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Sun Z, Kou C, Gao Z, Guo X, Han B, Feng Y, Ding Q, Bai W. Association between the copy number variations of Methyl-CpG binding domain family and schizophrenia. Gene 2024; 930:148836. [PMID: 39127413 DOI: 10.1016/j.gene.2024.148836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Revised: 07/17/2024] [Accepted: 08/07/2024] [Indexed: 08/12/2024]
Abstract
Schizophrenia is recognized as one of the most severe psychiatric disorders, with its pathogenesis likely involving genetic, epigenetic, developmental, and environmental factors. Members of the Methyl-CpG Binding Domain (MBD) Family play a crucial role in the regulation of genomic DNA methylation, and studies have implicated the association between MBD family and neurodevelopmental disorders. Copy number variations (CNVs) are a significant genetic basis for human genomic variation, also playing a critical role in the genetic processes of schizophrenia. Therefore, we aimed to evaluate the susceptibility of MBD family CNVs to schizophrenia by exploring and validating them in two separate populations using CNVplex™ and qPCR methods, and to explore the relationship between MBD family CNVs and clinical phenotypes in the overall population using chi-square tests and Fisher's exact tests. Results suggest that an increase in MBD1 gene copy number and a deficiency in MBD2 gene copy number may be associated with the risk of schizophrenia. The deficiency in MBD2 gene copy number may increase the risk of delusion of reference and delusion of persecutory in the overall sample, as well as in males. This research provides preliminary evidence supporting the association between MBD family CNVs and schizophrenia, highlighting the potential role of the MBD family in the pathogenesis of schizophrenia.
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Affiliation(s)
- Zhouyang Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, Jilin Province, 130021, China
| | - Changgui Kou
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, Jilin Province, 130021, China
| | - Zibo Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, Jilin Province, 130021, China
| | - Xinru Guo
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, Jilin Province, 130021, China
| | - Beibei Han
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, Jilin Province, 130021, China
| | - Yuan Feng
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, Jilin Province, 130021, China
| | - Qianlu Ding
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, Jilin Province, 130021, China
| | - Wei Bai
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, Jilin Province, 130021, China.
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2
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Tomusiak A, Floro A, Tiwari R, Riley R, Matsui H, Andrews N, Kasler HG, Verdin E. Development of an epigenetic clock resistant to changes in immune cell composition. Commun Biol 2024; 7:934. [PMID: 39095531 PMCID: PMC11297166 DOI: 10.1038/s42003-024-06609-4] [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: 09/22/2023] [Accepted: 07/14/2024] [Indexed: 08/04/2024] Open
Abstract
Epigenetic clocks are age predictors that use machine-learning models trained on DNA CpG methylation values to predict chronological or biological age. Increases in predicted epigenetic age relative to chronological age (epigenetic age acceleration) are connected to aging-associated pathologies, and changes in epigenetic age are linked to canonical aging hallmarks. However, epigenetic clocks rely on training data from bulk tissues whose cellular composition changes with age. Here, we found that human naive CD8+ T cells, which decrease in frequency during aging, exhibit an epigenetic age 15-20 years younger than effector memory CD8+ T cells from the same individual. Importantly, homogenous naive T cells isolated from individuals of different ages show a progressive increase in epigenetic age, indicating that current epigenetic clocks measure two independent variables, aging and immune cell composition. To isolate the age-associated cell intrinsic changes, we created an epigenetic clock, the IntrinClock, that did not change among 10 immune cell types tested. IntrinClock shows a robust predicted epigenetic age increase in a model of replicative senescence in vitro and age reversal during OSKM-mediated reprogramming.
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Affiliation(s)
- Alan Tomusiak
- Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, 94945, CA, USA
- Department of Gerontology, University of Southern California, 3715 McClintock Ave, Los Angeles, 90089, CA, USA
| | - Ariel Floro
- Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, 94945, CA, USA
- Department of Gerontology, University of Southern California, 3715 McClintock Ave, Los Angeles, 90089, CA, USA
| | - Ritesh Tiwari
- Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, 94945, CA, USA
| | - Rebeccah Riley
- Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, 94945, CA, USA
| | - Hiroyuki Matsui
- Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, 94945, CA, USA
| | - Nicolas Andrews
- Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, 94945, CA, USA
| | - Herbert G Kasler
- Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, 94945, CA, USA
| | - Eric Verdin
- Buck Institute for Research on Aging, 8001 Redwood Blvd, Novato, 94945, CA, USA.
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3
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Yusipov I, Kalyakulina A, Trukhanov A, Franceschi C, Ivanchenko M. Map of epigenetic age acceleration: A worldwide analysis. Ageing Res Rev 2024; 100:102418. [PMID: 39002646 DOI: 10.1016/j.arr.2024.102418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 07/03/2024] [Accepted: 07/08/2024] [Indexed: 07/15/2024]
Abstract
We present a systematic analysis of epigenetic age acceleration based on by far the largest collection of publicly available DNA methylation data for healthy samples (93 datasets, 23 K samples), focusing on the geographic (25 countries) and ethnic (31 ethnicities) aspects around the world. We employed the most popular epigenetic tools for assessing age acceleration and examined their quality metrics and ability to extrapolate to epigenetic data from different tissue types and age ranges different from the training data of these models. In most cases, the models proved to be inconsistent with each other and showed different signs of age acceleration, with the PhenoAge model tending to systematically underestimate and different versions of the GrimAge model tending to systematically overestimate the age prediction of healthy subjects. Referring to data availability and consistency, most countries and populations are still not represented in GEO, moreover, different datasets use different criteria for determining healthy controls. Because of this, it is difficult to fully isolate the contribution of "geography/environment", "ethnicity" and "healthiness" to epigenetic age acceleration. Among the explored metrics, only the DunedinPACE, which measures aging rate, appears to adequately reflect the standard of living and socioeconomic indicators in countries, although it has a limited application to blood methylation data only. Invariably, by epigenetic age acceleration, males age faster than females in most of the studied countries and populations.
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Affiliation(s)
- Igor Yusipov
- Artificial Intelligence Research Center, Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, Nizhny Novgorod 603022, Russia; Institute of Biogerontology, Lobachevsky State University, Nizhny Novgorod 603022, Russia.
| | - Alena Kalyakulina
- Artificial Intelligence Research Center, Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, Nizhny Novgorod 603022, Russia; Institute of Biogerontology, Lobachevsky State University, Nizhny Novgorod 603022, Russia.
| | - Arseniy Trukhanov
- Mriya Life Institute, National Academy of Active Longevity, Moscow 124489, Russia.
| | - Claudio Franceschi
- Institute of Biogerontology, Lobachevsky State University, Nizhny Novgorod 603022, Russia.
| | - Mikhail Ivanchenko
- Artificial Intelligence Research Center, Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, Nizhny Novgorod 603022, Russia; Institute of Biogerontology, Lobachevsky State University, Nizhny Novgorod 603022, Russia.
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4
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Wei X, Li J, Cheng Z, Wei S, Yu G, Olsen ML. Decoding the Epigenetic Landscape: Insights into 5mC and 5hmC Patterns in Mouse Cortical Cell Types. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.06.602342. [PMID: 39026756 PMCID: PMC11257419 DOI: 10.1101/2024.07.06.602342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
The DNA modifications, 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC), represent powerful epigenetic regulators of temporal and spatial gene expression. Yet, how the cooperation of these genome-wide, epigenetic marks determine unique transcriptional signatures across different brain cell populations is unclear. Here we applied Nanopore sequencing of native DNA to obtain a complete, genome-wide, single-base resolution atlas of 5mC and 5hmC modifications in neurons, astrocytes and microglia in the mouse cortex (99% genome coverage, 40 million CpG sites). In tandem with RNA sequencing, analysis of 5mC and 5hmC patterns across cell types reveals astrocytes drive uniquely high brain 5hmC levels and support two decades of research regarding methylation patterns, gene expression and alternative splicing, benchmarking this resource. As such, we provide the most comprehensive DNA methylation data in mouse brain as an interactive, online tool (NAM-Me, https://olsenlab.shinyapps.io/NAMME/) to serve as a resource dataset for those interested in the methylome landscape.
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Affiliation(s)
- Xiaoran Wei
- Biomedical and Veterinary Sciences Graduate Program, Virginia Tech, Blacksburg, VA, the United States
- School of Neuroscience, Virginia Tech, Blacksburg, VA, the United States
| | - Jiangtao Li
- School of Neuroscience, Virginia Tech, Blacksburg, VA, the United States
- Genetics, Bioinformatics and Computational Biology Graduate Program, Virginia Tech, Blacksburg, VA, the United States
| | - Zuolin Cheng
- Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA, the United States
| | - Songtao Wei
- Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA, the United States
| | - Guoqiang Yu
- Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA, the United States
| | - Michelle L Olsen
- School of Neuroscience, Virginia Tech, Blacksburg, VA, the United States
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Caspi A, Shireby G, Mill J, Moffitt TE, Sugden K, Hannon E. Accelerated Pace of Aging in Schizophrenia: Five Case-Control Studies. Biol Psychiatry 2024; 95:1038-1047. [PMID: 37924924 PMCID: PMC11063120 DOI: 10.1016/j.biopsych.2023.10.023] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 09/29/2023] [Accepted: 10/21/2023] [Indexed: 11/06/2023]
Abstract
BACKGROUND Schizophrenia is associated with increased risk of developing multiple aging-related diseases, including metabolic, respiratory, and cardiovascular diseases, and Alzheimer's and related dementias, leading to the hypothesis that schizophrenia is accompanied by accelerated biological aging. This has been difficult to test because there is no widely accepted measure of biological aging. Epigenetic clocks are promising algorithms that are used to calculate biological age on the basis of information from combined cytosine-phosphate-guanine sites (CpGs) across the genome, but they have yielded inconsistent and often negative results about the association between schizophrenia and accelerated aging. Here, we tested the schizophrenia-aging hypothesis using a DNA methylation measure that is uniquely designed to predict an individual's rate of aging. METHODS We brought together 5 case-control datasets to calculate DunedinPACE (Pace of Aging Calculated from the Epigenome), a new measure trained on longitudinal data to detect differences between people in their pace of aging over time. Data were available from 1812 psychosis cases (schizophrenia or first-episode psychosis) and 1753 controls. Mean chronological age was 38.9 (SD = 13.6) years. RESULTS We observed consistent associations across datasets between schizophrenia and accelerated aging as measured by DunedinPACE. These associations were not attributable to tobacco smoking or clozapine medication. CONCLUSIONS Schizophrenia is accompanied by accelerated biological aging by midlife. This may explain the wide-ranging risk among people with schizophrenia for developing multiple different age-related physical diseases, including metabolic, respiratory, and cardiovascular diseases, and dementia. Measures of biological aging could prove valuable for assessing patients' risk for physical and cognitive decline and for evaluating intervention effectiveness.
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Affiliation(s)
- Avshalom Caspi
- Department of Psychology & Neuroscience, Duke University, Durham, North Carolina; Social, Genetic and Developmental Psychiatry, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, United Kingdom; PROMENTA, Department of Psychology, University of Oslo, Oslo, Norway.
| | - Gemma Shireby
- Centre of Longitudinal Studies, University College London, Exeter, United Kingdom
| | - Jonathan Mill
- University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
| | - Terrie E Moffitt
- Department of Psychology & Neuroscience, Duke University, Durham, North Carolina; Social, Genetic and Developmental Psychiatry, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, United Kingdom; PROMENTA, Department of Psychology, University of Oslo, Oslo, Norway
| | - Karen Sugden
- Department of Psychology & Neuroscience, Duke University, Durham, North Carolina
| | - Eilis Hannon
- University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
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Zhu T, Tong H, Du Z, Beck S, Teschendorff AE. An improved epigenetic counter to track mitotic age in normal and precancerous tissues. Nat Commun 2024; 15:4211. [PMID: 38760334 PMCID: PMC11101651 DOI: 10.1038/s41467-024-48649-8] [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: 09/24/2023] [Accepted: 05/09/2024] [Indexed: 05/19/2024] Open
Abstract
The cumulative number of stem cell divisions in a tissue, known as mitotic age, is thought to be a major determinant of cancer-risk. Somatic mutational and DNA methylation (DNAm) clocks are promising tools to molecularly track mitotic age, yet their relationship is underexplored and their potential for cancer risk prediction in normal tissues remains to be demonstrated. Here we build and validate an improved pan-tissue DNAm counter of total mitotic age called stemTOC. We demonstrate that stemTOC's mitotic age proxy increases with the tumor cell-of-origin fraction in each of 15 cancer-types, in precancerous lesions, and in normal tissues exposed to major cancer risk factors. Extensive benchmarking against 6 other mitotic counters shows that stemTOC compares favorably, specially in the preinvasive and normal-tissue contexts. By cross-correlating stemTOC to two clock-like somatic mutational signatures, we confirm the mitotic-like nature of only one of these. Our data points towards DNAm as a promising molecular substrate for detecting mitotic-age increases in normal tissues and precancerous lesions, and hence for developing cancer-risk prediction strategies.
