient centrifugation. Peripheral blood mononuclear cells (PBMCs) were collected from the same samples and enriched for monocytes using negative selection techniques. Flow-cytometry was used for immunoprofiling assays. Monocyte DNA was extracted for Illumina EPIC array-based methylation analysis. Results: Compared to individuals with normal SE (NSE), those with low SE (LSE) exhibited significantly higher plasma concentrations (pg/ml) of proinflammatory cytokines IL-8 (p = 0.051) and TNF-α (p = 0.011). Metagenomic analysis revealed that the relative abundance (%) of specific gut bacteria significantly differed between SE groups - some of which directly correlated with SE scores. Gene ontology analysis revealed that 104 significantly differentially methylated loci (DML) between SE groups were preferentially located at genes involved in immunometabolic processes. Horvath clock analyses indicated epigenetic age (Epi-Age) deceleration in individuals with LSE and acceleration in individuals with NSE (p = 0.042), yet was not reproduced by other clocks. Discussion: These data reveal novel differences in the immunoepigenetic-gut microbiome axis with respect to SE, warranting further investigation into its relationship to brain activity and mental health in NHPI. Unexpected results from Epi-Age analyses warrant further investigation into the relationship between biological age and disparate health outcomes among the NHPI population. The modifiable component of epigenetic processes and the gut microbiome makes this axis an attractive target for potential therapeutics, biomarker discovery, and novel prevention strategies.
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Affiliation(s)
- Celyna Y Becerra
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
- IDeA Networks of Biomedical Research Excellence (INBRE), University of Hawaii at Manoa, Honolulu, HI, United States
| | - Riley K Wells
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
- Department of Molecular Biosciences and Bioengineering, University of Hawaii at Manoa, Honolulu, HI, United States
| | - Braden P Kunihiro
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
- IDeA Networks of Biomedical Research Excellence (INBRE), University of Hawaii at Manoa, Honolulu, HI, United States
| | - Rosa H Lee
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Lesley Umeda
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
- Department of Molecular Biosciences and Bioengineering, University of Hawaii at Manoa, Honolulu, HI, United States
| | - Nina P Allan
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Noelle C Rubas
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Trevor A McCracken
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Chandler K L Nunokawa
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Ming-Hao Lee
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Felix Gerard S Pidlaoan
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Krit Phankitnirondorn
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Christian K Dye
- Department of Environmental Health Sciences, Columbia University Irving Medical Center, NY, NY, United States
| | - Brennan Y Yamamoto
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Rafael Peres
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
| | - Ruben Juarez
- Department of Economics, University of Hawaii at Manoa, Honolulu, HI, United States
- University of Hawaii Economic Research Organization (UHERO), University of Hawaii at Manoa, Honolulu, HI, United States
| | - Alika K Maunakea
- Department of Anatomy, Biochemistry, and Physiology, John A. Burns School of Medicine, Honolulu, HI, United States
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13
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Alba-Linares JJ, Pérez RF, Tejedor JR, Bastante-Rodríguez D, Ponce F, Carbonell NG, Zafra RG, Fernández AF, Fraga MF, Lurbe E. Maternal obesity and gestational diabetes reprogram the methylome of offspring beyond birth by inducing epigenetic signatures in metabolic and developmental pathways. Cardiovasc Diabetol 2023; 22:44. [PMID: 36870961 PMCID: PMC9985842 DOI: 10.1186/s12933-023-01774-y] [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: 12/06/2022] [Accepted: 02/15/2023] [Indexed: 03/06/2023] Open
Abstract
BACKGROUND Obesity is a negative chronic metabolic health condition that represents an additional risk for the development of multiple pathologies. Epidemiological studies have shown how maternal obesity or gestational diabetes mellitus during pregnancy constitute serious risk factors in relation to the appearance of cardiometabolic diseases in the offspring. Furthermore, epigenetic remodelling may help explain the molecular mechanisms that underlie these epidemiological findings. Thus, in this study we explored the DNA methylation landscape of children born to mothers with obesity and gestational diabetes during their first year of life. METHODS We used Illumina Infinium MethylationEPIC BeadChip arrays to profile more than 770,000 genome-wide CpG sites in blood samples from a paediatric longitudinal cohort consisting of 26 children born to mothers who suffered from obesity or obesity with gestational diabetes mellitus during pregnancy and 13 healthy controls (measurements taken at 0, 6 and 12 month; total N = 90). We carried out cross-sectional and longitudinal analyses to derive DNA methylation alterations associated with developmental and pathology-related epigenomics. RESULTS We identified abundant DNA methylation changes during child development from birth to 6 months and, to a lesser extent, up to 12 months of age. Using cross-sectional analyses, we discovered DNA methylation biomarkers maintained across the first year of life that could discriminate children born to mothers who suffered from obesity or obesity with gestational diabetes. Importantly, enrichment analyses suggested that these alterations constitute epigenetic signatures that affect genes and pathways involved in the metabolism of fatty acids, postnatal developmental processes and mitochondrial bioenergetics, such as CPT1B, SLC38A4, SLC35F3 and FN3K. Finally, we observed evidence of an interaction between developmental DNA methylation changes and maternal metabolic condition alterations. CONCLUSIONS Our observations highlight the first six months of development as being the most crucial for epigenetic remodelling. Furthermore, our results support the existence of systemic intrauterine foetal programming linked to obesity and gestational diabetes that affects the childhood methylome beyond birth, which involves alterations related to metabolic pathways, and which may interact with ordinary postnatal development programmes.
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Affiliation(s)
- Juan José Alba-Linares
- Cancer Epigenetics and Nanomedicine Laboratory, Nanomaterials and Nanotechnology Research Center (CINN-CSIC), University of Oviedo, Oviedo, Spain
- Health Research Institute of Asturias (ISPA-FINBA), University of Oviedo, Oviedo, Spain
- Institute of Oncology of Asturias (IUOPA), University of Oviedo, Oviedo, Spain
- Department of Organisms and Systems Biology (B.O.S.), University of Oviedo, Oviedo, Spain
- Biomedical Research Networking Center on Rare Diseases (CIBERER), Institute of Health Carlos III (ISCIII), Madrid, Spain
| | - Raúl F Pérez
- Cancer Epigenetics and Nanomedicine Laboratory, Nanomaterials and Nanotechnology Research Center (CINN-CSIC), University of Oviedo, Oviedo, Spain
- Health Research Institute of Asturias (ISPA-FINBA), University of Oviedo, Oviedo, Spain
- Institute of Oncology of Asturias (IUOPA), University of Oviedo, Oviedo, Spain
- Department of Organisms and Systems Biology (B.O.S.), University of Oviedo, Oviedo, Spain
- Biomedical Research Networking Center on Rare Diseases (CIBERER), Institute of Health Carlos III (ISCIII), Madrid, Spain
| | - Juan Ramón Tejedor
- Cancer Epigenetics and Nanomedicine Laboratory, Nanomaterials and Nanotechnology Research Center (CINN-CSIC), University of Oviedo, Oviedo, Spain
- Health Research Institute of Asturias (ISPA-FINBA), University of Oviedo, Oviedo, Spain
- Institute of Oncology of Asturias (IUOPA), University of Oviedo, Oviedo, Spain
- Department of Organisms and Systems Biology (B.O.S.), University of Oviedo, Oviedo, Spain
- Biomedical Research Networking Center on Rare Diseases (CIBERER), Institute of Health Carlos III (ISCIII), Madrid, Spain
| | - David Bastante-Rodríguez
- Cancer Epigenetics and Nanomedicine Laboratory, Nanomaterials and Nanotechnology Research Center (CINN-CSIC), University of Oviedo, Oviedo, Spain
- Health Research Institute of Asturias (ISPA-FINBA), University of Oviedo, Oviedo, Spain
- Institute of Oncology of Asturias (IUOPA), University of Oviedo, Oviedo, Spain
- Department of Organisms and Systems Biology (B.O.S.), University of Oviedo, Oviedo, Spain
- Biomedical Research Networking Center on Rare Diseases (CIBERER), Institute of Health Carlos III (ISCIII), Madrid, Spain
| | - Francisco Ponce
- Health Research Institute INCLIVA, Valencia, Spain
- Biomedical Research Networking Center for Physiopathology of Obesity and Nutrition (CIBEROBN), Institute of Health Carlos III (ISCIII), Madrid, Spain
| | - Nuria García Carbonell
- Health Research Institute INCLIVA, Valencia, Spain
- Servicio de Pediatría, Consorcio Hospital General Universitario de Valencia, Valencia, Spain
| | - Rafael Gómez Zafra
- Health Research Institute INCLIVA, Valencia, Spain
- Servicio de Pediatría, Consorcio Hospital General Universitario de Valencia, Valencia, Spain
| | - Agustín F Fernández
- Cancer Epigenetics and Nanomedicine Laboratory, Nanomaterials and Nanotechnology Research Center (CINN-CSIC), University of Oviedo, Oviedo, Spain
- Health Research Institute of Asturias (ISPA-FINBA), University of Oviedo, Oviedo, Spain
- Institute of Oncology of Asturias (IUOPA), University of Oviedo, Oviedo, Spain
- Department of Organisms and Systems Biology (B.O.S.), University of Oviedo, Oviedo, Spain
- Biomedical Research Networking Center on Rare Diseases (CIBERER), Institute of Health Carlos III (ISCIII), Madrid, Spain
| | - Mario F Fraga
- Cancer Epigenetics and Nanomedicine Laboratory, Nanomaterials and Nanotechnology Research Center (CINN-CSIC), University of Oviedo, Oviedo, Spain.
- Health Research Institute of Asturias (ISPA-FINBA), University of Oviedo, Oviedo, Spain.
- Institute of Oncology of Asturias (IUOPA), University of Oviedo, Oviedo, Spain.
- Department of Organisms and Systems Biology (B.O.S.), University of Oviedo, Oviedo, Spain.
- Biomedical Research Networking Center on Rare Diseases (CIBERER), Institute of Health Carlos III (ISCIII), Madrid, Spain.
| | - Empar Lurbe
- Health Research Institute INCLIVA, Valencia, Spain.
- Biomedical Research Networking Center for Physiopathology of Obesity and Nutrition (CIBEROBN), Institute of Health Carlos III (ISCIII), Madrid, Spain.
- Servicio de Pediatría, Consorcio Hospital General Universitario de Valencia, Valencia, Spain.
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14
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Chen L, Li Z, Wu H. CeDAR: incorporating cell type hierarchy improves cell type-specific differential analyses in bulk omics data. Genome Biol 2023; 24:37. [PMID: 36855165 PMCID: PMC9972684 DOI: 10.1186/s13059-023-02857-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 01/17/2023] [Indexed: 03/02/2023] Open
Abstract
Bulk high-throughput omics data contain signals from a mixture of cell types. Recent developments of deconvolution methods facilitate cell type-specific inferences from bulk data. Our real data exploration suggests that differential expression or methylation status is often correlated among cell types. Based on this observation, we develop a novel statistical method named CeDAR to incorporate the cell type hierarchy in cell type-specific differential analyses of bulk data. Extensive simulation and real data analyses demonstrate that this approach significantly improves the accuracy and power in detecting cell type-specific differential signals compared with existing methods, especially in low-abundance cell types.
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Affiliation(s)
- Luxiao Chen
- Department of Biostatistics and Bioinformatics, Emory University, GA 30322 Atlanta, USA
| | - Ziyi Li
- Department of Biostatistics, The University of MD Anderson Cancer Center, 77030 Houston, TX, USA
| | - Hao Wu
- Faculty of Computer Science and Control Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen University Town, Shenzhen, 518055 P.R. China
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15
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Raffington L, Schneper L, Mallard T, Fisher J, Vinnik L, Hollis-Hansen K, Notterman DA, Tucker-Drob EM, Mitchell C, Harden KP. Measuring the long arm of childhood in real-time: Epigenetic predictors of BMI and social determinants of health across childhood and adolescence. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.20.524709. [PMID: 36712110 PMCID: PMC9882281 DOI: 10.1101/2023.01.20.524709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Children who are socioeconomically disadvantaged are at increased risk for high body mass index (BMI) and multiple diseases in adulthood. The developmental origins of health and disease hypothesis proposes that early life conditions affect later-life health in a manner that is only partially modifiable by later-life experiences. Epigenetic mechanisms may regulate the influence of early life conditions on later life health. Recent epigenetic studies of adult blood samples have identified DNA-methylation sites associated with higher BMI and worse health (epigenetic-BMI). Here, we used longitudinal and twin study designs to examine whether epigenetic predictors of BMI developed in adults are valid biomarkers of child BMI and are sensitive to early life social determinants of health. Salivary epigenetic-BMI was calculated from two samples: (1) N=1,183 8-to-19-year-olds (609 female, mean age=13.4) from the Texas Twin Project (TTP), and (2) N=2,020 children (1,011 female) measured at 9 and 15 years from the Future of Families and Child Well-Being Study (FFCWS). We found that salivary epigenetic-BMI is robustly associated with children's BMI (r=0.36 to r=0.50). Longitudinal analysis suggested that epigenetic-BMI is highly stable across adolescence, but remains both a leading and lagging indicator of BMI change. Twin analyses showed that epigenetic-BMI captures differences in BMI between monozygotic twins. Moreover, children from more disadvantaged socioeconomic status (SES) and marginalized race/ethnic groups had higher epigenetic-BMI, even when controlling for concurrent BMI, pubertal development, and tobacco exposure. SES at birth relative to concurrent SES best predicted epigenetic-BMI in childhood and adolescence. We show for the first time that epigenetic predictors of BMI calculated from pediatric saliva samples are valid biomarkers of childhood BMI that are sensitive to social inequalities. Our findings are in line with the hypothesis that early life conditions are especially important factors in epigenetic regulation of later life health. Research showing that health later in life is linked to early life conditions have important implications for the development of early-life interventions that could significantly extend healthy life span.
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Affiliation(s)
- Laurel Raffington
- Max Planck Institute for Human Development, Max Planck Research Group Biosocial – Biology, Social Disparities, and Development, Lentzeallee 94, 14195 Berlin, Germany
- Population Research Center, The University of Texas at Austin, Austin, TX, USA
| | - Lisa Schneper
- Department of Molecular Biology, Princeton University, Princeton, NJ
| | - Travis Mallard
- Population Research Center, The University of Texas at Austin, Austin, TX, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Jonah Fisher
- Survey Research Center, University of Michigan, Ann Arbor, MI
| | - Liza Vinnik
- Population Research Center, The University of Texas at Austin, Austin, TX, USA
| | | | | | | | - Colter Mitchell
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Population Studies Center, University of Michigan, Ann Arbor, MI
| | - Kathryn P. Harden
- Population Research Center, The University of Texas at Austin, Austin, TX, USA
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16
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Joustra V, Li Yim AYF, Hageman I, Levin E, Adams A, Satsangi J, de Jonge WJ, Henneman P, D'Haens G. Long-term Temporal Stability of Peripheral Blood DNA Methylation Profiles in Patients With Inflammatory Bowel Disease. Cell Mol Gastroenterol Hepatol 2023; 15:869-885. [PMID: 36581079 PMCID: PMC9972576 DOI: 10.1016/j.jcmgh.2022.12.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 12/20/2022] [Accepted: 12/20/2022] [Indexed: 12/31/2022]
Abstract
BACKGROUND & AIMS There is great current interest in the potential application of DNA methylation alterations in peripheral blood leukocytes (PBLs) as biomarkers of susceptibility, progression, and treatment response in inflammatory bowel disease (IBD). However, the intra-individual stability of PBL methylation in IBD has not been characterized. Here, we studied the long-term stability of all probes located on the Illumina HumanMethylation EPIC BeadChip array. METHODS We followed a cohort of 46 adult patients with IBD (36 Crohn's disease [CD], 10 ulcerative colitis [UC]; median age, 44 years; interquartile range [IQR] 27-56 years; 50% female) that received standard care follow-up at the Amsterdam University Medical Centers. Paired PBL samples were collected at 2 time points with a median of 7 years (range, 2-9 years) in between. Differential methylation and intra-class correlation (ICC) analyses were used to identify time-associated differences and temporally stable CpGs, respectively. RESULTS Around 60% of all EPIC array loci presented poor intra-individual stability (ICC <0.50); 78.114 (≈9%) showed good (ICC, 0.75-0.89), and 41.274 (≈5%) showed excellent (ICC ≥0.90) stability, between both measured time points. Focusing on previously identified consistently differentially methylated positions indicated that 22 CD-, 11 UC-, and 24 IBD-associated loci demonstrated high stability (ICC ≥0.75) over time; of these, we observed a marked stability of CpG loci associated to the HLA genes. CONCLUSIONS Our data provide insight into the long-term stability of the PBL DNA methylome within an IBD context, facilitating the selection of biologically relevant and robust IBD-associated epigenetic biomarkers with increased potential for independent validation. These data also have potential implications in understanding disease pathogenesis.
