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Sahoo K, Sundararajan V. Methods in DNA methylation array dataset analysis: A review. Comput Struct Biotechnol J 2024; 23:2304-2325. [PMID: 38845821 PMCID: PMC11153885 DOI: 10.1016/j.csbj.2024.05.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 04/25/2024] [Accepted: 05/08/2024] [Indexed: 06/09/2024] Open
Abstract
Understanding the intricate relationships between gene expression levels and epigenetic modifications in a genome is crucial to comprehending the pathogenic mechanisms of many diseases. With the advancement of DNA Methylome Profiling techniques, the emphasis on identifying Differentially Methylated Regions (DMRs/DMGs) has become crucial for biomarker discovery, offering new insights into the etiology of illnesses. This review surveys the current state of computational tools/algorithms for the analysis of microarray-based DNA methylation profiling datasets, focusing on key concepts underlying the diagnostic/prognostic CpG site extraction. It addresses methodological frameworks, algorithms, and pipelines employed by various authors, serving as a roadmap to address challenges and understand changing trends in the methodologies for analyzing array-based DNA methylation profiling datasets derived from diseased genomes. Additionally, it highlights the importance of integrating gene expression and methylation datasets for accurate biomarker identification, explores prognostic prediction models, and discusses molecular subtyping for disease classification. The review also emphasizes the contributions of machine learning, neural networks, and data mining to enhance diagnostic workflow development, thereby improving accuracy, precision, and robustness.
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Affiliation(s)
| | - Vino Sundararajan
- Correspondence to: Department of Bio Sciences, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore 632 014, Tamil Nadu, India.
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Alhassan D, Olbricht GR, Adekpedjou A. Differential methylation region detection via an array-adaptive normalized kernel-weighted model. PLoS One 2024; 19:e0306036. [PMID: 38941289 PMCID: PMC11213316 DOI: 10.1371/journal.pone.0306036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Accepted: 06/09/2024] [Indexed: 06/30/2024] Open
Abstract
A differentially methylated region (DMR) is a genomic region that has significantly different methylation patterns between biological conditions. Identifying DMRs between different biological conditions is critical for developing disease biomarkers. Although methods for detecting DMRs in microarray data have been introduced, developing methods with high precision, recall, and accuracy in determining the true length of DMRs remains a challenge. In this study, we propose a normalized kernel-weighted model to account for similar methylation profiles using the relative probe distance from "nearby" CpG sites. We also extend this model by proposing an array-adaptive version in attempt to account for the differences in probe spacing between Illumina's Infinium 450K and EPIC bead array respectively. We also study the asymptotic results of our proposed statistic. We compare our approach with a popular DMR detection method via simulation studies under large and small treatment effect settings. We also discuss the susceptibility of our method in detecting the true length of the DMRs under these two settings. Lastly, we demonstrate the biological usefulness of our method when combined with pathway analysis methods on oral cancer data. We have created an R package called idDMR, downloadable from GitHub repository with link: https://github.com/DanielAlhassan/idDMR, that allows for the convenient implementation of our array-adaptive DMR method.
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Affiliation(s)
- Daniel Alhassan
- Department of Mathematics and Statistics, Missouri University of Science and Technology, Rolla, MO, United States of America
| | - Gayla R. Olbricht
- Department of Mathematics and Statistics, Missouri University of Science and Technology, Rolla, MO, United States of America
| | - Akim Adekpedjou
- Department of Mathematics and Statistics, Missouri University of Science and Technology, Rolla, MO, United States of America
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3
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Marra PS, Seki T, Nishizawa Y, Chang G, Yamanishi K, Nishiguchi T, Shibata K, Braun P, Shinozaki G. Genome-wide DNA methylation analysis in female veterans with military sexual trauma and comorbid PTSD/MDD. J Affect Disord 2024; 351:624-630. [PMID: 38309478 PMCID: PMC11107447 DOI: 10.1016/j.jad.2024.01.241] [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: 08/28/2023] [Revised: 01/12/2024] [Accepted: 01/26/2024] [Indexed: 02/05/2024]
Abstract
BACKGROUND Military sexual trauma (MST) is a prevalent issue within the U.S. military. Victims are more likely to develop comorbid diseases such as posttraumatic stress disorder (PTSD) and major depressive disorder (MDD). Nonetheless, not everyone who suffers from MST develops PTSD and/or MDD. DNA methylation, which can regulate gene expression, might give us insight into the molecular mechanisms behind this discrepancy. Therefore, we sought to identify genomic loci and enriched biological pathways that differ between patients with and without MST, PTSD, and MDD. METHODS Saliva samples were collected from 113 female veterans. Following DNA extraction and processing, DNA methylation levels were measured through the Infinium HumanMethylationEPIC BeadChip array. We used limma and bump hunting methods to generate the differentially methylated positions and differentially methylated regions (DMRs), respectively. Concurrently, we used Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome to find enriched pathways. RESULTS A DMR close to the transcription start site of ZFP57 was differentially methylated between subjects with and without PTSD, replicating previous findings and emphasizing the potential role of ZFP57 in PTSD susceptibility. In the pathway analyses, none survived multiple correction, although top GO terms included some potentially relevant to MST, PTSD, and MDD etiology. CONCLUSION We conducted one of the first DNA methylation analyses investigating MST along with PTSD and MDD. In addition, we found one DMR near ZFP57 to be associated with PTSD. The replication of this finding indicates further investigation of ZFP57 in PTSD may be warranted.
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Affiliation(s)
- Pedro S Marra
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA, USA; Department of Psychiatry, University of Iowa Hospitals and Clinics, Iowa City, IA, USA; University of California, San Francisco School of Medicine, San Francisco, CA, USA
| | - Tomoteru Seki
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA, USA; Department of Psychiatry, Tokyo Medical University, Shinjuku, Tokyo, Japan
| | - Yoshitaka Nishizawa
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA, USA; Department of Neuropsychiatry, Osaka Medical and Pharmaceutical University, Takatsuki, Osaka, Japan
| | - Gloria Chang
- Department of Psychiatry, University of Iowa Hospitals and Clinics, Iowa City, IA, USA; Developmental Psychology Graduate Program, Department of Psychological Sciences, University of Missouri, Columbia, MO, USA
| | - Kyosuke Yamanishi
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA, USA; Department of Neuropsychiatry, Hyogo Medical University, Nishinomiya, Hyogo, Japan
| | - Tsuyoshi Nishiguchi
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA, USA; Department of Neuropsychiatry, Tottori University Faculty of Medicine, Yonago, Tottori, Japan
| | - Kazuki Shibata
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA, USA; Sumitomo Pharma Co. Ltd, Osaka, Osaka, Japan
| | - Patricia Braun
- Department of Biology, Clarke University, Dubuque, IA, USA
| | - Gen Shinozaki
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA, USA; Department of Psychiatry, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
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Chrétienneau C, Spindola LM, Vorspan F, Lagerberg TV, Marie‐Claire C, Bellivier F, Mouly S, Laplanche J, Bloch V, Le Hellard S, Icick R. An epigenetic candidate-gene association study of parental styles in suicide attempters with substance use disorders. Addict Biol 2024; 29:e13392. [PMID: 38564607 PMCID: PMC10986931 DOI: 10.1111/adb.13392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 02/07/2024] [Accepted: 02/27/2024] [Indexed: 04/04/2024]
Abstract
Suicide attempts (SA) are prevalent in substance use disorders (SUD). Epigenetic mechanisms may play a pivotal role in the molecular mechanisms of environmental effects eliciting suicidal behaviour in this population. Hypothalamic-pituitary-adrenal axis (HPA), oxytocin and neurotrophin pathways have been consistently involved in SA, yet , their interplay with childhood adversity remains unclear, particularly in SUD. In 24 outpatients with SUDs, we examined the relation between three parental dysfunctional styles and history of SA with methylation of 32 genes from these pathways, eventually analysing 823 methylation sites. Extensive phenotypic characterization was obtained using a semi-structured interview. Parental style was patient-reported using the Measure of Parental Style (MOPS) questionnaire, analysed with and without imputation of missing items. Linear regressions were performed to adjust for possible confounders, followed by multiple testing correction. We describe both differentially methylated probes (DMPs) and regions (DMRs) for each set of analyses (with and without imputation of MOPS items). Without imputation, five DMRs in OXTR, CRH and NTF3 significantly interacted with MOPS father abuse to increase the risk for lifetime SA, thus covering the three pathways. After imputation of missing MOPS items, two other DMPs from FKBP5 and SOCS3 significantly interacted with each of the three father styles to increase the risk for SA. Although our findings must be interpreted with caution due to small sample size, they suggest implications of stress reactivity genes in the suicidal risk of SUD patients and highlight the significance of father dysfunction as a potential marker of childhood adversity in SUD patients.
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Affiliation(s)
- Clara Chrétienneau
- Département Universitaire de Psychiatrie et de Médecine Addictologique, GHU APHP. NordAssistance Publique – Hôpitaux de ParisParisFrance
- INSERM UMR‐S 1144, Optimisation Thérapeutique en Neurospsychopharmacologie, OTeNUniversité Paris CitéParisFrance
- FHU NOR‐SUD Network of Research in Substance Use DisordersParisFrance
| | - Leticia M. Spindola
- NORMENT, Department of Clinical ScienceUniversity of BergenBergenNorway
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical GeneticsHaukeland University HospitalBergenNorway
| | - Florence Vorspan
- Département Universitaire de Psychiatrie et de Médecine Addictologique, GHU APHP. NordAssistance Publique – Hôpitaux de ParisParisFrance
- INSERM UMR‐S 1144, Optimisation Thérapeutique en Neurospsychopharmacologie, OTeNUniversité Paris CitéParisFrance
- FHU NOR‐SUD Network of Research in Substance Use DisordersParisFrance
| | - Trine Vik Lagerberg
- Division of Mental Health and Addiction Department of Psychology, Faculty of Social SciencesOslo University Hospital | University of Oslo, Oslo, NorwayOsloNorway
| | - Cynthia Marie‐Claire
- INSERM UMR‐S 1144, Optimisation Thérapeutique en Neurospsychopharmacologie, OTeNUniversité Paris CitéParisFrance
- FHU NOR‐SUD Network of Research in Substance Use DisordersParisFrance
| | - Frank Bellivier
- Département Universitaire de Psychiatrie et de Médecine Addictologique, GHU APHP. NordAssistance Publique – Hôpitaux de ParisParisFrance
- INSERM UMR‐S 1144, Optimisation Thérapeutique en Neurospsychopharmacologie, OTeNUniversité Paris CitéParisFrance
- FHU NOR‐SUD Network of Research in Substance Use DisordersParisFrance
| | - Stéphane Mouly
- Department of Internal MedicineLariboisière Hospital, Assistance Publique‐Hôpitaux de ParisParisFrance
- Université Paris CitéParisFrance
| | - Jean‐Louis Laplanche
- INSERM UMR‐S 1144, Optimisation Thérapeutique en Neurospsychopharmacologie, OTeNUniversité Paris CitéParisFrance
- FHU NOR‐SUD Network of Research in Substance Use DisordersParisFrance
| | - Vanessa Bloch
- INSERM UMR‐S 1144, Optimisation Thérapeutique en Neurospsychopharmacologie, OTeNUniversité Paris CitéParisFrance
- FHU NOR‐SUD Network of Research in Substance Use DisordersParisFrance
- Pharmacie HospitalièreAssistance Publique – Hôpitaux de Paris, GHU APHP. NordParisFrance
| | - Stéphanie Le Hellard
- NORMENT, Department of Clinical ScienceUniversity of BergenBergenNorway
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical GeneticsHaukeland University HospitalBergenNorway
| | - Romain Icick
- Département Universitaire de Psychiatrie et de Médecine Addictologique, GHU APHP. NordAssistance Publique – Hôpitaux de ParisParisFrance
- INSERM UMR‐S 1144, Optimisation Thérapeutique en Neurospsychopharmacologie, OTeNUniversité Paris CitéParisFrance
- FHU NOR‐SUD Network of Research in Substance Use DisordersParisFrance
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5
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Tesfaye M, Spindola LM, Stavrum AK, Shadrin A, Melle I, Andreassen OA, Le Hellard S. Sex effects on DNA methylation affect discovery in epigenome-wide association study of schizophrenia. Mol Psychiatry 2024:10.1038/s41380-024-02513-9. [PMID: 38503926 DOI: 10.1038/s41380-024-02513-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 02/27/2024] [Accepted: 03/01/2024] [Indexed: 03/21/2024]
Abstract
Sex differences in the epidemiology and clinical characteristics of schizophrenia are well-known; however, the molecular mechanisms underlying these differences remain unclear. Further, the potential advantages of sex-stratified meta-analyses of epigenome-wide association studies (EWAS) of schizophrenia have not been investigated. Here, we performed sex-stratified EWAS meta-analyses to investigate whether sex stratification improves discovery, and to identify differentially methylated regions (DMRs) in schizophrenia. Peripheral blood-derived DNA methylation data from 1519 cases of schizophrenia (male n = 989, female n = 530) and 1723 controls (male n = 997, female n = 726) from three publicly available datasets, and the TOP cohort were meta-analyzed to compare sex-specific, sex-stratified, and sex-adjusted EWAS. The predictive power of each model was assessed by polymethylation score (PMS). The number of schizophrenia-associated differentially methylated positions identified was higher for the sex-stratified model than for the sex-adjusted one. We identified 20 schizophrenia-associated DMRs in the sex-stratified analysis. PMS from sex-stratified analysis outperformed that from sex-adjusted analysis in predicting schizophrenia. Notably, PMSs from the sex-stratified and female-only analyses, but not those from sex-adjusted or the male-only analyses, significantly predicted schizophrenia in males. The findings suggest that sex-stratified EWAS meta-analyses improve the identification of schizophrenia-associated epigenetic changes and highlight an interaction between sex and schizophrenia status on DNA methylation. Sex-specific DNA methylation may have potential implications for precision psychiatry and the development of stratified treatments for schizophrenia.
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Grants
- 273291, 273446, 326813, 223273 Norges Forskningsråd (Research Council of Norway)
- 273291, 273446, 326813, 223273 Norges Forskningsråd (Research Council of Norway)
- 273291, 273446, 326813, 223273 Norges Forskningsråd (Research Council of Norway)
- 273291, 273446, 326813, 223273 Norges Forskningsråd (Research Council of Norway)
- 273291, 273446, 326813, 223273 Norges Forskningsråd (Research Council of Norway)
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Affiliation(s)
- Markos Tesfaye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway.
| | - Leticia M Spindola
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
- Bergen Center for Brain Plasticity, Haukeland University Hospital, Bergen, Norway
| | - Anne-Kristin Stavrum
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Alexey Shadrin
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Ingrid Melle
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Stephanie Le Hellard
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway.
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway.
- Bergen Center for Brain Plasticity, Haukeland University Hospital, Bergen, Norway.
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6
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Dill-McFarland KA, Simmons JD, Peterson GJ, Nguyen FK, Campo M, Benchek P, Stein CM, Vaisar T, Mayanja-Kizza H, Boom WH, Hawn TR. Epigenetic programming of host lipid metabolism associates with resistance to TST/IGRA conversion after exposure to Mycobacterium tuberculosis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.27.582348. [PMID: 38464296 PMCID: PMC10925331 DOI: 10.1101/2024.02.27.582348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Mycobacterium tuberculosis (Mtb) exposure leads to a range of outcomes including clearance, latent TB infection (LTBI), and pulmonary tuberculosis (TB). Some heavily exposed individuals resist tuberculin skin test (TST) and interferon gamma release assay (IGRA) conversion (RSTR), which suggests that they employ IFNγ-independent mechanisms of Mtb control. Here, we compare monocyte epigenetic profiles of RSTR and LTBI from a Ugandan household contact cohort. Chromatin accessibility did not differ between uninfected RSTR and LTBI monocytes. In contrast, methylation significantly differed at 174 CpG sites and across 63 genomic regions. Consistent with previous transcriptional findings in this cohort, differential methylation was enriched in lipid and cholesterol associated pathways including in the genes APOC3, KCNQ1, and PLA2G3. In addition, methylation was enriched in Hippo signaling, which is associated with cholesterol homeostasis and includes CIT and SHANK2. Lipid export and Hippo signaling pathways were also associated with gene expression in response to Mtb in RSTR as well as IFN stimulation in monocyte-derived macrophages (MDMs) from an independent healthy donor cohort. Moreover, serum-derived HDL from RSTR had elevated ABCA1-mediated cholesterol efflux capacity (CEC) compared to LTBI. Our findings suggest that resistance to TST/IGRA conversion is linked to regulation of lipid accumulation in monocytes, which could facilitate early Mtb clearance among RSTR subjects through IFNγ-independent mechanisms.
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Affiliation(s)
| | - Jason D Simmons
- Department of Medicine, University of Washington, Seattle, WA, USA
| | | | - Felicia K Nguyen
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Monica Campo
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Penelope Benchek
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA
| | - Catherine M Stein
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Tomas Vaisar
- Department of Medicine, University of Washington, Seattle, WA, USA
| | | | - W Henry Boom
- Department of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Thomas R Hawn
- Department of Medicine, University of Washington, Seattle, WA, USA
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7
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Nazer N, Sepehri MH, Mohammadzade H, Mehrmohamadi M. A novel approach toward optimal workflow selection for DNA methylation biomarker discovery. BMC Bioinformatics 2024; 25:37. [PMID: 38262949 PMCID: PMC10804576 DOI: 10.1186/s12859-024-05658-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 01/15/2024] [Indexed: 01/25/2024] Open
Abstract
DNA methylation is a major epigenetic modification involved in many physiological processes. Normal methylation patterns are disrupted in many diseases and methylation-based biomarkers have shown promise in several contexts. Marker discovery typically involves the analysis of publicly available DNA methylation data from high-throughput assays. Numerous methods for identification of differentially methylated biomarkers have been developed, making the need for best practices guidelines and context-specific analyses workflows exceedingly high. To this end, here we propose TASA, a novel method for simulating methylation array data in various scenarios. We then comprehensively assess different data analysis workflows using real and simulated data and suggest optimal start-to-finish analysis workflows. Our study demonstrates that the choice of analysis pipeline for DNA methylation-based marker discovery is crucial and different across different contexts.