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Affiliation(s)
- Tianyu Zhu
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Huige Tong
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Zhaozhen Du
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Stephan Beck
- Medical Genomics Group, UCL Cancer Institute, University College London, 72 Huntley Street, WC1E 6BT, London, UK
| | - Andrew E Teschendorff
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China.
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7
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Davyson E, Shen X, Huider F, Adams M, Borges K, McCartney D, Barker L, Van Dongen J, Boomsma D, Weihs A, Grabe H, Kühn L, Teumer A, Völzke H, Zhu T, Kaprio J, Ollikainen M, David FS, Meinert S, Stein F, Forstner AJ, Dannlowski U, Kircher T, Tapuc A, Czamara D, Binder EB, Brückl T, Kwong A, Yousefi P, Wong C, Arseneault L, Fisher HL, Mill J, Cox S, Redmond P, Russ TC, van den Oord E, Aberg KA, Penninx B, Marioni RE, Wray NR, McIntosh AM. Antidepressant Exposure and DNA Methylation: Insights from a Methylome-Wide Association Study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.01.24306640. [PMID: 38746357 PMCID: PMC11092700 DOI: 10.1101/2024.05.01.24306640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Importance Understanding antidepressant mechanisms could help design more effective and tolerated treatments. Objective Identify DNA methylation (DNAm) changes associated with antidepressant exposure. Design Case-control methylome-wide association studies (MWAS) of antidepressant exposure were performed from blood samples collected between 2006-2011 in Generation Scotland (GS). The summary statistics were tested for enrichment in specific tissues, gene ontologies and an independent MWAS in the Netherlands Study of Depression and Anxiety (NESDA). A methylation profile score (MPS) was derived and tested for its association with antidepressant exposure in eight independent cohorts, alongside prospective data from GS. Setting Cohorts; GS, NESDA, FTC, SHIP-Trend, FOR2107, LBC1936, MARS-UniDep, ALSPAC, E-Risk, and NTR. Participants Participants with DNAm data and self-report/prescription derived antidepressant exposure. Main Outcomes and Measures Whole-blood DNAm levels were assayed by the EPIC/450K Illumina array (9 studies, N exposed = 661, N unexposed = 9,575) alongside MBD-Seq in NESDA (N exposed = 398, N unexposed = 414). Antidepressant exposure was measured by self- report and/or antidepressant prescriptions. Results The self-report MWAS (N = 16,536, N exposed = 1,508, mean age = 48, 59% female) and the prescription-derived MWAS (N = 7,951, N exposed = 861, mean age = 47, 59% female), found hypermethylation at seven and four DNAm sites (p < 9.42x10 -8 ), respectively. The top locus was cg26277237 ( KANK1, p self-report = 9.3x10 -13 , p prescription = 6.1x10 -3 ). The self-report MWAS found a differentially methylated region, mapping to DGUOK-AS1 ( p adj = 5.0x10 -3 ) alongside significant enrichment for genes expressed in the amygdala, the "synaptic vesicle membrane" gene ontology and the top 1% of CpGs from the NESDA MWAS (OR = 1.39, p < 0.042). The MPS was associated with antidepressant exposure in meta-analysed data from external cohorts (N studies = 9, N = 10,236, N exposed = 661, f3 = 0.196, p < 1x10 -4 ). Conclusions and Relevance Antidepressant exposure is associated with changes in DNAm across different cohorts. Further investigation into these changes could inform on new targets for antidepressant treatments. 3 Key Points Question: Is antidepressant exposure associated with differential whole blood DNA methylation?Findings: In this methylome-wide association study of 16,536 adults across Scotland, antidepressant exposure was significantly associated with hypermethylation at CpGs mapping to KANK1 and DGUOK-AS1. A methylation profile score trained on this sample was significantly associated with antidepressant exposure (pooled f3 [95%CI]=0.196 [0.105, 0.288], p < 1x10 -4 ) in a meta-analysis of external datasets. Meaning: Antidepressant exposure is associated with hypermethylation at KANK1 and DGUOK-AS1 , which have roles in mitochondrial metabolism and neurite outgrowth. If replicated in future studies, targeting these genes could inform the design of more effective and better tolerated treatments for depression.
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Zhao J, Li H, Qu J, Zong X, Liu Y, Kuang Z, Wang H. A multi-organization epigenetic age prediction based on a channel attention perceptron networks. Front Genet 2024; 15:1393856. [PMID: 38725481 PMCID: PMC11080615 DOI: 10.3389/fgene.2024.1393856] [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: 03/01/2024] [Accepted: 04/09/2024] [Indexed: 05/12/2024] Open
Abstract
DNA methylation indicates the individual's aging, so-called Epigenetic clocks, which will improve the research and diagnosis of aging diseases by investigating the correlation between methylation loci and human aging. Although this discovery has inspired many researchers to develop traditional computational methods to quantify the correlation and predict the chronological age, the performance bottleneck delayed access to the practical application. Since artificial intelligence technology brought great opportunities in research, we proposed a perceptron model integrating a channel attention mechanism named PerSEClock. The model was trained on 24,516 CpG loci that can utilize the samples from all types of methylation identification platforms and tested on 15 independent datasets against seven methylation-based age prediction methods. PerSEClock demonstrated the ability to assign varying weights to different CpG loci. This feature allows the model to enhance the weight of age-related loci while reducing the weight of irrelevant loci. The method is free to use for academics at www.dnamclock.com/#/original.
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Affiliation(s)
- Jian Zhao
- School of Computer Science and Technology, Changchun University, Changchun, China
| | - Haixia Li
- School of Computer Science and Technology, Changchun University, Changchun, China
| | - Jing Qu
- School of Computer Science and Technology, Jilin University, Changchun, China
- School of Information Science and Technology, Institute of Computational Biology, Northeast Normal University, Changchun, China
| | - Xizeng Zong
- Clinical Research Centre, Guangzhou First People’s Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
- School of Computer Science and Engineering, Changchun University of Technology, Changchun, China
| | - Yuchen Liu
- Department of Medicine, Boston University School of Medicine, Boston, MA, United States
| | - Zhejun Kuang
- School of Computer Science and Technology, Changchun University, Changchun, China
| | - Han Wang
- School of Information Science and Technology, Institute of Computational Biology, Northeast Normal University, Changchun, China
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9
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Kok DE, Saunders R, Nelson A, Smith D, Ford D, Mathers JC, McKay JA. Influence of maternal folate depletion on Art3 DNA methylation in the murine adult brain; potential consequences for brain and neurocognitive health. Mutagenesis 2024; 39:196-204. [PMID: 38417824 PMCID: PMC11040152 DOI: 10.1093/mutage/geae007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 02/27/2024] [Indexed: 03/01/2024] Open
Abstract
The developmental origins of health and disease hypothesis suggest early-life environment impacts health outcomes throughout the life course. In particular, epigenetic marks, including DNA methylation, are thought to be key mechanisms through which environmental exposures programme later-life health. Adequate maternal folate status before and during pregnancy is essential in the protection against neural tube defects, but data are emerging that suggest early-life folate exposures may also influence neurocognitive outcomes in childhood and, potentially, thereafter. Since folate is key to the supply of methyl donors for DNA methylation, we hypothesize that DNA methylation may be a mediating mechanism through which maternal folate influences neurocognitive outcomes. Using bisulphite sequencing, we measured DNA methylation of five genes (Art3, Rsp16, Tspo, Wnt16, and Pcdhb6) in the brain tissue of adult offspring of dams who were depleted of folate (n = 5, 0.4 mg folic acid/kg diet) during pregnancy (~19-21 days) and lactation (mean 22 days) compared with controls (n = 6, 2 mg folic acid/kg diet). Genes were selected as methylation of their promoters had previously been found to be altered by maternal folate intake in mice and humans across the life course, and because they have potential associations with neurocognitive outcomes. Maternal folate depletion was significantly associated with Art3 gene hypomethylation in subcortical brain tissue of adult mice at 28 weeks of age (mean decrease 6.2%, P = .03). For the other genes, no statistically significant differences were found between folate depleted and control groups. Given its association with neurocognitive outcomes, we suggest Art3 warrants further study in the context of lifecourse brain health. We have uncovered a potential biomarker that, once validated in accessible biospecimens and human context, may be useful to track the impact of early-life folate exposure on later-life neurocognitive health, and potentially be used to develop and monitor the effects of interventions.
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Affiliation(s)
- Dieuwertje E Kok
- Division of Human Nutrition and Health, Wageningen University & Research, P.O. Box 17, 6700 AA Wageningen Stippeneng 4, 6708 WE Wageningen Wageningen Campus l Building 124 (Helix), Wageningen, The Netherlands
| | - Rachael Saunders
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Northumberland Building, Newcastle Upon Tyne, NE1 8ST, United Kingdom
| | - Andrew Nelson
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Northumberland Building, Newcastle Upon Tyne, NE1 8ST, United Kingdom
| | - Darren Smith
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Northumberland Building, Newcastle Upon Tyne, NE1 8ST, United Kingdom
| | - Dianne Ford
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Northumberland Building, Newcastle Upon Tyne, NE1 8ST, United Kingdom
| | - John C Mathers
- Human Nutrition & Exercise Research Centre, Centre for Healthier Lives, Population Health Sciences Institute, Newcastle University, Room M2.060, 2nd floor William Leech Building, Framlington Place, Newcastle upon Tyne, NE2 4HH, United Kingdom
| | - Jill A McKay
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Northumberland Building, Newcastle Upon Tyne, NE1 8ST, United Kingdom
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10
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Kiltschewskij DJ, Reay WR, Geaghan MP, Atkins JR, Xavier A, Zhang X, Watkeys OJ, Carr VJ, Scott RJ, Green MJ, Cairns MJ. Alteration of DNA Methylation and Epigenetic Scores Associated With Features of Schizophrenia and Common Variant Genetic Risk. Biol Psychiatry 2024; 95:647-661. [PMID: 37480976 DOI: 10.1016/j.biopsych.2023.07.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 07/07/2023] [Accepted: 07/10/2023] [Indexed: 07/24/2023]
Abstract
BACKGROUND Unpacking molecular perturbations associated with features of schizophrenia is a critical step toward understanding phenotypic heterogeneity in this disorder. Recent epigenome-wide association studies have uncovered pervasive dysregulation of DNA methylation in schizophrenia; however, clinical features of the disorder that account for a large proportion of phenotypic variability are relatively underexplored. METHODS We comprehensively analyzed patterns of DNA methylation in a cohort of 381 individuals with schizophrenia from the deeply phenotyped Australian Schizophrenia Research Bank. Epigenetic changes were investigated in association with cognitive status, age of onset, treatment resistance, Global Assessment of Functioning scores, and common variant polygenic risk scores for schizophrenia. We subsequently explored alterations within genes previously associated with psychiatric illness, phenome-wide epigenetic covariance, and epigenetic scores. RESULTS Epigenome-wide association studies of the 5 primary traits identified 662 suggestively significant (p < 6.72 × 10-5) differentially methylated probes, with a further 432 revealed after controlling for schizophrenia polygenic risk on the remaining 4 traits. Interestingly, we uncovered many probes within genes associated with a variety of psychiatric conditions as well as significant epigenetic covariance with phenotypes and exposures including acute myocardial infarction, C-reactive protein, and lung cancer. Epigenetic scores for treatment-resistant schizophrenia strikingly exhibited association with clozapine administration, while epigenetic proxies of plasma protein expression, such as CCL17, MMP10, and PRG2, were associated with several features of schizophrenia. CONCLUSIONS Our findings collectively provide novel evidence suggesting that several features of schizophrenia are associated with alteration of DNA methylation, which may contribute to interindividual phenotypic variation in affected individuals.