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Affiliation(s)
- Vincent Joustra
- Department of Gastroenterology and Hepatology, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Andrew Y F Li Yim
- Genome Diagnostics Laboratory, Department of Human Genetics, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands; Tytgat Institute for Liver and Intestinal Research, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Ishtu Hageman
- Tytgat Institute for Liver and Intestinal Research, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Evgeni Levin
- Department of Vascular Medicine, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands; Horaizon BV, Delft, the Netherlands
| | - Alex Adams
- Oxford University- Hospitals NHS Foundation Trust- John Radcliffe Hospital, Translational Gastroenterology Unit- NIHR Oxford Biomedical Research Centre, Oxford, United Kingdom
| | - Jack Satsangi
- Oxford University- Hospitals NHS Foundation Trust- John Radcliffe Hospital, Translational Gastroenterology Unit- NIHR Oxford Biomedical Research Centre, Oxford, United Kingdom
| | - Wouter J de Jonge
- Tytgat Institute for Liver and Intestinal Research, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Peter Henneman
- Genome Diagnostics Laboratory, Department of Human Genetics, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Geert D'Haens
- Department of Gastroenterology and Hepatology, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
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17
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Wattacheril JJ, Raj S, Knowles DA, Greally JM. Using epigenomics to understand cellular responses to environmental influences in diseases. PLoS Genet 2023; 19:e1010567. [PMID: 36656803 PMCID: PMC9851565 DOI: 10.1371/journal.pgen.1010567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
It is a generally accepted model that environmental influences can exert their effects, at least in part, by changing the molecular regulators of transcription that are described as epigenetic. As there is biochemical evidence that some epigenetic regulators of transcription can maintain their states long term and through cell division, an epigenetic model encompasses the idea of maintenance of the effect of an exposure long after it is no longer present. The evidence supporting this model is mostly from the observation of alterations of molecular regulators of transcription following exposures. With the understanding that the interpretation of these associations is more complex than originally recognised, this model may be oversimplistic; therefore, adopting novel perspectives and experimental approaches when examining how environmental exposures are linked to phenotypes may prove worthwhile. In this review, we have chosen to use the example of nonalcoholic fatty liver disease (NAFLD), a common, complex human disease with strong environmental and genetic influences. We describe how epigenomic approaches combined with emerging functional genetic and single-cell genomic techniques are poised to generate new insights into the pathogenesis of environmentally influenced human disease phenotypes exemplified by NAFLD.
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Affiliation(s)
- Julia J. Wattacheril
- Department of Medicine, Center for Liver Disease and Transplantation, Columbia University Irving Medical Center, New York Presbyterian Hospital, New York, New York, United States of America
| | - Srilakshmi Raj
- Division of Genomics, Department of Genetics, Albert Einstein College of Medicine, Bronx, New York, United States of America
| | - David A. Knowles
- New York Genome Center, New York, New York, United States of America
- Department of Computer Science, Columbia University, New York, New York, United States of America
- Department of Systems Biology, Columbia University, New York, New York, United States of America
| | - John M. Greally
- Division of Genomics, Department of Genetics, Albert Einstein College of Medicine, Bronx, New York, United States of America
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18
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Holliday KM, Gondalia R, Baldassari A, Justice AE, Stewart JD, Liao D, Yanosky JD, Jordahl KM, Bhatti P, Assimes TL, Pankow JS, Guan W, Fornage M, Bressler J, North KE, Conneely KN, Li Y, Hou L, Vokonas PS, Ward-Caviness CK, Wilson R, Wolf K, Waldenberger M, Cyrys J, Peters A, Boezen HM, Vonk JM, Sayols-Baixeras S, Lee M, Baccarelli AA, Whitsel EA. Gaseous air pollutants and DNA methylation in a methylome-wide association study of an ethnically and environmentally diverse population of U.S. adults. ENVIRONMENTAL RESEARCH 2022; 212:113360. [PMID: 35500859 PMCID: PMC9354583 DOI: 10.1016/j.envres.2022.113360] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 04/18/2022] [Accepted: 04/20/2022] [Indexed: 06/03/2023]
Abstract
Epigenetic mechanisms may underlie air pollution-health outcome associations. We estimated gaseous air pollutant-DNA methylation (DNAm) associations using twelve subpopulations within Women's Health Initiative (WHI) and Atherosclerosis Risk in Communities (ARIC) cohorts (n = 8397; mean age 61.3 years; 83% female; 46% African-American, 46% European-American, 8% Hispanic/Latino). We used geocoded participant address-specific mean ambient carbon monoxide (CO), nitrogen oxides (NO2; NOx), ozone (O3), and sulfur dioxide (SO2) concentrations estimated over the 2-, 7-, 28-, and 365-day periods before collection of blood samples used to generate Illumina 450 k array leukocyte DNAm measurements. We estimated methylome-wide, subpopulation- and race/ethnicity-stratified pollutant-DNAm associations in multi-level, linear mixed-effects models adjusted for sociodemographic, behavioral, meteorological, and technical covariates. We combined stratum-specific estimates in inverse variance-weighted meta-analyses and characterized significant associations (false discovery rate; FDR<0.05) at Cytosine-phosphate-Guanine (CpG) sites without among-strata heterogeneity (PCochran's Q > 0.05). We attempted replication in the Cooperative Health Research in Region of Augsburg (KORA) study and Normative Aging Study (NAS). We observed a -0.3 (95% CI: -0.4, -0.2) unit decrease in percent DNAm per interquartile range (IQR, 7.3 ppb) increase in 28-day mean NO2 concentration at cg01885635 (chromosome 3; regulatory region 290 bp upstream from ZNF621; FDR = 0.03). At intragenic sites cg21849932 (chromosome 20; LIME1; intron 3) and cg05353869 (chromosome 11; KLHL35; exon 2), we observed a -0.3 (95% CI: -0.4, -0.2) unit decrease (FDR = 0.04) and a 1.2 (95% CI: 0.7, 1.7) unit increase (FDR = 0.04), respectively, in percent DNAm per IQR (17.6 ppb) increase in 7-day mean ozone concentration. Results were not fully replicated in KORA and NAS. We identified three CpG sites potentially susceptible to gaseous air pollution-induced DNAm changes near genes relevant for cardiovascular and lung disease. Further harmonized investigations with a range of gaseous pollutants and averaging durations are needed to determine the effect of gaseous air pollutants on DNA methylation and ultimately gene expression.
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Affiliation(s)
- Katelyn M Holliday
- Department of Family Medicine and Community Health, School of Medicine, Duke University, Durham, NC, USA; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
| | - Rahul Gondalia
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Antoine Baldassari
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | | | - James D Stewart
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Duanping Liao
- Division of Epidemiology, Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Jeff D Yanosky
- Division of Epidemiology, Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Kristina M Jordahl
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - Parveen Bhatti
- Cancer Control Research, BC Cancer, Vancouver, BC, Canada
| | | | - James S Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | - Weihua Guan
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA; Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jan Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Karen N Conneely
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Yun Li
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA; Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University Chicago, Evanston, IL, USA; Center for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University Chicago, Evanston, IL, USA
| | - Pantel S Vokonas
- VA Normative Aging Study, VA Boston Healthcare System, Schools of Medicine and Public Health, Boston University, Boston, MA, USA
| | - Cavin K Ward-Caviness
- Environmental Public Health Division, National Health and Environmental Effects Research Laboratory, 104 Mason Farm Rd, Chapel Hill, NC, 27514, USA
| | - Rory Wilson
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany; Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Kathrin Wolf
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany; Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Josef Cyrys
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany; Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig Maximilians University, Munich, Germany
| | - H Marike Boezen
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, the Netherlands; University of Groningen, University Medical Center Groningen, GRIAC Research Institute, the Netherlands
| | - Judith M Vonk
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, the Netherlands; University of Groningen, University Medical Center Groningen, GRIAC Research Institute, the Netherlands
| | - Sergi Sayols-Baixeras
- Cardiovascular Epidemiology and Genetics Research Group, Hospital Del Mar Medical Research Institute (IMIM), Campus Del Mar, Universitat Pompeu Fabra, Barcelona, Spain; Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Molecular Epidemiology and Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Mikyeong Lee
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Andrea A Baccarelli
- Laboratory of Environmental Epigenetics, Departments of Environmental Health Sciences and Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
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19
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Chilunga FP, Meeks KAC, Henneman P, Agyemang C, Doumatey AP, Rotimi CN, Adeyemo AA. An epigenome-wide association study of insulin resistance in African Americans. Clin Epigenetics 2022; 14:88. [PMID: 35836279 PMCID: PMC9281172 DOI: 10.1186/s13148-022-01309-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 07/04/2022] [Indexed: 11/18/2022] Open
Abstract
Background African Americans have a high risk for type 2 diabetes (T2D) and insulin resistance. Studies among other population groups have identified DNA methylation loci associated with insulin resistance, but data in African Americans are lacking. Using DNA methylation profiles of blood samples obtained from the Illumina Infinium® HumanMethylation450 BeadChip, we performed an epigenome-wide association study to identify DNA methylation loci associated with insulin resistance among 136 non-diabetic, unrelated African American men (mean age 41.6 years) from the Howard University Family Study. Results We identified three differentially methylated positions (DMPs) for homeostatic model assessment of insulin resistance (HOMA-IR) at 5% FDR. One DMP (cg14013695, HOXA5) is a known locus among Mexican Americans, while the other two DMPs are novel—cg00456326 (OSR1; beta = 0.027) and cg20259981 (ST18; beta = 0.010). Although the cg00456326 DMP is novel, the OSR1 gene has previously been found associated with both insulin resistance and T2D in Europeans. The genes HOXA5 and ST18 have been implicated in biological processes relevant to insulin resistance. Differential methylation at the significant HOXA5 and OSR1 DMPs is associated with differences in gene expression in the iMETHYL database. Analysis of differentially methylated regions (DMRs) did not identify any epigenome-wide DMRs for HOMA-IR. We tested transferability of HOMA-IR associated DMPs from five previous EWAS in Mexican Americans, Indian Asians, Europeans, and European ancestry Americans. Out of the 730 previously reported HOMA-IR DMPs, 47 (6.4%) were associated with HOMA-IR in this cohort of African Americans. Conclusions The findings from our study suggest substantial differences in DNA methylation patterns associated with insulin resistance across populations. Two of the DMPs we identified in African Americans have not been reported in other populations, and we found low transferability of HOMA-IR DMPs reported in other populations in African Americans. More work in African-ancestry populations is needed to confirm our findings as well as functional analyses to understand how such DNA methylation alterations contribute to T2D pathology. Supplementary Information The online version contains supplementary material available at 10.1186/s13148-022-01309-4.
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Affiliation(s)
- Felix P Chilunga
- Department of Public & Occupational Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Karlijn A C Meeks
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Peter Henneman
- Department of Human Genetics, Amsterdam Reproduction & Development Research Institute, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Charles Agyemang
- Department of Public & Occupational Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Ayo P Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Adebowale A Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
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20
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Lee Y, Riskedal E, Kalleberg KT, Istre M, Lind A, Lund-Johansen F, Reiakvam O, Søraas AVL, Harris JR, Dahl JA, Hadley CL, Jugessur A. EWAS of post-COVID-19 patients shows methylation differences in the immune-response associated gene, IFI44L, three months after COVID-19 infection. Sci Rep 2022; 12:11478. [PMID: 35798818 PMCID: PMC9261254 DOI: 10.1038/s41598-022-15467-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 06/23/2022] [Indexed: 11/24/2022] Open
Abstract
Although substantial progress has been made in managing COVID-19, it is still difficult to predict a patient’s prognosis. We explored the epigenetic signatures of COVID-19 in peripheral blood using data from an ongoing prospective observational study of COVID-19 called the Norwegian Corona Cohort Study. A series of EWASs were performed to compare the DNA methylation profiles between COVID-19 cases and controls three months post-infection. We also investigated differences associated with severity and long-COVID. Three CpGs—cg22399236, cg03607951, and cg09829636—were significantly hypomethylated (FDR < 0.05) in COVID-19 positive individuals. cg03607951 is located in IFI44L which is involved in innate response to viral infection and several systemic autoimmune diseases. cg09829636 is located in ANKRD9, a gene implicated in a wide variety of cellular processes, including the degradation of IMPDH2. The link between ANKRD9 and IMPDH2 is striking given that IMPDHs are considered therapeutic targets for COVID-19. Furthermore, gene ontology analyses revealed pathways involved in response to viruses. The lack of significant differences associated with severity and long-COVID may be real or reflect limitations in sample size. Our findings support the involvement of interferon responsive genes in the pathophysiology of COVID-19 and indicate a possible link to systemic autoimmune diseases.
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Affiliation(s)
- Yunsung Lee
- Centre for Fertility and Health, Norwegian Institute of Public Health, Skøyen, P.O. box 222, 0213, Oslo, Norway
| | | | | | - Mette Istre
- Department of Microbiology, Oslo University Hospital Rikshospitalet, 0372, Oslo, Norway
| | - Andreas Lind
- Department of Microbiology, Oslo University Hospital Ullevaal, 0372, Oslo, Norway
| | | | - Olaug Reiakvam
- Department of Microbiology, Oslo University Hospital Rikshospitalet, 0372, Oslo, Norway
| | - Arne V L Søraas
- Department of Microbiology, Oslo University Hospital Rikshospitalet, 0372, Oslo, Norway
| | - Jennifer R Harris
- Centre for Fertility and Health, Norwegian Institute of Public Health, Skøyen, P.O. box 222, 0213, Oslo, Norway
| | - John Arne Dahl
- Department of Microbiology, Oslo University Hospital Rikshospitalet, 0372, Oslo, Norway
| | | | - Astanand Jugessur
- Centre for Fertility and Health, Norwegian Institute of Public Health, Skøyen, P.O. box 222, 0213, Oslo, Norway.,Department of Global Public Health and Primary Care, University of Bergen, P.O. box 7804, 5020, Bergen, Norway
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21
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Mannens MMAM, Lombardi MP, Alders M, Henneman P, Bliek J. Further Introduction of DNA Methylation (DNAm) Arrays in Regular Diagnostics. Front Genet 2022; 13:831452. [PMID: 35860466 PMCID: PMC9289263 DOI: 10.3389/fgene.2022.831452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 06/08/2022] [Indexed: 12/01/2022] Open
Abstract
Methylation tests have been used for decades in regular DNA diagnostics focusing primarily on Imprinting disorders or specific loci annotated to specific disease associated gene promotors. With the introduction of DNA methylation (DNAm) arrays such as the Illumina Infinium HumanMethylation450 Beadchip array or the Illumina Infinium Methylation EPIC Beadchip array (850 k), it has become feasible to study the epigenome in a timely and cost-effective way. This has led to new insights regarding the complexity of well-studied imprinting disorders such as the Beckwith Wiedemann syndrome, but it has also led to the introduction of tests such as EpiSign, implemented as a diagnostic test in which a single array experiment can be compared to databases with known episignatures of multiple genetic disorders, especially neurodevelopmental disorders. The successful use of such DNAm tests is rapidly expanding. More and more disorders are found to be associated with discrete episignatures which enables fast and definite diagnoses, as we have shown. The first examples of environmentally induced clinical disorders characterized by discrete aberrant DNAm are discussed underlining the broad application of DNAm testing in regular diagnostics. Here we discuss exemplary findings in our laboratory covering this broad range of applications and we discuss further use of DNAm tests in the near future.