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Affiliation(s)
- Naghme Nazer
- Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
| | | | - Hoda Mohammadzade
- Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
| | - Mahya Mehrmohamadi
- Department of Biotechnology, College of Science, University of Tehran, Tehran, Iran.
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8
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Wortinger LA, Stavrum AK, Shadrin AA, Szabo A, Rukke SH, Nerland S, Smelror RE, Jørgensen KN, Barth C, Andreou D, Weibell MA, Djurovic S, Andreassen OA, Thoresen M, Ursini G, Agartz I, Le Hellard S. Divergent epigenetic responses to perinatal asphyxia in severe mental disorders. Transl Psychiatry 2024; 14:16. [PMID: 38191519 PMCID: PMC10774425 DOI: 10.1038/s41398-023-02709-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 12/07/2023] [Accepted: 12/12/2023] [Indexed: 01/10/2024] Open
Abstract
Epigenetic modifications influenced by environmental exposures are molecular sources of phenotypic heterogeneity found in schizophrenia and bipolar disorder and may contribute to shared etiopathogenetic mechanisms of these two disorders. Newborns who experienced perinatal asphyxia have suffered reduced oxygen delivery to the brain around the time of birth, which increases the risk of later psychiatric diagnosis. This study aimed to investigate DNA methylation in blood cells for associations with a history of perinatal asphyxia, a neurologically harmful condition occurring within the biological environment of birth. We utilized prospective data from the Medical Birth Registry of Norway to identify incidents of perinatal asphyxia in 643 individuals with schizophrenia or bipolar disorder and 676 healthy controls. We performed an epigenome wide association study to distinguish differentially methylated positions associated with perinatal asphyxia. We found an interaction between methylation and exposure to perinatal asphyxia on case-control status, wherein having a history of perinatal asphyxia was associated with an increase of methylation in healthy controls and a decrease of methylation in patients on 4 regions of DNA important for brain development and function. The differentially methylated regions were observed in genes involved in oligodendrocyte survival and axonal myelination and functional recovery (LINGO3); assembly, maturation and maintenance of the brain (BLCAP;NNAT and NANOS2) and axonal transport processes and neural plasticity (SLC2A14). These findings are consistent with the notion that an opposite epigenetic response to perinatal asphyxia, in patients compared with controls, may contribute to molecular mechanisms of risk for schizophrenia and bipolar disorder.
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Affiliation(s)
- Laura A Wortinger
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Anne-Kristin Stavrum
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
- Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Alexey A Shadrin
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Attila Szabo
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | | | - Stener Nerland
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Runar Elle Smelror
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kjetil Nordbø Jørgensen
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatry, Telemark Hospital, Skien, Norway
| | - Claudia Barth
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dimitrios Andreou
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden
| | - Melissa A Weibell
- TIPS-Network for Clinical Research in Psychosis, Department of Psychiatry, Stavanger University Hospital, Stavanger, Norway
- Faculty of Health, Network for Medical Sciences, University of Stavanger, Stavanger, Norway
| | - Srdjan Djurovic
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Marianne Thoresen
- Department of Physiology, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
- Neonatal Neuroscience, Translational Health Sciences, University of Bristol, Bristol, United Kingdom
| | - Gianluca Ursini
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ingrid Agartz
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden
| | - Stephanie Le Hellard
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
- Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
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Giuili E, Grolaux R, Macedo CZNM, Desmyter L, Pichon B, Neuens S, Vilain C, Olsen C, Van Dooren S, Smits G, Defrance M. Comprehensive evaluation of the implementation of episignatures for diagnosis of neurodevelopmental disorders (NDDs). Hum Genet 2023; 142:1721-1735. [PMID: 37889307 PMCID: PMC10676303 DOI: 10.1007/s00439-023-02609-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 10/10/2023] [Indexed: 10/28/2023]
Abstract
Episignatures are popular tools for the diagnosis of rare neurodevelopmental disorders. They are commonly based on a set of differentially methylated CpGs used in combination with a support vector machine model. DNA methylation (DNAm) data often include missing values due to changes in data generation technology and batch effects. While many normalization methods exist for DNAm data, their impact on episignature performance have never been assessed. In addition, technologies to quantify DNAm evolve quickly and this may lead to poor transposition of existing episignatures generated on deprecated array versions to new ones. Indeed, probe removal between array versions, technologies or during preprocessing leads to missing values. Thus, the effect of missing data on episignature performance must also be carefully evaluated and addressed through imputation or an innovative approach to episignatures design. In this paper, we used data from patients suffering from Kabuki and Sotos syndrome to evaluate the influence of normalization methods, classification models and missing data on the prediction performances of two existing episignatures. We compare how six popular normalization methods for methylarray data affect episignature classification performances in Kabuki and Sotos syndromes and provide best practice suggestions when building new episignatures. In this setting, we show that Illumina, Noob or Funnorm normalization methods achieved higher classification performances on the testing sets compared to Quantile, Raw and Swan normalization methods. We further show that penalized logistic regression and support vector machines perform best in the classification of Kabuki and Sotos syndrome patients. Then, we describe a new paradigm to build episignatures based on the detection of differentially methylated regions (DMRs) and evaluate their performance compared to classical differentially methylated cytosines (DMCs)-based episignatures in the presence of missing data. We show that the performance of classical DMC-based episignatures suffers from the presence of missing data more than the DMR-based approach. We present a comprehensive evaluation of how the normalization of DNA methylation data affects episignature performance, using three popular classification models. We further evaluate how missing data affect those models' predictions. Finally, we propose a novel methodology to develop episignatures based on differentially methylated regions identification and show how this method slightly outperforms classical episignatures in the presence of missing data.
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Affiliation(s)
- Edoardo Giuili
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Brussels, Belgium
| | - Robin Grolaux
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Brussels, Belgium
| | - Catarina Z N M Macedo
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Brussels, Belgium
| | - Laurence Desmyter
- Center for Human Genetics, Hôpital Erasme, Hôpital Universitaire de Bruxelles, Université Libre de Bruxelles, Brussels, Belgium
| | - Bruno Pichon
- Center for Human Genetics, Hôpital Erasme, Hôpital Universitaire de Bruxelles, Université Libre de Bruxelles, Brussels, Belgium
| | - Sebastian Neuens
- Center for Human Genetics, Hôpital Erasme, Hôpital Universitaire de Bruxelles, Université Libre de Bruxelles, Brussels, Belgium
- Department of Genetics, Hôpital Universitaire Des Enfants Reine Fabiola, Hôpital Universitaire de Bruxelles, Université Libre de Bruxelles, Brussels, Belgium
| | - Catheline Vilain
- Center for Human Genetics, Hôpital Erasme, Hôpital Universitaire de Bruxelles, Université Libre de Bruxelles, Brussels, Belgium
- Department of Genetics, Hôpital Universitaire Des Enfants Reine Fabiola, Hôpital Universitaire de Bruxelles, Université Libre de Bruxelles, Brussels, Belgium
| | - Catharina Olsen
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Brussels, Belgium
- Clinical Sciences, Research Group Reproduction and Genetics, Brussels Interuniversity Genomics High Throughput Core (BRIGHTcore), Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
- Clinical Sciences, Research Group Reproduction and Genetics, Centre for Medical Genetics, Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
| | - Sonia Van Dooren
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Brussels, Belgium
- Clinical Sciences, Research Group Reproduction and Genetics, Brussels Interuniversity Genomics High Throughput Core (BRIGHTcore), Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
- Clinical Sciences, Research Group Reproduction and Genetics, Centre for Medical Genetics, Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
| | - Guillaume Smits
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Brussels, Belgium
- Center for Human Genetics, Hôpital Erasme, Hôpital Universitaire de Bruxelles, Université Libre de Bruxelles, Brussels, Belgium
- Department of Genetics, Hôpital Universitaire Des Enfants Reine Fabiola, Hôpital Universitaire de Bruxelles, Université Libre de Bruxelles, Brussels, Belgium
| | - Matthieu Defrance
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Brussels, Belgium.
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10
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Zheng Y, Lunetta KL, Liu C, Smith AK, Sherva R, Miller MW, Logue MW. A novel principal component based method for identifying differentially methylated regions in Illumina Infinium MethylationEPIC BeadChip data. Epigenetics 2023; 18:2207959. [PMID: 37196182 PMCID: PMC10193914 DOI: 10.1080/15592294.2023.2207959] [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: 09/18/2022] [Revised: 03/22/2023] [Accepted: 04/19/2023] [Indexed: 05/19/2023] Open
Abstract
Differentially methylated regions (DMRs) are genomic regions with methylation patterns across multiple CpG sites that are associated with a phenotype. In this study, we proposed a Principal Component (PC) based DMR analysis method for use with data generated using the Illumina Infinium MethylationEPIC BeadChip (EPIC) array. We obtained methylation residuals by regressing the M-values of CpGs within a region on covariates, extracted PCs of the residuals, and then combined association information across PCs to obtain regional significance. Simulation-based genome-wide false positive (GFP) rates and true positive rates were estimated under a variety of conditions before determining the final version of our method, which we have named DMRPC. Then, DMRPC and another DMR method, coMethDMR, were used to perform epigenome-wide analyses of several phenotypes known to have multiple associated methylation loci (age, sex, and smoking) in a discovery and a replication cohort. Among regions that were analysed by both methods, DMRPC identified 50% more genome-wide significant age-associated DMRs than coMethDMR. The replication rate for the loci that were identified by only DMRPC was higher than the rate for those that were identified by only coMethDMR (90% for DMRPC vs. 76% for coMethDMR). Furthermore, DMRPC identified replicable associations in regions of moderate between-CpG correlation which are typically not analysed by coMethDMR. For the analyses of sex and smoking, the advantage of DMRPC was less clear. In conclusion, DMRPC is a new powerful DMR discovery tool that retains power in genomic regions with moderate correlation across CpGs.
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Affiliation(s)
- Yuanchao Zheng
- National Center for PTSD, VA Boston Healthcare System, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Kathryn L. Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Alicia K. Smith
- Department of Gynecology and Obstetrics, Emory University, Atlanta, GA, USA
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Richard Sherva
- National Center for PTSD, VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA
| | - Mark W. Miller
- National Center for PTSD, VA Boston Healthcare System, Boston, MA, USA
- Biomedical Genetics, Boston University School of Medicine, Boston, MA, USA
| | - Mark W. Logue
- National Center for PTSD, VA Boston Healthcare System, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA
- Biomedical Genetics, Boston University School of Medicine, Boston, MA, USA
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11
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Chatterjee S, Chowdhury S, Ryu D, Basu S. Bayesian functional data analysis over dependent regions and its application for identification of differentially methylated regions. Biometrics 2023; 79:3294-3306. [PMID: 37479677 DOI: 10.1111/biom.13902] [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: 09/21/2021] [Accepted: 05/08/2023] [Indexed: 07/23/2023]
Abstract
We consider a Bayesian functional data analysis for observations measured as extremely long sequences. Splitting the sequence into several small windows with manageable lengths, the windows may not be independent especially when they are neighboring each other. We propose to utilize Bayesian smoothing splines to estimate individual functional patterns within each window and to establish transition models for parameters involved in each window to address the dependence structure between windows. The functional difference of groups of individuals at each window can be evaluated by the Bayes factor based on Markov Chain Monte Carlo samples in the analysis. In this paper, we examine the proposed method through simulation studies and apply it to identify differentially methylated genetic regions in TCGA lung adenocarcinoma data.
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Affiliation(s)
- Suvo Chatterjee
- Department of Epidemiology and Biostatistics, Indiana University, School of Public Health, Bloomington, Indiana, USA
| | - Shrabanti Chowdhury
- Department of Genetics and Genomic Sciences and Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Duchwan Ryu
- Department of Statistics and Actuarial Science, Northern Illinois University, Illinois, USA
| | - Sanjib Basu
- Division of Epidemiology and Biostatistics, University of Illinois Chicago, Illinois, USA
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12
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Zhang L, Li J. Unlocking the secrets: the power of methylation-based cfDNA detection of tissue damage in organ systems. Clin Epigenetics 2023; 15:168. [PMID: 37858233 PMCID: PMC10588141 DOI: 10.1186/s13148-023-01585-8] [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: 06/08/2023] [Accepted: 10/11/2023] [Indexed: 10/21/2023] Open
Abstract
BACKGROUND Detecting organ and tissue damage is essential for early diagnosis, treatment decisions, and monitoring disease progression. Methylation-based assays offer a promising approach, as DNA methylation patterns can change in response to tissue damage. These assays have potential applications in early detection, monitoring disease progression, evaluating treatment efficacy, and assessing organ viability for transplantation. cfDNA released into the bloodstream upon tissue or organ injury can serve as a biomarker for damage. The epigenetic state of cfDNA, including DNA methylation patterns, can provide insights into the extent of tissue and organ damage. CONTENT Firstly, this review highlights DNA methylation as an extensively studied epigenetic modification that plays a pivotal role in processes such as cell growth, differentiation, and disease development. It then presents a variety of highly precise 5-mC methylation detection techniques that serve as powerful tools for gaining profound insights into epigenetic alterations linked with tissue damage. Subsequently, the review delves into the mechanisms underlying DNA methylation changes in organ and tissue damage, encompassing inflammation, oxidative stress, and DNA damage repair mechanisms. Next, it addresses the current research status of cfDNA methylation in the detection of specific organ tissues and organ damage. Finally, it provides an overview of the multiple steps involved in identifying specific methylation markers associated with tissue and organ damage for clinical trials. This review will explore the mechanisms and current state of research on cfDNA methylation-based assay detecting organ and tissue damage, the underlying mechanisms, and potential applications in clinical practice.
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Affiliation(s)
- Lijing Zhang
- National Center for Clinical Laboratories, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology, No. 1 Dahua Road, Dongdan, Beijing, 100730, People's Republic of China
- Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing Hospital, Beijing, People's Republic of China
- Beijing Engineering Research Center of Laboratory Medicine, Beijing, People's Republic of China
| | - Jinming Li
- National Center for Clinical Laboratories, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology, No. 1 Dahua Road, Dongdan, Beijing, 100730, People's Republic of China.
- Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing Hospital, Beijing, People's Republic of China.
- Beijing Engineering Research Center of Laboratory Medicine, Beijing, People's Republic of China.
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13
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Collender P, Bozack AK, Veazie S, Nwanaji-Enwerem JC, Van Der Laan L, Kogut K, Riddell C, Eskenazi B, Holland N, Deardorff J, Cardenas A. Maternal adverse childhood experiences (ACEs) and DNA methylation of newborns in cord blood. Clin Epigenetics 2023; 15:162. [PMID: 37845746 PMCID: PMC10577922 DOI: 10.1186/s13148-023-01581-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 10/07/2023] [Indexed: 10/18/2023] Open
Abstract
BACKGROUND Adverse childhood experiences (ACEs) increase the risk of poor health outcomes later in life. Psychosocial stressors may also have intergenerational health effects by which parental ACEs are associated with mental and physical health of children. Epigenetic programming may be one mechanism linking parental ACEs to child health. This study aimed to investigate epigenome-wide associations of maternal preconception ACEs with DNA methylation patterns of children. In the Center for the Health Assessment of Mothers and Children of Salinas study, cord blood DNA methylation was measured using the Illumina HumanMethylation450 BeadChip. Preconception ACEs, which occurred during the mothers' childhoods, were collected using a standard ACE questionnaire including 10 ACE indicators. Maternal ACE exposures were defined in this study as (1) the total number of ACEs; (2) the total number of ACEs categorized as 0, 1-3, and > 4; and (3) individual ACEs. Associations of ACE exposures with differential methylated positions, regions, and CpG modules determined using weighted gene co-expression network analysis were evaluated adjusting for covariates. RESULTS Data on maternal ACEs and cord blood DNA methylation were available for 196 mother/newborn pairs. One differential methylated position was associated with maternal experience of emotional abuse (cg05486260/FAM135B gene; q value < 0.05). Five differential methylated regions were significantly associated with the total number of ACEs, and 36 unique differential methylated regions were associated with individual ACEs (Šidák p value < 0.05). Fifteen CpG modules were significantly correlated with the total number of ACEs or individual ACEs, of which 8 remained significant in fully adjusted models (p value < 0.05). Significant modules were enriched for pathways related to neurological and immune development and function. CONCLUSIONS Maternal ACEs prior to conception were associated with cord blood DNA methylation of offspring at birth. Although there was limited overlap between differential methylated regions and CpGs in modules associated with ACE exposures, statistically significant regions and networks were related to genes involved in neurological and immune function. Findings may provide insights to pathways linking psychosocial stressors to health. Further research is needed to understand the relationship between changes in DNA methylation and child health.
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Affiliation(s)
- Phillip Collender
- Division of Environmental Health Sciences, University of California, Berkeley, CA, USA
| | - Anne K Bozack
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Research Park, 1701 Page Mill Road, Stanford, CA, 94304, USA
| | - Stephanie Veazie
- Division of Epidemiology, School of Public Health, University of California, Berkeley, CA, USA
| | - Jamaji C Nwanaji-Enwerem
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
- Department of Emergency Medicine, School of Medicine, Emory University, Atlanta, GA, USA
| | - Lars Van Der Laan
- Department of Statistics, University of Washington, Seattle, WA, USA
| | - Katherine Kogut
- Division of Epidemiology, School of Public Health, University of California, Berkeley, CA, USA
- Center for Environmental Research of Community Health, CERCH, School of Public Health, University of California, Berkeley, CA, USA
| | - Corinne Riddell
- Division of Epidemiology, School of Public Health, University of California, Berkeley, CA, USA
- Division of Biostatistics, School of Public Health, University of California, Berkeley, CA, USA
| | - Brenda Eskenazi
- Center for Environmental Research of Community Health, CERCH, School of Public Health, University of California, Berkeley, CA, USA
- Division of Community Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
| | - Nina Holland
- Division of Environmental Health Sciences, University of California, Berkeley, CA, USA
- Center for Environmental Research of Community Health, CERCH, School of Public Health, University of California, Berkeley, CA, USA
| | - Julianna Deardorff
- Center for Environmental Research of Community Health, CERCH, School of Public Health, University of California, Berkeley, CA, USA
- Division of Community Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
| | - Andres Cardenas
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Research Park, 1701 Page Mill Road, Stanford, CA, 94304, USA.