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Affiliation(s)
- Dylan J Kiltschewskij
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, New South Wales, Australia; Precision Medicine Program, Hunter Medical Research Institute, New Lambton, New South Wales, Australia
| | - William R Reay
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, New South Wales, Australia; Precision Medicine Program, Hunter Medical Research Institute, New Lambton, New South Wales, Australia
| | - Michael P Geaghan
- Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
| | - Joshua R Atkins
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, New South Wales, Australia
| | - Alexandre Xavier
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, New South Wales, Australia; Centre for Information Based Medicine, Hunter Medical Research Institute, New Lambton, New South Wales, Australia
| | - Xiajie Zhang
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, New South Wales, Australia; Centre for Information Based Medicine, Hunter Medical Research Institute, New Lambton, New South Wales, Australia
| | - Oliver J Watkeys
- School of Psychiatry, University of New South Wales, Sydney, New South Wales, Australia
| | - Vaughan J Carr
- School of Psychiatry, University of New South Wales, Sydney, New South Wales, Australia; Department of Psychiatry, School of Clinical Sciences, Monash University, Clayton, Victoria, Australia
| | - Rodney J Scott
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, New South Wales, Australia; Centre for Information Based Medicine, Hunter Medical Research Institute, New Lambton, New South Wales, Australia
| | - Melissa J Green
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, New South Wales, Australia; School of Psychiatry, University of New South Wales, Sydney, New South Wales, Australia
| | - Murray J Cairns
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, New South Wales, Australia; Precision Medicine Program, Hunter Medical Research Institute, New Lambton, New South Wales, Australia.
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11
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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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12
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Polakkattil BK, Vellichirammal NN, Nair IV, Nair CM, Banerjee M. Methylome-wide and meQTL analysis helps to distinguish treatment response from non-response and pathogenesis markers in schizophrenia. Front Psychiatry 2024; 15:1297760. [PMID: 38516266 PMCID: PMC10954811 DOI: 10.3389/fpsyt.2024.1297760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 02/06/2024] [Indexed: 03/23/2024] Open
Abstract
Schizophrenia is a complex condition with entwined genetic and epigenetic risk factors, posing a challenge to disentangle the intermixed pathological and therapeutic epigenetic signatures. To resolve this, we performed 850K methylome-wide and 700K genome-wide studies on the same set of schizophrenia patients by stratifying them into responders, non-responders, and drug-naïve patients. The key genes that signified the response were followed up using real-time gene expression studies to understand the effect of antipsychotics at the gene transcription level. The study primarily implicates hypermethylation in therapeutic response and hypomethylation in the drug-non-responsive state. Several differentially methylated sites and regions colocalized with the schizophrenia genome-wide association study (GWAS) risk genes and variants, supporting the convoluted gene-environment association. Gene ontology and protein-protein interaction (PPI) network analyses revealed distinct patterns that differentiated the treatment response from drug resistance. The study highlights the strong involvement of several processes related to nervous system development, cell adhesion, and signaling in the antipsychotic response. The ability of antipsychotic medications to alter the pathology by modulating gene expression or methylation patterns is evident from the general increase in the gene expression of response markers and histone modifiers and the decrease in class II human leukocyte antigen (HLA) genes following treatment with varying concentrations of medications like clozapine, olanzapine, risperidone, and haloperidol. The study indicates a directional overlap of methylation markers between pathogenesis and therapeutic response, thereby suggesting a careful distinction of methylation markers of pathogenesis from treatment response. In addition, there is a need to understand the trade-off between genetic and epigenetic observations. It is suggested that methylomic changes brought about by drugs need careful evaluation for their positive effects on pathogenesis, course of disease progression, symptom severity, side effects, and refractoriness.
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Affiliation(s)
- Binithamol K. Polakkattil
- Human Molecular Genetics Laboratory, Rajiv Gandhi Centre for Biotechnology, Thiruvananthapuram, Kerala, India
- Research Center, University of Kerala, Thiruvananthapuram, Kerala, India
| | - Neetha N. Vellichirammal
- Human Molecular Genetics Laboratory, Rajiv Gandhi Centre for Biotechnology, Thiruvananthapuram, Kerala, India
| | - Indu V. Nair
- Mental Health Centre, Thiruvananthapuram, Kerala, India
| | | | - Moinak Banerjee
- Human Molecular Genetics Laboratory, Rajiv Gandhi Centre for Biotechnology, Thiruvananthapuram, Kerala, India
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13
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Viola TW, Danzer C, Mardini V, Szobot C, Chrusciel JH, Stertz L, Schmitz JM, Walss-Bass C, Fries GR, Grassi-Oliveira R. Prenatal cocaine exposure and its influence on pediatric epigenetic clocks and epigenetic scores in humans. Sci Rep 2024; 14:1946. [PMID: 38253635 PMCID: PMC10803757 DOI: 10.1038/s41598-024-52433-5] [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: 10/09/2023] [Accepted: 01/18/2024] [Indexed: 01/24/2024] Open
Abstract
The investigation of the effects of prenatal cocaine exposure (PCE) on offspring has been inconsistent, with few studies investigating biological outcomes in humans. We profiled genome-wide DNA methylation (DNAm) of umbilical cord blood (UCB) from newborns with (n = 35) and without (n = 47) PCE. We used DNAm data to (1) assess pediatric epigenetic clocks at birth and (2) to estimate epigenetic scores (ES) for lifetime disorders. We generated gestational epigenetic age estimates (DNAmGA) based on Knight and Bohlin epigenetic clocks. We also investigated the association between DNAmGA and UCB serum brain-derived neurotrophic factor (BDNF) levels. Considering the large-scale DNAm data availability and existing evidence regarding PCE as a risk for health problems later in life, we generated ES for tobacco smoking, psychosis, autism, diabetes, and obesity. A gene ontology (GO) analysis on the CpGs included in the ES with group differences was performed. PCE was associated with lower DNAmGA in newborns, and this effect remained significant when controlling for potential confounders, such as blood cell type composition predicted by DNAm and obstetric data. DNAmGA was negatively correlated with BDNF levels in the serum of UCB. Higher tobacco smoking, psychosis, and diabetes ES were found in the PCE group. The GO analysis revealed GABAergic synapses as a potential pathway altered by PCE. Our findings of decelerated DNAmGA and ES for adverse phenotypes associated with PCE, suggest that the effects of gestational cocaine exposure on the epigenetic landscape of human newborns are detectable at birth.
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Affiliation(s)
- Thiago Wendt Viola
- School of Medicine, Developmental Cognitive Neuroscience Lab, Pontifical Catholic University of Rio Grande Do Sul (PUCRS), Porto Alegre, RS, Brazil
| | - Christina Danzer
- Translational Neuropsychiatry Unit, Department of Clinical Medicine, Aarhus University, Palle Juul-Jensens Boulevard 11, A701-129, 8200, Aarhus, Denmark
| | - Victor Mardini
- Clinical Hospital of Porto Alegre, Porto Alegre, RS, Brazil
| | - Claudia Szobot
- Clinical Hospital of Porto Alegre, Porto Alegre, RS, Brazil
| | - João Henrique Chrusciel
- School of Medicine, Developmental Cognitive Neuroscience Lab, Pontifical Catholic University of Rio Grande Do Sul (PUCRS), Porto Alegre, RS, Brazil
| | - Laura Stertz
- Faillace Department of Psychiatry and Behavioral Sciences, Translational Psychiatry Program, The University of Texas Health Science Center at Houston, Houston, USA
| | - Joy M Schmitz
- Faillace Department of Psychiatry and Behavioral Sciences, Translational Psychiatry Program, The University of Texas Health Science Center at Houston, Houston, USA
| | - Consuelo Walss-Bass
- Faillace Department of Psychiatry and Behavioral Sciences, Translational Psychiatry Program, The University of Texas Health Science Center at Houston, Houston, USA
| | - Gabriel R Fries
- Faillace Department of Psychiatry and Behavioral Sciences, Translational Psychiatry Program, The University of Texas Health Science Center at Houston, Houston, USA
| | - Rodrigo Grassi-Oliveira
- School of Medicine, Developmental Cognitive Neuroscience Lab, Pontifical Catholic University of Rio Grande Do Sul (PUCRS), Porto Alegre, RS, Brazil.
- Translational Neuropsychiatry Unit, Department of Clinical Medicine, Aarhus University, Palle Juul-Jensens Boulevard 11, A701-129, 8200, Aarhus, Denmark.
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14
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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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15
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Tang Y, Tan Y, Palaniyappan L, Yao Y, Luo Q, Li Y. Epigenetic profile of the immune system associated with symptom severity and treatment response in schizophrenia. J Psychiatry Neurosci 2024; 49:E45-E58. [PMID: 38359932 PMCID: PMC10890792 DOI: 10.1503/jpn.230099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 09/19/2023] [Accepted: 09/25/2023] [Indexed: 02/17/2024] Open
Abstract
BACKGROUND Environmental modification of genetic information (epigenetics) is often invoked to explain interindividual differences in the phenotype of schizophrenia. In clinical practice, such variability is most prominent in the symptom profile and the treatment response. Epigenetic regulation of immune function is of particular interest, given the therapeutic relevance of this mechanism in schizophrenia. METHODS We analyzed the DNA methylation data of immune-relevant genes in patients with schizophrenia whose disease duration was less than 3 years, with previous lifetime antipsychotic treatment of no more than 2 weeks total. RESULTS A total of 441 patients met the inclusion criteria. Core symptoms were consistently associated with 206 methylation positions, many of which had previously been implicated in inflammatory responses. Of these, 24 methylation positions were located either in regulatory regions or near the CpG islands of 20 genes, including the SRC gene, which is a key player in glutamatergic signalling. These symptom-associated immune genes were enriched in neuronal development functions, such as neuronal migration and glutamatergic synapse. Compared with using only clinical information (including scores on the Positive and Negative Syndrome Scale), integrating methylation data into the model significantly improved the predictive ability (as indicated by area under the curve) for response to 8 weeks of antipsychotic treatment. LIMITATIONS We focused on a small number of methylation probes (immune-centred search) and lacked nutritional data and direct brain-based measures. CONCLUSION Epigenetic modifications of the immune system are associated with symptom severity at onset and subsequent treatment response in schizophrenia.
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Affiliation(s)
- Yuanhao Tang
- From the National Clinical Research Center for Aging and Medicine at Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science and School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China (Tang, Yao); the Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China (Tan, Li); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, Que. (Palaniyappan); Robarts Research Institute and Department of Medical Biophysics, Western University, London, Ont. (Palaniyappan); the Lawson Health Research Institute, London, Ont. (Palaniyappan); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Luo)
| | - Yunlong Tan
- From the National Clinical Research Center for Aging and Medicine at Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science and School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China (Tang, Yao); the Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China (Tan, Li); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, Que. (Palaniyappan); Robarts Research Institute and Department of Medical Biophysics, Western University, London, Ont. (Palaniyappan); the Lawson Health Research Institute, London, Ont. (Palaniyappan); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Luo)
| | - Lena Palaniyappan
- From the National Clinical Research Center for Aging and Medicine at Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science and School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China (Tang, Yao); the Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China (Tan, Li); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, Que. (Palaniyappan); Robarts Research Institute and Department of Medical Biophysics, Western University, London, Ont. (Palaniyappan); the Lawson Health Research Institute, London, Ont. (Palaniyappan); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Luo)
| | - Yin Yao
- From the National Clinical Research Center for Aging and Medicine at Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science and School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China (Tang, Yao); the Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China (Tan, Li); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, Que. (Palaniyappan); Robarts Research Institute and Department of Medical Biophysics, Western University, London, Ont. (Palaniyappan); the Lawson Health Research Institute, London, Ont. (Palaniyappan); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Luo)
| | - Qiang Luo
- From the National Clinical Research Center for Aging and Medicine at Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science and School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China (Tang, Yao); the Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China (Tan, Li); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, Que. (Palaniyappan); Robarts Research Institute and Department of Medical Biophysics, Western University, London, Ont. (Palaniyappan); the Lawson Health Research Institute, London, Ont. (Palaniyappan); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Luo)
| | - Yanli Li
- From the National Clinical Research Center for Aging and Medicine at Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science and School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China (Tang, Yao); the Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China (Tan, Li); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, Que. (Palaniyappan); Robarts Research Institute and Department of Medical Biophysics, Western University, London, Ont. (Palaniyappan); the Lawson Health Research Institute, London, Ont. (Palaniyappan); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Luo)
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16
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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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17
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Reiner A, Bakulski KM, Fisher JD, Dou JF, Schneper L, Mitchell C, Notterman DA, Zawistowski M, Ware EB. Sex-specific DNA methylation in saliva from the multi-ethnic Future of Families and Child Wellbeing Study. Epigenetics 2023; 18:2222244. [PMID: 37300819 PMCID: PMC10259311 DOI: 10.1080/15592294.2023.2222244] [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: 01/12/2023] [Revised: 05/11/2023] [Accepted: 06/01/2023] [Indexed: 06/12/2023] Open
Abstract
The prevalence and severity of many diseases differs by sex, potentially due to sex-specific patterns in DNA methylation. Autosomal sex-specific differences in DNA methylation have been observed in cord blood and placental tissue but are not well studied in saliva or in diverse populations. We sought to characterize sex-specific DNA methylation on autosomal chromosomes in saliva samples from children in the Future of Families and Child Wellbeing Study, a multi-ethnic prospective birth cohort containing an oversampling of Black, Hispanic and low-income families. DNA methylation from saliva samples was analysed on 796 children (50.6% male) at both ages 9 and 15 with DNA methylation measured using the Illumina HumanMethylation 450k array. An epigenome-wide association analysis of the age 9 samples identified 8,430 sex-differentiated autosomal DNA methylation sites (P < 2.4 × 10-7), of which 76.2% had higher DNA methylation in female children. The strongest sex-difference was in the cg26921482 probe, in the AMDHD2 gene, with 30.6% higher DNA methylation in female compared to male children (P < 1 × 10-300). Treating the age 15 samples as an internal replication set, we observed highly consistent results between the ages 9 and 15 measurements, indicating stable and replicable sex-differentiation. Further, we directly compared our results to previously published DNA methylation sex differences in both cord blood and saliva and again found strong consistency. Our findings support widespread and robust sex-differential DNA methylation across age, human tissues, and populations. These findings help inform our understanding of potential biological processes contributing to sex differences in human physiology and disease.