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22
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Mehrgou A, Teimourian S. Update of gene expression/methylation and MiRNA profiling in colorectal cancer; application in diagnosis, prognosis, and targeted therapy. PLoS One 2022; 17:e0265527. [PMID: 35333898 PMCID: PMC8956198 DOI: 10.1371/journal.pone.0265527] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 03/02/2022] [Indexed: 01/22/2023] Open
Abstract
Background
Colorectal cancer is one of the most deadliest malignancies worldwide. Due to the dearth of appropriate biomarkers, the diagnosis of this mortal disease is usually deferred, in its turn, culminating in the failure of prevention. By the same token, proper biomarkers are at play in determining the quality of prognosis. In other words, the survival rate is contingent upon the regulation of such biomarkers.
Materials and methods
The information regarding expression (GSE41258, and GSE31905), methylation (GSE101764), and miRNA (dbDEMC) were downloaded. MEXPRESS and GEPIA confirmed the validated differentially expressed/methylated genes using TCGA data. Taking advantage of the correlation plots and receiver-operating-characteristic (ROC) curves, expression and methylation profiles were compared. The interactions between validated differentially expressed genes and differentially expressed miRNA were recognized and visualized by miRTarBase and Cytoscape, respectively. Then, the protein-protein interaction (PPI) network and hub genes were established via STRING and Cytohubba plugin. Utilizing R packages (DOSE, Enrichplot, and clusterProfiler) and DAVID database, the Functional Enrichment analysis and the detection of KEGG pathways were performed. Ultimately, in order to recognize the prognostic value of found biomarkers, they were evaluated through drawing survival plots for CRC patients.
Results
In this research, we found an expression profile (with 13 novel genes), a methylation profile (with two novel genes), and a miRNA profile with diagnostic value. Concerning diagnosis, the expression profile was evaluated more powerful in comparison with the methylation profile. Furthermore, a prognosis-related expression profile was detected.
Conclusion
In addition to diagnostic- and prognostic-applicability, the discerned profiles can assist in targeted therapy and current therapeutic strategies.
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Affiliation(s)
- Amir Mehrgou
- Department of Medical Genetics and Molecular Biology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Shahram Teimourian
- Department of Medical Genetics, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
- * E-mail:
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23
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Zhang Z, Zeng C, Zhang W. Characterization of the Illumina EPIC Array for Optimal Applications in Epigenetic Research Targeting Diverse Human Populations. EPIGENETICS COMMUNICATIONS 2022; 2:7. [PMCID: PMC9718568 DOI: 10.1186/s43682-022-00015-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
The Illumina EPIC array is widely used for high-throughput profiling of DNA cytosine modifications in human samples, covering more than 850,000 modification sites across various genomic features. The application of this platform is expected to provide novel insights into the epigenetic contribution to human complex traits and diseases. Considering the diverse inter-population genetic and epigenetic variation, it will benefit the research community with a comprehensive characterization of this platform for its applicability to major global populations. Specifically, we mapped 866,836 CpG probes from the EPIC array to the human genome reference. We detected 91,034 CpG probes that did not align reliably to the human genome reference. In addition, 21,256 CpG probes were found to ambiguously map to multiple loci in the human genome, and 448 probes showing inaccurate genomic information from the original Illumina annotations. We further characterized those uniquely mapped CpG probes in terms of whether they contained common genetic variants, i.e., single nucleotide polymorphisms (SNPs), in major global populations, by utilizing the 1000 Genomes Project data. A list of optimal CpG probes on the EPIC array was generated for major global populations, with the aim of providing a resource to facilitate future studies of diverse human populations. In conclusion, our analysis indicated that studies of diverse human populations using the EPIC array would be benefited by taking into account of the technical features of this platform.
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Affiliation(s)
- Zhou Zhang
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois 60611, USA
| | - Chang Zeng
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois 60611, USA
| | - Wei Zhang
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois 60611, USA.,The Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois 60611, USA
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24
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Lee RS, Zandi PP, Lin Y, Seifuddin F, Benke KS, McCaul ME, Reitz K, Wand GS. Methylomic and transcriptomic predictors of one-month exposure to cortisol in healthy individuals. Stress 2021; 24:840-848. [PMID: 34279166 DOI: 10.1080/10253890.2021.1946509] [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] [Indexed: 10/20/2022] Open
Abstract
Allostatic load (AL) refers to the cumulative "wear and tear" on an organism throughout its lifetime. One of the primary contributing factors to AL is prolonged exposure to stress or its primary catabolic agent cortisol. Chronic exposure to stress or cortisol is associated with numerous diseases, including cardiovascular disease, metabolic disorders, and psychiatric disorders. Therefore, a molecular marker capable of integrating a past history of cortisol exposure would be of great utility for assessing disease risk. To this end, we recruited 87 healthy males and females of European ancestry between 18 and 60 years old, extracted genomic DNA and RNA from leukocytes, and implemented a gene-centric DNA enrichment method coupled with bisulfite sequencing and RNA-Seq of total RNA for the determination of genome-wide methylation and gene transcription, respectively. Sequencing data were analyzed against awakening and bedtime cortisol data to identify differentially methylated regions (DMRs) and CpGs (DMCs) and differentially expressed genes (DEGs). Six candidate DMCs (punadjusted < 0.005) and nine DEGs (punadjusted < 0.0005) were used to construct a prediction model that could capture past 30+ days of both bedtime and awakening cortisol levels. Utilizing a cross-validation approach, we obtained a regression coefficient of R2 = 0.308 for predicting continuous awakening cortisol and an area under the curve (AUC) = 0.753 for dichotomous (high vs. low tertile) awakening cortisol, and R2 = 0.224 and AUC = 0.723 for continuous and dichotomous bedtime cortisol levels, respectively. To our knowledge, the current study represents the first attempt to identify genome-wide predictors of cortisol exposure that utilizes both methylation and transcription targets. The utility of our approach needs to be replicated in an independent cohort of samples for which similar cortisol metrics are available.
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Affiliation(s)
- Richard S Lee
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Peter P Zandi
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Yian Lin
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Fayaz Seifuddin
- Bioinformatics and Computational Biology Core, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Kelly S Benke
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Mary E McCaul
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Kendall Reitz
- Department of and Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Gary S Wand
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of and Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
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25
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Planterose Jiménez B, Kayser M, Vidaki A. Revisiting genetic artifacts on DNA methylation microarrays exposes novel biological implications. Genome Biol 2021; 22:274. [PMID: 34548083 PMCID: PMC8454075 DOI: 10.1186/s13059-021-02484-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 09/01/2021] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Illumina DNA methylation microarrays enable epigenome-wide analysis vastly used for the discovery of novel DNA methylation variation in health and disease. However, the microarrays' probe design cannot fully consider the vast human genetic diversity, leading to genetic artifacts. Distinguishing genuine from artifactual genetic influence is of particular relevance in the study of DNA methylation heritability and methylation quantitative trait loci. But despite its importance, current strategies to account for genetic artifacts are lagging due to a limited mechanistic understanding on how such artifacts operate. RESULTS To address this, we develop and benchmark UMtools, an R-package containing novel methods for the quantification and qualification of genetic artifacts based on fluorescence intensity signals. With our approach, we model and validate known SNPs/indels on a genetically controlled dataset of monozygotic twins, and we estimate minor allele frequency from DNA methylation data and empirically detect variants not included in dbSNP. Moreover, we identify examples where genetic artifacts interact with each other or with imprinting, X-inactivation, or tissue-specific regulation. Finally, we propose a novel strategy based on co-methylation that can discern between genetic artifacts and genuine genomic influence. CONCLUSIONS We provide an atlas to navigate through the huge diversity of genetic artifacts encountered on DNA methylation microarrays. Overall, our study sets the ground for a paradigm shift in the study of the genetic component of epigenetic variation in DNA methylation microarrays.
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Affiliation(s)
- Benjamin Planterose Jiménez
- Erasmus MC, University Medical Center Rotterdam, Department of Genetic Identification, Rotterdam, the Netherlands
| | - Manfred Kayser
- Erasmus MC, University Medical Center Rotterdam, Department of Genetic Identification, Rotterdam, the Netherlands
| | - Athina Vidaki
- Erasmus MC, University Medical Center Rotterdam, Department of Genetic Identification, Rotterdam, the Netherlands
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26
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Seiler Vellame D, Castanho I, Dahir A, Mill J, Hannon E. Characterizing the properties of bisulfite sequencing data: maximizing power and sensitivity to identify between-group differences in DNA methylation. BMC Genomics 2021; 22:446. [PMID: 34126923 PMCID: PMC8204428 DOI: 10.1186/s12864-021-07721-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 05/13/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The combination of sodium bisulfite treatment with highly-parallel sequencing is a common method for quantifying DNA methylation across the genome. The power to detect between-group differences in DNA methylation using bisulfite-sequencing approaches is influenced by both experimental (e.g. read depth, missing data and sample size) and biological (e.g. mean level of DNA methylation and difference between groups) parameters. There is, however, no consensus about the optimal thresholds for filtering bisulfite sequencing data with implications for the reproducibility of findings in epigenetic epidemiology. RESULTS We used a large reduced representation bisulfite sequencing (RRBS) dataset to assess the distribution of read depth across DNA methylation sites and the extent of missing data. To investigate how various study variables influence power to identify DNA methylation differences between groups, we developed a framework for simulating bisulfite sequencing data. As expected, sequencing read depth, group size, and the magnitude of DNA methylation difference between groups all impacted upon statistical power. The influence on power was not dependent on one specific parameter, but reflected the combination of study-specific variables. As a resource to the community, we have developed a tool, POWEREDBiSeq, which utilizes our simulation framework to predict study-specific power for the identification of DNAm differences between groups, taking into account user-defined read depth filtering parameters and the minimum sample size per group. CONCLUSIONS Our data-driven approach highlights the importance of filtering bisulfite-sequencing data by minimum read depth and illustrates how the choice of threshold is influenced by the specific study design and the expected differences between groups being compared. The POWEREDBiSeq tool, which can be applied to different types of bisulfite sequencing data (e.g. RRBS, whole genome bisulfite sequencing (WGBS), targeted bisulfite sequencing and amplicon-based bisulfite sequencing), can help users identify the level of data filtering needed to optimize power and aims to improve the reproducibility of bisulfite sequencing studies.
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Affiliation(s)
- Dorothea Seiler Vellame
- College of Medicine and Health, University of Exeter, Royal Devon and Exeter Hospital, Exeter, EX2 5DW, UK.
| | - Isabel Castanho
- College of Medicine and Health, University of Exeter, Royal Devon and Exeter Hospital, Exeter, EX2 5DW, UK
- Department of Pathology, Beth Israel Deaconess Medical Center, 330 Brookline-Avenue, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Aisha Dahir
- College of Medicine and Health, University of Exeter, Royal Devon and Exeter Hospital, Exeter, EX2 5DW, UK
| | - Jonathan Mill
- College of Medicine and Health, University of Exeter, Royal Devon and Exeter Hospital, Exeter, EX2 5DW, UK.
| | - Eilis Hannon
- College of Medicine and Health, University of Exeter, Royal Devon and Exeter Hospital, Exeter, EX2 5DW, UK.
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27
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Chilunga FP, Henneman P, Venema A, Meeks KAC, Requena-Méndez A, Beune E, Mockenhaupt FP, Smeeth L, Bahendeka S, Danquah I, Klipstein-Grobusch K, Adeyemo A, Mannens MMAM, Agyemang C. Genome-wide DNA methylation analysis on C-reactive protein among Ghanaians suggests molecular links to the emerging risk of cardiovascular diseases. NPJ Genom Med 2021; 6:46. [PMID: 34117263 PMCID: PMC8196035 DOI: 10.1038/s41525-021-00213-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 05/20/2021] [Indexed: 12/28/2022] Open
Abstract
Molecular mechanisms at the intersection of inflammation and cardiovascular diseases (CVD) among Africans are still unknown. We performed an epigenome-wide association study to identify loci associated with serum C-reactive protein (marker of inflammation) among Ghanaians and further assessed whether differentially methylated positions (DMPs) were linked to CVD in previous reports, or to estimated CVD risk in the same population. We used the Illumina Infinium® HumanMethylation450 BeadChip to obtain DNAm profiles of blood samples in 589 Ghanaians from the RODAM study (without acute infections, not taking anti-inflammatory medications, CRP levels < 40 mg/L). We then used linear models to identify DMPs associated with CRP concentrations. Post-hoc, we evaluated associations of identified DMPs with elevated CVD risk estimated via ASCVD risk score. We also performed subset analyses at CRP levels ≤10 mg/L and replication analyses on candidate probes. Finally, we assessed for biological relevance of our findings in public databases. We subsequently identified 14 novel DMPs associated with CRP. In post-hoc evaluations, we found that DMPs in PC, BTG4 and PADI1 showed trends of associations with estimated CVD risk, we identified a separate DMP in MORC2 that was associated with CRP levels ≤10 mg/L, and we successfully replicated 65 (24%) of previously reported DMPs. All DMPs with gene annotations (13) were biologically linked to inflammation or CVD traits. We have identified epigenetic loci that may play a role in the intersection between inflammation and CVD among Ghanaians. Further studies among other Africans are needed to confirm our findings.
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Affiliation(s)
- Felix P Chilunga
- Department of Public Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands.
| | - Peter Henneman
- Department of Clinical Genetics, Amsterdam Reproduction & Development research institute, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Andrea Venema
- Department of Clinical Genetics, Amsterdam Reproduction & Development research institute, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Karlijn A C Meeks
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ana Requena-Méndez
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Department of Global Public Health, Karolinska Institutet, Solna, Sweden
| | - Erik Beune
- Department of Public Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Frank P Mockenhaupt
- Institute of Tropical Medicine and International Health, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Liam Smeeth
- Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Silver Bahendeka
- Department of Medicine, MKPGMS-Uganda Martyrs University, Kampala, Uganda
| | - Ina Danquah
- Heidelberg Institute of Global Health (HIGH), Universitätsklinikum Heidelberg, Heidelberg, Germany
| | - Kerstin Klipstein-Grobusch
- Julius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Division of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Marcel M A M Mannens
- Department of Clinical Genetics, Amsterdam Reproduction & Development research institute, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Charles Agyemang
- Department of Public Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
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28
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Chilunga FP, Henneman P, Venema A, Meeks KAC, Gonzalez JR, Ruiz-Arenas C, Requena-Méndez A, Beune E, Spranger J, Smeeth L, Bahendeka S, Owusu-Dabo E, Klipstein-Grobusch K, Adeyemo A, Mannens MMAM, Agyemang C. DNA methylation as the link between migration and the major noncommunicable diseases: the RODAM study. Epigenomics 2021; 13:653-666. [PMID: 33890479 PMCID: PMC8173498 DOI: 10.2217/epi-2020-0329] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 03/29/2021] [Indexed: 01/19/2023] Open
Abstract
Aim: We assessed epigenome-wide DNA methylation (DNAm) differences between migrant and non-migrant Ghanaians. Materials & methods: We used the Illumina Infinium® HumanMethylation450 BeadChip to profile DNAm of 712 Ghanaians in whole blood. We used linear models to detect differentially methylated positions (DMPs) associated with migration. We performed multiple post hoc analyses to validate our findings. Results: We identified 13 DMPs associated with migration (delta-beta values: 0.2-4.5%). Seven DMPs in CPLX2, EIF4E3, MEF2D, TLX3, ST8SIA1, ANG and CHRM3 were independent of extrinsic genomic influences in public databases. Two DMPs in NLRC5 were associated with duration of stay in Europe among migrants. All DMPs were biologically linked to migration-related factors. Conclusion: Our findings provide the first insights into DNAm differences between migrants and non-migrants.