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
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14
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Bodelon C, Gierach GL, Hatch EE, Riseberg E, Hutchinson A, Yeager M, Sandler DP, Taylor JA, Hoover RN, Xu Z, Titus L, Palmer JR, Troisi R. In utero exposure to diethylstilbestrol and blood DNA methylation in adult women: Results from a meta-analysis of two cohort studies. ENVIRONMENTAL RESEARCH 2023; 231:115990. [PMID: 37149030 PMCID: PMC10442904 DOI: 10.1016/j.envres.2023.115990] [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: 02/13/2023] [Revised: 04/10/2023] [Accepted: 04/24/2023] [Indexed: 05/08/2023]
Abstract
BACKGROUND Prenatal exposure to diethylstilbestrol (DES) is associated with several adverse health outcomes. Animal studies have shown associations between prenatal DES exposure and DNA methylation. OBJECTIVE The aim of this study was to explore blood DNA methylation in women exposed and unexposed to DES in utero. METHODS Sixty women (40 exposed and 20 unexposed) in the National Cancer Institute's Combined DES Cohort Study and 199 women (99 exposed and 100 unexposed women) in the Sister Study Cohort were included in this analysis. Within each study, robust linear regression models were used to assess associations between DES exposure and blood DNA methylation. Study-specific associations were combined using fixed-effect meta-analysis with inverse variance weights. Our analysis focused on CpG sites located within nine candidate genes identified in animal models. We further explored whether in utero DES exposure was associated with age acceleration. RESULTS Blood DNA methylation levels at 10 CpG sites in six of the nine candidate genes were statistically significantly associated with prenatal DES exposure (P < 0.05) in this meta-analysis. Genes included EGF, EMB, EGFR, WNT11, FOS, and TGFB1, which are related to cell proliferation and differentiation. The most statistically significant CpG site was cg19830739 in gene EGF, and it was associated with lower methylation levels in women prenatally exposed to DES compared with those not exposed (P < 0.0001; false discovery rate<0.05). The association between prenatal DES exposure in utero and age acceleration was not statistically significant (P = 0.07 for meta-analyzed results). CONCLUSIONS There are few opportunities to investigate the effects of prenatal DES exposure. These findings suggest that in utero DES exposure may be associated with differential blood DNA methylation levels, which could mediate the increased risk of several adverse health outcomes observed in exposed women. Our findings need further evaluation using larger data sets.
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Affiliation(s)
- Clara Bodelon
- Integrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
| | - Gretchen L Gierach
- Integrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Elizabeth E Hatch
- Department of Epidemiology, Boston University School of Public Health, Boston University, Boston, MA, USA
| | - Emily Riseberg
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Amy Hutchinson
- Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Meredith Yeager
- Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA; Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Robert N Hoover
- Trans-Divisional Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Linda Titus
- Public Health, Muskie School of Public Service, University of Southern Maine, Portland, ME, USA
| | - Julie R Palmer
- Slone Epidemiology Center and Department of Medicine, Boston University School of Medicine, Boston University, Boston, MA, USA
| | - Rebecca Troisi
- Trans-Divisional Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
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15
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Ohnmacht AJ, Rajamani A, Avar G, Kutkaite G, Gonçalves E, Saur D, Menden MP. The pharmacoepigenomic landscape of cancer cell lines reveals the epigenetic component of drug sensitivity. Commun Biol 2023; 6:825. [PMID: 37558831 PMCID: PMC10412573 DOI: 10.1038/s42003-023-05198-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] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Accepted: 08/01/2023] [Indexed: 08/11/2023] Open
Abstract
Aberrant DNA methylation accompanies genetic alterations during oncogenesis and tumour homeostasis and contributes to the transcriptional deregulation of key signalling pathways in cancer. Despite increasing efforts in DNA methylation profiling of cancer patients, there is still a lack of epigenetic biomarkers to predict treatment efficacy. To address this, we analyse 721 cancer cell lines across 22 cancer types treated with 453 anti-cancer compounds. We systematically detect the predictive component of DNA methylation in the context of transcriptional and mutational patterns, i.e., in total 19 DNA methylation biomarkers across 17 drugs and five cancer types. DNA methylation constitutes drug sensitivity biomarkers by mediating the expression of proximal genes, thereby enhancing biological signals across multi-omics data modalities. Our method reproduces anticipated associations, and in addition, we find that the NEK9 promoter hypermethylation may confer sensitivity to the NEDD8-activating enzyme (NAE) inhibitor pevonedistat in melanoma through downregulation of NEK9. In summary, we envision that epigenomics will refine existing patient stratification, thus empowering the next generation of precision oncology.
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Affiliation(s)
- Alexander Joschua Ohnmacht
- Computational Health Center, Helmholtz Munich, 85764, Neuherberg, Germany
- Department of Biology, Ludwig-Maximilians University Munich, 82152, Martinsried, Germany
| | - Anantharamanan Rajamani
- Division of Translational Cancer Research, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
- Chair of Translational Cancer Research and Institute of Experimental Cancer Therapy, Klinikum rechts der Isar, School of Medicine, Technische Universität München, Ismaninger Str. 22, 81675, Munich, Germany
- Center for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany
| | - Göksu Avar
- Computational Health Center, Helmholtz Munich, 85764, Neuherberg, Germany
- Department of Biology, Ludwig-Maximilians University Munich, 82152, Martinsried, Germany
| | - Ginte Kutkaite
- Computational Health Center, Helmholtz Munich, 85764, Neuherberg, Germany
- Department of Biology, Ludwig-Maximilians University Munich, 82152, Martinsried, Germany
| | - Emanuel Gonçalves
- Instituto Superior Técnico (IST), Universidade de Lisboa, 1049-001, Lisbon, Portugal
- INESC-ID, 1000-029, Lisbon, Portugal
| | - Dieter Saur
- Division of Translational Cancer Research, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
- Chair of Translational Cancer Research and Institute of Experimental Cancer Therapy, Klinikum rechts der Isar, School of Medicine, Technische Universität München, Ismaninger Str. 22, 81675, Munich, Germany
- Center for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany
| | - Michael Patrick Menden
- Computational Health Center, Helmholtz Munich, 85764, Neuherberg, Germany.
- Department of Biology, Ludwig-Maximilians University Munich, 82152, Martinsried, Germany.
- Department of Biochemistry and Pharmacology, University of Melbourne, Victoria, VIC, 3010, Australia.
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16
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Wang C, Amini H, Xu Z, Peralta AA, Yazdi MD, Qiu X, Wei Y, Just A, Heiss J, Hou L, Zheng Y, Coull BA, Kosheleva A, Baccarelli AA, Schwartz JD. Long-term exposure to ambient fine particulate components and leukocyte epigenome-wide DNA Methylation in older men: the Normative Aging Study. Environ Health 2023; 22:54. [PMID: 37550674 PMCID: PMC10405403 DOI: 10.1186/s12940-023-01007-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 07/26/2023] [Indexed: 08/09/2023]
Abstract
BACKGROUND Epigenome-wide association studies of ambient fine particulate matter (PM2.5) have been reported. However, few have examined PM2.5 components (PMCs) and sources or included repeated measures. The lack of high-resolution exposure measurements is the key limitation. We hypothesized that significant changes in DNA methylation might vary by PMCs and the sources. METHODS We predicted the annual average of 14 PMCs using novel high-resolution exposure models across the contiguous U.S., between 2000-2018. The resolution was 50 m × 50 m in the Greater Boston Area. We also identified PM2.5 sources using positive matrix factorization. We repeatedly collected blood samples and measured leukocyte DNAm with the Illumina HumanMethylation450K BeadChip in the Normative Aging Study. We then used median regression with subject-specific intercepts to estimate the associations between long-term (one-year) exposure to PMCs / PM2.5 sources and DNA methylation at individual cytosine-phosphate-guanine CpG sites. Significant probes were identified by the number of independent degrees of freedom approach, using the number of principal components explaining > 95% of the variation of the DNA methylation data. We also performed regional and pathway analyses to identify significant regions and pathways. RESULTS We included 669 men with 1,178 visits between 2000-2013. The subjects had a mean age of 75 years. The identified probes, regions, and pathways varied by PMCs and their sources. For example, iron was associated with 6 probes and 6 regions, whereas nitrate was associated with 15 probes and 3 regions. The identified pathways from biomass burning, coal burning, and heavy fuel oil combustion sources were associated with cancer, inflammation, and cardiovascular diseases, whereas there were no pathways associated with all traffic. CONCLUSIONS Our findings showed that the effects of PM2.5 on DNAm varied by its PMCs and sources.
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Affiliation(s)
- Cuicui Wang
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.
| | - Heresh Amini
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Department of Public Health, Faculty of Health and Medical Sciences, Section of Environmental Health, University of Copenhagen, Copenhagen, Denmark
| | - Zongli Xu
- Biostatistics & Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, Durham, NC, USA
| | - Adjani A Peralta
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Mahdieh Danesh Yazdi
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Program in Public Health, Department of Family, Population, and Preventive Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Xinye Qiu
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Yaguang Wei
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Allan Just
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Jonathan Heiss
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Yinan Zheng
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Brent A Coull
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Anna Kosheleva
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Columbia Mailman School of Public Health, New York, NY, 10032, USA
| | - Joel D Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
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17
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Almojil D, Diawara A, Soulama I, Dieng MM, Manikandan V, Sermé SS, Sombié S, Diarra A, Barry A, Coulibaly SA, Sirima SB, Idaghdour Y. Impact of Plasmodium falciparum infection on DNA methylation of circulating immune cells. Front Genet 2023; 14:1197933. [PMID: 37470040 PMCID: PMC10352500 DOI: 10.3389/fgene.2023.1197933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 06/02/2023] [Indexed: 07/21/2023] Open
Abstract
The regulation of immune cell responses to infection is a complex process that involves various molecular mechanisms, including epigenetic regulation. DNA methylation has been shown to play central roles in regulating gene expression and modulating cell response during infection. However, the nature and extent to which DNA methylation is involved in the host immune response in human malaria remains largely unknown. Here, we present a longitudinal study investigating the temporal dynamics of genome-wide in vivo DNA methylation profiles using 189 MethylationEPIC 850 K profiles from 66 children in Burkina Faso, West Africa, sampled three times: before infection, during symptomatic parasitemia, and after malaria treatment. The results revealed major changes in the DNA methylation profiles of children in response to both Plasmodium falciparum infection and malaria treatment, with widespread hypomethylation of CpGs upon infection (82% of 6.8 K differentially methylated regions). We document a remarkable reversal of CpG methylation profiles upon treatment to pre-infection states. These changes implicate divergence in core immune processes, including the regulation of lymphocyte, neutrophil, and myeloid leukocyte function. Integrative DNA methylation-mRNA analysis of a top differentially methylated region overlapping the pro-inflammatory gene TNF implicates DNA methylation of TNF cis regulatory elements in the molecular mechanisms of TNF regulation in human malaria. Our results highlight a central role of epigenetic regulation in mounting the host immune response to P. falciparum infection and in response to malaria treatment.
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Affiliation(s)
- Dareen Almojil
- Program in Biology, Division of Science and Mathematics, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Aïssatou Diawara
- Program in Biology, Division of Science and Mathematics, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Issiaka Soulama
- Centre National de Recherche et de Formation sur le Paludisme, Ouagadougou, Burkina Faso
| | - Mame Massar Dieng
- Program in Biology, Division of Science and Mathematics, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Vinu Manikandan
- Program in Biology, Division of Science and Mathematics, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Samuel S. Sermé
- Centre National de Recherche et de Formation sur le Paludisme, Ouagadougou, Burkina Faso
| | - Salif Sombié
- Centre National de Recherche et de Formation sur le Paludisme, Ouagadougou, Burkina Faso
| | - Amidou Diarra
- Centre National de Recherche et de Formation sur le Paludisme, Ouagadougou, Burkina Faso
| | - Aissata Barry
- Centre National de Recherche et de Formation sur le Paludisme, Ouagadougou, Burkina Faso
| | | | - Sodiomon B. Sirima
- Centre National de Recherche et de Formation sur le Paludisme, Ouagadougou, Burkina Faso
| | - Youssef Idaghdour
- Program in Biology, Division of Science and Mathematics, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
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18
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Ventham NT, Kennedy NA, Kalla R, Adams AT, Noble A, Ennis H, Mowat C, Dunlop MG, Satsangi J. Genome-Wide Methylation Profiling in 229 Patients With Crohn's Disease Requiring Intestinal Resection: Epigenetic Analysis of the Trial of Prevention of Post-operative Crohn's Disease (TOPPIC). Cell Mol Gastroenterol Hepatol 2023; 16:431-450. [PMID: 37331566 PMCID: PMC10372903 DOI: 10.1016/j.jcmgh.2023.06.001] [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: 08/04/2022] [Revised: 06/02/2023] [Accepted: 06/02/2023] [Indexed: 06/20/2023]
Abstract
BACKGROUND & AIMS DNA methylation alterations may provide important insights into gene-environment interaction in cancer, aging, and complex diseases, such as inflammatory bowel disease (IBD). We aim first to determine whether the circulating DNA methylome in patients requiring surgery may predict Crohn's disease (CD) recurrence following intestinal resection; and second to compare the circulating methylome seen in patients with established CD with that we had reported in a series of inception cohorts. METHODS TOPPIC was a placebo-controlled, randomized controlled trial of 6-mercaptopurine at 29 UK centers in patients with CD undergoing ileocolic resection between 2008 and 2012. Genomic DNA was extracted from whole blood samples from 229 of the 240 patients taken before intestinal surgery and analyzed using 450KHumanMethylation and Infinium Omni Express Exome arrays (Illumina, San Diego, CA). Coprimary objectives were to determine whether methylation alterations may predict clinical disease recurrence; and to assess whether the epigenetic alterations previously reported in newly diagnosed IBD were present in the patients with CD recruited into the TOPPIC study. Differential methylation and variance analysis was performed comparing patients with and without clinical evidence of recurrence. Secondary analyses included investigation of methylation associations with smoking, genotype (MeQTLs), and chronologic age. Validation of our previously published case-control observation of the methylome was performed using historical control data (CD, n = 123; Control, n = 198). RESULTS CD recurrence in patients following surgery is associated with 5 differentially methylated positions (Holm P < .05), including probes mapping to WHSC1 (P = 4.1 × 10-9, Holm P = .002) and EFNA3 (P = 4.9 × 10-8, Holm P = .02). Five differentially variable positions are demonstrated in the group of patients with evidence of disease recurrence including a probe mapping to MAD1L1 (P = 6.4 × 10-5). DNA methylation clock analyses demonstrated significant age acceleration in CD compared with control subjects (GrimAge + 2 years; 95% confidence interval, 1.2-2.7 years), with some evidence for accelerated aging in patients with CD with disease recurrence following surgery (GrimAge +1.04 years; 95% confidence interval, -0.04 to 2.22). Significant methylation differences between CD cases and control subjects were seen by comparing this cohort in conjunction with previously published control data, including validation of our previously described differentially methylated positions (RPS6KA2 P = 1.2 × 10-19, SBNO2 = 1.2 × 10-11) and regions (TXK [false discovery rate, P = 3.6 × 10-14], WRAP73 [false discovery rate, P = 1.9 × 10-9], VMP1 [false discovery rate, P = 1.7 × 10-7], and ITGB2 [false discovery rate, P = 1.4 × 10-7]). CONCLUSIONS We demonstrate differential methylation and differentially variable methylation in patients developing clinical recurrence within 3 years of surgery. Moreover, we report replication of the CD-associated methylome, previously characterized only in adult and pediatric inception cohorts, in patients with medically refractory disease needing surgery.
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Affiliation(s)
- Nicholas T Ventham
- Centre for Genomic and Experimental Medicine, The University of Edinburgh, Edinburgh, Midlothian, United Kingdom.
| | - Nicholas A Kennedy
- Centre for Genomic and Experimental Medicine, The University of Edinburgh, Edinburgh, Midlothian, United Kingdom
| | - Rahul Kalla
- Centre for Genomic and Experimental Medicine, The University of Edinburgh, Edinburgh, Midlothian, United Kingdom
| | - Alex T Adams
- Centre for Genomic and Experimental Medicine, The University of Edinburgh, Edinburgh, Midlothian, United Kingdom
| | - Alexandra Noble
- Centre for Genomic and Experimental Medicine, The University of Edinburgh, Edinburgh, Midlothian, United Kingdom
| | - Holly Ennis
- Centre for Genomic and Experimental Medicine, The University of Edinburgh, Edinburgh, Midlothian, United Kingdom
| | - Craig Mowat
- Centre for Genomic and Experimental Medicine, The University of Edinburgh, Edinburgh, Midlothian, United Kingdom
| | - Malcolm G Dunlop
- Centre for Genomic and Experimental Medicine, The University of Edinburgh, Edinburgh, Midlothian, United Kingdom
| | - Jack Satsangi
- Centre for Genomic and Experimental Medicine, The University of Edinburgh, Edinburgh, Midlothian, United Kingdom
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19
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Yu JCY, Zeng Y, Zhao K, Lu T, Oros Klein K, Colmegna I, Lora M, Bhatnagar SR, Leask A, Greenwood CMT, Hudson M. Novel insights into systemic sclerosis using a sensitive computational method to analyze whole-genome bisulfite sequencing data. Clin Epigenetics 2023; 15:96. [PMID: 37270501 DOI: 10.1186/s13148-023-01513-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 05/28/2023] [Indexed: 06/05/2023] Open
Abstract
BACKGROUND Abnormal DNA methylation is thought to contribute to the onset and progression of systemic sclerosis. Currently, the most comprehensive assay for profiling DNA methylation is whole-genome bisulfite sequencing (WGBS), but its precision depends on read depth and it may be subject to sequencing errors. SOMNiBUS, a method for regional analysis, attempts to overcome some of these limitations. Using SOMNiBUS, we re-analyzed WGBS data previously analyzed using bumphunter, an approach that initially fits single CpG associations, to contrast DNA methylation estimates by both methods. METHODS Purified CD4+ T lymphocytes of 9 SSc and 4 control females were sequenced using WGBS. We separated the resulting sequencing data into regions with dense CpG data, and differentially methylated regions (DMRs) were inferred with the SOMNiBUS region-level test, adjusted for age. Pathway enrichment analysis was performed with ingenuity pathway analysis (IPA). We compared the results obtained by SOMNiBUS and bumphunter. RESULTS Of 8268 CpG regions of ≥ 60 CpGs eligible for analysis with SOMNiBUS, we identified 131 DMRs and 125 differentially methylated genes (DMGs; p-values less than Bonferroni-corrected threshold of 6.05-06 controlling family-wise error rate at 0.05; 1.6% of the regions). In comparison, bumphunter identified 821,929 CpG regions, 599 DMRs (of which none had ≥ 60 CpGs) and 340 DMGs (q-value of 0.05; 0.04% of all regions). The top ranked gene identified by SOMNiBUS was FLT4, a lymphangiogenic orchestrator, and the top ranked gene on chromosome X was CHST7, known to catalyze the sulfation of glycosaminoglycans in the extracellular matrix. The top networks identified by IPA included connective tissue disorders. CONCLUSIONS SOMNiBUS is a complementary method of analyzing WGBS data that enhances biological insights into SSc and provides novel avenues of investigation into its pathogenesis.