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Affiliation(s)
- Allison Reiner
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Kelly M Bakulski
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Jonah D Fisher
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, USA
| | - John F Dou
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Lisa Schneper
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA
| | - Colter Mitchell
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, USA
| | - Daniel A Notterman
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA
| | - Matthew Zawistowski
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Erin B Ware
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, USA
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18
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Vellame DS, Shireby G, MacCalman A, Dempster EL, Burrage J, Gorrie-Stone T, Schalkwyk LS, Mill J, Hannon E. Uncertainty quantification of reference-based cellular deconvolution algorithms. Epigenetics 2023; 18:2137659. [PMID: 36539387 PMCID: PMC9980651 DOI: 10.1080/15592294.2022.2137659] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 10/12/2022] [Indexed: 12/24/2022] Open
Abstract
The majority of epigenetic epidemiology studies to date have generated genome-wide profiles from bulk tissues (e.g., whole blood) however these are vulnerable to confounding from variation in cellular composition. Proxies for cellular composition can be mathematically derived from the bulk tissue profiles using a deconvolution algorithm; however, there is no method to assess the validity of these estimates for a dataset where the true cellular proportions are unknown. In this study, we describe, validate and characterize a sample level accuracy metric for derived cellular heterogeneity variables. The CETYGO score captures the deviation between a sample's DNA methylation profile and its expected profile given the estimated cellular proportions and cell type reference profiles. We demonstrate that the CETYGO score consistently distinguishes inaccurate and incomplete deconvolutions when applied to reconstructed whole blood profiles. By applying our novel metric to >6,300 empirical whole blood profiles, we find that estimating accurate cellular composition is influenced by both technical and biological variation. In particular, we show that when using a common reference panel for whole blood, less accurate estimates are generated for females, neonates, older individuals and smokers. Our results highlight the utility of a metric to assess the accuracy of cellular deconvolution, and describe how it can enhance studies of DNA methylation that are reliant on statistical proxies for cellular heterogeneity. To facilitate incorporating our methodology into existing pipelines, we have made it freely available as an R package (https://github.com/ds420/CETYGO).
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Affiliation(s)
| | - Gemma Shireby
- University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK
| | - Ailsa MacCalman
- University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK
| | - Emma L Dempster
- University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK
| | - Joe Burrage
- University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK
| | - Tyler Gorrie-Stone
- School of Biological Sciences, University of Essex, Colchester CO4 3SQ, UK
| | | | - Jonathan Mill
- University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK
| | - Eilis Hannon
- University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK
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19
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Harvanek ZM, Boks MP, Vinkers CH, Higgins-Chen AT. The Cutting Edge of Epigenetic Clocks: In Search of Mechanisms Linking Aging and Mental Health. Biol Psychiatry 2023; 94:694-705. [PMID: 36764569 PMCID: PMC10409884 DOI: 10.1016/j.biopsych.2023.02.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 01/31/2023] [Accepted: 02/01/2023] [Indexed: 02/11/2023]
Abstract
Individuals with psychiatric disorders are at increased risk of age-related diseases and early mortality. Recent studies demonstrate that this link between mental health and aging is reflected in epigenetic clocks, aging biomarkers based on DNA methylation. The reported relationships between epigenetic clocks and mental health are mostly correlational, and the mechanisms are poorly understood. Here, we review recent progress concerning the molecular and cellular processes underlying epigenetic clocks as well as novel technologies enabling further studies of the causes and consequences of epigenetic aging. We then review the current literature on how epigenetic clocks relate to specific aspects of mental health, such as stress, medications, substance use, health behaviors, and symptom clusters. We propose an integrated framework where mental health and epigenetic aging are each broken down into multiple distinct processes, which are then linked to each other, using stress and schizophrenia as examples. This framework incorporates the heterogeneity and complexity of both mental health conditions and aging, may help reconcile conflicting results, and provides a basis for further hypothesis-driven research in humans and model systems to investigate potentially causal mechanisms linking aging and mental health.
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Affiliation(s)
- Zachary M Harvanek
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Marco P Boks
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University of Utrecht, Utrecht, the Netherlands
| | - Christiaan H Vinkers
- Department of Psychiatry, Amsterdam University Medical Center, location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Mood, Anxiety, Psychosis, Sleep & Stress program, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Albert T Higgins-Chen
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut; Department of Pathology, Yale University School of Medicine, New Haven, Connecticut.
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20
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Flynn LT, Gao WJ. DNA methylation and the opposing NMDAR dysfunction in schizophrenia and major depression disorders: a converging model for the therapeutic effects of psychedelic compounds in the treatment of psychiatric illness. Mol Psychiatry 2023; 28:4553-4567. [PMID: 37679470 PMCID: PMC11034997 DOI: 10.1038/s41380-023-02235-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 08/17/2023] [Accepted: 08/22/2023] [Indexed: 09/09/2023]
Abstract
Psychedelic compounds are being increasingly explored as a potential therapeutic option for treating several psychiatric conditions, despite relatively little being known about their mechanism of action. One such possible mechanism, DNA methylation, is a process of epigenetic regulation that changes gene expression via chemical modification of nitrogenous bases. DNA methylation has been implicated in the pathophysiology of several psychiatric conditions, including schizophrenia (SZ) and major depressive disorder (MDD). In this review, we propose alterations to DNA methylation as a converging model for the therapeutic effects of psychedelic compounds, highlighting the N-methyl D-aspartate receptor (NMDAR), a crucial mediator of synaptic plasticity with known dysfunction in both diseases, as an example and anchoring point. We review the established evidence relating aberrant DNA methylation to NMDAR dysfunction in SZ and MDD and provide a model asserting that psychedelic substances may act through an epigenetic mechanism to provide therapeutic effects in the context of these disorders.
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Affiliation(s)
- L Taylor Flynn
- Department of Neurobiology & Anatomy, Drexel University College of Medicine, Philadelphia, PA, USA
- MD/PhD program, Drexel University College of Medicine, Philadelphia, PA, USA
| | - Wen-Jun Gao
- Department of Neurobiology & Anatomy, Drexel University College of Medicine, Philadelphia, PA, USA.
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21
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Zhang S, Shi K, Lyu N, Zhang Y, Liang G, Zhang W, Wang X, Wen H, Wen L, Ma H, Wang J, Yu X, Guan L. Genome-wide DNA methylation analysis in families with multiple individuals diagnosed with schizophrenia and intellectual disability. World J Biol Psychiatry 2023; 24:741-753. [PMID: 37017099 DOI: 10.1080/15622975.2023.2198595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 03/21/2023] [Accepted: 03/30/2023] [Indexed: 04/06/2023]
Abstract
OBJECTIVES Schizophrenia (SZ) and intellectual disability (ID) are both included in the continuum of neurodevelopmental disorders (NDDs). DNA methylation is known to be important in the occurrence of NDDs. The family study is conducive to eliminate the effects of relative epigenetic backgrounds, and to screen for differentially methylated positions (DMPs) and regions (DMRs) that are truly associated with NDDs. METHODS Four monozygotic twin families were recruited, and both twin individuals suffered from NDDs (either SZ, ID, or SZ plus ID). Genome-wide methylation analysis was performed in all samples and each family. DMPs and DMRs between NDD patients and unaffected individuals were identified. Functional and pathway enrichment analyses were performed on the annotated genes. RESULTS Two significant DMPs annotated to CYP2E1 were found in all samples. In Family One, 1476 DMPs mapped to 880 genes, and 162 DMRs overlapping with 153 unique genes were recognised. Our results suggested that the altered methylation levels of FYN, STAT3, RAC1, and NR4A2 were associated with the development of SZ and ID. Neurodevelopment and the immune system may participate in the occurrence of SZ and ID. CONCLUSIONS Our findings suggested that DNA methylation participated in the development of NDDs by affecting neurodevelopment and the immune system.
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Affiliation(s)
- Shengmin Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Centre for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Kaiyu Shi
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Centre for Mental Disorders (Peking University Sixth Hospital), Beijing, China
- Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Nan Lyu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Centre for Mental Disorders (Peking University Sixth Hospital), Beijing, China
- Beijing Anding Hospital, Beijing Key Laboratory of Mental Disorders, The National Clinical Research Centre for Mental Disorders, The Advanced Innovation Centre for Human Brain Protection, Capital Medical University, Beijing, China
| | - Yunshu Zhang
- The Sixth People's Hospital of Hebei Province, Hebei Mental Health Centre, Baoding, Hebei, China
| | | | - Wufang Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Centre for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Xijin Wang
- The First Psychiatric Hospital of Harbin, Harbin, Heilongjiang, China
| | - Hong Wen
- The Third Hospital of Mianyang, Mianyang, Sichuan, China
| | - Liping Wen
- Zigong Mental Health Centre, Zigong, Sichuan, China
| | - Hong Ma
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Centre for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Jijun Wang
- Shanghai Mental Health Centre, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Xin Yu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Centre for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Lili Guan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Centre for Mental Disorders (Peking University Sixth Hospital), Beijing, China
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22
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Varshavsky M, Harari G, Glaser B, Dor Y, Shemer R, Kaplan T. Accurate age prediction from blood using a small set of DNA methylation sites and a cohort-based machine learning algorithm. CELL REPORTS METHODS 2023; 3:100567. [PMID: 37751697 PMCID: PMC10545910 DOI: 10.1016/j.crmeth.2023.100567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 06/18/2023] [Accepted: 08/03/2023] [Indexed: 09/28/2023]
Abstract
Chronological age prediction from DNA methylation sheds light on human aging, health, and lifespan. Current clocks are mostly based on linear models and rely upon hundreds of sites across the genome. Here, we present GP-age, an epigenetic non-linear cohort-based clock for blood, based upon 11,910 methylomes. Using 30 CpG sites alone, GP-age outperforms state-of-the-art models, with a median accuracy of ∼2 years on held-out blood samples, for both array and sequencing-based data. We show that aging-related changes occur at multiple neighboring CpGs, with implications for using fragment-level analysis of sequencing data in aging research. By training three independent clocks, we show enrichment of donors with consistent deviation between predicted and actual age, suggesting individual rates of biological aging. Overall, we provide a compact yet accurate alternative to array-based clocks for blood, with applications in longitudinal aging research, forensic profiling, and monitoring epigenetic processes in transplantation medicine and cancer.
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Affiliation(s)
- Miri Varshavsky
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel; The Center for Computational Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Gil Harari
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel; Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel
| | - Benjamin Glaser
- Department of Endocrinology and Metabolism, Hadassah Medical Center and Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Yuval Dor
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel; The Center for Computational Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Ruth Shemer
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel
| | - Tommy Kaplan
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel; Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel; The Center for Computational Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel.