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Affiliation(s)
- Felix P Chilunga
- Department of Public Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands
| | - Peter Henneman
- Department of Clinical Genetics, Amsterdam Reproduction & Development Research Institute, Amsterdam University Medical Centers, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands
| | - Andrea Venema
- Department of Clinical Genetics, Amsterdam Reproduction & Development Research Institute, Amsterdam University Medical Centers, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands
| | - Karlijn AC Meeks
- Center for Research on Genomics & Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20894, USA
| | - Juan R Gonzalez
- Barcelona Institute for Global Health (ISGlobal, University of Barcelona), 08003 Barcelona, Spain
| | - Carlos Ruiz-Arenas
- Barcelona Institute for Global Health (ISGlobal, University of Barcelona), 08003 Barcelona, Spain
| | - Ana Requena-Méndez
- Barcelona Institute for Global Health (ISGlobal, University of Barcelona), 08003 Barcelona, Spain
- Department of Global Public Health, Karolinska Institutet, SE-171 77 Stockholm, Sweden
| | - Erik Beune
- Department of Public Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands
| | - Joachim Spranger
- Department of Endocrinology, Diabetes & Metabolism, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Liam Smeeth
- Department of Non-communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, 1E 7HT, UK
| | - Silver Bahendeka
- Department of Medicine, MKPGMS-Uganda Martyrs University, 8H33+5M Kampala, Uganda
| | - Ellis Owusu-Dabo
- School of Public Health, Kwame Nkrumah University of Science & Technology, MCFH+R9 Kumasi, Ghana
| | - Kerstin Klipstein-Grobusch
- Julius Global Health, Julius Center for Health Sciences & Primary Care, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, The Netherlands
- Division of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences, University of The Witwatersrand, 2193 Johannesburg, South Africa
| | - Adebowale Adeyemo
- Center for Research on Genomics & Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20894, USA
| | - Marcel MAM Mannens
- Department of Clinical Genetics, Amsterdam Reproduction & Development Research Institute, Amsterdam University Medical Centers, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands
| | - Charles Agyemang
- Department of Public Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands
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29
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Zhang M, Xi Z, Saez-Atienzar S, Chia R, Moreno D, Sato C, Montazer Haghighi M, Traynor BJ, Zinman L, Rogaeva E. Combined epigenetic/genetic study identified an ALS age of onset modifier. Acta Neuropathol Commun 2021; 9:75. [PMID: 33892821 PMCID: PMC8066440 DOI: 10.1186/s40478-021-01183-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 04/14/2021] [Indexed: 12/16/2022] Open
Abstract
Age at onset of amyotrophic lateral sclerosis (ALS) is highly variable (eg, 27-74 years in carriers of the G4C2-expansion in C9orf72). It might be influenced by environmental and genetic factors via the modulation of DNA methylation (DNAm) at CpG-sites. Hence, we combined an epigenetic and genetic approach to test the hypothesis that some common single nucleotide polymorphisms (SNPs) at CpG-sites (CpG-SNPs) could modify ALS age of onset. Our genome-wide DNAm analysis suggested three CpG-SNPs whose DNAm levels are significantly associated with age of onset in 249 ALS patients (q < 0.05). Next, genetic analysis validated the association of rs4970944 with age of onset in the discovery (n = 469; P = 0.025) and replication (n = 4160; P = 0.007) ALS cohorts. A meta-analysis of the cohorts combined showed that the median onset in AA-carriers is two years later than in GG-carriers (n = 4629; P = 0.0012). A similar association was observed with its tagging SNPs, implicating a 16 Kb region at the 1q21.3 locus as a modifier of ALS age of onset. Notably, rs4970944 genotypes are also associated with age of onset in C9orf72-carriers (n = 333; P = 0.025), suggesting that each A-allele delays onset by 1.6 years. Analysis of Genotype-Tissue Expression data revealed that the protective A-allele is linked with the reduced expression of CTSS in cerebellum (P = 0.00018), which is a critical brain region in the distributed neural circuits subserving motor control. CTSS encodes cathepsin S protein playing a key role in antigen presentation. In conclusion, we identified a 16 Kb locus tagged by rs4970944 as a modifier of ALS age of onset. Our findings support the role of antigen presenting processes in modulating age of onset of ALS and suggest potential drug targets (eg, CTSS). Future replication studies are encouraged to validate the link between the locus tagged by rs4970944 and age of onset in independent ALS cohorts, including different ethnic groups.
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Affiliation(s)
- Ming Zhang
- Shanghai First Rehabilitation Hospital, School of Medicine, Tongji University, Shanghai, 200090, China.
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, 60 Leonard Ave., Toronto, ON, M5T 0S8, Canada.
- Clinical Center for Brain and Spinal Cord Research, Tongji University, Shanghai, 200092, China.
- Institute for Advanced Study, Tongji University, Shanghai, China.
| | - Zhengrui Xi
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, 60 Leonard Ave., Toronto, ON, M5T 0S8, Canada
| | - Sara Saez-Atienzar
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Ruth Chia
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Danielle Moreno
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, 60 Leonard Ave., Toronto, ON, M5T 0S8, Canada
| | - Christine Sato
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, 60 Leonard Ave., Toronto, ON, M5T 0S8, Canada
| | - Mahdi Montazer Haghighi
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, 60 Leonard Ave., Toronto, ON, M5T 0S8, Canada
| | - Bryan J Traynor
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Lorne Zinman
- Sunnybrook Health Sciences Centre, 2075 Bayview Ave, Toronto, ON, M4N 3M5, Canada
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, Canada
| | - Ekaterina Rogaeva
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, 60 Leonard Ave., Toronto, ON, M5T 0S8, Canada.
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, Canada.
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30
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Hop PJ, Zwamborn RAJ, Hannon EJ, Dekker AM, van Eijk K, Walker E, Iacoangeli A, Jones A, Shatunov A, Khleifat AA, Opie-Martin S, Shaw C, Morrison K, Shaw P, McLaughlin R, Hardiman O, Al-Chalabi A, Van Den Berg L, Mill J, Veldink JH. Cross-reactive probes on Illumina DNA methylation arrays: a large study on ALS shows that a cautionary approach is warranted in interpreting epigenome-wide association studies. NAR Genom Bioinform 2020; 2:lqaa105. [PMID: 33554115 PMCID: PMC7745769 DOI: 10.1093/nargab/lqaa105] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 10/27/2020] [Accepted: 11/25/2020] [Indexed: 12/11/2022] Open
Abstract
Illumina DNA methylation arrays are a widely used tool for performing genome-wide DNA methylation analyses. However, measurements obtained from these arrays may be affected by technical artefacts that result in spurious associations if left unchecked. Cross-reactivity represents one of the major challenges, meaning that probes may map to multiple regions in the genome. Although several studies have reported on this issue, few studies have empirically examined the impact of cross-reactivity in an epigenome-wide association study (EWAS). In this paper, we report on cross-reactivity issues that we discovered in a large EWAS on the presence of the C9orf72 repeat expansion in ALS patients. Specifically, we found that that the majority of the significant probes inadvertently cross-hybridized to the C9orf72 locus. Importantly, these probes were not flagged as cross-reactive in previous studies, leading to novel insights into the extent to which cross-reactivity can impact EWAS. Our findings are particularly relevant for epigenetic studies into diseases associated with repeat expansions and other types of structural variation. More generally however, considering that most spurious associations were not excluded based on pre-defined sets of cross-reactive probes, we believe that the presented data-driven flag and consider approach is relevant for any type of EWAS.
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Affiliation(s)
- Paul J Hop
- Department of Neurology, UMC Utrecht Brain Center, 3584 CG, Utrecht, the Netherlands
| | - Ramona A J Zwamborn
- Department of Neurology, UMC Utrecht Brain Center, 3584 CG, Utrecht, the Netherlands
| | - Eilis J Hannon
- University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK
| | - Annelot M Dekker
- Department of Neurology, UMC Utrecht Brain Center, 3584 CG, Utrecht, the Netherlands
| | - Kristel R van Eijk
- Department of Neurology, UMC Utrecht Brain Center, 3584 CG, Utrecht, the Netherlands
| | - Emma M Walker
- University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK
| | - Alfredo Iacoangeli
- Department of Basic and Clinical Neuroscience, King’s College London, Maurice Wohl Clinical Neuroscience Institute, London SE5 9RS, UK
- Department of Biostatistics and Health Informatics, King’s College London, London SE5 8AF, UK
| | - Ashley R Jones
- Department of Basic and Clinical Neuroscience, King’s College London, Maurice Wohl Clinical Neuroscience Institute, London SE5 9RS, UK
| | - Aleksey Shatunov
- Department of Basic and Clinical Neuroscience, King’s College London, Maurice Wohl Clinical Neuroscience Institute, London SE5 9RS, UK
| | - Ahmad Al Khleifat
- Department of Basic and Clinical Neuroscience, King’s College London, Maurice Wohl Clinical Neuroscience Institute, London SE5 9RS, UK
| | - Sarah Opie-Martin
- Department of Basic and Clinical Neuroscience, King’s College London, Maurice Wohl Clinical Neuroscience Institute, London SE5 9RS, UK
| | - Christopher E Shaw
- Department of Basic and Clinical Neuroscience, King’s College London, Maurice Wohl Clinical Neuroscience Institute, London SE5 9RS, UK
- UK Dementia Research Institute, King’s College London, London WC2R 2LS, UK
| | - Karen E Morrison
- Faculty of Medicine, Health & Life Sciences, Queen’s University Belfast, 90 Lisburn Road, Belfast, BT9 6AG, Northern Ireland, UK
| | - Pamela J Shaw
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield S10 2HQ, UK
| | - Russell L McLaughlin
- Complex Trait Genomics Laboratory, Smurfit Institute of Genetics, Trinity College Dublin, Dublin D02 DK07, Republic of Ireland
| | - Orla Hardiman
- Academic Unit of Neurology, Trinity College Dublin, Trinity Biomedical Sciences Institute, Dublin D02 PN40, Republic of Ireland
- Department of Neurology, Beaumont Hospital, Dublin D02 PN40, Republic of Ireland
| | - Ammar Al-Chalabi
- Department of Basic and Clinical Neuroscience, King’s College London, Maurice Wohl Clinical Neuroscience Institute, London SE5 9RS, UK
- Department of Neurology, King’s College Hospital, Bessemer Road, London, SE5 9RX, UK
| | | | - Jonathan Mill
- University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK
| | - Jan H Veldink
- Department of Neurology, UMC Utrecht Brain Center, 3584 CG, Utrecht, the Netherlands
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31
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Yang CX, Schon E, Obeidat M, Kobor MS, McEwen L, MacIsaac J, Lin D, Novak RM, Hudson F, Klinker H, Dharan N, Horvath S, Bourbeau J, Tan W, Sin DD, Man SFP, Kunisaki K, Leung JM. Occurrence of Accelerated Epigenetic Aging and Methylation Disruptions in Human Immunodeficiency Virus Infection Before Antiretroviral Therapy. J Infect Dis 2020; 223:1681-1689. [PMID: 32959881 DOI: 10.1093/infdis/jiaa599] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 09/17/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Whether accelerated aging develops over the course of chronic human immunodeficiency virus (HIV) infection or can be observed before significant immunosuppression on is unknown. We studied DNA methylation in blood to estimate cellular aging in persons living with HIV (PLWH) before the initiation of antiretroviral therapy (ART). METHODS A total of 378 ART-naive PLWH who had CD4 T-cell counts >500/µL and were enrolled in the Strategic Timing of Antiretroviral Therapy trial (Pulmonary Substudy) were compared with 34 HIV-negative controls. DNA methylation was performed using the Illumina MethylationEPIC BeadChip. Differentially methylated positions (DMPs) and differentially methylated regions (DMRs) in PLWH compared with controls were identified using a robust linear model. Methylation age was calculated using a previously described epigenetic clock. RESULTS There were a total of 56 639 DMPs and 6103 DMRs at a false discovery rate of <0.1. The top 5 DMPs corresponded to genes NLRC5, VRK2, B2M, and GPR6 and were highly enriched for cancer-related pathways. PLWH had significantly higher methylation age than HIV-negative controls (P = .001), with black race, low CD4 and high CD8 T-cell counts, and duration of HIV being risk factors for age acceleration. CONCLUSIONS PLWH before the initiation of ART and with preserved immune status show evidence of advanced methylation aging.
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Affiliation(s)
- Chen Xi Yang
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, British Columbia, Canada
| | - Emma Schon
- Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Ma'en Obeidat
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, British Columbia, Canada.,Division of Respiratory Medicine, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Michael S Kobor
- Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Lisa McEwen
- Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Julie MacIsaac
- Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - David Lin
- Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Richard M Novak
- Section of Infectious Diseases, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Fleur Hudson
- MRC Clinical Trials Unit, University College London, London, United Kingdom
| | - Hartwig Klinker
- University of Würzburg Medical Center, Department of Internal Medicine II, Division of Infectious Diseases, Würzburg, Germany
| | | | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Jean Bourbeau
- Respiratory Epidemiology and Clinical Research Unit, McGill University, Montreal, Quebec, Canada
| | - Wan Tan
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, British Columbia, Canada.,Division of Respiratory Medicine, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Don D Sin
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, British Columbia, Canada.,Division of Respiratory Medicine, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - S F Paul Man
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, British Columbia, Canada.,Division of Respiratory Medicine, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Ken Kunisaki
- Minneapolis Veterans Affairs Health Care System, Section of Pulmonary, Critical Care and Sleep Medicine, Minneapolis, Minnesota, USA.,Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, University of Minnesota, Minneapolis, Minnesota, USA
| | - Janice M Leung
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, British Columbia, Canada.,Division of Respiratory Medicine, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
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32
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Åsenius F, Gorrie-Stone TJ, Brew A, Panchbhaya Y, Williamson E, Schalkwyk LC, Rakyan VK, Holland ML, Marzi SJ, Williams DJ. The DNA methylome of human sperm is distinct from blood with little evidence for tissue-consistent obesity associations. PLoS Genet 2020; 16:e1009035. [PMID: 33048947 PMCID: PMC7584170 DOI: 10.1371/journal.pgen.1009035] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 10/23/2020] [Accepted: 08/07/2020] [Indexed: 12/19/2022] Open
Abstract
Epidemiological research suggests that paternal obesity may increase the risk of fathering small for gestational age offspring. Studies in non-human mammals indicate that such associations could be mediated by DNA methylation changes in spermatozoa that influence offspring development in utero. Human obesity is associated with differential DNA methylation in peripheral blood. It is unclear, however, whether this differential DNA methylation is reflected in spermatozoa. We profiled genome-wide DNA methylation using the Illumina MethylationEPIC array in a cross-sectional study of matched human blood and sperm from lean (discovery n = 47; replication n = 21) and obese (n = 22) males to analyse tissue covariation of DNA methylation, and identify obesity-associated methylomic signatures. We found that DNA methylation signatures of human blood and spermatozoa are highly discordant, and methylation levels are correlated at only a minority of CpG sites (~1%). At the majority of these sites, DNA methylation appears to be influenced by genetic variation. Obesity-associated DNA methylation in blood was not generally reflected in spermatozoa, and obesity was not associated with altered covariation patterns or accelerated epigenetic ageing in the two tissues. However, one cross-tissue obesity-specific hypermethylated site (cg19357369; chr4:2429884; P = 8.95 × 10-8; 2% DNA methylation difference) was identified, warranting replication and further investigation. When compared to a wide range of human somatic tissue samples (n = 5,917), spermatozoa displayed differential DNA methylation across pathways enriched in transcriptional regulation. Overall, human sperm displays a unique DNA methylation profile that is highly discordant to, and practically uncorrelated with, that of matched peripheral blood. We observed that obesity was only nominally associated with differential DNA methylation in sperm, and therefore suggest that spermatozoal DNA methylation is an unlikely mediator of intergenerational effects of metabolic traits.