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Affiliation(s)
- Jeffrey C Y Yu
- McGill University, 845 Sherbrooke St W, Montreal, H3A 0G4, Canada
| | - Yixiao Zeng
- McGill University, 845 Sherbrooke St W, Montreal, H3A 0G4, Canada
| | - Kaiqiong Zhao
- McGill University, 845 Sherbrooke St W, Montreal, H3A 0G4, Canada
| | - Tianyuan Lu
- McGill University, 845 Sherbrooke St W, Montreal, H3A 0G4, Canada
| | - Kathleen Oros Klein
- Lady Davis Institute for Medical Research, Jewish General Hospital, 3755 Côte Sainte Catherine, Montreal, H3T 1E2, Canada
| | - Inés Colmegna
- McGill University, 845 Sherbrooke St W, Montreal, H3A 0G4, Canada
- Research Institute of the McGill University Health Center, Montreal, Canada
| | - Maximilien Lora
- Research Institute of the McGill University Health Center, Montreal, Canada
| | | | | | - Celia M T Greenwood
- McGill University, 845 Sherbrooke St W, Montreal, H3A 0G4, Canada
- Lady Davis Institute for Medical Research, Jewish General Hospital, 3755 Côte Sainte Catherine, Montreal, H3T 1E2, Canada
| | - Marie Hudson
- McGill University, 845 Sherbrooke St W, Montreal, H3A 0G4, Canada.
- Lady Davis Institute for Medical Research, Jewish General Hospital, 3755 Côte Sainte Catherine, Montreal, H3T 1E2, Canada.
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20
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Nannini DR, Zheng Y, Joyce BT, Kim K, Gao T, Wang J, Jacobs DR, Schreiner PJ, Yaffe K, Greenland P, Lloyd-Jones DM, Hou L. Genome-wide DNA methylation association study of recent and cumulative marijuana use in middle aged adults. Mol Psychiatry 2023; 28:2572-2582. [PMID: 37258616 PMCID: PMC10611566 DOI: 10.1038/s41380-023-02106-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 04/24/2023] [Accepted: 05/03/2023] [Indexed: 06/02/2023]
Abstract
Marijuana is a widely used psychoactive substance in the US and medical and recreational legalization has risen over the past decade. Despite the growing number of individuals using marijuana, studies investigating the association between epigenetic factors and recent and cumulative marijuana use remain limited. We therefore investigated the association between recent and cumulative marijuana use and DNA methylation levels. Participants from the Coronary Artery Risk Development in Young Adults Study with whole blood collected at examination years (Y) 15 and Y20 were randomly selected to undergo DNA methylation profiling at both timepoints using the Illumina MethylationEPIC BeadChip. Recent use of marijuana was queried at each examination and used to estimate cumulative marijuana use from Y0 to Y15 and Y20. At Y15 (n = 1023), we observed 22 and 31 methylation markers associated (FDR P ≤ 0.05) with recent and cumulative marijuana use and 132 and 16 methylation markers at Y20 (n = 883), respectively. We replicated 8 previously reported methylation markers associated with marijuana use. We further identified 640 cis-meQTLs and 198 DMRs associated with recent and cumulative use at Y15 and Y20. Differentially methylated genes were statistically overrepresented in pathways relating to cellular proliferation, hormone signaling, and infections as well as schizophrenia, bipolar disorder, and substance-related disorders. We identified numerous methylation markers, pathways, and diseases associated with recent and cumulative marijuana use in middle-aged adults, providing additional insight into the association between marijuana use and the epigenome. These results provide novel insights into the role marijuana has on the epigenome and related health conditions.
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Affiliation(s)
- Drew R Nannini
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
| | - Yinan Zheng
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Brian T Joyce
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Kyeezu Kim
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Tao Gao
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Jun Wang
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - David R Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Pamela J Schreiner
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Kristine Yaffe
- University of California at San Francisco School of Medicine, San Francisco, CA, USA
| | - Philip Greenland
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Donald M Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
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21
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Mallick K, Chakraborty S, Mallik S, Bandyopadhyay S. A scalable unsupervised learning of scRNAseq data detects rare cells through integration of structure-preserving embedding, clustering and outlier detection. Brief Bioinform 2023; 24:bbad125. [PMID: 37185897 DOI: 10.1093/bib/bbad125] [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: 08/31/2022] [Revised: 02/06/2023] [Accepted: 02/24/2023] [Indexed: 05/17/2023] Open
Abstract
Single-cell RNA-seq analysis has become a powerful tool to analyse the transcriptomes of individual cells. In turn, it has fostered the possibility of screening thousands of single cells in parallel. Thus, contrary to the traditional bulk measurements that only paint a macroscopic picture, gene measurements at the cell level aid researchers in studying different tissues and organs at various stages. However, accurate clustering methods for such high-dimensional data remain exiguous and a persistent challenge in this domain. Of late, several methods and techniques have been promulgated to address this issue. In this article, we propose a novel framework for clustering large-scale single-cell data and subsequently identifying the rare-cell sub-populations. To handle such sparse, high-dimensional data, we leverage PaCMAP (Pairwise Controlled Manifold Approximation), a feature extraction algorithm that preserves both the local and the global structures of the data and Gaussian Mixture Model to cluster single-cell data. Subsequently, we exploit Edited Nearest Neighbours sampling and Isolation Forest/One-class Support Vector Machine to identify rare-cell sub-populations. The performance of the proposed method is validated using the publicly available datasets with varying degrees of cell types and rare-cell sub-populations. On several benchmark datasets, the proposed method outperforms the existing state-of-the-art methods. The proposed method successfully identifies cell types that constitute populations ranging from 0.1 to 8% with F1-scores of 0.91 0.09. The source code is available at https://github.com/scrab017/RarPG.
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Affiliation(s)
- Koushik Mallick
- Computer Science and Engineering, RCC Institute of Information Technology, Canal South Road, 700015, West Bengal, India
| | - Sikim Chakraborty
- Centre for Economy and Growth, Observer Research Foundation, Rouse Avenue, New Delhi, 110002, Delhi, India
| | - Saurav Mallik
- Department of Environmental Health, Harvard T H Chan School of Public Health, 677 Huntington Ave, 02115, MA, USA
| | - Sanghamitra Bandyopadhyay
- Machine Intelligence Unit, Indian Statistical Institute, Barrackpore Trunk Rd., 700108, West Bengal, India
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22
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Zhang W, Young JI, Gomez L, Schmidt MA, Lukacsovich D, Varma A, Chen XS, Martin ER, Wang L. Distinct CSF biomarker-associated DNA methylation in Alzheimer's disease and cognitively normal subjects. Alzheimers Res Ther 2023; 15:78. [PMID: 37038196 PMCID: PMC10088180 DOI: 10.1186/s13195-023-01216-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Accepted: 03/21/2023] [Indexed: 04/12/2023]
Abstract
BACKGROUND Growing evidence has demonstrated that DNA methylation (DNAm) plays an important role in Alzheimer's disease (AD) and that DNAm differences can be detected in the blood of AD subjects. Most studies have correlated blood DNAm with the clinical diagnosis of AD in living individuals. However, as the pathophysiological process of AD can begin many years before the onset of clinical symptoms, there is often disagreement between neuropathology in the brain and clinical phenotypes. Therefore, blood DNAm associated with AD neuropathology, rather than with clinical data, would provide more relevant information on AD pathogenesis. METHODS We performed a comprehensive analysis to identify blood DNAm associated with cerebrospinal fluid (CSF) pathological biomarkers for AD. Our study included matched samples of whole blood DNA methylation, CSF Aβ42, phosphorylated tau181 (pTau181), and total tau (tTau) biomarkers data, measured on the same subjects and at the same clinical visits from a total of 202 subjects (123 CN or cognitively normal, 79 AD) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. To validate our findings, we also examined the association between premortem blood DNAm and postmortem brain neuropathology measured on a group of 69 subjects in the London dataset. RESULTS We identified a number of novel associations between blood DNAm and CSF biomarkers, demonstrating that changes in pathological processes in the CSF are reflected in the blood epigenome. Overall, the CSF biomarker-associated DNAm is relatively distinct in CN and AD subjects, highlighting the importance of analyzing omics data measured on cognitively normal subjects (which includes preclinical AD subjects) to identify diagnostic biomarkers, and considering disease stages in the development and testing of AD treatment strategies. Moreover, our analysis revealed biological processes associated with early brain impairment relevant to AD are marked by DNAm in the blood, and blood DNAm at several CpGs in the DMR on HOXA5 gene are associated with pTau181 in the CSF, as well as tau-pathology and DNAm in the brain, nominating DNAm at this locus as a promising candidate AD biomarker. CONCLUSIONS Our study provides a valuable resource for future mechanistic and biomarker studies of DNAm in AD.
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Affiliation(s)
- Wei Zhang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14Th Street, Miami, FL, 33136, USA
| | - Juan I Young
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - Lissette Gomez
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - Michael A Schmidt
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - David Lukacsovich
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14Th Street, Miami, FL, 33136, USA
| | - Achintya Varma
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - X Steven Chen
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14Th Street, Miami, FL, 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - Eden R Martin
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - Lily Wang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14Th Street, Miami, FL, 33136, USA.
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA.
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA.
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, 33136, USA.
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23
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Tang X, Mo Z, Chang C, Qian X. Group-shrinkage feature selection with a spatial network for mining DNA methylation data. Comput Biol Med 2023; 154:106573. [PMID: 36706568 DOI: 10.1016/j.compbiomed.2023.106573] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 01/05/2023] [Accepted: 01/22/2023] [Indexed: 01/25/2023]
Abstract
Identifying disease-related biomarkers from high-dimensional DNA methylation data helps in reducing early screening costs and inferring pathogenesis mechanisms. Good discovery results have been achieved through spatial correlation methods of methylation sites, group-based regularization, and network constraints. However, these methods still have some key limitations as they cannot exclude isolated differential sites and only consider adjacent site ordering. Therefore, we propose a group-shrinkage feature selection algorithm to encourage the selection of clustered sites and discourage the selection of isolated differential sites. Specifically, a network-guided group-shrinkage strategy is developed to penalize weakly-correlated isolated methylation sites through a network structure constraint. The spatial network is constructed based on spatial correlation information of DNA methylation sites, where this information accounts for the uneven site distribution. The experimental simulations and applications demonstrated that the proposed method outperforms the advanced regularization methods, especially in rejecting isolated methylation sites; hence this study provides an efficient and clinical-valuable method for biomarker candidate discovery in DNA methylation data. Additionally, the proposed method exhibits enhanced reliability due to introducing biological prior knowledge into a regularization-based feature selection framework and could promote more research in the integration between biological prior knowledge and classical feature selection methods, thus facilitating their clinical application. Our source codes will be released at https://github.com/SJTUBME-QianLab/Group-shrinkage-Spatial-Network once this manuscript is accepted for publication.
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Affiliation(s)
- Xinlu Tang
- Medical Image and Health Informatics Lab, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
| | - Zhanfeng Mo
- School of Computer Science and Engineering, Nanyang Technological University, Singapore.
| | - Cheng Chang
- Department of Nuclear Medicine, Shanghai, Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200030, China.
| | - Xiaohua Qian
- Medical Image and Health Informatics Lab, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
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24
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Zhang W, Young JI, Gomez L, Schmidt MA, Lukacsovich D, Varma A, Chen XS, Martin ER, Wang L. Distinct CSF biomarker-associated DNA methylation in Alzheimer's disease and cognitively normal subjects. RESEARCH SQUARE 2023:rs.3.rs-2391364. [PMID: 36865230 PMCID: PMC9980279 DOI: 10.21203/rs.3.rs-2391364/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/23/2023]
Abstract
Background Growing evidence has demonstrated that DNA methylation (DNAm) plays an important role in Alzheimer's disease (AD) and that DNAm differences can be detected in the blood of AD subjects. Most studies have correlated blood DNAm with the clinical diagnosis of AD in living individuals. However, as the pathophysiological process of AD can begin many years before the onset of clinical symptoms, there is often disagreement between neuropathology in the brain and clinical phenotypes. Therefore, blood DNAm associated with AD neuropathology, rather than with clinical data, would provide more relevant information on AD pathogenesis. Methods We performed a comprehensive analysis to identify blood DNAm associated with cerebrospinal fluid (CSF) pathological biomarkers for AD. Our study included matched samples of whole blood DNA methylation, CSF Aβ 42 , phosphorylated tau 181 (pTau 181 ), and total tau (tTau) biomarkers data, measured on the same subjects and at the same clinical visits from a total of 202 subjects (123 CN or cognitively normal, 79 AD) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. To validate our findings, we also examined the association between premortem blood DNAm and postmortem brain neuropathology measured on a group of 69 subjects in the London dataset. Results We identified a number of novel associations between blood DNAm and CSF biomarkers, demonstrating that changes in pathological processes in the CSF are reflected in the blood epigenome. Overall, the CSF biomarker-associated DNAm is relatively distinct in CN and AD subjects, highlighting the importance of analyzing omics data measured on cognitively normal subjects (which includes preclinical AD subjects) to identify diagnostic biomarkers, and considering disease stages in the development and testing of AD treatment strategies. Moreover, our analysis revealed biological processes associated with early brain impairment relevant to AD are marked by DNAm in the blood, and blood DNAm at several CpGs in the DMR on HOXA5 gene are associated with pTau 181 in the CSF, as well as tau-pathology and DNAm in the brain, nominating DNAm at this locus as a promising candidate AD biomarker. Conclusions Our study provides a valuable resource for future mechanistic and biomarker studies of DNAm in AD.
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Affiliation(s)
- Wei Zhang
- University of Miami, Miller School of Medicine
| | - Juan I Young
- Dr. John T Macdonald Foundation, University of Miami, Miller School of Medicine
| | | | - Michael A Schmidt
- Dr. John T Macdonald Foundation, University of Miami, Miller School of Medicine
| | | | | | | | - Eden R Martin
- Dr. John T Macdonald Foundation, University of Miami, Miller School of Medicine
| | - Lily Wang
- University of Miami, Miller School of Medicine
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25
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Khandelwal M, Kumar Rout R, Umer S, Mallik S, Li A. Multifactorial feature extraction and site prognosis model for protein methylation data. Brief Funct Genomics 2023; 22:20-30. [PMID: 36310537 DOI: 10.1093/bfgp/elac034] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 09/23/2022] [Accepted: 09/28/2022] [Indexed: 01/24/2023] Open
Abstract
Integrated studies (multi-omics studies) comprising genetic, proteomic and epigenetic data analyses have become an emerging topic in biomedical research. Protein methylation is a posttranslational modification that plays an essential role in various cellular activities. The prediction of methylation sites (arginine and lysine) is vital to understand the molecular processes of protein methylation. However, current experimental techniques used for methylation site predictions are tedious and expensive. Hence, computational techniques for predicting methylation sites in proteins are necessary. For predicting methylation sites, various computational methods have been proposed in recent years. Most existing methods require structural and evolutionary information for retrieving features, acquiring this information is not always convenient. Thus, we proposed a novel method, called multi-factorial feature extraction and site prognosis model (MufeSPM), for the prediction of protein methylation sites based on information theory features (Renyi, Shannon, Havrda-Charvat and Arimoto entropy), amino acid composition and physicochemical properties acquired from protein methylation data. A random forest algorithm was used to predict methylation sites in protein sequences. This paper also studied the impact of different features and classifiers on arginine and lysine methylation data sets. For the R methylation data set, MufeSPM yielded 82.45%($\pm $ 3.47) accuracy, and for the K methylation data set, it provided an average accuracy of 71.94%($\pm $ 2.12). Additionally, the area under the receiver operating characteristic curve for different classifiers in predicting methylation site was provided. The experimental results signify that MufeSPM performs better than the state-of-the-art predictors.
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Affiliation(s)
- Monika Khandelwal
- Computer Science & Engineering, National Institute of Technology Srinagar, Hazratbal, Srinagar, 190006, Jammu and Kashmir, India
| | - Ranjeet Kumar Rout
- Computer Science & Engineering, National Institute of Technology Srinagar, Hazratbal, Srinagar, 190006, Jammu and Kashmir, India
| | - Saiyed Umer
- Computer Science & Engineering, Aliah University, Kolkata, 700016, West Bengal, India
| | - Saurav Mallik
- Department of Environmental Health, Harvard T H Chan School of Public Health, Huntington Ave, Boston, 02115, MA, USA
| | - Aimin Li
- School of Computer Science and Engineering, Xi'an University of Technology, Jinhua S Rd, 710048, Shaanxi, China
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Wang C, Xu Z, Qiu X, Wei Y, Peralta AA, Yazdi MD, Jin T, Li W, Just A, Heiss J, Hou L, Zheng Y, Coull BA, Kosheleva A, Sparrow D, Amarasiriwardena C, Wright RO, Baccarelli AA, Schwartz JD. Epigenome-wide DNA methylation in leukocytes and toenail metals: The normative aging study. ENVIRONMENTAL RESEARCH 2023; 217:114797. [PMID: 36379232 PMCID: PMC9825663 DOI: 10.1016/j.envres.2022.114797] [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: 09/07/2022] [Revised: 10/27/2022] [Accepted: 11/10/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Environmental metal exposures have been associated with multiple deleterious health endpoints. DNA methylation (DNAm) may provide insight into the mechanisms underlying these relationships. Toenail metals are non-invasive biomarkers, reflecting a medium-term time exposure window. OBJECTIVES This study examined variation in leukocyte DNAm and toenail arsenic (As), cadmium (Cd), lead (Pb), manganese (Mn), and mercury (Hg) among elderly men in the Normative Aging Study, a longitudinal cohort. METHODS We repeatedly collected samples of blood and toenail clippings. We measured DNAm in leukocytes with the Illumina HumanMethylation450 K BeadChip. We first performed median regression to evaluate the effects of each individual toenail metal on DNAm at three levels: individual cytosine-phosphate-guanine (CpG) sites, regions, and pathways. Then, we applied a Bayesian kernel machine regression (BKMR) to assess the joint and individual effects of metal mixtures on DNAm. Significant CpGs were identified using a multiple testing correction based on the independent degrees of freedom approach for correlated outcomes. The approach considers the effective degrees of freedom in the DNAm data using the principal components that explain >95% variation of the data. RESULTS We included 564 subjects (754 visits) between 1999 and 2013. The numbers of significantly differentially methylated CpG sites, regions, and pathways varied by metals. For example, we found six significant pathways for As, three for Cd, and one for Mn. The As-associated pathways were associated with cancer (e.g., skin cancer) and cardiovascular disease, whereas the Cd-associated pathways were related to lung cancer. Metal mixtures were also associated with 47 significant CpG sites, as well as pathways, mainly related to cancer and cardiovascular disease. CONCLUSIONS This study provides an approach to understanding the potential epigenetic mechanisms underlying observed relations between toenail metals and adverse health endpoints.