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23
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Luo Q, Dwaraka VB, Chen Q, Tong H, Zhu T, Seale K, Raffaele JM, Zheng SC, Mendez TL, Chen Y, Carreras N, Begum S, Mendez K, Voisin S, Eynon N, Lasky-Su JA, Smith R, Teschendorff AE. A meta-analysis of immune-cell fractions at high resolution reveals novel associations with common phenotypes and health outcomes. Genome Med 2023; 15:59. [PMID: 37525279 PMCID: PMC10388560 DOI: 10.1186/s13073-023-01211-5] [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: 03/08/2023] [Accepted: 07/10/2023] [Indexed: 08/02/2023] Open
Abstract
BACKGROUND Changes in cell-type composition of tissues are associated with a wide range of diseases and environmental risk factors and may be causally implicated in disease development and progression. However, these shifts in cell-type fractions are often of a low magnitude, or involve similar cell subtypes, making their reliable identification challenging. DNA methylation profiling in a tissue like blood is a promising approach to discover shifts in cell-type abundance, yet studies have only been performed at a relatively low cellular resolution and in isolation, limiting their power to detect shifts in tissue composition. METHODS Here we derive a DNA methylation reference matrix for 12 immune-cell types in human blood and extensively validate it with flow-cytometric count data and in whole-genome bisulfite sequencing data of sorted cells. Using this reference matrix, we perform a directional Stouffer and fixed effects meta-analysis comprising 23,053 blood samples from 22 different cohorts, to comprehensively map associations between the 12 immune-cell fractions and common phenotypes. In a separate cohort of 4386 blood samples, we assess associations between immune-cell fractions and health outcomes. RESULTS Our meta-analysis reveals many associations of cell-type fractions with age, sex, smoking and obesity, many of which we validate with single-cell RNA sequencing. We discover that naïve and regulatory T-cell subsets are higher in women compared to men, while the reverse is true for monocyte, natural killer, basophil, and eosinophil fractions. Decreased natural killer counts associated with smoking, obesity, and stress levels, while an increased count correlates with exercise and sleep. Analysis of health outcomes revealed that increased naïve CD4 + T-cell and N-cell fractions associated with a reduced risk of all-cause mortality independently of all major epidemiological risk factors and baseline co-morbidity. A machine learning predictor built only with immune-cell fractions achieved a C-index value for all-cause mortality of 0.69 (95%CI 0.67-0.72), which increased to 0.83 (0.80-0.86) upon inclusion of epidemiological risk factors and baseline co-morbidity. CONCLUSIONS This work contributes an extensively validated high-resolution DNAm reference matrix for blood, which is made freely available, and uses it to generate a comprehensive map of associations between immune-cell fractions and common phenotypes, including health outcomes.
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Affiliation(s)
- Qi Luo
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Varun B Dwaraka
- TruDiagnostics, 881 Corporate Dr., Lexington, KY, 40503, USA
| | - Qingwen Chen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Huige Tong
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Tianyu Zhu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Kirsten Seale
- Institute for Health and Sport (iHeS), Victoria University, Footscray, VIC, 3011, Australia
| | - Joseph M Raffaele
- PhysioAge LLC, 30 Central Park South / Suite 8A, New York, NY, 10019, USA
| | - Shijie C Zheng
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
| | - Tavis L Mendez
- TruDiagnostics, 881 Corporate Dr., Lexington, KY, 40503, USA
| | - Yulu Chen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | | | - Sofina Begum
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Kevin Mendez
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Sarah Voisin
- Institute for Health and Sport (iHeS), Victoria University, Footscray, VIC, 3011, Australia
| | - Nir Eynon
- Australian Regenerative Medicine Institute, Monash University, Clayton, VIC, 3800, Australia
| | - Jessica A Lasky-Su
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
| | - Ryan Smith
- TruDiagnostics, 881 Corporate Dr., Lexington, KY, 40503, USA.
| | - Andrew E Teschendorff
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China.
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24
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Fang Q, Yuan Z, Hu H, Zhang W, Wang G, Wang X. Genome-wide discovery of circulating cell-free DNA methylation biomarkers for colorectal cancer detection. Clin Epigenetics 2023; 15:119. [PMID: 37501075 PMCID: PMC10375686 DOI: 10.1186/s13148-023-01518-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 06/12/2023] [Indexed: 07/29/2023] Open
Abstract
BACKGROUND Colorectal polyp is known a precursor of colorectal cancer (CRC) that holds an increased risk for progression to CRC. Circulating cell-free DNA (cfDNA) methylation has shown favorable performance in the detection and monitoring the malignant progression in a variety of cancers. RESULTS To discover cfDNA methylation markers for the diagnosis of CRC, we first performed a genome-wide analysis between eight CRC and eight polyp tissues using the Infinium HumanMethylationEPIC BeadChip. We identified 7008 DMCs, and after filtering, we validated 39 DMCs by MethylTarget sequencing in 62 CRC and 56 polyp tissues. A panel of four CpGs (cg04486886, cg06712559, cg13539460, and cg27541454) was selected as the methylation marker in tissue by LASSO and random forest models. A diagnosis prediction model was built based on the four CpGs, and the methylation diagnosis score (md-score) can effectively discriminate tissues with CRC from polyp patients (AUROC > 0.9). Finally, the cg27541454 was confirmed hypermethylated in CRC (AUC = 0.85) in the plasma validation cohort. CONCLUSIONS Our findings suggest that the md-score could robustly detect CRC from polyp tissues, and cg27541454 may be a promising candidate noninvasive biomarker for CRC early diagnosis.
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Affiliation(s)
- Qingxiao Fang
- Colorectal Cancer Surgery Department, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Ziming Yuan
- Colorectal Cancer Surgery Department, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Hanqing Hu
- Colorectal Cancer Surgery Department, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Weiyuan Zhang
- Colorectal Cancer Surgery Department, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Guiyu Wang
- Colorectal Cancer Surgery Department, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
| | - Xishan Wang
- Colorectal Cancer Surgery Department, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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25
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Ni P, Zhou C, Liang S, Jiang Y, Liu D, Shao Z, Noh H, Zhao L, Tian Y, Zhang C, Wei J, Li X, Yu H, Ni R, Yu X, Qi X, Zhang Y, Ma X, Deng W, Guo W, Wang Q, Sham PC, Chung S, Li T. YBX1-Mediated DNA Methylation-Dependent SHANK3 Expression in PBMCs and Developing Cortical Interneurons in Schizophrenia. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2300455. [PMID: 37211699 PMCID: PMC10369273 DOI: 10.1002/advs.202300455] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 04/05/2023] [Indexed: 05/23/2023]
Abstract
Schizophrenia (SCZ) is a severe psychiatric and neurodevelopmental disorder. The pathological process of SCZ starts early during development, way before the first onset of psychotic symptoms. DNA methylation plays an important role in regulating gene expression and dysregulated DNA methylation is involved in the pathogenesis of various diseases. The methylated DNA immunoprecipitation-chip (MeDIP-chip) is performed to investigate genome-wide DNA methylation dysregulation in peripheral blood mononuclear cells (PBMCs) of patients with first-episode SCZ (FES). Results show that the SHANK3 promoter is hypermethylated, and this hypermethylation (HyperM) is negatively correlated with the cortical surface area in the left inferior temporal cortex and positively correlated with the negative symptom subscores in FES. The transcription factor YBX1 is further found to bind to the HyperM region of SHANK3 promoter in induced pluripotent stem cells (iPSCs)-derived cortical interneurons (cINs) but not glutamatergic neurons. Furthermore, a direct and positive regulatory effect of YBX1 on the expression of SHANK3 is confirmed in cINs using shRNAs. In summary, the dysregulated SHANK3 expression in cINs suggests the potential role of DNA methylation in the neuropathological mechanism underlying SCZ. The results also suggest that HyperM of SHANK3 in PBMCs can serve as a potential peripheral biomarker of SCZ.
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Affiliation(s)
- Peiyan Ni
- The Mental Health Center and Psychiatric LaboratoryState Key Laboratory of BiotherapyWest China HospitalSichuan UniversityChengdu610041P. R. China
- Department of PsychiatryMcLean Hospital/Harvard Medical SchoolBelmontMA02478USA
- Department of Cell Biology and AnatomyNew York Medical CollegeValhallaNY10595USA
| | - Chuqing Zhou
- The Mental Health Center and Psychiatric LaboratoryState Key Laboratory of BiotherapyWest China HospitalSichuan UniversityChengdu610041P. R. China
| | - Sugai Liang
- Department of NeurobiologyAffiliated Mental Health Center & Hangzhou Seventh People's HospitalZhejiang University School of MedicineHangzhouZhejiang310058China
| | - Youhui Jiang
- The Mental Health Center and Psychiatric LaboratoryState Key Laboratory of BiotherapyWest China HospitalSichuan UniversityChengdu610041P. R. China
| | - Dongxin Liu
- Department of Cell Biology and AnatomyNew York Medical CollegeValhallaNY10595USA
| | - Zhicheng Shao
- Department of PsychiatryMcLean Hospital/Harvard Medical SchoolBelmontMA02478USA
| | - Haneul Noh
- Department of PsychiatryMcLean Hospital/Harvard Medical SchoolBelmontMA02478USA
- Department of Cell Biology and AnatomyNew York Medical CollegeValhallaNY10595USA
| | - Liansheng Zhao
- The Mental Health Center and Psychiatric LaboratoryState Key Laboratory of BiotherapyWest China HospitalSichuan UniversityChengdu610041P. R. China
| | - Yang Tian
- The Mental Health Center and Psychiatric LaboratoryState Key Laboratory of BiotherapyWest China HospitalSichuan UniversityChengdu610041P. R. China
| | - Chengcheng Zhang
- The Mental Health Center and Psychiatric LaboratoryState Key Laboratory of BiotherapyWest China HospitalSichuan UniversityChengdu610041P. R. China
| | - Jinxue Wei
- The Mental Health Center and Psychiatric LaboratoryState Key Laboratory of BiotherapyWest China HospitalSichuan UniversityChengdu610041P. R. China
| | - Xiaojing Li
- The Mental Health Center and Psychiatric LaboratoryState Key Laboratory of BiotherapyWest China HospitalSichuan UniversityChengdu610041P. R. China
| | - Hua Yu
- The Mental Health Center and Psychiatric LaboratoryState Key Laboratory of BiotherapyWest China HospitalSichuan UniversityChengdu610041P. R. China
| | - Rongjun Ni
- The Mental Health Center and Psychiatric LaboratoryState Key Laboratory of BiotherapyWest China HospitalSichuan UniversityChengdu610041P. R. China
| | - Xueli Yu
- Department of NeurobiologyAffiliated Mental Health Center & Hangzhou Seventh People's HospitalZhejiang University School of MedicineHangzhouZhejiang310058China
- NHC and CAMS Key Laboratory of Medical NeurobiologyMOE Frontier Science Center for Brain Science and Brain‐Machine IntegrationSchool of Brain Science and Brain MedicineZhejiang UniversityHangzhouZhejiang310058China
| | - Xueyu Qi
- Department of NeurobiologyAffiliated Mental Health Center & Hangzhou Seventh People's HospitalZhejiang University School of MedicineHangzhouZhejiang310058China
- NHC and CAMS Key Laboratory of Medical NeurobiologyMOE Frontier Science Center for Brain Science and Brain‐Machine IntegrationSchool of Brain Science and Brain MedicineZhejiang UniversityHangzhouZhejiang310058China
| | - Yamin Zhang
- The Mental Health Center and Psychiatric LaboratoryState Key Laboratory of BiotherapyWest China HospitalSichuan UniversityChengdu610041P. R. China
| | - Xiaohong Ma
- The Mental Health Center and Psychiatric LaboratoryState Key Laboratory of BiotherapyWest China HospitalSichuan UniversityChengdu610041P. R. China
| | - Wei Deng
- Department of NeurobiologyAffiliated Mental Health Center & Hangzhou Seventh People's HospitalZhejiang University School of MedicineHangzhouZhejiang310058China
- NHC and CAMS Key Laboratory of Medical NeurobiologyMOE Frontier Science Center for Brain Science and Brain‐Machine IntegrationSchool of Brain Science and Brain MedicineZhejiang UniversityHangzhouZhejiang310058China
| | - Wanjun Guo
- Department of NeurobiologyAffiliated Mental Health Center & Hangzhou Seventh People's HospitalZhejiang University School of MedicineHangzhouZhejiang310058China
- NHC and CAMS Key Laboratory of Medical NeurobiologyMOE Frontier Science Center for Brain Science and Brain‐Machine IntegrationSchool of Brain Science and Brain MedicineZhejiang UniversityHangzhouZhejiang310058China
| | - Qiang Wang
- The Mental Health Center and Psychiatric LaboratoryState Key Laboratory of BiotherapyWest China HospitalSichuan UniversityChengdu610041P. R. China
| | - Pak C. Sham
- Department of PsychiatryLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong, SAR999077China
- Centre for PanorOmic SciencesThe University of Hong KongHong Kong, SAR999077China
| | - Sangmi Chung
- Department of PsychiatryMcLean Hospital/Harvard Medical SchoolBelmontMA02478USA
- Department of Cell Biology and AnatomyNew York Medical CollegeValhallaNY10595USA
| | - Tao Li
- Department of NeurobiologyAffiliated Mental Health Center & Hangzhou Seventh People's HospitalZhejiang University School of MedicineHangzhouZhejiang310058China
- NHC and CAMS Key Laboratory of Medical NeurobiologyMOE Frontier Science Center for Brain Science and Brain‐Machine IntegrationSchool of Brain Science and Brain MedicineZhejiang UniversityHangzhouZhejiang310058China
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26
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Villar JD, Stavrum AK, Spindola LM, Torsvik A, Bjella T, Steen NE, Djurovic S, Andreassen OA, Steen VM, Le Hellard S. Differences in white blood cell proportions between schizophrenia cases and controls are influenced by medication and variations in time of day. Transl Psychiatry 2023; 13:211. [PMID: 37330513 DOI: 10.1038/s41398-023-02507-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 05/27/2023] [Accepted: 06/01/2023] [Indexed: 06/19/2023] Open
Abstract
Cases with schizophrenia (SCZ) and healthy controls show differences in white blood cell (WBC) counts and blood inflammation markers. Here, we investigate whether time of blood draw and treatment with psychiatric medications are related to differences in estimated WBC proportions between SCZ cases and controls. DNA methylation data from whole blood was used to estimate proportions of six subtypes of WBCs in SCZ patients (n = 333) and healthy controls (n = 396). We tested the association of case-control status with estimated cell-type proportions and the neutrophil-to-lymphocyte ratio (NLR) in 4 models: with/without adjusting for time of blood draw, and then compared results from blood samples drawn during a 12-h (07:00-19:00) or 7-h (07:00-14:00) period. We also investigated WBC proportions in a subgroup of medication-free patients (n = 51). Neutrophil proportions were significantly higher in SCZ cases (mean=54.1%) vs. controls (mean=51.1%; p = <0.001), and CD8+T lymphocyte proportions were lower in SCZ cases (mean=12.1%) vs. controls (mean=13.2%; p = 0.001). The effect sizes in the 12-h sample (07:00-19:00) showed a significant difference between SCZ vs. controls for neutrophils, CD4+T, CD8+T, and B-cells, which remained significant after adjusting for time of blood draw. In the samples matched for time of blood draw during 07.00-14.00, we also observed an association with neutrophils, CD4+T, CD8+T, and B-cells that was unaffected by further adjustment for time of blood draw. In the medication-free patients, we observed differences that remained significant in neutrophils (p = 0.01) and CD4+T (p = 0.01) after adjusting for time of day. The association of SCZ with NLR was significant in all models (range: p < 0.001 to p = 0.03) in both medicated and unmedicated patients. In conclusion, controlling for pharmacological treatment and circadian cycling of WBC is necessary for unbiased estimates in case-control studies. Nevertheless, the association of WBC with SCZ remains, even after adjusting for the time of day.