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Affiliation(s)
- Fredrika Åsenius
- UCL EGA Institute for Women’s Health, University College London, London, United Kingdom
| | | | - Ama Brew
- The Blizard Institute, Queen Mary University of London, London, United Kingdom
| | - Yasmin Panchbhaya
- UCL Genomics, Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Elizabeth Williamson
- Fertility & reproductive medicine laboratory, University College Hospital, London, United Kingdom
| | | | - Vardhman K. Rakyan
- The Blizard Institute, Queen Mary University of London, London, United Kingdom
| | - Michelle L. Holland
- Department of Medical and Molecular Genetics, School of Basic and Medical Biosciences, King’s College London, London, United Kingdom
| | - Sarah J. Marzi
- UK Dementia Research Institute, Imperial College London, London, United Kingdom
- Department of Brain Sciences, Imperial College London, London, United Kingdom
| | - David J. Williams
- UCL EGA Institute for Women’s Health, University College London, London, United Kingdom
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33
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Gagné-Ouellet V, Breton E, Thibeault K, Fortin CA, Desgagné V, Girard Tremblay É, Cardenas A, Guérin R, Perron P, Hivert MF, Bouchard L. Placental Epigenome-Wide Association Study Identified Loci Associated with Childhood Adiposity at 3 Years of Age. Int J Mol Sci 2020; 21:ijms21197201. [PMID: 33003475 PMCID: PMC7582906 DOI: 10.3390/ijms21197201] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 08/22/2020] [Accepted: 09/21/2020] [Indexed: 12/20/2022] Open
Abstract
The aim of this study was to identify placental DNA methylation (DNAm) variations associated with adiposity at 3 years of age. We quantified placental DNAm using the Infinium MethylationEPIC BeadChips. We assessed associations between DNAm at single-CpGs and skinfold thickness using robust linear regression models adjusted for gestational age, child's sex, age at follow-up and cellular heterogeneity. We sought replication of DNAm association with child adiposity in an independent cohort. We quantified placental mRNA levels for annotated gene using qRT-PCR and tested for correlation with DNAm. Lower DNAm at cg22593959 and cg22436429 was associated with higher adiposity (β = -1.18, q = 0.002 and β = -0.82, q = 0.04). The cg22593959 is located in an intergenic region (chr7q31.3), whereas cg22436429 is within the TFAP2E gene (1p34.3). DNAm at cg22593959 and cg22436429 was correlated with mRNA levels at FAM3C (rs = -0.279, p = 0.005) and TFAP2E (rs = 0.216, p = 0.03). In an independent cohort, the association between placental DNAm at cg22593959 and childhood adiposity was of similar strength and direction (β = -3.8 ± 4.1, p = 0.36), yet non-significant. Four genomic regions were also associated with skinfold thickness within FMN1, MAGI2, SKAP2 and BMPR1B genes. We identified placental epigenetic variations associated with adiposity at 3 years of age suggesting that childhood fat accretion patterns might be established during fetal life.
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Affiliation(s)
- Valérie Gagné-Ouellet
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada; (V.G.-O.); (E.B.); (K.T.); (C.-A.F.); (V.D.); (É.G.T.); (R.G.)
| | - Edith Breton
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada; (V.G.-O.); (E.B.); (K.T.); (C.-A.F.); (V.D.); (É.G.T.); (R.G.)
| | - Kathrine Thibeault
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada; (V.G.-O.); (E.B.); (K.T.); (C.-A.F.); (V.D.); (É.G.T.); (R.G.)
| | - Carol-Ann Fortin
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada; (V.G.-O.); (E.B.); (K.T.); (C.-A.F.); (V.D.); (É.G.T.); (R.G.)
| | - Véronique Desgagné
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada; (V.G.-O.); (E.B.); (K.T.); (C.-A.F.); (V.D.); (É.G.T.); (R.G.)
- Department of Medical Biology, CIUSSS Saguenay-Lac-Saint-Jean—Hôpital Universitaire de Chicoutimi, Saguenay, QC G7H 5H6, Canada
| | - Élise Girard Tremblay
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada; (V.G.-O.); (E.B.); (K.T.); (C.-A.F.); (V.D.); (É.G.T.); (R.G.)
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA 94720-7360, USA;
| | - Renée Guérin
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada; (V.G.-O.); (E.B.); (K.T.); (C.-A.F.); (V.D.); (É.G.T.); (R.G.)
- Department of Medical Biology, CIUSSS Saguenay-Lac-Saint-Jean—Hôpital Universitaire de Chicoutimi, Saguenay, QC G7H 5H6, Canada
| | - Patrice Perron
- Department of Medicine, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada; (P.P.); (M.-F.H.)
- Centre de Recherche du CHUS, Sherbrooke, QC J1H 5N4, Canada
| | - Marie-France Hivert
- Department of Medicine, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada; (P.P.); (M.-F.H.)
- Diabetes Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Luigi Bouchard
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada; (V.G.-O.); (E.B.); (K.T.); (C.-A.F.); (V.D.); (É.G.T.); (R.G.)
- Department of Medical Biology, CIUSSS Saguenay-Lac-Saint-Jean—Hôpital Universitaire de Chicoutimi, Saguenay, QC G7H 5H6, Canada
- Centre de Recherche du CHUS, Sherbrooke, QC J1H 5N4, Canada
- Correspondence:
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Dritsoula A, Kislikova M, Oomatia A, Webster AP, Beck S, Ponticos M, Lindsey B, Norman J, Wheeler DC, Oates T, Caplin B. "Epigenome-wide methylation profile of chronic kidney disease-derived arterial DNA uncovers novel pathways in disease-associated cardiovascular pathology.". Epigenetics 2020; 16:718-728. [PMID: 32930636 DOI: 10.1080/15592294.2020.1819666] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Chronic kidney disease (CKD) related cardiovascular disease (CVD) is characterized by vascular remodelling with well-established structural and functional changes in the vascular wall such as arterial stiffness, matrix deposition, and calcification. These phenotypic changes resemble pathology seen in ageing, and are likely to be mediated by sustained alterations in gene expression, which may be caused by epigenetic changes such as tissue-specific DNA methylation. We aimed to investigate tissue specific changes in DNA methylation that occur in CKD-related CVD. Genome-wide DNA methylation changes were examined in bisulphite converted genomic DNA isolated from the vascular media of CKD and healthy arteries. Methylation-specific PCR was used to validate the array data, and the association between DNA methylation and gene and protein expression was examined. The DNA methylation age was compared to the chronological age in both cases and controls. Three hundred and nineteen differentially methylated regions (DMR) were identified spread across the genome. Pathway analysis revealed that DMRs associated with genes were involved in embryonic and vascular development, and signalling pathways such as TGFβ and FGF. Expression of top differentially methylated gene HOXA5 showed a significant negative correlation with DNA methylation. Interestingly, DNA methylation age and chronological age were highly correlated, but there was no evidence of accelerated age-related DNA methylation in the arteries of CKD patients. In conclusion, we demonstrated that differential DNA methylation in the arterial tissue of CKD patients represents a potential mediator of arterial pathology and may be used to uncover novel pathways in the genesis of CKD-associated complications.
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Affiliation(s)
- Athina Dritsoula
- Department of Renal Medicine, Division of Medicine, UCL, London, UK
| | - Maria Kislikova
- Department of Renal Medicine, Division of Medicine, UCL, London, UK.,Department of Nephrology, University Hospital Marqués de Valdecilla, University of Cantabria, IDIVAL, Santander, Spain
| | - Amin Oomatia
- Department of Renal Medicine, Division of Medicine, UCL, London, UK
| | - Amy P Webster
- Department of Cancer Biology, Cancer Institute, UCL, London, UK
| | - Stephan Beck
- Department of Cancer Biology, Cancer Institute, UCL, London, UK
| | - Markella Ponticos
- Centre for Rheumatology and Connective Tissue Diseases, Division of Medicine, UCL, London, UK
| | - Ben Lindsey
- Department of Renal Medicine, Division of Medicine, UCL, London, UK
| | - Jill Norman
- Department of Renal Medicine, Division of Medicine, UCL, London, UK
| | - David C Wheeler
- Department of Renal Medicine, Division of Medicine, UCL, London, UK
| | - Thomas Oates
- Department of Renal Medicine, Division of Medicine, UCL, London, UK.,Departments of Nephrology and General Medicine, Royal London Hospital, Barts Health NHS Trust, London, UK
| | - Ben Caplin
- Department of Renal Medicine, Division of Medicine, UCL, London, UK
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35
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DNA methylation study of Huntington's disease and motor progression in patients and in animal models. Nat Commun 2020; 11:4529. [PMID: 32913184 PMCID: PMC7484780 DOI: 10.1038/s41467-020-18255-5] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Accepted: 08/14/2020] [Indexed: 01/10/2023] Open
Abstract
Although Huntington's disease (HD) is a well studied Mendelian genetic disorder, less is known about its associated epigenetic changes. Here, we characterize DNA methylation levels in six different tissues from 3 species: a mouse huntingtin (Htt) gene knock-in model, a transgenic HTT sheep model, and humans. Our epigenome-wide association study (EWAS) of human blood reveals that HD mutation status is significantly (p < 10-7) associated with 33 CpG sites, including the HTT gene (p = 6.5 × 10-26). These Htt/HTT associations were replicated in the Q175 Htt knock-in mouse model (p = 6.0 × 10-8) and in the transgenic sheep model (p = 2.4 × 10-88). We define a measure of HD motor score progression among manifest HD cases based on multiple clinical assessments. EWAS of motor progression in manifest HD cases exhibits significant (p < 10-7) associations with methylation levels at three loci: near PEX14 (p = 9.3 × 10-9), GRIK4 (p = 3.0 × 10-8), and COX4I2 (p = 6.5 × 10-8). We conclude that HD is accompanied by profound changes of DNA methylation levels in three mammalian species.
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Hoang TT, Sikdar S, Xu CJ, Lee MK, Cardwell J, Forno E, Imboden M, Jeong A, Madore AM, Qi C, Wang T, Bennett BD, Ward JM, Parks CG, Beane-Freeman LE, King D, Motsinger-Reif A, Umbach DM, Wyss AB, Schwartz DA, Celedón JC, Laprise C, Ober C, Probst-Hensch N, Yang IV, Koppelman GH, London SJ. Epigenome-wide association study of DNA methylation and adult asthma in the Agricultural Lung Health Study. Eur Respir J 2020; 56:13993003.00217-2020. [PMID: 32381493 PMCID: PMC7469973 DOI: 10.1183/13993003.00217-2020] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Accepted: 04/15/2020] [Indexed: 12/11/2022]
Abstract
Epigenome-wide studies of methylation in children support a role for epigenetic mechanisms in asthma; however, studies in adults are rare and few have examined non-atopic asthma. We conducted the largest epigenome-wide association study (EWAS) of blood DNA methylation in adults in relation to non-atopic and atopic asthma. We measured DNA methylation in blood using the Illumina MethylationEPIC array among 2286 participants in a case-control study of current adult asthma nested within a United States agricultural cohort. Atopy was defined by serum specific immunoglobulin E (IgE). Participants were categorised as atopy without asthma (n=185), non-atopic asthma (n=673), atopic asthma (n=271), or a reference group of neither atopy nor asthma (n=1157). Analyses were conducted using logistic regression. No associations were observed with atopy without asthma. Numerous cytosine–phosphate–guanine (CpG) sites were differentially methylated in non-atopic asthma (eight at family-wise error rate (FWER) p<9×10−8, 524 at false discovery rate (FDR) less than 0.05) and implicated 382 novel genes. More CpG sites were identified in atopic asthma (181 at FWER, 1086 at FDR) and implicated 569 novel genes. 104 FDR CpG sites overlapped. 35% of CpG sites in non-atopic asthma and 91% in atopic asthma replicated in studies of whole blood, eosinophils, airway epithelium, or nasal epithelium. Implicated genes were enriched in pathways related to the nervous system or inflammation. We identified numerous, distinct differentially methylated CpG sites in non-atopic and atopic asthma. Many CpG sites from blood replicated in asthma-relevant tissues. These circulating biomarkers reflect risk and sequelae of disease, as well as implicate novel genes associated with non-atopic and atopic asthma. Distinct methylation signals are found in non-atopic and atopic asthma. Most are related to gene expression and are replicated in asthma-relevant tissues, confirming the value of blood DNA methylation for identifying novel genes linked in asthma pathogenesis.https://bit.ly/2VnbJg3
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Affiliation(s)
- Thanh T Hoang
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Dept of Health and Human Services, Research Triangle Park, NC, USA.,Joint first authors
| | - Sinjini Sikdar
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Dept of Health and Human Services, Research Triangle Park, NC, USA.,Dept of Mathematics and Statistics, Old Dominion University, Norfolk, VA, USA.,Joint first authors
| | - Cheng-Jian Xu
- Centre for Individualised Infection Medicine (CiiM), Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany.,Centre for Experimental and Clinical Infection Research (TWINCORE), Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany.,Joint first authors
| | - Mi Kyeong Lee
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Dept of Health and Human Services, Research Triangle Park, NC, USA
| | - Jonathan Cardwell
- Dept of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Erick Forno
- Division of Pulmonary Medicine, UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA, USA.,Dept of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Medea Imboden
- Chronic Disease Epidemiology Unit, Dept of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland.,Dept of Public Health, University of Basel, Basel, Switzerland
| | - Ayoung Jeong
- Chronic Disease Epidemiology Unit, Dept of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland.,Dept of Public Health, University of Basel, Basel, Switzerland
| | - Anne-Marie Madore
- Département des Sciences Fondamentales, Université du Québec à Chicoutimi, Saguenay, QC, Canada
| | - Cancan Qi
- Dept of Pediatric Pulmonology and Pediatric Allergy, University Medical Center Groningen, University of Groningen, Beatrix Children's Hospital and GRIAC Research Institute, Groningen, The Netherlands
| | - Tianyuan Wang
- Integrative Bioinformatics Support Group, National Institutes of Health, Dept of Health and Human Services, Research Triangle Park, NC, USA
| | - Brian D Bennett
- Integrative Bioinformatics Support Group, National Institutes of Health, Dept of Health and Human Services, Research Triangle Park, NC, USA
| | - James M Ward
- Integrative Bioinformatics Support Group, National Institutes of Health, Dept of Health and Human Services, Research Triangle Park, NC, USA
| | - Christine G Parks
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Dept of Health and Human Services, Research Triangle Park, NC, USA
| | - Laura E Beane-Freeman
- Occupational and Environmental Epidemiology Branch, National Cancer Institute, Bethesda, MD, USA
| | - Debra King
- Clinical Pathology Group, National Institute of Environmental Health Sciences, National Institutes of Health, Dept of Health and Human Services, Research Triangle Park, NC, USA
| | - Alison Motsinger-Reif
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Dept of Health and Human Services, Research Triangle Park, NC, USA
| | - David M Umbach
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Dept of Health and Human Services, Research Triangle Park, NC, USA
| | - Annah B Wyss
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Dept of Health and Human Services, Research Triangle Park, NC, USA
| | - David A Schwartz
- Dept of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Juan C Celedón
- Division of Pulmonary Medicine, UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA, USA.,Dept of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Catherine Laprise
- Département des Sciences Fondamentales, Université du Québec à Chicoutimi, Saguenay, QC, Canada.,Centre Intersectoriel en Santé Durable, Département des Sciences Fondamentales, Université du Québec à Chicoutimi, Saguenay, QC, Canada.,Dept of Pediatrics, Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay-Lac-Saint-Jean, Saguenay, QC, Canada
| | - Carole Ober
- Dept of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Nicole Probst-Hensch
- Chronic Disease Epidemiology Unit, Dept of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland.,Dept of Public Health, University of Basel, Basel, Switzerland
| | - Ivana V Yang
- Dept of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Gerard H Koppelman
- Dept of Pediatric Pulmonology and Pediatric Allergy, University Medical Center Groningen, University of Groningen, Beatrix Children's Hospital and GRIAC Research Institute, Groningen, The Netherlands
| | - Stephanie J London
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Dept of Health and Human Services, Research Triangle Park, NC, USA
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Cypris O, Eipel M, Franzen J, Rösseler C, Tharmapalan V, Kuo CC, Vieri M, Nikolić M, Kirschner M, Brümmendorf TH, Zenke M, Lampert A, Beier F, Wagner W. PRDM8 reveals aberrant DNA methylation in aging syndromes and is relevant for hematopoietic and neuronal differentiation. Clin Epigenetics 2020; 12:125. [PMID: 32819411 PMCID: PMC7439574 DOI: 10.1186/s13148-020-00914-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 07/30/2020] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Dyskeratosis congenita (DKC) and idiopathic aplastic anemia (AA) are bone marrow failure syndromes that share characteristics of premature aging with severe telomere attrition. Aging is also reflected by DNA methylation changes, which can be utilized to predict donor age. There is evidence that such epigenetic age predictions are accelerated in premature aging syndromes, but it is yet unclear how this is related to telomere length. DNA methylation analysis may support diagnosis of DKC and AA, which still remains a challenge for these rare diseases. RESULTS In this study, we analyzed blood samples of 70 AA and 18 DKC patients to demonstrate that their epigenetic age predictions are overall increased, albeit not directly correlated with telomere length. Aberrant DNA methylation was observed in the gene PRDM8 in DKC and AA as well as in other diseases with premature aging phenotype, such as Down syndrome and Hutchinson-Gilford-Progeria syndrome. Aberrant DNA methylation patterns were particularly found within subsets of cell populations in DKC and AA samples as measured with barcoded bisulfite amplicon sequencing (BBA-seq). To gain insight into the functional relevance of PRDM8, we used CRISPR/Cas9 technology to generate induced pluripotent stem cells (iPSCs) with heterozygous and homozygous knockout. Loss of PRDM8 impaired hematopoietic and neuronal differentiation of iPSCs, even in the heterozygous knockout clone, but it did not impact on epigenetic age. CONCLUSION Taken together, our results demonstrate that epigenetic aging is accelerated in DKC and AA, independent from telomere attrition. Furthermore, aberrant DNA methylation in PRDM8 provides another biomarker for bone marrow failure syndromes and modulation of this gene in cellular subsets may be related to the hematopoietic and neuronal phenotypes observed in premature aging syndromes.