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Affiliation(s)
- Cuicui Wang
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
| | - Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Xinye Qiu
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Yaguang Wei
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Adjani A Peralta
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Mahdieh Danesh Yazdi
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Program in Public Health, Department of Family, Population, and Preventive Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Tingfan Jin
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Wenyuan Li
- School of Public Health and Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Allan Just
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jonathan Heiss
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Yinan Zheng
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Brent A Coull
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Anna Kosheleva
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - David Sparrow
- VA Normative Aging Study, VA Boston Healthcare System, Boston, MA 02130, USA; Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA
| | - Chitra Amarasiriwardena
- Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Robert O Wright
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Columbia Mailman School of Public Health, New York, NY 10032, USA
| | - Joel D Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
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27
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Wang C, DeMeo DL, Kim ES, Cardenas A, Fong KC, Lee LO, Spiro A, Whitsel EA, Horvath S, Hou L, Baccarelli AA, Li Y, Stewart JD, Manson JE, Grodstein F, Kubzansky LD, Schwartz JD. Epigenome-Wide Analysis of DNA Methylation and Optimism in Women and Men. Psychosom Med 2023; 85:89-97. [PMID: 36201768 PMCID: PMC9771983 DOI: 10.1097/psy.0000000000001147] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
OBJECTIVE Higher optimism is associated with reduced mortality and a lower risk of age-related chronic diseases. DNA methylation (DNAm) may provide insight into mechanisms underlying these relationships. We hypothesized that DNAm would differ among older individuals who are more versus less optimistic. METHODS Using cross-sectional data from two population-based cohorts of women with diverse races/ethnicities ( n = 3816) and men (only White, n = 667), we investigated the associations of optimism with epigenome-wide leukocyte DNAm. Random-effects meta-analyses were subsequently used to pool the individual results. Significantly differentially methylated cytosine-phosphate-guanines (CpGs) were identified by the "number of independent degrees of freedom" approach: effective degrees of freedom correction using the number of principal components (PCs), explaining >95% of the variation of the DNAm data (PC-correction). We performed regional analyses using comb-p and pathway analyses using the Ingenuity Pathway Analysis software. RESULTS We found that essentially all CpGs (total probe N = 359,862) were homogeneous across sex and race/ethnicity in the DNAm-optimism association. In the single CpG site analyses based on homogeneous CpGs, we identified 13 significantly differentially methylated probes using PC-correction. We found four significantly differentially methylated regions and two significantly differentially methylated pathways. The annotated genes from the single CpG site and regional analyses are involved in psychiatric disorders, cardiovascular disease, cognitive impairment, and cancer. Identified pathways were related to cancer, and neurodevelopmental and neurodegenerative disorders. CONCLUSION Our findings provide new insights into possible mechanisms underlying optimism and health.
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Affiliation(s)
- Cuicui Wang
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Dawn L. DeMeo
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Eric S. Kim
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Lee Kum Sheung Center for Health and Happiness, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Psychology, University of British Columbia, BC V6T 1Z4, Canada
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, CA 94720, USA
- Department of Population Medicine, Division of Chronic Disease Research Across the Lifecourse, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - Kelvin C. Fong
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- School of the Environment, Yale University, New Haven, CT 06511, USA
| | - Lewina O. Lee
- National Center for Posttraumatic Stress Disorder, VA Boston Healthcare System, Boston, MA 02130, USA
- Department Psychiatry, Boston University School of Medicine, Boston, MA 02118, USA
| | - Avron Spiro
- Department Psychiatry, Boston University School of Medicine, Boston, MA 02118, USA
- Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System, Boston, MA 02130, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA
| | - Eric A. Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, Chapel Hill, NC 27599, USA
- Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Steve Horvath
- Department of Human Genetics, University of California, Los Angeles, CA 90095, USA
- Department of Biostatistics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Andrea A. Baccarelli
- Department of Environmental Health Sciences, Columbia Mailman School of Public Health, New York, NY 10032, USA
| | - Yun Li
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA
- Department of Computer Science, University of North Carolina, Chapel Hill, NC, 27599 USA
| | - James D. Stewart
- Cardiovascular Program, Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC, 27599, USA
| | - JoAnn E. Manson
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Francine Grodstein
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Laura D. Kubzansky
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Lee Kum Sheung Center for Health and Happiness, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Joel D. Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
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Broséus L, Vaiman D, Tost J, Martin CRS, Jacobi M, Schwartz JD, Béranger R, Slama R, Heude B, Lepeule J. Maternal blood pressure associates with placental DNA methylation both directly and through alterations in cell-type composition. BMC Med 2022; 20:397. [PMID: 36266660 PMCID: PMC9585724 DOI: 10.1186/s12916-022-02610-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 10/14/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Maternal blood pressure levels reflect cardiovascular adaptation to pregnancy and proper maternal-fetal exchanges through the placenta and are very sensitive to numerous environmental stressors. Maternal hypertension during pregnancy has been associated with impaired placental functions and with an increased risk for children to suffer from cardiovascular and respiratory diseases later on. Investigating changes in placental DNA methylation levels and cell-type composition in association with maternal blood pressure could help elucidate its relationships with placental and fetal development. METHODS Taking advantage of a large cohort of 666 participants, we investigated the association between epigenome-wide DNA methylation patterns in the placenta, measured using the Infinium HumanMethylation450 BeadChip, placental cell-type composition, estimated in silico, and repeated measurements of maternal steady and pulsatile blood pressure indicators during pregnancy. RESULTS At the site-specific level, no significant association was found between maternal blood pressure and DNA methylation levels after correction for multiple testing (false discovery rate < 0.05), but 5 out of 24 previously found CpG associations were replicated (p-value < 0.05). At the regional level, our analyses highlighted 64 differentially methylated regions significantly associated with at least one blood pressure component, including 35 regions associated with mean arterial pressure levels during late pregnancy. These regions were found enriched for genes implicated in lung development and diseases. Further mediation analyses show that a significant part of the association between steady blood pressure-but not pulsatile pressure-and placental methylation can be explained by alterations in placental cell-type composition. In particular, elevated blood pressure levels are associated with a decrease in the ratio between mesenchymal stromal cells and syncytiotrophoblasts, even in the absence of preeclampsia. CONCLUSIONS This study provides the first evidence that the association between maternal steady blood pressure during pregnancy and placental DNA methylation is both direct and partly explained by changes in cell-type composition. These results could hint at molecular mechanisms linking maternal hypertension to lung development and early origins of childhood respiratory problems and at the importance of controlling maternal blood pressure during pregnancy.
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Affiliation(s)
- Lucile Broséus
- University Grenoble Alpes, INSERM, Team of Environmental Epidemiology Applied to Development and Respiratory Health, Institute for Advanced Biosciences (IAB), Grenoble, France.
| | - Daniel Vaiman
- From Gametes to Birth, Institut Cochin, U1016 INSERM, UMR 8104 CNRS, Paris-Descartes University, Paris, France
| | - Jörg Tost
- Laboratory for Epigenetics and Environment, Centre National de Recherche en Génomique Humaine, CEA - Institut de Biologie François Jacob, University Paris Saclay, Evry, France
| | - Camino Ruano San Martin
- From Gametes to Birth, Institut Cochin, U1016 INSERM, UMR 8104 CNRS, Paris-Descartes University, Paris, France
| | - Milan Jacobi
- University Grenoble Alpes, INSERM, Team of Environmental Epidemiology Applied to Development and Respiratory Health, Institute for Advanced Biosciences (IAB), Grenoble, France
| | - Joel D Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Rémi Béranger
- Univ. Rennes, CHU Rennes, INSERM, EHESP, IRSET (Institut de recherche en santé, environnement et travail), UMR 1085, Rennes, France
| | - Rémy Slama
- University Grenoble Alpes, INSERM, Team of Environmental Epidemiology Applied to Development and Respiratory Health, Institute for Advanced Biosciences (IAB), Grenoble, France
| | - Barbara Heude
- Univ. Paris, Centre for Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Paris, France
| | - Johanna Lepeule
- University Grenoble Alpes, INSERM, Team of Environmental Epidemiology Applied to Development and Respiratory Health, Institute for Advanced Biosciences (IAB), Grenoble, France.
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Oluwayiose OA, Wu H, Gao F, Baccarelli AA, Sofer T, Pilsner JR. Aclust2.0: a revamped unsupervised R tool for Infinium methylation beadchips data analyses. Bioinformatics 2022; 38:4820-4822. [PMID: 36028931 PMCID: PMC9563687 DOI: 10.1093/bioinformatics/btac583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 07/27/2022] [Accepted: 08/25/2022] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION A wide range of computational packages has been developed for regional DNA methylation analyses of Illumina's Infinium array data. Aclust, one of the first unsupervised algorithms, was originally designed to analyze regional methylation of Infinium's 27K and 450K arrays by clustering neighboring methylation sites prior to downstream analyses. However, Aclust relied on outdated packages that rendered it largely non-operational especially with the newer Infinium EPIC and mouse arrays. RESULTS We have created Aclust2.0, a streamlined pipeline that involves five steps for the analyses of human (450K and EPIC) and mouse array data. Aclust2.0 provides a user-friendly pipeline and versatile for regional DNA methylation analyses for molecular epidemiological and mouse studies. AVAILABILITY AND IMPLEMENTATION Aclust2.0 is freely available on Github (https://github.com/OluwayioseOA/Alcust2.0.git).
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Affiliation(s)
- Oladele A Oluwayiose
- Department of Obstetrics and Gynecology, School of Medicine, C.S. Mott Center for Human Growth and Development, Wayne State University, Detroit, MI 48201, USA
| | - Haotian Wu
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY 10032, USA
| | - Feng Gao
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY 10032, USA
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY 10032, USA
| | - Tamar Sofer
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - J Richard Pilsner
- Department of Obstetrics and Gynecology, School of Medicine, C.S. Mott Center for Human Growth and Development, Wayne State University, Detroit, MI 48201, USA
- Institute of Environmental Health Sciences, Wayne State University, Detroit, MI 48201, USA
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C. Silva T, Zhang W, Young JI, Gomez L, Schmidt MA, Varma A, Chen XS, Martin ER, Wang L. Distinct sex-specific DNA methylation differences in Alzheimer's disease. Alzheimers Res Ther 2022; 14:133. [PMID: 36109771 PMCID: PMC9479371 DOI: 10.1186/s13195-022-01070-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 08/30/2022] [Indexed: 01/17/2023]
Abstract
BACKGROUND Sex is increasingly recognized as a significant factor contributing to the biological and clinical heterogeneity in AD. There is also growing evidence for the prominent role of DNA methylation (DNAm) in Alzheimer's disease (AD). METHODS We studied sex-specific DNA methylation differences in the blood samples of AD subjects compared to cognitively normal subjects, by performing sex-specific meta-analyses of two large blood-based epigenome-wide association studies (ADNI and AIBL), which included DNA methylation data for a total of 1284 whole blood samples (632 females and 652 males). Within each dataset, we used two complementary analytical strategies, a sex-stratified analysis that examined methylation to AD associations in male and female samples separately, and a methylation-by-sex interaction analysis that compared the magnitude of these associations between different sexes. After adjusting for age, estimated immune cell type proportions, batch effects, and correcting for inflation, the inverse-variance fixed-effects meta-analysis model was used to identify the most consistent DNAm differences across datasets. In addition, we also evaluated the performance of the sex-specific methylation-based risk prediction models for AD diagnosis using an independent external dataset. RESULTS In the sex-stratified analysis, we identified 2 CpGs, mapped to the PRRC2A and RPS8 genes, significantly associated with AD in females at a 5% false discovery rate, and an additional 25 significant CpGs (21 in females, 4 in males) at P-value < 1×10-5. In methylation-by-sex interaction analysis, we identified 5 significant CpGs at P-value < 10-5. Out-of-sample validations using the AddNeuroMed dataset showed in females, the best logistic prediction model included age, estimated immune cell-type proportions, and methylation risk scores (MRS) computed from 9 of the 23 CpGs identified in AD vs. CN analysis that are also available in AddNeuroMed dataset (AUC = 0.74, 95% CI: 0.65-0.83). In males, the best logistic prediction model included only age and MRS computed from 2 of the 5 CpGs identified in methylation-by-sex interaction analysis that are also available in the AddNeuroMed dataset (AUC = 0.70, 95% CI: 0.56-0.82). CONCLUSIONS Overall, our results show that the DNA methylation differences in AD are largely distinct between males and females. Our best-performing sex-specific methylation-based prediction model in females performed better than that for males and additionally included estimated cell-type proportions. The significant discriminatory classification of AD samples with our methylation-based prediction models demonstrates that sex-specific DNA methylation could be a predictive biomarker for AD. As sex is a strong factor underlying phenotypic variability in AD, the results of our study are particularly relevant for a better understanding of the epigenetic architecture that underlie AD and for promoting precision medicine in AD.
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Affiliation(s)
- Tiago C. Silva
- grid.26790.3a0000 0004 1936 8606Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136 USA
| | - Wei Zhang
- grid.26790.3a0000 0004 1936 8606Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136 USA
| | - Juan I. Young
- grid.26790.3a0000 0004 1936 8606Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Lissette Gomez
- grid.26790.3a0000 0004 1936 8606John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Michael A. Schmidt
- grid.26790.3a0000 0004 1936 8606Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Achintya Varma
- grid.26790.3a0000 0004 1936 8606John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - X. Steven Chen
- grid.26790.3a0000 0004 1936 8606Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL 33136 USA
| | - Eden R. Martin
- grid.26790.3a0000 0004 1936 8606Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Lily Wang
- grid.26790.3a0000 0004 1936 8606Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL 33136 USA
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Sharma R, Frasch MG, Zelgert C, Zimmermann P, Fabre B, Wilson R, Waldenberger M, MacDonald JW, Bammler TK, Lobmaier SM, Antonelli MC. Maternal-fetal stress and DNA methylation signatures in neonatal saliva: an epigenome-wide association study. Clin Epigenetics 2022; 14:87. [PMID: 35836289 PMCID: PMC9281078 DOI: 10.1186/s13148-022-01310-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Accepted: 07/05/2022] [Indexed: 01/02/2023] Open
Abstract
BACKGROUND Maternal stress before, during and after pregnancy has profound effects on the development and lifelong function of the infant's neurocognitive development. We hypothesized that the programming of the central nervous system (CNS), hypothalamic-pituitary-adrenal (HPA) axis and autonomic nervous system (ANS) induced by prenatal stress (PS) is reflected in electrophysiological and epigenetic biomarkers. In this study, we aimed to find noninvasive epigenetic biomarkers of PS in the newborn salivary DNA. RESULTS A total of 728 pregnant women were screened for stress exposure using Cohen Perceived Stress Scale (PSS), 164 women were enrolled, and 114 dyads were analyzed. Prenatal Distress Questionnaire (PDQ) was also administered to assess specific pregnancy worries. Transabdominal fetal electrocardiograms (taECG) were recorded to derive coupling between maternal and fetal heart rates resulting in a 'Fetal Stress Index' (FSI). Upon delivery, we collected maternal hair strands for cortisol measurements and newborn's saliva for epigenetic analyses. DNA was extracted from saliva samples, and DNA methylation was measured using EPIC BeadChip array (850 k CpG sites). Linear regression was used to identify associations between PSS/PDQ/FSI/Cortisol and DNA methylation. We found epigenome-wide significant associations for 5 CpG with PDQ and cortisol at FDR < 5%. Three CpGs were annotated to genes (Illumina Gene annotation file): YAP1, TOMM20 and CSMD1, and two CpGs were located approximately lay at 50 kb from SSBP4 and SCAMP1. In addition, two differentiated methylation regions (DMR) related to maternal stress measures PDQ and cortisol were found: DAXX and ARL4D. CONCLUSIONS Genes annotated to these CpGs were found to be involved in secretion and transportation, nuclear signaling, Hippo signaling pathways, apoptosis, intracellular trafficking and neuronal signaling. Moreover, some CpGs are annotated to genes related to autism, post-traumatic stress disorder (PTSD) and schizophrenia. However, our results should be viewed as hypothesis generating until replicated in a larger sample. Early assessment of such noninvasive PS biomarkers will allow timelier detection of babies at risk and a more effective allocation of resources for early intervention programs to improve child development. A biomarker-guided early intervention strategy is the first step in the prevention of future health problems, reducing their personal and societal impact.
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Affiliation(s)
- Ritika Sharma
- Department of Obstetrics and Gynecology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, Munich, Germany
| | - Martin G Frasch
- Department of Obstetrics and Gynecology and Center On Human Development and Disability (CHDD), University of Washington, Seattle, WA, USA
| | - Camila Zelgert
- Department of Obstetrics and Gynecology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Peter Zimmermann
- Department of Obstetrics and Gynecology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Bibiana Fabre
- Instituto de Fisiopatología y Bioquímica Clínica (INFIBIOC), Facultad de Farmacia y Bioquímica, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Rory Wilson
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, Munich, Germany
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, Munich, Germany
| | - James W MacDonald
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA
| | - Theo K Bammler
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA
| | - Silvia M Lobmaier
- Department of Obstetrics and Gynecology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Marta C Antonelli
- Department of Obstetrics and Gynecology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
- Instituto de Biología Celular y Neurociencia "Prof. E. De Robertis", Facultad de Medicina, Universidad de Buenos Aires, Buenos Aires, Argentina.