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Affiliation(s)
- Jonelle D Villar
- 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.
| | - 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
| | - 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
| | - Anja Torsvik
- 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
| | - Thomas Bjella
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Niels Eiel Steen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Srdjan Djurovic
- 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
| | - Vidar M Steen
- 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
| | - 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.
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27
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Luykx JJ, Gonzalez-Diaz JM, Guu TW, van der Horst MZ, van Dellen E, Boks MP, Guloksuz S, DeLisi LE, Sommer IE, Cummins R, Shiers D, Lee J, Every-Palmer S, Mhalla A, Chadly Z, Chan SKW, Cotes RO, Takahashi S, Benros ME, Wagner E, Correll CU, Hasan A, Siskind D, Endres D, MacCabe J, Tiihonen J. An international research agenda for clozapine-resistant schizophrenia. Lancet Psychiatry 2023:S2215-0366(23)00109-8. [PMID: 37329895 DOI: 10.1016/s2215-0366(23)00109-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 02/24/2023] [Accepted: 03/17/2023] [Indexed: 06/19/2023]
Abstract
Treatment-resistant symptoms occur in about a third of patients with schizophrenia and are associated with a substantial reduction in their quality of life. The development of new treatment options for clozapine-resistant schizophrenia constitutes a crucial, unmet need in psychiatry. Additionally, an overview of past and possible future research avenues to optimise the early detection, diagnosis, and management of clozapine-resistant schizophrenia is unavailable. In this Health Policy, we discuss the ongoing challenges associated with clozapine-resistant schizophrenia faced by patients and health-care providers worldwide to improve the understanding of this condition. We then revisit several clozapine guidelines, the diagnostic tests and treatment options for clozapine-resistant schizophrenia, and currently applied research approaches in clozapine-resistant schizophrenia. We also suggest methodologies and targets for future research, divided into innovative nosology-oriented field trials (eg, examining dimensional symptom staging), translational approaches (eg, genetics), epidemiological research (eg, real-world studies), and interventional studies (eg, non-traditional trial designs incorporating lived experiences and caregivers' perspectives). Finally, we note that low-income and middle-income countries are under-represented in studies on clozapine-resistant schizophrenia and propose an agenda to guide multinational research on the cause and treatment of clozapine-resistant schizophrenia. We hope that this research agenda will empower better global representation of patients living with clozapine-resistant schizophrenia and ultimately improve their functional outcomes and quality of life.
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Affiliation(s)
- Jurjen J Luykx
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, Netherlands; Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands; GGNet Mental Health, Warnsveld, Netherlands.
| | - Jairo M Gonzalez-Diaz
- Barcelona Clínic Schizophrenia Unit, Neurosciences Institute, Hospital Clinic, Universitat de Barcelona, Barcelona, Spain; UR Center for Mental Health, School of Medicine and Health Sciences, Universidad del Rosario, Bogotá, Colombia; Clínica Nuestra Señora de la Paz, Orden Hospitalaria de San Juan de Dios, Bogotá, Colombia
| | - Ta-Wei Guu
- Department of Old Age Psychiatry, Institute of Psychiatry Psychology and Neuroscience, King's College London, London, UK; Division of Psychiatry, Department of Internal Medicine, China Medical University Beigang Hospital, Yunlin, Taiwan
| | - Marte Z van der Horst
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands; GGNet Mental Health, Warnsveld, Netherlands
| | - Edwin van Dellen
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands; Department of Intensive Care Medicine, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands; Department of Neurology, UZ Brussel and Vrije Universiteit Brussel, Jette, Belgium
| | - Marco P Boks
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Sinan Guloksuz
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, Netherlands; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Lynn E DeLisi
- Department of Psychiatry, Cambridge Health Alliance, Harvard Medical School, Cambridge, MA, USA
| | - Iris E Sommer
- Department of Biomedical Sciences of Cells and Systems, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | | | - David Shiers
- Psychosis Research Unit, Greater Manchester Mental Health NHS Trust, Manchester, UK
| | - Jimmy Lee
- Department of Psychosis, Institute of Mental Health, Singapore; Neuroscience and Mental Health, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Susanna Every-Palmer
- Department of Psychological Medicine, University of Otago Wellington, Wellington, New Zealand
| | - Ahmed Mhalla
- Department of Psychiatry, Fattouma Bourguiba Hospital, Faculty of Medicine of Monastir, University of Monastir, Monastir, Tunisia
| | - Zohra Chadly
- Department of Pharmacology, Fattouma Bourguiba Hospital, Faculty of Medicine of Monastir, University of Monastir, Monastir, Tunisia
| | - Sherry K W Chan
- Department of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China; State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Robert O Cotes
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Shun Takahashi
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Japan; Graduate School of Rehabilitation Science, Osaka Metropolitan University, Habikino, Japan; Clinical Research and Education Center, Asakayama General Hospital, Sakai, Japan; Department of Neuropsychiatry, Wakayama Medical University, Wakayama, Japan
| | - Michael E Benros
- Biological and Precision Psychiatry, Copenhagen Research Center for Mental Health, Mental Health Center Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark; Department of Immunology and Microbiology, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
| | - Elias Wagner
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Christoph U Correll
- Department of Child and Adolescent Psychiatry, Charité Universitaetsmedizin Berlin, Berlin, Germany; Department of Psychiatry and Molecular Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA; Department of Psychiatry, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
| | - Alkomiet Hasan
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Augsburg, Medical Faculty, Augsburg, Germany
| | - Dan Siskind
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia; Metro South Addiction and Mental Health Service, Brisbane, QLD, Australia
| | - Dominique Endres
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - James MacCabe
- Department of Psychosis Studies, Institute of Psychiatry Psychology and Neuroscience, King's College London, London, UK
| | - Jari Tiihonen
- Department of Forensic Psychiatry, University of Eastern Finland, Niuvanniemi Hospital, Kuopio, Finland; Department of Clinical Neuroscience, Karolinska Institutet, and Center for Psychiatry Research, Stockholm City Council, Stockholm, Sweden
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28
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Alameda L, Liu Z, Sham PC, Aas M, Trotta G, Rodriguez V, Di Forti M, Stilo SA, Kandaswamy R, Arango C, Arrojo M, Bernardo M, Bobes J, de Haan L, Del-Ben CM, Gayer-Anderson C, Sideli L, Jones PB, Jongsma HE, Kirkbride JB, La Cascia C, Lasalvia A, Tosato S, Llorca PM, Menezes PR, van Os J, Quattrone D, Rutten BP, Santos JL, Sanjuán J, Selten JP, Szöke A, Tarricone I, Tortelli A, Velthorst E, Morgan C, Dempster E, Hannon E, Burrage J, Dwir D, Arumuham A, Mill J, Murray RM, Wong CCY. Exploring the mediation of DNA methylation across the epigenome between childhood adversity and First Episode of Psychosis-findings from the EU-GEI study. Mol Psychiatry 2023; 28:2095-2106. [PMID: 37062770 DOI: 10.1038/s41380-023-02044-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 03/04/2023] [Accepted: 03/20/2023] [Indexed: 04/18/2023]
Abstract
ABTRACT Studies conducted in psychotic disorders have shown that DNA-methylation (DNAm) is sensitive to the impact of Childhood Adversity (CA). However, whether it mediates the association between CA and psychosis is yet to be explored. Epigenome wide association studies (EWAS) using the Illumina Infinium-Methylation EPIC array in peripheral blood tissue from 366 First-episode of psychosis and 517 healthy controls was performed. Adversity scores were created for abuse, neglect and composite adversity with the Childhood Trauma Questionnaire (CTQ). Regressions examining (I) CTQ scores with psychosis; (II) with DNAm EWAS level and (III) between DNAm and caseness, adjusted for a variety of confounders were conducted. Divide-Aggregate Composite-null Test for the composite null-hypothesis of no mediation effect was conducted. Enrichment analyses were conducted with missMethyl package and the KEGG database. Our results show that CA was associated with psychosis (Composite: OR = 1.68; p = <0.001; abuse: OR = 2.16; p < 0.001; neglect: OR = 2.27; p = <0.001). None of the CpG sites significantly mediated the adversity-psychosis association after Bonferroni correction (p < 8.1 × 10-8). However, 28, 34 and 29 differentially methylated probes associated with 21, 27, 20 genes passed a less stringent discovery threshold (p < 5 × 10-5) for composite, abuse and neglect respectively, with a lack of overlap between abuse and neglect. These included genes previously associated to psychosis in EWAS studies, such as PANK1, SPEG TBKBP1, TSNARE1 or H2R. Downstream gene ontology analyses did not reveal any biological pathways that survived false discovery rate correction. Although at a non-significant level, DNAm changes in genes previously associated with schizophrenia in EWAS studies may mediate the CA-psychosis association. These results and associated involved processes such as mitochondrial or histaminergic disfunction, immunity or neural signalling requires replication in well powered samples. The lack of overlap between mediating genes associated with abuse and neglect suggests differential biological trajectories linking CA subtypes and psychosis.