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Affiliation(s)
- Olivia Cypris
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University, Pauwelsstrasse 20, Aachen, Germany
| | - Monika Eipel
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University, Pauwelsstrasse 20, Aachen, Germany
| | - Julia Franzen
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University, Pauwelsstrasse 20, Aachen, Germany
| | - Corinna Rösseler
- Institute of Physiology, Medical Faculty University Hospital Aachen, RWTH Aachen University, Aachen, Germany
| | - Vithurithra Tharmapalan
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University, Pauwelsstrasse 20, Aachen, Germany
| | - Chao-Chung Kuo
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University, Pauwelsstrasse 20, Aachen, Germany
| | - Margherita Vieri
- Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, Medical Faculty University Hospital Aachen, RWTH Aachen University, Aachen, Germany
| | - Miloš Nikolić
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University, Pauwelsstrasse 20, Aachen, Germany
| | - Martin Kirschner
- Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, Medical Faculty University Hospital Aachen, RWTH Aachen University, Aachen, Germany
| | - Tim H. Brümmendorf
- Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, Medical Faculty University Hospital Aachen, RWTH Aachen University, Aachen, Germany
| | - Martin Zenke
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University, Pauwelsstrasse 20, Aachen, Germany
- Institute for Biomedical Engineering – Cell Biology, RWTH Aachen University Medical School, Aachen, Germany
| | - Angelika Lampert
- Institute of Physiology, Medical Faculty University Hospital Aachen, RWTH Aachen University, Aachen, Germany
| | - Fabian Beier
- Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, Medical Faculty University Hospital Aachen, RWTH Aachen University, Aachen, Germany
| | - Wolfgang Wagner
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University, Pauwelsstrasse 20, Aachen, Germany
- Institute for Biomedical Engineering – Cell Biology, RWTH Aachen University Medical School, Aachen, Germany
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38
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Curtis SW, Cobb DO, Kilaru V, Terrell ML, Marder ME, Barr DB, Marsit CJ, Marcus M, Conneely KN, Smith AK. Genome-wide DNA methylation differences and polychlorinated biphenyl (PCB) exposure in a US population. Epigenetics 2020; 16:338-352. [PMID: 32660331 DOI: 10.1080/15592294.2020.1795605] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Exposure to polychlorinated biphenyls (PCBs), an endocrine-disrupting compound, is ubiquitous despite decades-old bans on the manufacture and use of PCBs. Increased exposure to PCBs is associated with adverse health consequences throughout life, including type 2 diabetes and cancer. PCB exposure is also associated with alterations in epigenetic marks and gene transcription, which could lead to adverse health outcomes, but many of these are population-specific. To further investigate the association between PCB and epigenetic marks, DNA methylation was measured at 787,684 CpG sites in 641 peripheral blood samples from the Michigan Polybrominated Biphenyl (PBB) Registry. 1345 CpGs were associated with increased total PCB level after controlling for age, sex, and 24 surrogate variables (FDR < 0.05). These CpGs were enriched in active promoter and transcription associated regions (p < 0.05), and in regions around the binding sites for transcription factors involved in xenobiotic metabolism and immune function (FDR < 0.05). PCB exposure also associated with proportions of CD4T, NK, and granulocyte cell types, and with the neutrophil to lymphocyte ratio (NLR) (p < 0.05), and the estimated effect sizes of PCB on the epigenome were correlated with the effect sizes previously reported in an epigenome-wide study of C-reactive protein (r = 0.29; p = 2.22e-5), supporting previous studies on the association between PCB and immune dysfunction. These results indicate that PCB exposure is associated with differences in epigenetic marks in active regions of the genome, and future work should investigate whether these may mediate the association between PCB and health consequences.
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Affiliation(s)
- Sarah W Curtis
- Genetics and Molecular Biology Program, Laney Graduate School, Emory University School of Medicine , Atlanta, GA, USA
| | - Dawayland O Cobb
- Department of Gynecology and Obstetrics, Emory University School of Medicine , Atlanta, GA, USA
| | - Varun Kilaru
- Department of Gynecology and Obstetrics, Emory University School of Medicine , Atlanta, GA, USA
| | - Metrecia L Terrell
- Department of Epidemiology, Emory University Rollins School of Public Health , Atlanta, GA, USA
| | - M Elizabeth Marder
- Gangarosa Department of Environmental Health, Emory University Rollins School of Public Health , Atlanta, GA, USA
| | - Dana Boyd Barr
- Gangarosa Department of Environmental Health, Emory University Rollins School of Public Health , Atlanta, GA, USA
| | - Carmen J Marsit
- Gangarosa Department of Environmental Health, Emory University Rollins School of Public Health , Atlanta, GA, USA
| | - Michele Marcus
- Departments of Epidemiology and Department of Pediatrics Emory University School of Medicine, Environmental Health, Emory University Rollins School of Public Health , Atlanta, GA, USA
| | - Karen N Conneely
- Department of Human Genetics, Emory University School of Medicine , Atlanta, GA, USA
| | - Alicia K Smith
- Departments of Gynecology and Obstetrics & Psychiatry and Behavioral Science, Emory University School of Medicine , Atlanta, GA, USA
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39
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Romanowska J, Haaland ØA, Jugessur A, Gjerdevik M, Xu Z, Taylor J, Wilcox AJ, Jonassen I, Lie RT, Gjessing HK. Gene-methylation interactions: discovering region-wise DNA methylation levels that modify SNP-associated disease risk. Clin Epigenetics 2020; 12:109. [PMID: 32678018 PMCID: PMC7367265 DOI: 10.1186/s13148-020-00881-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 06/10/2020] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Current technology allows rapid assessment of DNA sequences and methylation levels at a single-site resolution for hundreds of thousands of sites in the human genome, in thousands of individuals simultaneously. This has led to an increase in epigenome-wide association studies (EWAS) of complex traits, particularly those that are poorly explained by previous genome-wide association studies (GWAS). However, the genome and epigenome are intertwined, e.g., DNA methylation is known to affect gene expression through, for example, genomic imprinting. There is thus a need to go beyond single-omics data analyses and develop interaction models that allow a meaningful combination of information from EWAS and GWAS. RESULTS We present two new methods for genetic association analyses that treat offspring DNA methylation levels as environmental exposure. Our approach searches for statistical interactions between SNP alleles and DNA methylation (G ×Me) and between parent-of-origin effects and DNA methylation (PoO ×Me), using case-parent triads or dyads. We use summarized methylation levels over nearby genomic region to ease biological interpretation. The methods were tested on a dataset of parent-offspring dyads, with EWAS data on the offspring. Our results showed that methylation levels around a SNP can significantly alter the estimated relative risk. Moreover, we show how a control dataset can identify false positives. CONCLUSIONS The new methods, G ×Me and PoO ×Me, integrate DNA methylation in the assessment of genetic relative risks and thus enable a more comprehensive biological interpretation of genome-wide scans. Moreover, our strategy of condensing DNA methylation levels within regions helps overcome specific disadvantages of using sparse chip-based measurements. The methods are implemented in the freely available R package Haplin ( https://cran.r-project.org/package=Haplin ), enabling fast scans of multi-omics datasets.
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Affiliation(s)
- Julia Romanowska
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, N-5020, Norway.
- Computational Biology Unit, University of Bergen, Bergen, N-5020, Norway.
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, N-0213, Norway.
| | - Øystein A Haaland
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, N-5020, Norway
| | - Astanand Jugessur
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, N-5020, Norway
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, N-0213, Norway
- Department of Genetics and Bioinformatics, Norwegian Institute of Public Health, Oslo, N-0473, Norway
| | - Miriam Gjerdevik
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, N-5020, Norway
- Department of Genetics and Bioinformatics, Norwegian Institute of Public Health, Oslo, N-0473, Norway
| | - Zongli Xu
- National Institute of Environmental Health Sciences, Research Triangle Park, 27709, NC, USA
| | - Jack Taylor
- National Institute of Environmental Health Sciences, Research Triangle Park, 27709, NC, USA
| | - Allen J Wilcox
- National Institute of Environmental Health Sciences, Research Triangle Park, 27709, NC, USA
| | - Inge Jonassen
- Computational Biology Unit, University of Bergen, Bergen, N-5020, Norway
| | - Rolv T Lie
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, N-5020, Norway
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, N-0213, Norway
| | - Håkon K Gjessing
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, N-5020, Norway
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, N-0213, Norway
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40
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LaBarre BA, Goncearenco A, Petrykowska HM, Jaratlerdsiri W, Bornman MSR, Hayes VM, Elnitski L. MethylToSNP: identifying SNPs in Illumina DNA methylation array data. Epigenetics Chromatin 2019; 12:79. [PMID: 31861999 PMCID: PMC6923858 DOI: 10.1186/s13072-019-0321-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Accepted: 12/09/2019] [Indexed: 12/16/2022] Open
Abstract
Background Current array-based methods for the measurement of DNA methylation rely on the process of sodium bisulfite conversion to differentiate between methylated and unmethylated cytosine bases in DNA. In the absence of genotype data this process can lead to ambiguity in data interpretation when a sample has polymorphisms at a methylation probe site. A common way to minimize this problem is to exclude such potentially problematic sites, with some methods removing as much as 60% of array probes from consideration before data analysis. Results Here, we present an algorithm implemented in an R Bioconductor package, MethylToSNP, which detects a characteristic data pattern to infer sites likely to be confounded by polymorphisms. Additionally, the tool provides a stringent reliability score to allow thresholding on SNP predictions. We calibrated parameters and thresholds used by the algorithm on simulated and real methylation data sets. We illustrate findings using methylation data from YRI (Yoruba in Ibadan, Nigeria), CEPH (European descent) and KhoeSan (southern African) populations. Our polymorphism predictions made using MethylToSNP have been validated through SNP databases and bisulfite and genomic sequencing. Conclusions The benefits of this method are threefold. First, it prevents extensive data loss by considering only SNPs specific to the individuals in the study. Second, it offers the possibility to identify new polymorphisms in samples for which there is little known about the genetic landscape. Third, it identifies variants as they exist in functional regions of a genome, such as in CTCF (transcriptional repressor) sites and enhancers, that may be common alleles or personal mutations with potential to deleteriously affect genomic regulatory activities. We demonstrate that MethylToSNP is applicable to the Illumina 450K and Illumina 850K EPIC array data and is also backwards compatible to the 27K methylation arrays. Going forward, this kind of nuanced approach can increase the amount of information derived from precious data sets by considering samples of the project individually to enable more informed decisions about data cleaning.
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Affiliation(s)
- Brenna A LaBarre
- Graduate Program in Bioinformatics, Boston University, Boston, MA, USA.,Genomic Functional Analysis Section, Translational and Functional Genomics Branch, National Human Genome Research Institute, National Institutes of Health, 49 Convent Dr., Bethesda, MD, 20892, USA
| | - Alexander Goncearenco
- Genomic Functional Analysis Section, Translational and Functional Genomics Branch, National Human Genome Research Institute, National Institutes of Health, 49 Convent Dr., Bethesda, MD, 20892, USA
| | - Hanna M Petrykowska
- Genomic Functional Analysis Section, Translational and Functional Genomics Branch, National Human Genome Research Institute, National Institutes of Health, 49 Convent Dr., Bethesda, MD, 20892, USA
| | - Weerachai Jaratlerdsiri
- Laboratory for Human Comparative & Prostate Cancer Genomics, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
| | - M S Riana Bornman
- School of Health Systems and Public Health, University of Pretoria, Hatfield, Pretoria, South Africa
| | - Vanessa M Hayes
- Laboratory for Human Comparative & Prostate Cancer Genomics, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia.,School of Health Systems and Public Health, University of Pretoria, Hatfield, Pretoria, South Africa.,Sydney Medical School, University of Sydney, Camperdown, NSW, Australia
| | - Laura Elnitski
- Genomic Functional Analysis Section, Translational and Functional Genomics Branch, National Human Genome Research Institute, National Institutes of Health, 49 Convent Dr., Bethesda, MD, 20892, USA.
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41
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Gondalia R, Baldassari A, Holliday KM, Justice AE, Méndez-Giráldez R, Stewart JD, Liao D, Yanosky JD, Brennan KJM, Engel SM, Jordahl KM, Kennedy E, Ward-Caviness CK, Wolf K, Waldenberger M, Cyrys J, Peters A, Bhatti P, Horvath S, Assimes TL, Pankow JS, Demerath EW, Guan W, Fornage M, Bressler J, North KE, Conneely KN, Li Y, Hou L, Baccarelli AA, Whitsel EA. Methylome-wide association study provides evidence of particulate matter air pollution-associated DNA methylation. ENVIRONMENT INTERNATIONAL 2019; 132:104723. [PMID: 31208937 PMCID: PMC6754789 DOI: 10.1016/j.envint.2019.03.071] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Revised: 03/28/2019] [Accepted: 03/29/2019] [Indexed: 05/17/2023]
Abstract
BACKGROUND DNA methylation (DNAm) may contribute to processes that underlie associations between air pollution and poor health. Therefore, our objective was to evaluate associations between DNAm and ambient concentrations of particulate matter (PM) ≤2.5, ≤10, and 2.5-10 μm in diameter (PM2.5; PM10; PM2.5-10). METHODS We conducted a methylome-wide association study among twelve cohort- and race/ethnicity-stratified subpopulations from the Women's Health Initiative and the Atherosclerosis Risk in Communities study (n = 8397; mean age: 61.5 years; 83% female; 45% African American; 9% Hispanic/Latino American). We averaged geocoded address-specific estimates of daily and monthly mean PM concentrations over 2, 7, 28, and 365 days and 1 and 12 months before exams at which we measured leukocyte DNAm in whole blood. We estimated subpopulation-specific, DNAm-PM associations at approximately 485,000 Cytosine-phosphate-Guanine (CpG) sites in multi-level, linear, mixed-effects models. We combined subpopulation- and site-specific estimates in fixed-effects, inverse variance-weighted meta-analyses, then for associations that exceeded methylome-wide significance and were not heterogeneous across subpopulations (P < 1.0 × 10-7; PCochran's Q > 0.10), we characterized associations using publicly accessible genomic databases and attempted replication in the Cooperative Health Research in the Region of Augsburg (KORA) study. RESULTS Analyses identified significant DNAm-PM associations at three CpG sites. Twenty-eight-day mean PM10 was positively associated with DNAm at cg19004594 (chromosome 20; MATN4; P = 3.33 × 10-8). One-month mean PM10 and PM2.5-10 were positively associated with DNAm at cg24102420 (chromosome 10; ARPP21; P = 5.84 × 10-8) and inversely associated with DNAm at cg12124767 (chromosome 7; CFTR; P = 9.86 × 10-8). The PM-sensitive CpG sites mapped to neurological, pulmonary, endocrine, and cardiovascular disease-related genes, but DNAm at those sites was not associated with gene expression in blood cells and did not replicate in KORA. CONCLUSIONS Ambient PM concentrations were associated with DNAm at genomic regions potentially related to poor health among racially, ethnically and environmentally diverse populations of U.S. women and men. Further investigation is warranted to uncover mechanisms through which PM-induced epigenomic changes may cause disease.