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Sammallahti S, Koopman-Verhoeff ME, Binter AC, Mulder RH, Cabré-Riera A, Kvist T, Malmberg ALK, Pesce G, Plancoulaine S, Heiss JA, Rifas-Shiman SL, Röder SW, Starling AP, Wilson R, Guerlich K, Haftorn KL, Page CM, Luik AI, Tiemeier H, Felix JF, Raikkonen K, Lahti J, Relton CL, Sharp GC, Waldenberger M, Grote V, Heude B, Annesi-Maesano I, Hivert MF, Zenclussen AC, Herberth G, Dabelea D, Grazuleviciene R, Vafeiadi M, Håberg SE, London SJ, Guxens M, Richmond RC, Cecil CAM. Longitudinal associations of DNA methylation and sleep in children: a meta-analysis. Clin Epigenetics 2022; 14:83. [PMID: 35790973 PMCID: PMC9258202 DOI: 10.1186/s13148-022-01298-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 06/04/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Sleep is important for healthy functioning in children. Numerous genetic and environmental factors, from conception onwards, may influence this phenotype. Epigenetic mechanisms such as DNA methylation have been proposed to underlie variation in sleep or may be an early-life marker of sleep disturbances. We examined if DNA methylation at birth or in school age is associated with parent-reported and actigraphy-estimated sleep outcomes in children. METHODS We meta-analysed epigenome-wide association study results. DNA methylation was measured from cord blood at birth in 11 cohorts and from peripheral blood in children (4-13 years) in 8 cohorts. Outcomes included parent-reported sleep duration, sleep initiation and fragmentation problems, and actigraphy-estimated sleep duration, sleep onset latency and wake-after-sleep-onset duration. RESULTS We found no associations between DNA methylation at birth and parent-reported sleep duration (n = 3658), initiation problems (n = 2504), or fragmentation (n = 1681) (p values above cut-off 4.0 × 10-8). Lower methylation at cg24815001 and cg02753354 at birth was associated with longer actigraphy-estimated sleep duration (p = 3.31 × 10-8, n = 577) and sleep onset latency (p = 8.8 × 10-9, n = 580), respectively. DNA methylation in childhood was not cross-sectionally associated with any sleep outcomes (n = 716-2539). CONCLUSION DNA methylation, at birth or in childhood, was not associated with parent-reported sleep. Associations observed with objectively measured sleep outcomes could be studied further if additional data sets become available.
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Affiliation(s)
- Sara Sammallahti
- grid.5645.2000000040459992XDepartment of Adolescent and Child Psychiatry, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.7737.40000 0004 0410 2071Department of Obstetrics and Gynaecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - M. Elisabeth Koopman-Verhoeff
- grid.5645.2000000040459992XDepartment of Adolescent and Child Psychiatry, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.5645.2000000040459992XGeneration R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.5132.50000 0001 2312 1970Institute of Education and Child Studies, Leiden University, Leiden, The Netherlands
| | - Anne-Claire Binter
- Barcelona Institute for Global Health, ISGlobal, Campus Mar, Doctor Aiguader, 88, 08003, Barcelona, Spain. .,Universitat Pompeu Fabra, Barcelona, Spain. .,Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain.
| | - Rosa H. Mulder
- grid.5645.2000000040459992XDepartment of Adolescent and Child Psychiatry, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.5645.2000000040459992XGeneration R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Alba Cabré-Riera
- grid.434607.20000 0004 1763 3517Barcelona Institute for Global Health, ISGlobal, Campus Mar, Doctor Aiguader, 88, 08003 Barcelona, Spain ,grid.5612.00000 0001 2172 2676Universitat Pompeu Fabra, Barcelona, Spain ,grid.413448.e0000 0000 9314 1427Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
| | - Tuomas Kvist
- grid.7737.40000 0004 0410 2071Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Anni L. K. Malmberg
- grid.7737.40000 0004 0410 2071Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Giancarlo Pesce
- grid.462844.80000 0001 2308 1657INSERM UMR-S 1136, Team of Epidemiology of Allergic and Respiratory Diseases (EPAR), Institute Pierre Louis of Epidemiology and Public Health (IPLESP), Sorbonne University, Paris, France
| | - Sabine Plancoulaine
- grid.508487.60000 0004 7885 7602CRESS, Inserm, INRAE, Université de Paris Cité, Paris, France
| | - Jonathan A. Heiss
- grid.59734.3c0000 0001 0670 2351Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Sheryl L. Rifas-Shiman
- grid.67104.340000 0004 0415 0102Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA USA
| | - Stefan W. Röder
- grid.7492.80000 0004 0492 3830Department of Environmental Immunology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Anne P. Starling
- grid.430503.10000 0001 0703 675XDepartment of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO USA ,grid.430503.10000 0001 0703 675XCenter for Lifecourse Epidemiology of Adiposity and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO USA ,grid.10698.360000000122483208Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Rory Wilson
- grid.4567.00000 0004 0483 2525Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria Germany
| | - Kathrin Guerlich
- grid.411095.80000 0004 0477 2585Division of Metabolic and Nutritional Medicine, Department of Pediatrics, Dr. Von Hauner Children’s Hospital, LMU University Hospital Munich, Munich, Germany
| | - Kristine L. Haftorn
- grid.418193.60000 0001 1541 4204Department of Genetics and Bioinformatics, Norwegian Institute of Public Health, Oslo, Norway ,grid.418193.60000 0001 1541 4204Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway ,grid.5510.10000 0004 1936 8921Institute of Health and Society, University of Oslo, Oslo, Norway
| | - Christian M. Page
- grid.418193.60000 0001 1541 4204Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway ,grid.5510.10000 0004 1936 8921Department of Mathematics, University of Oslo, Oslo, Norway
| | - Annemarie I. Luik
- grid.5645.2000000040459992XDepartment of Adolescent and Child Psychiatry, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Henning Tiemeier
- grid.5645.2000000040459992XDepartment of Adolescent and Child Psychiatry, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.5645.2000000040459992XGeneration R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.38142.3c000000041936754XDepartment of Social and Behavioral Science, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Janine F. Felix
- grid.5645.2000000040459992XGeneration R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.5645.2000000040459992XDepartment of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Katri Raikkonen
- grid.7737.40000 0004 0410 2071Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Jari Lahti
- grid.7737.40000 0004 0410 2071Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Caroline L. Relton
- grid.5337.20000 0004 1936 7603MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK ,grid.5337.20000 0004 1936 7603Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Gemma C. Sharp
- grid.5337.20000 0004 1936 7603MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK ,grid.5337.20000 0004 1936 7603Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Melanie Waldenberger
- grid.4567.00000 0004 0483 2525Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria Germany
| | - Veit Grote
- grid.411095.80000 0004 0477 2585Division of Metabolic and Nutritional Medicine, Department of Pediatrics, Dr. Von Hauner Children’s Hospital, LMU University Hospital Munich, Munich, Germany
| | - Barbara Heude
- grid.508487.60000 0004 7885 7602CRESS, Inserm, INRAE, Université de Paris Cité, Paris, France
| | - Isabella Annesi-Maesano
- grid.121334.60000 0001 2097 0141IDESP, University of Montpellier and INSERM, Montpellier, France
| | - Marie-France Hivert
- grid.67104.340000 0004 0415 0102Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA USA
| | - Ana C. Zenclussen
- grid.7492.80000 0004 0492 3830Department of Environmental Immunology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany ,grid.9647.c0000 0004 7669 9786Perinatal Immunology Group, Saxonian Incubator for Clinical Translation - SIKT, Leipzig University, Leipzig, Germany
| | - Gunda Herberth
- grid.7492.80000 0004 0492 3830Department of Environmental Immunology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Dana Dabelea
- grid.430503.10000 0001 0703 675XDepartment of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO USA ,grid.430503.10000 0001 0703 675XCenter for Lifecourse Epidemiology of Adiposity and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO USA ,grid.430503.10000 0001 0703 675XDepartment of Pediatrics, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | - Regina Grazuleviciene
- grid.19190.300000 0001 2325 0545Department of Environmental Science, Vytautas Magnus University, Kaunas, Lithuania
| | - Marina Vafeiadi
- grid.8127.c0000 0004 0576 3437Department of Social Medicine, Faculty of Medicine, University of Crete, Heraklion, Crete Greece
| | - Siri E. Håberg
- grid.418193.60000 0001 1541 4204Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Stephanie J. London
- grid.280664.e0000 0001 2110 5790Epidemiology Branch, Department of Health and Human Services, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC USA
| | - Mònica Guxens
- grid.5645.2000000040459992XDepartment of Adolescent and Child Psychiatry, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.434607.20000 0004 1763 3517Barcelona Institute for Global Health, ISGlobal, Campus Mar, Doctor Aiguader, 88, 08003 Barcelona, Spain ,grid.5612.00000 0001 2172 2676Universitat Pompeu Fabra, Barcelona, Spain ,grid.413448.e0000 0000 9314 1427Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
| | - Rebecca C. Richmond
- grid.5337.20000 0004 1936 7603MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK ,grid.5337.20000 0004 1936 7603Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Charlotte A. M. Cecil
- grid.5645.2000000040459992XDepartment of Adolescent and Child Psychiatry, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.5645.2000000040459992XGeneration R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.10419.3d0000000089452978Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands ,grid.13097.3c0000 0001 2322 6764Department of Psychology, Institute of Psychology, Psychiatry and Neuroscience, King’s College London, London, UK
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Unsupervised Learning for Feature Representation Using Spatial Distribution of Amino Acids in Aldehyde Dehydrogenase (ALDH2) Protein Sequences. MATHEMATICS 2022. [DOI: 10.3390/math10132228] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Aldehyde dehydrogenase 2 (ALDH2) enzyme is required for alcohol detoxification. ALDH2 belongs to the aldehyde dehydrogenase family, the most important oxidative pathway of alcohol digestion. Two main liver isoforms of aldehyde dehydrogenase are cytosolic and mitochondrial. Approximately 50% of East Asians have ALDH2 deficiency (inactive mitochondrial isozyme), with lysine (K) for glutamate (E) substitution at position 487 (E487K). ALDH2 deficiency is also known as Alcohol Flushing Syndrome or Asian Glow. For people with an ALDH2 deficiency, their face turns red after drinking alcohol, and they are more susceptible to various diseases than ALDH2-normal people. This study performed a machine learning analysis of ALDH2 sequences of thirteen other species by comparing them with the human ALDH2 sequence. Based on the various quantitative metrics (physicochemical properties, secondary structure, Hurst exponent, Shannon entropy, and fractal dimension), these fourteen species were clustered into four clusters using the unsupervised machine learning (K-means clustering) algorithm. We also analyze these species using hierarchical clustering (agglomerative clustering) and draw the phylogenetic trees. The results show that Homo sapiens is more closely related to the Bos taurus and Sus scrofa species. Our experimental results suggest that the testing for discovering medicines may be done on these species before being tested in humans to alleviate the impacts of ALDH2 deficiency.
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34
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Freydenzon A, Nabais MF, Lin T, Williams KL, Wallace L, Henders AK, Blair IP, Wray NR, Pamphlett R, McRae AF. Association between DNA methylation variability and self-reported exposure to heavy metals. Sci Rep 2022; 12:10582. [PMID: 35732753 PMCID: PMC9217962 DOI: 10.1038/s41598-022-13892-w] [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: 07/29/2021] [Accepted: 05/30/2022] [Indexed: 11/30/2022] Open
Abstract
Individuals encounter varying environmental exposures throughout their lifetimes. Some exposures such as smoking are readily observed and have high personal recall; others are more indirect or sporadic and might only be inferred from long occupational histories or lifestyles. We evaluated the utility of using lifetime-long self-reported exposures for identifying differential methylation in an amyotrophic lateral sclerosis cases-control cohort of 855 individuals. Individuals submitted paper-based surveys on exposure and occupational histories as well as whole blood samples. Genome-wide DNA methylation levels were quantified using the Illumina Infinium Human Methylation450 array. We analyzed 15 environmental exposures using the OSCA software linear and MOA models, where we regressed exposures individually by methylation adjusted for batch effects and disease status as well as predicted scores for age, sex, cell count, and smoking status. We also regressed on the first principal components on clustered environmental exposures to detect DNA methylation changes associated with a more generalised definition of environmental exposure. Five DNA methylation probes across three environmental exposures (cadmium, mercury and metalwork) were significantly associated using the MOA models and seven through the linear models, with one additionally across a principal component representing chemical exposures. Methylome-wide significance for four of these markers was driven by extreme hyper/hypo-methylation in small numbers of individuals. The results indicate the potential for using self-reported exposure histories in detecting DNA methylation changes in response to the environment, but also highlight the confounded nature of environmental exposure in cohort studies.
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Affiliation(s)
- Anna Freydenzon
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Marta F Nabais
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.,University of Exeter Medical School, Exeter, EX2 5DW, Devon, UK
| | - Tian Lin
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Kelly L Williams
- Centre for Motor Neuron Disease Research, Macquarie University, Exeter, NSW, 2109, Australia
| | - Leanne Wallace
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Anjali K Henders
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Ian P Blair
- Centre for Motor Neuron Disease Research, Macquarie University, Exeter, NSW, 2109, Australia
| | - Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.,Queensland Brain Institute, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Roger Pamphlett
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, 2050, Australia
| | - Allan F McRae
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
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35
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Noronha NY, Barato M, Sae-Lee C, Pinhel MADS, Watanabe LM, Pereira VAB, Rodrigues GDS, Morais DA, de Sousa WT, Souza VCDO, Plaça JR, Salgado W, Barbosa F, Plösch T, Nonino CB. Novel Zinc-Related Differentially Methylated Regions in Leukocytes of Women With and Without Obesity. Front Nutr 2022; 9:785281. [PMID: 35369101 PMCID: PMC8967318 DOI: 10.3389/fnut.2022.785281] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 02/02/2022] [Indexed: 01/21/2023] Open
Abstract
Introduction Nutriepigenetic markers are predictive responses associated with changes in “surrounding” environmental conditions of humans, which may influence metabolic diseases. Although rich in calories, Western diets could be linked with the deficiency of micronutrients, resulting in the downstream of epigenetic and metabolic effects and consequently in obesity. Zinc (Zn) is an essential nutrient associated with distinct biological roles in human health. Despite the importance of Zn in metabolic processes, little is known about the relationship between Zn and epigenetic. Thus, the present study aimed to identify the epigenetic variables associated with Zn daily ingestion (ZnDI) and serum Zinc (ZnS) levels in women with and without obesity. Materials and Methods This is a case-control, non-randomized, single-center study conducted with 21 women allocated into two groups: control group (CG), composed of 11 women without obesity, and study group (SG), composed of 10 women with obesity. Anthropometric measurements, ZnDI, and ZnS levels were evaluated. Also, leukocyte DNA was extracted for DNA methylation analysis using 450 k Illumina BeadChips. The epigenetic clock was calculated by Horvath method. The chip analysis methylation pipeline (ChAMP) package selected the differentially methylated regions (DMRs). Results The SG had lower ZnS levels than the CG. Moreover, in SG, the ZnS levels were negatively associated with the epigenetic age acceleration. The DMR analysis revealed 37 DMRs associated with ZnDI and ZnS levels. The DMR of PM20D1 gene was commonly associated with ZnDI and ZnS levels and was hypomethylated in the SG. Conclusion Our findings provide new information on Zn's modulation of DNA methylation patterns and bring new perspectives for understanding the nutriepigenetic mechanisms in obesity.
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Affiliation(s)
- Natália Yumi Noronha
- Department of Internal Medicine, Ribeirao Preto Medical School, University of São Paulo, São Paulo, Brazil
| | - Mariana Barato
- Department of Molecular Biology, São José do Rio Preto Medical School, São Paulo, Brazil
| | - Chanachai Sae-Lee
- Research Division, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Marcela Augusta de Souza Pinhel
- Department of Internal Medicine, Ribeirao Preto Medical School, University of São Paulo, São Paulo, Brazil
- Department of Molecular Biology, São José do Rio Preto Medical School, São Paulo, Brazil
| | - Lígia Moriguchi Watanabe
- Department of Health Sciences, Ribeirão Preto Medical School, University of São Paulo, São Paulo, Brazil
| | | | | | - Déborah Araújo Morais
- Department of Clinical Analysis, Toxicology and Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, São Paulo, Brazil
| | - Wellington Tavares de Sousa
- Department of Clinical Analysis, Toxicology and Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, São Paulo, Brazil
| | - Vanessa Cristina de Oliveira Souza
- Department of Clinical Analysis, Toxicology and Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, São Paulo, Brazil
| | - Jessica Rodrigues Plaça
- National Institute of Science and Technology in Stem Cell and Cell Therapy and Center for Cell-Based Therapy, São Paulo, Brazil
| | - Wilson Salgado
- Department of Surgery and Anatomy, Ribeirao Preto Medical School, SãoPaulo, Brazil
| | - Fernando Barbosa
- Department of Clinical Analysis, Toxicology and Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, São Paulo, Brazil
| | - Torsten Plösch
- Department of Obstetrics and Gynecology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Carla Barbosa Nonino
- Department of Internal Medicine, Ribeirao Preto Medical School, University of São Paulo, São Paulo, Brazil
- Department of Health Sciences, Ribeirão Preto Medical School, University of São Paulo, São Paulo, Brazil
- *Correspondence: Carla Barbosa Nonino
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36
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Cristoferi I, Giacon TA, Boer K, van Baardwijk M, Neri F, Campisi M, Kimenai HJAN, Clahsen-van Groningen MC, Pavanello S, Furian L, Minnee RC. The applications of DNA methylation as a biomarker in kidney transplantation: a systematic review. Clin Epigenetics 2022; 14:20. [PMID: 35130936 PMCID: PMC8822833 DOI: 10.1186/s13148-022-01241-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 01/27/2022] [Indexed: 12/27/2022] Open
Abstract
Background Although kidney transplantation improves patient survival and quality of life, long-term results are hampered by both immune- and non-immune-mediated complications. Current biomarkers of post-transplant complications, such as allograft rejection, chronic renal allograft dysfunction, and cutaneous squamous cell carcinoma, have a suboptimal predictive value. DNA methylation is an epigenetic modification that directly affects gene expression and plays an important role in processes such as ischemia/reperfusion injury, fibrosis, and alloreactive immune response. Novel techniques can quickly assess the DNA methylation status of multiple loci in different cell types, allowing a deep and interesting study of cells’ activity and function. Therefore, DNA methylation has the potential to become an important biomarker for prediction and monitoring in kidney transplantation.