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Affiliation(s)
- Luis Alameda
- Service of General Psychiatry, Treatment and Early Intervention in Psychosis Program, Lausanne University Hospital (CHUV), Lausanne, Switzerland.
- Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience. King's College of London, London, UK.
- Instituto de Investigación Sanitaria de Sevilla, IbiS, Hospital Universitario Virgen del Rocío, Department of Psychiatry, Universidad de Sevilla, Seville, Spain.
| | - Zhonghua Liu
- Department of Biostatistics, Columbia University, New York, NY, USA
| | - Pak C Sham
- Department of Psychiatry, State Key Laboratory of Brain and Cognitive Sciences, and Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Monica Aas
- Social, Genetics and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Giulia Trotta
- Social, Genetics and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Victoria Rodriguez
- Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience. King's College of London, London, UK
| | - Marta Di Forti
- Social, Genetics and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Simona A Stilo
- Department of Mental Health and Addiction Services, ASP Crotone, Crotone, Italy
| | - Radhika Kandaswamy
- Social, Genetics and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, School of Medicine, Universidad Complutense, IiSGM, CIBERSAM, Madrid, Spain
| | - Manuel Arrojo
- Department of Psychiatry, Psychiatric Genetic Group, Instituto de Investigación Sanitaria de Santiago de Compostela, Complejo Hospitalario Universitario de Santiago de Compostela, Santiago, Spain
| | - Miguel Bernardo
- Barcelona Clinic Schizophrenia Unit, Neuroscience Institute, Hospital Clinic of Barcelona, University of Barcelona, Institut d'Investigacions Biomèdiques August Pi I Sunyer, Biomedical Research Networking Centre in Mental Health (CIBERSAM), Barcelona, Spain
| | - Julio Bobes
- Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain
- Department of Medicine, Psychiatry Area, School of Medicine, Universidad de Oviedo, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Oviedo, Spain
| | - Lieuwe de Haan
- Department of Psychiatry, Early Psychosis Section, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Cristina Marta Del-Ben
- Neuroscience and Behaviour Department, Ribeirão Preto Medical School, University of São Paulo, São Paulo, Brazil
| | | | - Lucia Sideli
- LUMSA University, Department of Human Science and Department of Psychosis Studies, KCL, Rome, Italy
| | - Peter B Jones
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- CAMEO Early Intervention Service, Cambridgeshire & Peterborough NHS Foundation Trust, Cambridge, UK
| | - Hannah E Jongsma
- Psylife Group, Division of Psychiatry, University College London, London, UK
| | - James B Kirkbride
- Psylife Group, Division of Psychiatry, University College London, London, UK
| | - Caterina La Cascia
- Section of Psychiatry, Department of Biomedicine, Neuroscience and advanced Diagnostic (BiND), University of Palermo, Palermo, Italy
| | - Antonio Lasalvia
- Section of Psychiatry, Department of Neuroscience, Biomedicine and Movement, University of Verona, Verona, Italy
| | - Sarah Tosato
- Section of Psychiatry, Department of Neuroscience, Biomedicine and Movement, University of Verona, Verona, Italy
| | | | - Paulo Rossi Menezes
- Department of Preventive Medicine, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Jim van Os
- Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience. King's College of London, London, UK
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, South Limburg Mental Health Research and Teaching Network, Maastricht University Medical Centre, Maastricht, The Netherlands
- Department Psychiatry, Brain Centre Rudolf Magnus, Utrecht University Medical Centre, Utrecht, The Netherlands
| | - Diego Quattrone
- Social, Genetics and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Bart P Rutten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, South Limburg Mental Health Research and Teaching Network, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Jose Luis Santos
- Department of Psychiatry, Servicio de Psiquiatría Hos"ital "Virgen de"a Luz", C/Hermandad de Donantes de Sangre, 16002, Cuenca, Spain
| | - Julio Sanjuán
- Department of Psychiatry, School of Medicine, Universidad de Valencia, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), C/Avda. Blasco Ibáñez 15, 46010, Valencia, Spain
| | - Jean-Paul Selten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, South Limburg Mental Health Research and Teaching Network, Maastricht University Medical Centre, Maastricht, The Netherlands
- Rivierduinen Institute for Mental Health Care, Leiden, The Netherlands
| | - Andrei Szöke
- University of Paris Est Creteil, INSERM, IMRB, AP-HP, Hôpitaux Universitaires, H. Mondor, DMU IMPACT, Creteil, France
| | - Ilaria Tarricone
- Bologna Transcultural Psychosomatic Team (BoTPT), Department of Medical and Surgical Science, Alma Mater Studiorum Università di Bologna, Bologna, Italy
| | | | - Eva Velthorst
- GGZ (Mental Health Services) Noord Holland Noord, Heerhugowaard, the Netherlands
| | - Craig Morgan
- ESRC Centre for Society and Mental Health, King's College London, London, UK
| | - Emma Dempster
- Department of Psychiatry, Center for Psychiatric Neuroscience, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Eilis Hannon
- Department of Psychiatry, Center for Psychiatric Neuroscience, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Joe Burrage
- Department of Psychiatry, Center for Psychiatric Neuroscience, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Daniella Dwir
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Atheeshaan Arumuham
- Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience. King's College of London, London, UK
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
- Institute of Clinical Sciences (ICS), Faculty of Medicine, Imperial College London, London, UK
| | - Jonathan Mill
- Department of Psychiatry, Center for Psychiatric Neuroscience, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Robin M Murray
- Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience. King's College of London, London, UK
| | - Chloe C Y Wong
- Social, Genetics and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
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29
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Nakamura T, Takata A. The molecular pathology of schizophrenia: an overview of existing knowledge and new directions for future research. Mol Psychiatry 2023; 28:1868-1889. [PMID: 36878965 PMCID: PMC10575785 DOI: 10.1038/s41380-023-02005-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 02/15/2023] [Accepted: 02/15/2023] [Indexed: 03/08/2023]
Abstract
Despite enormous efforts employing various approaches, the molecular pathology in the schizophrenia brain remains elusive. On the other hand, the knowledge of the association between the disease risk and changes in the DNA sequences, in other words, our understanding of the genetic pathology of schizophrenia, has dramatically improved over the past two decades. As the consequence, now we can explain more than 20% of the liability to schizophrenia by considering all analyzable common genetic variants including those with weak or no statistically significant association. Also, a large-scale exome sequencing study identified single genes whose rare mutations substantially increase the risk for schizophrenia, of which six genes (SETD1A, CUL1, XPO7, GRIA3, GRIN2A, and RB1CC1) showed odds ratios larger than ten. Based on these findings together with the preceding discovery of copy number variants (CNVs) with similarly large effect sizes, multiple disease models with high etiological validity have been generated and analyzed. Studies of the brains of these models, as well as transcriptomic and epigenomic analyses of patient postmortem tissues, have provided new insights into the molecular pathology of schizophrenia. In this review, we overview the current knowledge acquired from these studies, their limitations, and directions for future research that may redefine schizophrenia based on biological alterations in the responsible organ rather than operationalized criteria.
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Affiliation(s)
- Takumi Nakamura
- Laboratory for Molecular Pathology of Psychiatric Disorders, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan
| | - Atsushi Takata
- Laboratory for Molecular Pathology of Psychiatric Disorders, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan.
- Research Institute for Diseases of Old Age, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan.
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30
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Psychotic disorders as a framework for precision psychiatry. Nat Rev Neurol 2023; 19:221-234. [PMID: 36879033 DOI: 10.1038/s41582-023-00779-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/24/2023] [Indexed: 03/08/2023]
Abstract
People with psychotic disorders can show marked interindividual variations in the onset of illness, responses to treatment and relapse, but they receive broadly similar clinical care. Precision psychiatry is an approach that aims to stratify people with a given disorder according to different clinical outcomes and tailor treatment to their individual needs. At present, interindividual differences in outcomes of psychotic disorders are difficult to predict on the basis of clinical assessment alone. Therefore, current research in psychosis seeks to build models that predict outcomes by integrating clinical information with a range of biological measures. Here, we review recent progress in the application of precision psychiatry to psychotic disorders and consider the challenges associated with implementing this approach in clinical practice.
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Maternal SARS-CoV-2 exposure alters infant DNA methylation. Brain Behav Immun Health 2023; 27:100572. [PMID: 36570792 PMCID: PMC9758784 DOI: 10.1016/j.bbih.2022.100572] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Revised: 12/07/2022] [Accepted: 12/16/2022] [Indexed: 12/23/2022] Open
Abstract
Background Infection during pregnancy can increase the risk of neurodevelopmental disorders in offspring. The impact of maternal SARS-CoV-2 infection on infant neurodevelopment is poorly understood. The maternal immune response to infection may be mimicked in rodent models of maternal immune activation which recapitulate altered neurodevelopment and behavioural disturbances in the offspring. In these models, epigenetic mechanisms, in particular DNA methylation, are one pathway through which this risk is conferred in utero to offspring. We hypothesised that in utero exposure to SARS-CoV-2 in humans may alter infant DNA methylation, particularly in genes associated with neurodevelopment. We aimed to test this hypothesis in a pilot sample of children in Victoria, Australia, who were exposed in utero to SARS-CoV-2. Methods DNA was extracted from buccal swab specimens from (n = 4) SARS-CoV-2 in utero exposed and (n = 4) non-exposed infants and methylation status assessed across 850,000 methylation sites using an Illumina EPIC BeadChip. We also conducted an exploratory enrichment analysis using Gene Ontology annotations. Results 1962 hypermethylated CpG sites were identified with an unadjusted p-value of 0.05, where 1133 CpGs mapped to 959 unique protein coding genes, and 716 hypomethylated CpG sites mapped to 559 unique protein coding genes in SARS-CoV-2 exposed infants compared to non-exposed. One differentially methylated position (cg06758191), located in the gene body of AFAP1 that was hypomethylated in the SARS-CoV-2 exposed cohort was significant after correction for multiple testing (FDR-adjusted p-value <0.00083). Two significant differentially methylated regions were identified; a hypomethylated intergenic region located in chromosome 6p proximal to the genes ZP57 and HLA-F (fwer <0.004), and a hypomethylated region in the promoter and body of the gene GAREM2 (fwer <0.036). Gene network enrichment analysis revealed differential methylation in genes corresponding to pathways relevant to neurodevelopment, including the ERBB pathway. Conclusion These pilot data suggest that exposure to SARS-CoV-2 in utero differentially alters methylation of genes in pathways that play a role in human neurodevelopment.
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Fišar Z. Biological hypotheses, risk factors, and biomarkers of schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry 2023; 120:110626. [PMID: 36055561 DOI: 10.1016/j.pnpbp.2022.110626] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 08/24/2022] [Accepted: 08/25/2022] [Indexed: 12/19/2022]
Abstract
Both the discovery of biomarkers of schizophrenia and the verification of biological hypotheses of schizophrenia are an essential part of the process of understanding the etiology of this mental disorder. Schizophrenia has long been considered a neurodevelopmental disease whose symptoms are caused by impaired synaptic signal transduction and brain neuroplasticity. Both the onset and chronic course of schizophrenia are associated with risk factors-induced disruption of brain function and the establishment of a new homeostatic setpoint characterized by biomarkers. Different risk factors and biomarkers can converge to the same symptoms of schizophrenia, suggesting that the primary cause of the disease can be highly individual. Schizophrenia-related biomarkers include measurable biochemical changes induced by stress (elevated allostatic load), mitochondrial dysfunction, neuroinflammation, oxidative and nitrosative stress, and circadian rhythm disturbances. Here is a summary of selected valid biological hypotheses of schizophrenia formulated based on risk factors and biomarkers, neurodevelopment, neuroplasticity, brain chemistry, and antipsychotic medication. The integrative neurodevelopmental-vulnerability-neurochemical model is based on current knowledge of the neurobiology of the onset and progression of the disease and the effects of antipsychotics and psychotomimetics and reflects the complex and multifactorial nature of schizophrenia.
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Affiliation(s)
- Zdeněk Fišar
- Charles University and General University Hospital in Prague, First Faculty of Medicine, Department of Psychiatry, Czech Republic.