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Affiliation(s)
- Rahul Gondalia
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
| | - Antoine Baldassari
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Katelyn M Holliday
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Department of Community and Family Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Anne E Justice
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Geisinger Health System, Danville, PA, USA
| | - Raúl Méndez-Giráldez
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - James D Stewart
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Duanping Liao
- Division of Epidemiology, Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Jeff D Yanosky
- Division of Epidemiology, Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Kasey J M Brennan
- Laboratory of Environmental Epigenetics, Departments of Environmental Health Sciences and Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Stephanie M Engel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Kristina M Jordahl
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - Elizabeth Kennedy
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Cavin K Ward-Caviness
- Environmental Public Health Division, National Health and Environmental Effects Research Laboratory, 104 Mason Farm Rd, Chapel Hill, NC, USA
| | - Kathrin Wolf
- Institute of Epidemiology, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, Neuherberg, Germany
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, Neuherberg, Germany
| | - Josef Cyrys
- Institute of Epidemiology, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, Neuherberg, Germany; Environmental Science Center, University of Augsburg, Augsburg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, Neuherberg, Germany
| | - Parveen Bhatti
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - Steve Horvath
- Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA; Biostatistics, School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | | | - James S Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | - Ellen W Demerath
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | - Weihua Guan
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jan Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
| | - Karen N Conneely
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Yun Li
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA; Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University Chicago, Evanston, IL, USA; Center for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University Chicago, Evanston, IL, USA
| | - Andrea A Baccarelli
- Laboratory of Environmental Epigenetics, Departments of Environmental Health Sciences and Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA; Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
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Gaine ME, Seifuddin F, Sabunciyan S, Lee RS, Benke KS, Monson ET, Zandi PP, Potash JB, Willour VL. Differentially methylated regions in bipolar disorder and suicide. Am J Med Genet B Neuropsychiatr Genet 2019; 180:496-507. [PMID: 31350827 PMCID: PMC8375453 DOI: 10.1002/ajmg.b.32754] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Revised: 06/24/2019] [Accepted: 07/15/2019] [Indexed: 12/29/2022]
Abstract
The addition of a methyl group to, typically, a cytosine-guanine dinucleotide (CpG) creates distinct DNA methylation patterns across the genome that can regulate gene expression. Aberrant DNA methylation of CpG sites has been associated with many psychiatric disorders including bipolar disorder (BD) and suicide. Using the SureSelectXT system, Methyl-Seq, we investigated the DNA methylation status of CpG sites throughout the genome in 50 BD individuals (23 subjects who died by suicide and 27 subjects who died from other causes) and 31 nonpsychiatric controls. We identified differentially methylated regions (DMRs) from three analyses: (a) BD subjects compared to nonpsychiatric controls (BD-NC), (b) BD subjects who died by suicide compared to nonpsychiatric controls (BDS-NC), and (c) BDS subjects compared to BD subjects who died from other causes (BDS-BDNS). One DMR from the BDS-NC analysis, located in ARHGEF38, was significantly hypomethylated (23.4%) in BDS subjects. This finding remained significant after multiple testing (PBootstrapped = 9.0 × 10-3 ), was validated using pyrosequencing, and was more significant in males. A secondary analysis utilized Ingenuity Pathway Analysis to identify enrichment in nominally significant DMRs. This identified an association with several pathways including axonal guidance signaling, calcium signaling, β-adrenergic signaling, and opioid signaling. Our comprehensive study provides further support that DNA methylation alterations influence the risk for BD and suicide. However, further investigation is required to confirm these associations and identify their functional consequences.
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Affiliation(s)
- Marie E. Gaine
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Fayaz Seifuddin
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Sarven Sabunciyan
- Center for Epigenetics, Johns Hopkins School of Medicine, Baltimore, Maryland,Department of Pediatrics, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Richard S. Lee
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Kelly S. Benke
- Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - Eric T. Monson
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Peter P. Zandi
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland,Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - James B. Potash
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Virginia L. Willour
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, Iowa
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Johann PD, Jäger N, Pfister SM, Sill M. RF_Purify: a novel tool for comprehensive analysis of tumor-purity in methylation array data based on random forest regression. BMC Bioinformatics 2019; 20:428. [PMID: 31419933 PMCID: PMC6697926 DOI: 10.1186/s12859-019-3014-z] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Accepted: 07/30/2019] [Indexed: 11/17/2022] Open
Abstract
Background With the advent of array-based techniques to measure methylation levels in primary tumor samples, systematic investigations of methylomes have widely been performed on a large number of tumor entities. Most of these approaches are not based on measuring individual cell methylation but rather the bulk tumor sample DNA, which contains a mixture of tumor cells, infiltrating immune cells and other stromal components. This raises questions about the purity of a certain tumor sample, given the varying degrees of stromal infiltration in different entities. Previous methods to infer tumor purity require or are based on the use of matching control samples which are rarely available. Here we present a novel, reference free method to quantify tumor purity, based on two Random Forest classifiers, which were trained on ABSOLUTE as well as ESTIMATE purity values from TCGA tumor samples. We subsequently apply this method to a previously published, large dataset of brain tumors, proving that these models perform well in datasets that have not been characterized with respect to tumor purity . Results Using two gold standard methods to infer purity – the ABSOLUTE score based on whole genome sequencing data and the ESTIMATE score based on gene expression data- we have optimized Random Forest classifiers to predict tumor purity in entities that were contained in the TCGA project. We validated these classifiers using an independent test data set and cross-compared it to other methods which have been applied to the TCGA datasets (such as ESTIMATE and LUMP). Using Illumina methylation array data of brain tumor entities (as published in Capper et al. (Nature 555:469-474,2018)) we applied this model to estimate tumor purity and find that subgroups of brain tumors display substantial differences in tumor purity. Conclusions Random forest- based tumor purity prediction is a well suited tool to extrapolate gold standard measures of purity to novel methylation array datasets. In contrast to other available methylation based tumor purity estimation methods, our classifiers do not need a priori knowledge about the tumor entity or matching control tissue to predict tumor purity. Electronic supplementary material The online version of this article (10.1186/s12859-019-3014-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Pascal David Johann
- Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany. .,Hopp Children's Cancer Center (KiTZ), Heidelberg, Germany. .,Department of Pediatric Hematology and Oncology, University Children's Hospital Heidelberg, Heidelberg, Germany. .,German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Natalie Jäger
- Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Hopp Children's Cancer Center (KiTZ), Heidelberg, Germany.,German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Stefan M Pfister
- Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Hopp Children's Cancer Center (KiTZ), Heidelberg, Germany.,Department of Pediatric Hematology and Oncology, University Children's Hospital Heidelberg, Heidelberg, Germany.,German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Martin Sill
- Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Hopp Children's Cancer Center (KiTZ), Heidelberg, Germany.,German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
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Curtis SW, Cobb DO, Kilaru V, Terrell ML, Marder ME, Barr DB, Marsit CJ, Marcus M, Conneely KN, Smith AK. Exposure to polybrominated biphenyl and stochastic epigenetic mutations: application of a novel epigenetic approach to environmental exposure in the Michigan polybrominated biphenyl registry. Epigenetics 2019; 14:1003-1018. [PMID: 31200609 DOI: 10.1080/15592294.2019.1629232] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Endocrine-disrupting compounds are associated with altered epigenetic regulation and adverse health outcomes, although inconsistent results suggest that people have varied responses to the same exposure. Interpersonal variation in response to environmental exposures is not identified using standard, population-based methods. However, methods that capture an individual's response, such as analyzing stochastic epigenetic mutations (SEMs), may capture currently missed effects of environmental exposure. To test whether polybrominated biphenyl (PBB) was associated with SEMs, DNA methylation was measured using Illumina's MethylationEPIC array in PBB-exposed individuals, and SEMs were identified. Association was tested using a linear regression with robust sandwich variance estimators, controlling for age, sex, lipids, and cell types. The number of SEMs was variable (range: 119-18,309), and positively associated with age (p = 1.23e-17), but not with sex (p = 0.97). PBBs and SEMs were only positively associated in people who were older when they were exposed (p = 0.02 vs. p = 0.91). Many subjects had SEMs enriched in biological pathways, particularly in pathways involved with xenobiotic metabolism and endocrine function. Higher number of SEMs was also associated with higher age acceleration (intrinsic: p = 1.70e-3; extrinsic: p = 3.59e-11), indicating that SEMs may be associated with age-related health problems. Finding an association between environmental contaminants and higher SEMs may provide insight into individual differences in response to environmental contaminants, as well as into the biological mechanism behind SEM formation. Furthermore, these results suggest that people may be particularly vulnerable to epigenetic dysregulation from environmental exposures as they age.
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Affiliation(s)
- Sarah W Curtis
- a Genetics and Molecular Biology Program, Laney Graduate School, Emory University School of Medicine , Atlanta , GA , USA
| | - Dawayland O Cobb
- b Department of Gynecology and Obstetrics, Emory University School of Medicine , Atlanta , GA , USA
| | - Varun Kilaru
- b Department of Gynecology and Obstetrics, Emory University School of Medicine , Atlanta , GA , USA
| | - Metrecia L Terrell
- c Department of Epidemiology, Emory University Rollins School of Public Health , Atlanta , GA , USA
| | - M Elizabeth Marder
- d Department of Environmental Health, Emory University Rollins School of Public Health , Atlanta , GA , USA
| | - Dana Boyd Barr
- d Department of Environmental Health, Emory University Rollins School of Public Health , Atlanta , GA , USA
| | - Carmen J Marsit
- d Department of Environmental Health, Emory University Rollins School of Public Health , Atlanta , GA , USA
| | - Michele Marcus
- e Departments of Epidemiology, Environmental Health, Emory University Rollins School of Public Health, and Department of Pediatrics Emory University School of Medicine , Atlanta , GA , USA
| | - Karen N Conneely
- f Department of Human Genetics, Emory University School of Medicine , Atlanta , GA , USA
| | - Alicia K Smith
- g Departments of Gynecology and Obstetrics & Psychiatry and Behavioral Science, Emory University School of Medicine , Atlanta , GA , USA
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Kidney cytosine methylation changes improve renal function decline estimation in patients with diabetic kidney disease. Nat Commun 2019; 10:2461. [PMID: 31165727 PMCID: PMC6549146 DOI: 10.1038/s41467-019-10378-8] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Accepted: 05/07/2019] [Indexed: 02/07/2023] Open
Abstract
Epigenetic changes might provide the biological explanation for the long-lasting impact of metabolic alterations of diabetic kidney disease development. Here we examined cytosine methylation of human kidney tubules using Illumina Infinium 450 K arrays from 91 subjects with and without diabetes and varying degrees of kidney disease using a cross-sectional design. We identify cytosine methylation changes associated with kidney structural damage and build a model for kidney function decline. We find that the methylation levels of 65 probes are associated with the degree of kidney fibrosis at genome wide significance. In total 471 probes improve the model for kidney function decline. Methylation probes associated with kidney damage and functional decline enrich on kidney regulatory regions and associate with gene expression changes, including epidermal growth factor (EGF). Altogether, our work shows that kidney methylation differences can be detected in patients with diabetic kidney disease and improve kidney function decline models indicating that they are potentially functionally important. Patients with diabetes commonly develop diabetic kidney disease (DKD). Here Gluck et al. identify a set of probes differentially methylated in renal samples from patients with DKD, and find that inclusion of these methylation probes improves current prediction models of renal function decline.
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46
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Epigenome-wide Analysis Identifies Genes and Pathways Linked to Neurobehavioral Variation in Preterm Infants. Sci Rep 2019; 9:6322. [PMID: 31004082 PMCID: PMC6474865 DOI: 10.1038/s41598-019-42654-4] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Accepted: 04/03/2019] [Indexed: 02/07/2023] Open
Abstract
Neonatal molecular biomarkers of neurobehavioral responses (measures of brain-behavior relationships), when combined with neurobehavioral performance measures, could lead to better predictions of long-term developmental outcomes. To this end, we examined whether variability in buccal cell DNA methylation (DNAm) associated with neurobehavioral profiles in a cohort of infants born less than 30 weeks postmenstrual age (PMA) and participating in the Neonatal Neurobehavior and Outcomes in Very Preterm Infants (NOVI) Study (N = 536). We tested whether epigenetic age, age acceleration, or DNAm levels at individual loci differed between infants based on their NICU Network Neurobehavioral Scale (NNNS) profile classifications. We adjusted for recruitment site, infant sex, PMA, and tissue heterogeneity. Infants with an optimally well-regulated NNNS profile had older epigenetic age compared to other NOVI infants (β1 = 0.201, p-value = 0.026), but no significant difference in age acceleration. In contrast, infants with an atypical NNNS profile had differential methylation at 29 CpG sites (FDR < 10%). Some of the genes annotated to these CpGs included PLA2G4E, TRIM9, GRIK3, and MACROD2, which have previously been associated with neurological structure and function, or with neurobehavioral disorders. These findings contribute to the existing evidence that neonatal epigenetic variations may be informative for infant neurobehavior.
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47
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Bakulski KM, Dou J, Lin N, London SJ, Colacino JA. DNA methylation signature of smoking in lung cancer is enriched for exposure signatures in newborn and adult blood. Sci Rep 2019; 9:4576. [PMID: 30872662 PMCID: PMC6418160 DOI: 10.1038/s41598-019-40963-2] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2018] [Accepted: 02/21/2019] [Indexed: 12/20/2022] Open
Abstract
Smoking impacts DNA methylation genome-wide in blood of newborns from maternal smoking during pregnancy and adults from personal smoking. We compared smoking-related DNA methylation in lung adenocarcinoma (61 never smokers, 91 current smokers, and 238 former smokers) quantified with the Illumina450k BeadArray in The Cancer Genome Atlas with published large consortium meta-analyses of newborn and adult blood. We assessed whether CpG sites related to smoking in blood from newborns and adults were enriched in the lung adenocarcinoma methylation signal. Testing CpGs differentially methylated by smoke exposure, we identified 296 in lung adenocarcinoma meeting a P < 10-4 cutoff, while previous meta-analyses identified 3,042 in newborn blood, and 8,898 in adult blood meeting the same P < 10-4 cutoff. Lung signals were highly enriched for those seen in newborn (24 overlapping CpGs, Penrichment = 1.2 × 10-18) and adult blood (66 overlapping CpGs, Penrichment = 1.2 × 10-48). The 105 genes annotated to CpGs differentially methylated in lung tumors, but not blood, were enriched for RNA processing ontologies. Some epigenetic alterations associated with cigarette smoke exposure are tissue specific, but others are common across tissues. These findings support the value of blood-based methylation biomarkers for assessing exposure effects in target tissues.