Purpose of the study The aim of this study was to evaluate the role of DNA methylation as a potential biomarker of graft survival and complications development in kidney transplantation. Material and Methods A systematic review of several databases has been conducted. The Newcastle–Ottawa scale and the Jadad scale have been used to assess the risk of bias for observational and randomized studies, respectively.
Results Twenty articles reporting on DNA methylation as a biomarker for kidney transplantation were included, all using DNA methylation for prediction and monitoring. DNA methylation pattern alterations in cells isolated from different tissues, such as kidney biopsies, urine, and blood, have been associated with ischemia–reperfusion injury and chronic renal allograft dysfunction. These alterations occurred in different and specific loci. DNA methylation status has also proved to be important for immune response modulation, having a crucial role in regulatory T cell definition and activity. Research also focused on a better understanding of the role of this epigenetic modification assessment for regulatory T cells isolation and expansion for future tolerance induction-oriented therapies. Conclusions Studies included in this review are heterogeneous in study design, biological samples, and outcome. More coordinated investigations are needed to affirm DNA methylation as a clinically relevant biomarker important for prevention, monitoring, and intervention. Supplementary Information The online version contains supplementary material available at 10.1186/s13148-022-01241-7.
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Affiliation(s)
- Iacopo Cristoferi
- Division of HPB and Transplant Surgery, Department of Surgery, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands. .,Department of Pathology and Clinical Bioinformatics, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands. .,Erasmus MC Transplant Institute, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands.
| | - Tommaso Antonio Giacon
- Kidney and Pancreas Transplantation Unit, Department of Surgical, Oncological and Gastroenterological Sciences, Padua University Hospital, Via Giustiniani 2, 35128, Padua, Italy.,Occupational Medicine, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, Padua University, Via Giustiniani 2, 35128, Padua, Italy.,Environmental and Respiratory Physiology Laboratory, Department of Biomedical Sciences, Padua University, Via Marzolo 3, 35131, Padua, Italy.,Institute of Anaesthesia and Intensive Care, Department of Medicine - DIMED, Padua University Hospital, Via Cesare Battisti 267, 35128, Padua, Italy
| | - Karin Boer
- Erasmus MC Transplant Institute, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands.,Division of Nephrology and Transplantation, Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, The Netherlands
| | - Myrthe van Baardwijk
- Division of HPB and Transplant Surgery, Department of Surgery, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands.,Department of Pathology and Clinical Bioinformatics, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands.,Erasmus MC Transplant Institute, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands
| | - Flavia Neri
- Kidney and Pancreas Transplantation Unit, Department of Surgical, Oncological and Gastroenterological Sciences, Padua University Hospital, Via Giustiniani 2, 35128, Padua, Italy
| | - Manuela Campisi
- Occupational Medicine, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, Padua University, Via Giustiniani 2, 35128, Padua, Italy
| | - Hendrikus J A N Kimenai
- Division of HPB and Transplant Surgery, Department of Surgery, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands.,Erasmus MC Transplant Institute, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands
| | - Marian C Clahsen-van Groningen
- Department of Pathology and Clinical Bioinformatics, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands.,Erasmus MC Transplant Institute, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands.,Institute of Experimental Medicine and Systems Biology, RWTH Aachen University, Pauwelsstraße 30, 52074, Aachen, Germany
| | - Sofia Pavanello
- Occupational Medicine, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, Padua University, Via Giustiniani 2, 35128, Padua, Italy
| | - Lucrezia Furian
- Kidney and Pancreas Transplantation Unit, Department of Surgical, Oncological and Gastroenterological Sciences, Padua University Hospital, Via Giustiniani 2, 35128, Padua, Italy
| | - Robert C Minnee
- Division of HPB and Transplant Surgery, Department of Surgery, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands.,Erasmus MC Transplant Institute, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015GD, Rotterdam, the Netherlands
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OUP accepted manuscript. Hum Reprod Update 2022; 28:629-655. [DOI: 10.1093/humupd/dmac010] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 02/04/2022] [Indexed: 11/13/2022] Open
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Wang C, Cardenas A, Hutchinson JN, Just A, Heiss J, Hou L, Zheng Y, Coull BA, Kosheleva A, Koutrakis P, Baccarelli AA, Schwartz JD. Short- and intermediate-term exposure to ambient fine particulate elements and leukocyte epigenome-wide DNA methylation in older men: the Normative Aging Study. ENVIRONMENT INTERNATIONAL 2022; 158:106955. [PMID: 34717175 PMCID: PMC8710082 DOI: 10.1016/j.envint.2021.106955] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 10/18/2021] [Accepted: 10/22/2021] [Indexed: 05/08/2023]
Abstract
BACKGROUND Several epigenome-wide association studies (EWAS) of ambient particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5) have been reported. However, EWAS of PM2.5 elements (PEs), reflecting different emission sources, are very limited. OBJECTIVES We performed EWAS of short- and intermediate-term exposure to PM2.5 and 13 PEs. We hypothesized that significant changes in DNAm may vary by PM2.5 mass and its elements. METHODS We repeatedly collected blood samples in the Normative Aging Study and measured leukocyte DNA methylation (DNAm) with the Illumina HumanMethylation450K BeadChip. We collected daily PM2.5 and 13 PEs at a fixed central site. To estimate the associations between each PE and DNAm at individual cytosine-phosphate-guanine (CpG) sites, we incorporated a distributed-lag (0-27 d) term in the setting of median regression with subject-specific intercept and examined cumulative lag associations. We also accounted for selection bias due to loss to follow-up and mortality prior to enrollment. Significantly differentially methylated probes (DMPs) were identified using Bonferroni correction for multiple testing. We further conducted regional and pathway analyses to identify significantly differentially methylated regions (DMRs) and pathways. RESULTS We included 695 men with 1,266 visits between 1999 and 2013. The subjects had a mean age of 75 years. The significant DMPs, DMRs, and pathways varied by to PM2.5 total mass and PEs. For example, PM2.5 total mass was associated with 2,717 DMPs and 10,470 DMRs whereas Pb was associated with 3,173 DMPs and 637 DMRs. The identified pathways by PM2.5 mass were mostly involved in mood disorders, neuroplasticity, immunity, and inflammation, whereas the pathways associated with motor vehicles (BC, Cu, Pb, and Zn) were related with cardiovascular disease and cancer (e.g., "PPARs signaling"). CONCLUSIONS PM2.5 and PE were associated with methylation changes at multiple probes and along multiple pathways, in ways that varied by particle components.
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Affiliation(s)
- Cuicui Wang
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health and Center for Computational Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - John N Hutchinson
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Allan Just
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jonathan Heiss
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Yinan Zheng
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Brent A Coull
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Anna Kosheleva
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Petros Koutrakis
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Columbia Mailman School of Public Health, New York, NY 10032, USA
| | - Joel D Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
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Heery R, Schaefer MH. DNA methylation variation along the cancer epigenome and the identification of novel epigenetic driver events. Nucleic Acids Res 2021; 49:12692-12705. [PMID: 34871444 PMCID: PMC8682778 DOI: 10.1093/nar/gkab1167] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 11/08/2021] [Accepted: 11/10/2021] [Indexed: 12/12/2022] Open
Abstract
While large-scale studies applying various statistical approaches have identified hundreds of mutated driver genes across various cancer types, the contribution of epigenetic changes to cancer remains more enigmatic. This is partly due to the fact that certain regions of the cancer genome, due to their genomic and epigenomic properties, are more prone to dysregulated DNA methylation than others. Thus, it has been difficult to distinguish which promoter methylation changes are really driving carcinogenesis from those that are mostly just a reflection of their genomic location. By developing a novel method that corrects for epigenetic covariates, we reveal a small, concise set of potential epigenetic driver events. Interestingly, those changes suggest different modes of epigenetic carcinogenesis: first, we observe recurrent inactivation of known cancer genes across tumour types suggesting a higher convergence on common tumour suppressor pathways than previously anticipated. Second, in prostate cancer, a cancer type with few recurrently mutated genes, we demonstrate how the epigenome primes tumours towards higher tolerance of other aberrations.
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Affiliation(s)
- Richard Heery
- Department of Experimental Oncology, IEO European Institute of Oncology IRCCS, Via Adamello 16, 20139, Milan, Italy
| | - Martin H Schaefer
- Department of Experimental Oncology, IEO European Institute of Oncology IRCCS, Via Adamello 16, 20139, Milan, Italy
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Campagna MP, Xavier A, Lechner-Scott J, Maltby V, Scott RJ, Butzkueven H, Jokubaitis VG, Lea RA. Epigenome-wide association studies: current knowledge, strategies and recommendations. Clin Epigenetics 2021; 13:214. [PMID: 34863305 PMCID: PMC8645110 DOI: 10.1186/s13148-021-01200-8] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 11/19/2021] [Indexed: 02/06/2023] Open
Abstract
The aetiology and pathophysiology of complex diseases are driven by the interaction between genetic and environmental factors. The variability in risk and outcomes in these diseases are incompletely explained by genetics or environmental risk factors individually. Therefore, researchers are now exploring the epigenome, a biological interface at which genetics and the environment can interact. There is a growing body of evidence supporting the role of epigenetic mechanisms in complex disease pathophysiology. Epigenome-wide association studies (EWASes) investigate the association between a phenotype and epigenetic variants, most commonly DNA methylation. The decreasing cost of measuring epigenome-wide methylation and the increasing accessibility of bioinformatic pipelines have contributed to the rise in EWASes published in recent years. Here, we review the current literature on these EWASes and provide further recommendations and strategies for successfully conducting them. We have constrained our review to studies using methylation data as this is the most studied epigenetic mechanism; microarray-based data as whole-genome bisulphite sequencing remains prohibitively expensive for most laboratories; and blood-based studies due to the non-invasiveness of peripheral blood collection and availability of archived DNA, as well as the accessibility of publicly available blood-cell-based methylation data. Further, we address multiple novel areas of EWAS analysis that have not been covered in previous reviews: (1) longitudinal study designs, (2) the chip analysis methylation pipeline (ChAMP), (3) differentially methylated region (DMR) identification paradigms, (4) methylation quantitative trait loci (methQTL) analysis, (5) methylation age analysis and (6) identifying cell-specific differential methylation from mixed cell data using statistical deconvolution.
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Affiliation(s)
- Maria Pia Campagna
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
| | - Alexandre Xavier
- Centre for Information Based Medicine, Hunter Medical Research Institute, Newcastle, Australia
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, Australia
| | - Jeannette Lechner-Scott
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, Australia
- Department of Neurology, Division of Medicine, John Hunter Hospital, Newcastle, Australia
| | - Vicky Maltby
- Centre for Information Based Medicine, Hunter Medical Research Institute, Newcastle, Australia
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, Australia
| | - Rodney J Scott
- Centre for Information Based Medicine, Hunter Medical Research Institute, Newcastle, Australia
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, Australia
- Division of Molecular Medicine, New South Wales Health Pathology North, Newcastle, Australia
| | - Helmut Butzkueven
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
- Department of Neurology, Alfred Health, Melbourne, Australia
| | - Vilija G Jokubaitis
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
- Department of Neurology, Alfred Health, Melbourne, Australia
| | - Rodney A Lea
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, Australia.
- Centre for Genomics and Personalised Health, School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia.
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Gallon J, Coto-Llerena M, Ercan C, Bianco G, Paradiso V, Nuciforo S, Taha-Melitz S, Meier MA, Boldanova T, Pérez-Del-Pulgar S, Rodríguez-Tajes S, von Flüe M, Soysal SD, Kollmar O, Llovet JM, Villanueva A, Terracciano LM, Heim MH, Ng CKY, Piscuoglio S. Epigenetic priming in chronic liver disease impacts the transcriptional and genetic landscapes of hepatocellular carcinoma. Mol Oncol 2021; 16:665-682. [PMID: 34863035 PMCID: PMC8807355 DOI: 10.1002/1878-0261.13154] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 10/18/2021] [Accepted: 12/02/2021] [Indexed: 01/05/2023] Open
Abstract
Hepatocellular carcinomas (HCCs) usually arise from chronic liver disease (CLD). Precancerous cells in chronically inflamed environments may be 'epigenetically primed', sensitising them to oncogenic transformation. We investigated whether epigenetic priming in CLD may affect HCC outcomes by influencing the genomic and transcriptomic landscapes of HCC. Analysis of DNA methylation arrays from 10 paired CLD-HCC identified 339 shared dysregulated CpG sites and 18 shared differentially methylated regions compared with healthy livers. These regions were associated with dysregulated expression of genes with relevance in HCC, including ubiquitin D (UBD), cytochrome P450 family 2 subfamily C member 19 (CYP2C19) and O-6-methylguanine-DNA methyltransferase (MGMT). Methylation changes were recapitulated in an independent cohort of nine paired CLD-HCC. High CLD methylation score, defined using the 124 dysregulated CpGs in CLD and HCC in both cohorts, was associated with poor survival, increased somatic genetic alterations and TP53 mutations in two independent HCC cohorts. Oncogenic transcriptional and methylation dysregulation is evident in CLD and compounded in HCC. Epigenetic priming in CLD sculpts the transcriptional landscape of HCC and creates an environment favouring the acquisition of genetic alterations, suggesting that the extent of epigenetic priming in CLD could influence disease outcome.
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Affiliation(s)
- John Gallon
- Visceral Surgery and Precision Medicine Research Laboratory, Department of Biomedicine, University of Basel, Switzerland
| | - Mairene Coto-Llerena
- Visceral Surgery and Precision Medicine Research Laboratory, Department of Biomedicine, University of Basel, Switzerland.,Institute of Medical Genetics and Pathology, University Hospital Basel, Switzerland
| | - Caner Ercan
- Institute of Medical Genetics and Pathology, University Hospital Basel, Switzerland
| | - Gaia Bianco
- Visceral Surgery and Precision Medicine Research Laboratory, Department of Biomedicine, University of Basel, Switzerland
| | - Viola Paradiso
- Institute of Medical Genetics and Pathology, University Hospital Basel, Switzerland
| | - Sandro Nuciforo
- Hepatology Laboratory, Department of Biomedicine, University of Basel, Switzerland
| | - Stephanie Taha-Melitz
- Visceral Surgery and Precision Medicine Research Laboratory, Department of Biomedicine, University of Basel, Switzerland.,Clarunis, Department of Visceral Surgery, University Centre for Gastrointestinal and Liver Diseases, St. Clara Hospital and University Hospital Basel, Switzerland
| | - Marie-Anne Meier
- Hepatology Laboratory, Department of Biomedicine, University of Basel, Switzerland
| | - Tujana Boldanova
- Hepatology Laboratory, Department of Biomedicine, University of Basel, Switzerland.,Clarunis, Department of Visceral Surgery, University Centre for Gastrointestinal and Liver Diseases, St. Clara Hospital and University Hospital Basel, Switzerland
| | | | | | - Markus von Flüe
- Clarunis, Department of Visceral Surgery, University Centre for Gastrointestinal and Liver Diseases, St. Clara Hospital and University Hospital Basel, Switzerland
| | - Savas D Soysal
- Clarunis, Department of Visceral Surgery, University Centre for Gastrointestinal and Liver Diseases, St. Clara Hospital and University Hospital Basel, Switzerland
| | - Otto Kollmar
- Clarunis, Department of Visceral Surgery, University Centre for Gastrointestinal and Liver Diseases, St. Clara Hospital and University Hospital Basel, Switzerland
| | - Josep M Llovet
- Translational Research in Hepatic Oncology, Liver Unit, IDIBAPS, Hospital Clínic, University of Barcelona, Spain.,Liver Cancer Program, Divisions of Liver Diseases and Hematology/Medical Oncology, Department of Medicine, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Augusto Villanueva
- Liver Cancer Program, Divisions of Liver Diseases and Hematology/Medical Oncology, Department of Medicine, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Luigi M Terracciano
- Department of Pathology, Humanitas Clinical and Research Center, IRCCS, Milan, Italy.,Department of Biomedical Sciences, Humanitas University, Milan, Italy
| | - Markus H Heim
- Hepatology Laboratory, Department of Biomedicine, University of Basel, Switzerland.,Clarunis, Department of Visceral Surgery, University Centre for Gastrointestinal and Liver Diseases, St. Clara Hospital and University Hospital Basel, Switzerland
| | - Charlotte K Y Ng
- Department for BioMedical Research, University of Bern, Switzerland.,SIB, Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Salvatore Piscuoglio
- Visceral Surgery and Precision Medicine Research Laboratory, Department of Biomedicine, University of Basel, Switzerland.,Institute of Medical Genetics and Pathology, University Hospital Basel, Switzerland
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Bozack AK, Rifas-Shiman SL, Coull BA, Baccarelli AA, Wright RO, Amarasiriwardena C, Gold DR, Oken E, Hivert MF, Cardenas A. Prenatal metal exposure, cord blood DNA methylation and persistence in childhood: an epigenome-wide association study of 12 metals. Clin Epigenetics 2021; 13:208. [PMID: 34798907 PMCID: PMC8605513 DOI: 10.1186/s13148-021-01198-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 11/08/2021] [Indexed: 12/31/2022] Open
Abstract
Background Prenatal exposure to essential and non-essential metals impacts birth and child health, including fetal growth and neurodevelopment. DNA methylation (DNAm) may be involved in pathways linking prenatal metal exposure and health. In the Project Viva cohort, we analyzed the extent to which metals (As, Ba, Cd, Cr, Cs, Cu, Hg, Mg, Mn, Pb, Se, and Zn) measured in maternal erythrocytes were associated with differentially methylated positions (DMPs) and regions (DMRs) in cord blood and tested if associations persisted in blood collected in mid-childhood. We measured metal concentrations in first-trimester maternal erythrocytes, and DNAm in cord blood (N = 361) and mid-childhood blood (N = 333, 6–10 years) with the Illumina HumanMethylation450 BeadChip. For each metal individually, we tested for DMPs using linear models (considered significant at FDR < 0.05), and for DMRs using comb-p (Sidak p < 0.05). Covariates included biologically relevant variables and estimated cell-type composition. We also performed sex-stratified analyses. Results Pb was associated with decreased methylation of cg20608990 (CASP8) (FDR = 0.04), and Mn was associated with increased methylation of cg02042823 (A2BP1) in cord blood (FDR = 9.73 × 10–6). Both associations remained significant but attenuated in blood DNAm collected at mid-childhood (p < 0.01). Two and nine Mn-associated DMPs were identified in male and female infants, respectively (FDR < 0.05), with two and six persisting in mid-childhood (p < 0.05). All metals except Ba and Pb were associated with ≥ 1 DMR among all infants (Sidak p < 0.05). Overlapping DMRs annotated to genes in the human leukocyte antigen (HLA) region were identified for Cr, Cs, Cu, Hg, Mg, and Mn. Conclusions Prenatal metal exposure is associated with DNAm, including DMRs annotated to genes involved in neurodevelopment. Future research is needed to determine if DNAm partially explains the relationship between prenatal metal exposures and health outcomes. Supplementary Information The online version contains supplementary material available at 10.1186/s13148-021-01198-z.