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Affiliation(s)
- K M Bakulski
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA.
| | - J Dou
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - N Lin
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - S J London
- National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, USA
| | - J A Colacino
- Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
- Department of Nutritional Sciences, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
- Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
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48
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Porter LF, Saptarshi N, Fang Y, Rathi S, den Hollander AI, de Jong EK, Clark SJ, Bishop PN, Olsen TW, Liloglou T, Chavali VRM, Paraoan L. Whole-genome methylation profiling of the retinal pigment epithelium of individuals with age-related macular degeneration reveals differential methylation of the SKI, GTF2H4, and TNXB genes. Clin Epigenetics 2019; 11:6. [PMID: 30642396 PMCID: PMC6332695 DOI: 10.1186/s13148-019-0608-2] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Accepted: 01/02/2019] [Indexed: 12/13/2022] Open
Abstract
Background Age-related macular degeneration (AMD) is a degenerative disorder of the central retina and the foremost cause of blindness. The retinal pigment epithelium (RPE) is a primary site of disease pathogenesis. The genetic basis of AMD is relatively well understood; however, this knowledge is yet to yield a treatment for the most prevalent non-neovascular disease forms. Therefore, tissue-specific epigenetic mechanisms of gene regulation are of considerable interest in AMD. We aimed to identify differentially methylated genes associated with AMD in the RPE and differentiate local DNA methylation aberrations from global DNA methylation changes, as local DNA methylation changes may be more amenable to therapeutic manipulation. Methods Epigenome-wide association study and targeted gene expression profiling were carried out in RPE cells from eyes of human donors. We performed genome-wide DNA methylation profiling (Illumina 450k BeadChip array) on RPE cells from 44 human donor eyes (25 AMD and 19 normal controls). We validated the findings using bisulfite pyrosequencing in 55 RPE samples (30 AMD and 25 normal controls) including technical (n = 38) and independent replicate samples (n = 17). Long interspersed nucleotide element 1 (LINE-1) analysis was then applied to assess global DNA methylation changes in the RPE. RT-qPCR on independent donor RPE samples was performed to assess gene expression changes. Results Genome-wide DNA methylation profiling identified differential methylation of multiple loci including the SKI proto-oncogene (SKI) (p = 1.18 × 10−9), general transcription factor IIH subunit H4 (GTF2H4) (p = 7.03 × 10−7), and Tenascin X (TNXB) (p = 6.30 × 10−6) genes in AMD. Bisulfite pyrosequencing validated the differentially methylated locus cg18934822 in SKI, and cg22508626 within GTF2H4, and excluded global DNA methylation changes in the RPE in AMD. We further demonstrated the differential expression of SKI, GTF2H4, and TNXB in the RPE of independent AMD donors. Conclusions We report the largest genome-wide methylation analysis of RPE in AMD along with associated gene expression changes to date, for the first-time reaching genome-wide significance, and identified novel targets for functional and future therapeutic intervention studies. The novel differentially methylated genes SKI and GTF2H4 have not been previously associated with AMD, and regulate disease pathways implicated in AMD, including TGF beta signaling (SKI) and transcription-dependent DNA repair mechanisms (GTF2H4). Electronic supplementary material The online version of this article (10.1186/s13148-019-0608-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Louise F Porter
- St Paul's Eye Unit, Royal Liverpool University Hospital, Liverpool, UK. .,Department of Eye and Vision Science, William Duncan Building, University of Liverpool, Liverpool, UK.
| | - Neil Saptarshi
- Department of Eye and Vision Science, William Duncan Building, University of Liverpool, Liverpool, UK
| | - Yongxiang Fang
- Centre for Genomic Research, University of Liverpool, Liverpool, UK
| | - Sonika Rathi
- Department of Ophthalmology, University of Pennsylvania School of Medicine, Philadelphia, USA
| | - Anneke I den Hollander
- Department of Ophthalmology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Eiko K de Jong
- Department of Ophthalmology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Simon J Clark
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Paul N Bishop
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.,Manchester Royal Eye Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | | | | | - Venkata R M Chavali
- Department of Ophthalmology, University of Pennsylvania School of Medicine, Philadelphia, USA
| | - Luminita Paraoan
- Department of Eye and Vision Science, William Duncan Building, University of Liverpool, Liverpool, UK
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49
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Reese SE, Xu CJ, den Dekker HT, Lee MK, Sikdar S, Ruiz-Arenas C, Merid SK, Rezwan FI, Page CM, Ullemar V, Melton PE, Oh SS, Yang IV, Burrows K, Söderhäll C, Jima DD, Gao L, Arathimos R, Küpers LK, Wielscher M, Rzehak P, Lahti J, Laprise C, Madore AM, Ward J, Bennett BD, Wang T, Bell DA, Vonk JM, Håberg SE, Zhao S, Karlsson R, Hollams E, Hu D, Richards AJ, Bergström A, Sharp GC, Felix JF, Bustamante M, Gruzieva O, Maguire RL, Gilliland F, Baïz N, Nohr EA, Corpeleijn E, Sebert S, Karmaus W, Grote V, Kajantie E, Magnus MC, Örtqvist AK, Eng C, Liu AH, Kull I, Jaddoe VWV, Sunyer J, Kere J, Hoyo C, Annesi-Maesano I, Arshad SH, Koletzko B, Brunekreef B, Binder EB, Räikkönen K, Reischl E, Holloway JW, Jarvelin MR, Snieder H, Kazmi N, Breton CV, Murphy SK, Pershagen G, Anto JM, Relton CL, Schwartz DA, Burchard EG, Huang RC, Nystad W, Almqvist C, Henderson AJ, Melén E, Duijts L, Koppelman GH, London SJ. Epigenome-wide meta-analysis of DNA methylation and childhood asthma. J Allergy Clin Immunol 2018; 143:2062-2074. [PMID: 30579849 DOI: 10.1016/j.jaci.2018.11.043] [Citation(s) in RCA: 120] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Revised: 10/01/2018] [Accepted: 11/16/2018] [Indexed: 12/22/2022]
Abstract
BACKGROUND Epigenetic mechanisms, including methylation, can contribute to childhood asthma. Identifying DNA methylation profiles in asthmatic patients can inform disease pathogenesis. OBJECTIVE We sought to identify differential DNA methylation in newborns and children related to childhood asthma. METHODS Within the Pregnancy And Childhood Epigenetics consortium, we performed epigenome-wide meta-analyses of school-age asthma in relation to CpG methylation (Illumina450K) in blood measured either in newborns, in prospective analyses, or cross-sectionally in school-aged children. We also identified differentially methylated regions. RESULTS In newborns (8 cohorts, 668 cases), 9 CpGs (and 35 regions) were differentially methylated (epigenome-wide significance, false discovery rate < 0.05) in relation to asthma development. In a cross-sectional meta-analysis of asthma and methylation in children (9 cohorts, 631 cases), we identified 179 CpGs (false discovery rate < 0.05) and 36 differentially methylated regions. In replication studies of methylation in other tissues, most of the 179 CpGs discovered in blood replicated, despite smaller sample sizes, in studies of nasal respiratory epithelium or eosinophils. Pathway analyses highlighted enrichment for asthma-relevant immune processes and overlap in pathways enriched both in newborns and children. Gene expression correlated with methylation at most loci. Functional annotation supports a regulatory effect on gene expression at many asthma-associated CpGs. Several implicated genes are targets for approved or experimental drugs, including IL5RA and KCNH2. CONCLUSION Novel loci differentially methylated in newborns represent potential biomarkers of risk of asthma by school age. Cross-sectional associations in children can reflect both risk for and effects of disease. Asthma-related differential methylation in blood in children was substantially replicated in eosinophils and respiratory epithelium.
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Affiliation(s)
- Sarah E Reese
- Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC
| | - Cheng-Jian Xu
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands; Department of Pediatric Pulmonology and Pediatric Allergology, Beatrix Children's Hospital, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands; GRIAC Research Institute, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Herman T den Dekker
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands; Department of Pediatrics, Division of Respiratory Medicine and Allergology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands; Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Mi Kyeong Lee
- Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC
| | - Sinjini Sikdar
- Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC
| | - Carlos Ruiz-Arenas
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Simon K Merid
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Faisal I Rezwan
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Christian M Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway; Oslo Centre for Biostatistics and Epidemiology, Oslo University Hospital, Oslo, Norway
| | - Vilhelmina Ullemar
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Phillip E Melton
- Curtin/UWA Centre for Genetic Origins of Health and Disease, Faculty of Health and Medical Sciences, University of Western Australia, Crawley, Australia; School of Pharmacy and Biomedical Sciences, Curtin University, Bentley, Australia
| | - Sam S Oh
- Department of Medicine, University of California San Francisco, San Francisco, Calif
| | - Ivana V Yang
- Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colo
| | - Kimberley Burrows
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom; Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Cilla Söderhäll
- Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden; Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - Dereje D Jima
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC; Center for Human Health and the Environment, North Carolina State University, Raleigh, NC
| | - Lu Gao
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, Calif
| | - Ryan Arathimos
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Leanne K Küpers
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom; Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Matthias Wielscher
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment & Health, School of Public Health, Imperial College London, London, United Kingdom
| | - Peter Rzehak
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - Jari Lahti
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland; Helsinki Collegium for Advanced Studies, University of Helsinki, Helsinki, Finland
| | - Catherine Laprise
- Centre intégré universitaire de santé et de services sociaux du Saguenay, Saguenay, Quebec, Canada; Département des sciences fondamentales, Université du Québec à Chicoutimi, Saguenay, Quebec, Canada
| | - Anne-Marie Madore
- Département des sciences fondamentales, Université du Québec à Chicoutimi, Saguenay, Quebec, Canada
| | - James Ward
- Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC
| | - Brian D Bennett
- Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC
| | - Tianyuan Wang
- Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC
| | - Douglas A Bell
- Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC
| | | | - Judith M Vonk
- GRIAC Research Institute, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands; Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Siri E Håberg
- Division of Mental and Physical Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Shanshan Zhao
- Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Elysia Hollams
- Telethon Kids Institute, University of Western Australia, Perth, Australia
| | - Donglei Hu
- Department of Medicine, University of California San Francisco, San Francisco, Calif
| | - Adam J Richards
- Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colo
| | - Anna Bergström
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Centre for Occupational and Environmental Medicine, Stockholm County Council, Stockholm, Sweden
| | - Gemma C Sharp
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom; Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; Bristol Dental School, University of Bristol, Bristol, United Kingdom
| | - Janine F Felix
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands; 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
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; Center for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Olena Gruzieva
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Centre for Occupational and Environmental Medicine, Stockholm County Council, Stockholm, Sweden
| | - Rachel L Maguire
- Department of Biological Sciences, North Carolina State University, Raleigh, NC; Department of Community and Family Medicine, Duke University Medical Center, Durham, NC
| | - Frank Gilliland
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, Calif
| | - Nour Baïz
- Epidemiology of Allergic and Respiratory Diseases Department, IPLESP, INSERM and UPMC Sorbonne Université, Paris, France
| | - Ellen A Nohr
- Research Unit for Gynaecology and Obstetrics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Eva Corpeleijn
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Sylvain Sebert
- Biocenter Oulu, University of Oulu, Oulu, Finland; Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland; Department of Genomics of Complex Diseases, School of Public Health, Imperial College London, London, United Kingdom
| | - Wilfried Karmaus
- Division of Epidemiology, Biostatistics and Environmental Health, School of Public Health, University of Memphis, Memphis, Tenn
| | - Veit Grote
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - Eero Kajantie
- Chronic Disease Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland; Department of Obstetrics and Gynaecology, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland; Hospital for Children and Adolescents, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland
| | - Maria C Magnus
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom; Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; Division of Mental and Physical Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Anne K Örtqvist
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Celeste Eng
- Department of Medicine, University of California San Francisco, San Francisco, Calif
| | | | - Inger Kull
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden; Sachs' Children's Hospital, Södersjukhuset, Stockholm, Sweden
| | - Vincent W V Jaddoe
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands; Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands; Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Jordi Sunyer
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Juha Kere
- Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden; Department of Medical and Molecular Genetics, King's College London, London, United Kingdom
| | - Cathrine Hoyo
- Center for Human Health and the Environment, North Carolina State University, Raleigh, NC; Department of Biological Sciences, North Carolina State University, Raleigh, NC
| | - Isabella Annesi-Maesano
- Epidemiology of Allergic and Respiratory Diseases Department, IPLESP, INSERM and UPMC Sorbonne Université, Paris, France
| | - Syed Hasan Arshad
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom; David Hide Asthma and Allergy Research Centre, Isle of Wight, United Kingdom
| | - Berthold Koletzko
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - Bert Brunekreef
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Elisabeth B Binder
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Ga; Max-Planck-Institute of Psychiatry, Munich, Germany
| | - Katri Räikkönen
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Eva Reischl
- Research Unit of Molecular Epidemiology, Institute of Epidemiology II, Helmholtz Zentrum Muenchen, Munich, Germany
| | - John W Holloway
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, United Kingdom; Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment & Health, School of Public Health, Imperial College London, London, United Kingdom; Biocenter Oulu, University of Oulu, Oulu, Finland; Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Nabila Kazmi
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Carrie V Breton
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, Calif
| | - Susan K Murphy
- Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, NC; Nicholas School of the Environment, Duke University, Durham, NC
| | - Göran Pershagen
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Centre for Occupational and Environmental Medicine, Stockholm County Council, Stockholm, Sweden
| | - Josep Maria Anto
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Caroline L Relton
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom; Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - David A Schwartz
- Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colo
| | - Esteban G Burchard
- Department of Medicine, University of California San Francisco, San Francisco, Calif; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, Calif
| | - Rae-Chi Huang
- Telethon Kids Institute, University of Western Australia, Perth, Australia
| | - Wenche Nystad
- Division of Mental and Physical Health, Norwegian Institute of Public Health, Oslo, Norway
| | - 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
| | - A John Henderson
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Erik Melén
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Sachs' Children's Hospital, Södersjukhuset, Stockholm, Sweden
| | - Liesbeth Duijts
- Department of Pediatrics, Division of Respiratory Medicine and Allergology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands; Department of Pediatrics, Division of Neonatology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Gerard H Koppelman
- Department of Pediatric Pulmonology and Pediatric Allergology, Beatrix Children's Hospital, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands; GRIAC Research Institute, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Stephanie J London
- Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC.
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Genetic variants influence on the placenta regulatory landscape. PLoS Genet 2018; 14:e1007785. [PMID: 30452450 PMCID: PMC6277118 DOI: 10.1371/journal.pgen.1007785] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2018] [Revised: 12/03/2018] [Accepted: 10/24/2018] [Indexed: 12/21/2022] Open
Abstract
From genomic association studies, quantitative trait loci analysis, and epigenomic mapping, it is evident that significant efforts are necessary to define genetic-epigenetic interactions and understand their role in disease susceptibility and progression. For this reason, an analysis of the effects of genetic variation on gene expression and DNA methylation in human placentas at high resolution and whole-genome coverage will have multiple mechanistic and practical implications. By producing and analyzing DNA sequence variation (n = 303), DNA methylation (n = 303) and mRNA expression data (n = 80) from placentas from healthy women, we investigate the regulatory landscape of the human placenta and offer analytical approaches to integrate different types of genomic data and address some potential limitations of current platforms. We distinguish two profiles of interaction between expression and DNA methylation, revealing linear or bimodal effects, reflecting differences in genomic context, transcription factor recruitment, and possibly cell subpopulations. These findings help to clarify the interactions of genetic, epigenetic, and transcriptional regulatory mechanisms in normal human placentas. They also provide strong evidence for genotype-driven modifications of transcription and DNA methylation in normal placentas. In addition to these mechanistic implications, the data and analytical methods presented here will improve the interpretability of genome-wide and epigenome-wide association studies for human traits and diseases that involve placental functions. The placenta is a critical organ playing multiple roles including oxygen and metabolite transfer from mother to fetus, hormone production, and vascular perfusion. With this study, we aimed to deliver a placenta-specific regulatory map based on a combination of publicly available and newly generated data. To complete this reference, we obtained genotype information (n = 303), DNA methylation (n = 303) and expression data (n = 80) for placentas from healthy women. Our analysis of methylation and expression quantitative trait loci (QTLs) and correlations between methylation and expression data were designed to identify fundamental associations between genome, transcriptome, and epigenome in this key fetal organ. The results provide high-resolution genetic and epigenetic maps specific to the placenta based on a representative ethnically diverse cohort. As interest and efforts are growing to better understand the etiology of placental disease and the impact of the environment on placental function these data will provide a reference and enhance future investigations.
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