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Affiliation(s)
- Anne K Bozack
- Division of Environmental Health Sciences, School of Public Health, University of California Berkeley, 2121 Berkeley Way, Room 5302, Berkeley, CA, 94720, USA
| | - Sheryl L Rifas-Shiman
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Brent A Coull
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York City, NY, USA
| | - Robert O Wright
- Department of Environmental Medicine and Public Health and Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, NY, New York City, USA
| | - Chitra Amarasiriwardena
- Department of Environmental Medicine and Public Health and Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, NY, New York City, USA
| | - Diane R Gold
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.,Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.,Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health, University of California Berkeley, 2121 Berkeley Way, Room 5302, Berkeley, CA, 94720, USA. .,Center for Computational Biology, University of California, Berkeley, CA, USA.
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Nikolaienko O, Lønning PE, Knappskog S. ramr: an R/Bioconductor package for detection of rare aberrantly methylated regions. Bioinformatics 2021; 38:133-140. [PMID: 34383893 PMCID: PMC8696093 DOI: 10.1093/bioinformatics/btab586] [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: 12/01/2020] [Revised: 06/26/2021] [Accepted: 08/11/2021] [Indexed: 02/03/2023] Open
Abstract
MOTIVATION With recent advances in the field of epigenetics, the focus is widening from large and frequent disease- or phenotype-related methylation signatures to rare alterations transmitted mitotically or transgenerationally (constitutional epimutations). Merging evidence indicate that such constitutional alterations, albeit occurring at a low mosaic level, may confer risk of disease later in life. Given their inherently low incidence rate and mosaic nature, there is a need for bioinformatic tools specifically designed to analyze such events. RESULTS We have developed a method (ramr) to identify aberrantly methylated DNA regions (AMRs). ramr can be applied to methylation data obtained by array or next-generation sequencing techniques to discover AMRs being associated with elevated risk of cancer as well as other diseases. We assessed accuracy and performance metrics of ramr and confirmed its applicability for analysis of large public datasets. Using ramr we identified aberrantly methylated regions that are known or may potentially be associated with development of colorectal cancer and provided functional annotation of AMRs that arise at early developmental stages. AVAILABILITY AND IMPLEMENTATION The R package is freely available at https://github.com/BBCG/ramr and https://bioconductor.org/packages/ramr. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | - Per Eystein Lønning
- K. G. Jebsen Center for Genome-Directed Cancer Therapy, Department of Clinical Science, University of Bergen, Bergen, Norway,Department of Oncology, Haukeland University Hospital, Bergen, Norway
| | - Stian Knappskog
- K. G. Jebsen Center for Genome-Directed Cancer Therapy, Department of Clinical Science, University of Bergen, Bergen, Norway,Department of Oncology, Haukeland University Hospital, Bergen, Norway
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Chu X, Zhang B, Koeken VACM, Gupta MK, Li Y. Multi-Omics Approaches in Immunological Research. Front Immunol 2021; 12:668045. [PMID: 34177908 PMCID: PMC8226116 DOI: 10.3389/fimmu.2021.668045] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 05/28/2021] [Indexed: 12/14/2022] Open
Abstract
The immune system plays a vital role in health and disease, and is regulated through a complex interactive network of many different immune cells and mediators. To understand the complexity of the immune system, we propose to apply a multi-omics approach in immunological research. This review provides a complete overview of available methodological approaches for the different omics data layers relevant for immunological research, including genetics, epigenetics, transcriptomics, proteomics, metabolomics, and cellomics. Thereafter, we describe the various methods for data analysis as well as how to integrate different layers of omics data. Finally, we discuss the possible applications of multi-omics studies and opportunities they provide for understanding the complex regulatory networks as well as immune variation in various immune-related diseases.
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Affiliation(s)
- Xiaojing Chu
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
- Department of Computational Biology for Individualised Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - Bowen Zhang
- Department of Computational Biology for Individualised Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - Valerie A. C. M. Koeken
- Department of Computational Biology for Individualised Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, Netherlands
| | - Manoj Kumar Gupta
- Department of Computational Biology for Individualised Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - Yang Li
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
- Department of Computational Biology for Individualised Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, Netherlands
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Li W, Guo L, Tang W, Ma Y, Wang X, Shao Y, Zhao H, Ying J. Identification of DNA methylation biomarkers for risk of liver metastasis in early-stage colorectal cancer. Clin Epigenetics 2021; 13:126. [PMID: 34108011 PMCID: PMC8190869 DOI: 10.1186/s13148-021-01108-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 05/31/2021] [Indexed: 12/23/2022] Open
Abstract
Background Liver metastases can occur even in CRC patients who underwent curative surgery. While evidence suggested that adjuvant chemotherapy can help to reduce the occurrence of liver metastases for certain patients, it is not a recommended routine as the side effects outweigh the potential benefits, especially in Stage II CRC patients. This study aims to construct a model for predicting liver metastasis risk using differential methylation signals in primary CRC tumors, which can facilitate the decision for adjuvant chemotherapy. Methods Fifty-nine stage I/II and IV CRC patients were enrolled. Primary tumor, adjacent normal tissue, and metastatic tumor tissues were subject to targeted bisulfite sequencing for DNA methylation. The Least Absolute Shrinkage and Selection Operator (LASSO) algorithm was used to identify potential DMRs for predicting liver metastasis of CRC. Results We identified a total of 241,573 DMRs by comparing the DNA methylation profile of primary tumors of stage II patients who developed metastasis to those who were metastasis-free during the follow up period. 213 DMRs were associated with poor prognosis, among which 182 DMRS were found to be hypermethylated in the primary tumor of patients with metastases. Furthermore, by using the LASSO regression model, we identified 23 DMRs that contributed to a high probability of liver metastasis of CRC. The leave-one-out cross validation (LOOCV) was used to evaluate model predictive performance at an AUC of 0.701. In particular, 7 out of those 23 DMRs were found to be in the promoter region of genes that were previously reported prognostic biomarkers in diverse tumor types, including TNNI2, PAX8, GUF1, KLF4, EVI2B, CEP112, and long non-coding RNA AC011298. In addition, the model was also able to distinguish metastases of different sites (liver or lung) at an AUC of 0.933. Conclusion We have identified DNA methylation biomarkers associated with the risk of cancer liver metastasis in early-stage CRC patients. A risk prediction model based on those epigenetic markers was proposed for outcome assessment. Supplementary Information The online version contains supplementary material available at 10.1186/s13148-021-01108-3.
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Affiliation(s)
- Weihua Li
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Beijing, 100021, China
| | - Lei Guo
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Beijing, 100021, China
| | | | - Yutong Ma
- Nanjing Geneseeq Technology Inc., Nanjing, Jiangsu, China
| | - Xiaonan Wang
- Nanjing Geneseeq Technology Inc., Nanjing, Jiangsu, China
| | - Yang Shao
- Nanjing Geneseeq Technology Inc., Nanjing, Jiangsu, China
| | - Hong Zhao
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
| | - Jianming Ying
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Beijing, 100021, China.
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Methylome-wide change associated with response to electroconvulsive therapy in depressed patients. Transl Psychiatry 2021; 11:347. [PMID: 34091594 PMCID: PMC8179923 DOI: 10.1038/s41398-021-01474-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 05/10/2021] [Accepted: 05/21/2021] [Indexed: 12/31/2022] Open
Abstract
Electroconvulsive therapy (ECT) is a quick-acting and powerful antidepressant treatment considered to be effective in treating severe and pharmacotherapy-resistant forms of depression. Recent studies have suggested that epigenetic mechanisms can mediate treatment response and investigations about the relationship between the effects of ECT and DNA methylation have so far largely taken candidate approaches. In the present study, we examined the effects of ECT on the methylome associated with response in depressed patients (n = 34), testing for differentially methylated CpG sites before the first and after the last ECT treatment. We identified one differentially methylated CpG site associated with the effect of ECT response (defined as >50% decrease in Hamilton Depression Rating Scale score, HDRS), TNKS (q < 0.05; p = 7.15 × 10-8). When defining response continuously (ΔHDRS), the top suggestive differentially methylated CpG site was in FKBP5 (p = 3.94 × 10-7). Regional analyses identified two differentially methylated regions on chromosomes 8 (Šídák's p = 0.0031) and 20 (Šídák's p = 4.2 × 10-5) associated with ΔHDRS. Functional pathway analysis did not identify any significant pathways. A confirmatory look at candidates previously proposed to be involved in ECT mechanisms found CpG sites associated with response only at the nominally significant level (p < 0.05). Despite the limited sample size, the present study was able to identify epigenetic change associated with ECT response suggesting that this approach, especially when involving larger samples, has the potential to inform the study of mechanisms involved in ECT and severe and treatment-resistant depression.
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Xu Z, Xie C, Taylor JA, Niu L. ipDMR: identification of differentially methylated regions with interval P-values. Bioinformatics 2021; 37:711-713. [PMID: 32805005 PMCID: PMC8248314 DOI: 10.1093/bioinformatics/btaa732] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2020] [Revised: 08/05/2020] [Accepted: 08/11/2020] [Indexed: 12/18/2022] Open
Abstract
SUMMARY ipDMR is an R software tool for identification of differentially methylated regions (DMRs) using auto-correlated P-values for individual CpGs from epigenome-wide association analysis using array or bisulfite sequencing data. It summarizes P-values for adjacent CpGs, identifies association peaks and then extends peaks to find boundaries of DMRs. ipDMR uses BED format files as input and is easy to use. Simulations guided by real data found that ipDMR outperformed current available methods and provided slightly higher true positive rates and much lower false discovery rates. AVAILABILITY AND IMPLEMENTATION ipDMR is available at https://bioconductor.org/packages/release/bioc/html/ENmix.html. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Zongli Xu
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA
| | - Changchun Xie
- Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, College of Medicine, University of Cincinnati, Cincinnati, OH 45267, USA
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA.,Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA
| | - Liang Niu
- Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, College of Medicine, University of Cincinnati, Cincinnati, OH 45267, USA
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Epigenetic Alterations of Maternal Tobacco Smoking during Pregnancy: A Narrative Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18105083. [PMID: 34064931 PMCID: PMC8151244 DOI: 10.3390/ijerph18105083] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 04/29/2021] [Accepted: 05/04/2021] [Indexed: 12/11/2022]
Abstract
In utero exposure to maternal tobacco smoking is the leading cause of birth complications in addition to being associated with later impairment in child’s development. Epigenetic alterations, such as DNA methylation (DNAm), miRNAs expression, and histone modifications, belong to possible underlying mechanisms linking maternal tobacco smoking during pregnancy and adverse birth outcomes and later child’s development. The aims of this review were to provide an update on (1) the main results of epidemiological studies on the impact of in utero exposure to maternal tobacco smoking on epigenetic mechanisms, and (2) the technical issues and methods used in such studies. In contrast with miRNA and histone modifications, DNAm has been the most extensively studied epigenetic mechanism with regard to in utero exposure to maternal tobacco smoking. Most studies relied on cord blood and children’s blood, but placenta is increasingly recognized as a powerful tool, especially for markers of pregnancy exposures. Some recent studies suggest reversibility in DNAm in certain genomic regions as well as memory of smoking exposure in DNAm in other regions, upon smoking cessation before or during pregnancy. Furthermore, reversibility could be more pronounced in miRNA expression compared to DNAm. Increasing evidence based on longitudinal data shows that maternal smoking-associated DNAm changes persist during childhood. In this review, we also discuss some issues related to cell heterogeneity as well as downstream statistical analyses used to relate maternal tobacco smoking during pregnancy and epigenetics. The epigenetic effects of maternal smoking during pregnancy have been among the most widely investigated in the epigenetic epidemiology field. However, there are still huge gaps to fill in, including on the impact on miRNA expression and histone modifications to get a better view of the whole epigenetic machinery. The consistency of maternal tobacco smoking effects across epigenetic marks and across tissues will also provide crucial information for future studies. Advancement in bioinformatic and biostatistics approaches is key to develop a comprehensive analysis of these biological systems.
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Rytel MR, Butler R, Eliot M, Braun JM, Houseman EA, Kelsey KT. DNA methylation in the adipose tissue and whole blood of Agent Orange-exposed Operation Ranch Hand veterans: a pilot study. Environ Health 2021; 20:43. [PMID: 33849548 PMCID: PMC8045317 DOI: 10.1186/s12940-021-00717-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 03/08/2021] [Indexed: 05/26/2023]
Abstract
BACKGROUND Between 1962 and 1971, the US Air Force sprayed Agent Orange across Vietnam, exposing many soldiers to this dioxin-containing herbicide. Several negative health outcomes have been linked to Agent Orange exposure, but data is lacking on the effects this chemical has on the genome. Therefore, we sought to characterize the impact of Agent Orange exposure on DNA methylation in the whole blood and adipose tissue of veterans enrolled in the Air Force Health Study (AFHS). METHODS We received adipose tissue (n = 37) and whole blood (n = 42) from veterans in the AFHS. Study participants were grouped as having low, moderate, or high TCDD body burden based on their previously measured serum levels of dioxin. DNA methylation was assessed using the Illumina 450 K platform. RESULTS Epigenome-wide analysis indicated that there were no FDR-significantly methylated CpGs in either tissue with TCDD burden. However, 3 CpGs in the adipose tissue (contained within SLC9A3, LYNX1, and TNRC18) were marginally significantly (q < 0.1) hypomethylated, and 1 CpG in whole blood (contained within PTPRN2) was marginally significantly (q < 0.1) hypermethylated with high TCDD burden. Analysis for differentially methylated DNA regions yielded SLC9A3, among other regions in adipose tissue, to be significantly differentially methylated with higher TCDD burden. Comparing whole blood data to a study of dioxin exposed adults from Alabama identified a CpG within the gene SMO that was hypomethylated with dioxin exposure in both studies. CONCLUSION We found limited evidence of dioxin associated DNA methylation in adipose tissue and whole blood in this pilot study of Vietnam War veterans. Nevertheless, loci in the genes of SLC9A3 in adipose tissue, and PTPRN2 and SMO in whole blood, should be included in future exposure analyses.
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Affiliation(s)
- Matthew R. Rytel
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912 USA
| | - Rondi Butler
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912 USA
- Department of Pathology and Laboratory Medicine, Brown University School of Public Health, Providence, RI 02912 USA
| | - Melissa Eliot
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912 USA
| | - Joseph M. Braun
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912 USA
| | - E. Andres Houseman
- Statistical Bioinformatics, GlaxoSmithKline, 1250 S Collegeville Rd, Collegeville, PA 19426 USA
| | - Karl T. Kelsey
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912 USA
- Department of Pathology and Laboratory Medicine, Brown University School of Public Health, Providence, RI 02912 USA
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Kallak TK, Bränn E, Fransson E, Johansson Å, Lager S, Comasco E, Lyle R, Skalkidou A. DNA methylation in cord blood in association with prenatal depressive symptoms. Clin Epigenetics 2021; 13:78. [PMID: 33845866 PMCID: PMC8042709 DOI: 10.1186/s13148-021-01054-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 03/09/2021] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Prenatal symptoms of depression (PND) and anxiety affect up to every third pregnancy. Children of mothers with mental health problems are at higher risk of developmental problems, possibly through epigenetic mechanisms together with other factors such as genetic and environmental. We investigated DNA methylation in cord blood in relation to PND, taking into consideration a history of depression, co-morbidity with anxiety and selective serotonin reuptake inhibitors (SSRI) use, and stratified by sex of the child. Mothers (N = 373) prospectively filled out web-based questionnaires regarding mood symptoms and SSRI use throughout pregnancy. Cord blood was collected at birth and DNA methylation was measured using Illumina MethylationEPIC array at 850 000 CpG sites throughout the genome. Differentially methylated regions were identified using Kruskal-Wallis test, and Benjamini-Hochberg adjusted p-values < 0.05 were considered significant. RESULTS No differential DNA methylation was associated with PND alone; however, differential DNA methylation was observed in children exposed to comorbid PND with anxiety symptoms compared with healthy controls in ABCF1 (log twofold change - 0.2), but not after stratification by sex of the child. DNA methylation in children exposed to PND without SSRI treatment and healthy controls both differed in comparison with SSRI exposed children at several sites and regions, among which hypomethylation was observed in CpGs in the promoter region of CRBN (log2 fold change - 0.57), involved in brain development, and hypermethylation in MDFIC (log2 fold change 0.45), associated with the glucocorticoid stress response. CONCLUSION Although it is not possible to assess if these methylation differences are due to SSRI treatment itself or to more severe depression, our findings add on to existing knowledge that there might be different biological consequences for the child depending on whether maternal PND was treated with SSRIs or not.
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Affiliation(s)
| | - Emma Bränn
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
| | - Emma Fransson
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
| | - Åsa Johansson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Susanne Lager
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
| | - Erika Comasco
- Department of Neuroscience, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Robert Lyle
- Department of Medical Genetics and Norwegian Sequencing Centre (NSC), Oslo University Hospital, Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Alkistis Skalkidou
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
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