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Lu AKM, Lin JJ, Tseng HH, Wang XY, Jang FL, Chen PS, Huang CC, Hsieh S, Lin SH. DNA methylation signature aberration as potential biomarkers in treatment-resistant schizophrenia: Constructing a methylation risk score using a machine learning method. J Psychiatr Res 2023; 157:57-65. [PMID: 36442407 DOI: 10.1016/j.jpsychires.2022.11.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 11/08/2022] [Accepted: 11/12/2022] [Indexed: 11/18/2022]
Abstract
Treatment-resistant schizophrenia (TRS) is defined as a non-response to at least two trials of antipsychotic medication with an adequate dose and duration. We aimed to evaluate the discriminant abilities of DNA methylation probes and methylation risk score between treatment-resistant schizophrenia and non-treatment-resistant schizophrenia. This study recruited 96 schizophrenia patients (TRS and non-TRS) and 56 healthy controls (HC). Participants were divided into a discovery set and a validation set. In the discovery set, we conducted genome-wide methylation analysis (human MethylationEPIC 850K BeadChip) on the subject's blood DNA and discriminated significant methylation signatures, then verified these methylation signatures in the validation set. Based on genome-wide scans of TRS versus non-TRS, thirteen differentially methylated probes were identified at FDR <0.05 and >20% differences in DNA methylation β-values. Next, we selected six probes within gene coding regions (LOC404266, LOXL2, CERK, CHMP7, and SLC17A9) to conduct verification in the validation set using quantitative methylation-specific PCR (qMSP). These six methylation probes showed satisfactory discrimination between TRS patients and non-TRS patients, with an AUC ranging from 0.83 to 0.92, accuracy ranging from 77.8% to 87.3%, sensitivity ranging from 80% to 90%, and specificity ranging from 65.6% to 85%. This methylation risk score model showed satisfactory discrimination between TRS patients and non-TRS patients, with an accuracy of 88.3%. These findings support that methylation signatures may be used as an indicator of TRS vulnerability and provide a model for the clinical use of methylation to identify TRS.
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Affiliation(s)
- Andrew Ke-Ming Lu
- Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Jin-Jia Lin
- Department of Psychiatry, Chi Mei Medical Center, Tainan, Taiwan
| | - Huai-Hsuan Tseng
- Department of Psychiatry, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Xin-Yu Wang
- Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Fong-Lin Jang
- Department of Psychiatry, Chi Mei Medical Center, Tainan, Taiwan
| | - Po-See Chen
- Department of Psychiatry, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Institute of Behavioral Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Chih-Chun Huang
- Department of Psychiatry, National Cheng Kung University Hospital, Dou-Liou Branch, Yunlin, Taiwan
| | - Shulan Hsieh
- Department of Psychology, College of Social Sciences, National Cheng Kung University, Tainan, Taiwan
| | - Sheng-Hsiang Lin
- Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Department of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Biostatistics Consulting Center, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
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Mohd Asyraf AJ, Nour El Huda AR, Hanisah MN, Noorul Amilin H, Norlelawati AT. DNA methylation and copy number variation of the complement C4A gene in schizophrenia. GENE REPORTS 2022. [DOI: 10.1016/j.genrep.2022.101702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Domingos LB, Silva NR, Chaves Filho AJM, Sales AJ, Starnawska A, Joca S. Regulation of DNA Methylation by Cannabidiol and Its Implications for Psychiatry: New Insights from In Vivo and In Silico Models. Genes (Basel) 2022; 13:2165. [PMID: 36421839 PMCID: PMC9690868 DOI: 10.3390/genes13112165] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 11/11/2022] [Accepted: 11/16/2022] [Indexed: 12/24/2023] Open
Abstract
Cannabidiol (CBD) is a non-psychotomimetic compound present in cannabis sativa. Many recent studies have indicated that CBD has a promising therapeutic profile for stress-related psychiatric disorders, such as anxiety, schizophrenia and depression. Such a diverse profile has been associated with its complex pharmacology, since CBD can target different neurotransmitter receptors, enzymes, transporters and ion channels. However, the precise contribution of each of those mechanisms for CBD effects is still not yet completely understood. Considering that epigenetic changes make the bridge between gene expression and environment interactions, we review and discuss herein how CBD affects one of the main epigenetic mechanisms associated with the development of stress-related psychiatric disorders: DNA methylation (DNAm). Evidence from in vivo and in silico studies indicate that CBD can regulate the activity of the enzymes responsible for DNAm, due to directly binding to the enzymes and/or by indirectly regulating their activities as a consequence of neurotransmitter-mediated signaling. The implications of this new potential pharmacological target for CBD are discussed in light of its therapeutic and neurodevelopmental effects.
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Affiliation(s)
- Luana B. Domingos
- Department of Biomedicine, Aarhus University, 8000 Aarhus, Denmark
- Translational Neuropsychiatry Unit, Department of Clinical Medicine, Aarhus University, 8200 Aarhus, Denmark
| | - Nicole R. Silva
- Department of Biomedicine, Aarhus University, 8000 Aarhus, Denmark
- Translational Neuropsychiatry Unit, Department of Clinical Medicine, Aarhus University, 8200 Aarhus, Denmark
| | - Adriano J. M. Chaves Filho
- Department of Biomedicine, Aarhus University, 8000 Aarhus, Denmark
- Translational Neuropsychiatry Unit, Department of Clinical Medicine, Aarhus University, 8200 Aarhus, Denmark
| | - Amanda J. Sales
- Department of Pharmacology, School of Medicine of Ribeirao Preto, University of Sao Paulo, Ribeirao Preto 14049-900, SP, Brazil
| | - Anna Starnawska
- Department of Biomedicine, Aarhus University, 8000 Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8000 Aarhus, Denmark
- Center for Genomics and Personalized Medicine, CGPM, Center for Integrative Sequencing, iSEQ, 8000 Aarhus, Denmark
| | - Sâmia Joca
- Department of Biomedicine, Aarhus University, 8000 Aarhus, Denmark
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36
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Song J, Kuan PF. A systematic assessment of cell type deconvolution algorithms for DNA methylation data. Brief Bioinform 2022; 23:bbac449. [PMID: 36242584 PMCID: PMC9947552 DOI: 10.1093/bib/bbac449] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/11/2022] [Accepted: 09/20/2022] [Indexed: 12/14/2022] Open
Abstract
We performed systematic assessment of computational deconvolution methods that play an important role in the estimation of cell type proportions from bulk methylation data. The proposed framework methylDeConv (available as an R package) integrates several deconvolution methods for methylation profiles (Illumina HumanMethylation450 and MethylationEPIC arrays) and offers different cell-type-specific CpG selection to construct the extended reference library which incorporates the main immune cell subsets, epithelial cells and cell-free DNAs. We compared the performance of different deconvolution algorithms via simulations and benchmark datasets and further investigated the associations of the estimated cell type proportions to cancer therapy in breast cancer and subtypes in melanoma methylation case studies. Our results indicated that the deconvolution based on the extended reference library is critical to obtain accurate estimates of cell proportions in non-blood tissues.
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Affiliation(s)
- Junyan Song
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY
| | - Pei-Fen Kuan
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY
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37
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Sommerer Y, Ohlei O, Dobricic V, Oakley DH, Wesse T, Sedghpour Sabet S, Demuth I, Franke A, Hyman BT, Lill CM, Bertram L. A correlation map of genome-wide DNA methylation patterns between paired human brain and buccal samples. Clin Epigenetics 2022; 14:139. [PMID: 36320053 PMCID: PMC9628033 DOI: 10.1186/s13148-022-01357-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 10/17/2022] [Indexed: 11/06/2022] Open
Abstract
Epigenome-wide association studies (EWAS) assessing the link between DNA methylation (DNAm) and phenotypes related to structural brain measures, cognitive function, and neurodegenerative diseases are becoming increasingly more popular. Due to the inaccessibility of brain tissue in humans, several studies use peripheral tissues such as blood, buccal swabs, and saliva as surrogates. To aid the functional interpretation of EWAS findings in such settings, there is a need to assess the correlation of DNAm variability across tissues in the same individuals. In this study, we performed a correlation analysis between DNAm data of a total of n = 120 matched post-mortem buccal and prefrontal cortex samples. We identified nearly 25,000 (3% of approximately 730,000) cytosine-phosphate-guanine (CpG) sites showing significant (false discovery rate q < 0.05) correlations between buccal and PFC samples. Correlated CpG sites showed a preponderance to being located in promoter regions and showed a significant enrichment of being determined by genetic factors, i.e. methylation quantitative trait loci (mQTL), based on buccal and dorsolateral prefrontal cortex mQTL databases. Our novel buccal–brain DNAm correlation map will provide a valuable resource for future EWAS using buccal samples for studying DNAm effects on phenotypes relating to the brain. All correlation results are made freely available to the public online.
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Affiliation(s)
- Yasmine Sommerer
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany
| | - Olena Ohlei
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany
| | - Derek H Oakley
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Tanja Wesse
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Sanaz Sedghpour Sabet
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Ilja Demuth
- Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.,Division of Lipid Metabolism, Department of Endocrinology and Metabolic Diseases, Berlin Institute of Health, Berlin, Germany.,BCRT - Berlin Institute of Health Center for Regenerative Therapies, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Bradley T Hyman
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.,Massachusetts Alzheimer's Disease Research Center, Charlestown, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Christina M Lill
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany.,Ageing Epidemiology Unit (AGE), School of Public Health, Imperial College London, London, UK.,Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany. .,Department of Psychology, Center for Lifespan Changes in Brain and Cognition (LCBC), University of Oslo, Oslo, Norway.
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38
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Kalyakulina A, Yusipov I, Bacalini MG, Franceschi C, Vedunova M, Ivanchenko M. Disease classification for whole-blood DNA methylation: Meta-analysis, missing values imputation, and XAI. Gigascience 2022; 11:giac097. [PMID: 36259657 PMCID: PMC9718659 DOI: 10.1093/gigascience/giac097] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 08/01/2022] [Accepted: 09/15/2022] [Indexed: 07/25/2023] Open
Abstract
BACKGROUND DNA methylation has a significant effect on gene expression and can be associated with various diseases. Meta-analysis of available DNA methylation datasets requires development of a specific workflow for joint data processing. RESULTS We propose a comprehensive approach of combined DNA methylation datasets to classify controls and patients. The solution includes data harmonization, construction of machine learning classification models, dimensionality reduction of models, imputation of missing values, and explanation of model predictions by explainable artificial intelligence (XAI) algorithms. We show that harmonization can improve classification accuracy by up to 20% when preprocessing methods of the training and test datasets are different. The best accuracy results were obtained with tree ensembles, reaching above 95% for Parkinson's disease. Dimensionality reduction can substantially decrease the number of features, without detriment to the classification accuracy. The best imputation methods achieve almost the same classification accuracy for data with missing values as for the original data. XAI approaches have allowed us to explain model predictions from both populational and individual perspectives. CONCLUSIONS We propose a methodologically valid and comprehensive approach to the classification of healthy individuals and patients with various diseases based on whole-blood DNA methylation data using Parkinson's disease and schizophrenia as examples. The proposed algorithm works better for the former pathology, characterized by a complex set of symptoms. It allows to solve data harmonization problems for meta-analysis of many different datasets, impute missing values, and build classification models of small dimensionality.
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Affiliation(s)
- Alena Kalyakulina
- Correspondence author. Alena Kalyakulina, Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, Gagarin avenue 22, Nizhny Novgorod 603022, Russia. E-mail:
| | | | | | - Claudio Franceschi
- Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, 603022 Nizhny Novgorod, Russia
| | - Maria Vedunova
- Institute of Biology and Biomedicine, Lobachevsky State University, 603022 Nizhny Novgorod, Russia
| | - Mikhail Ivanchenko
- Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, 603022 Nizhny Novgorod, Russia
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Jiao S, Cao T, Cai H. Peripheral biomarkers of treatment-resistant schizophrenia: Genetic, inflammation and stress perspectives. Front Pharmacol 2022; 13:1005702. [PMID: 36313375 PMCID: PMC9597880 DOI: 10.3389/fphar.2022.1005702] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 09/26/2022] [Indexed: 11/16/2022] Open
Abstract
Treatment-resistant schizophrenia (TRS) often results in severe disability and functional impairment. Currently, the diagnosis of TRS is largely exclusionary and emphasizes the improvement of symptoms that may not be detected early and treated according to TRS guideline. As the gold standard, clozapine is the most prescribed selection for TRS. Therefore, how to predict TRS in advance is critical for forming subsequent treatment strategy especially clozapine is used during the early stage of TRS. Although mounting studies have identified certain clinical factors and neuroimaging characteristics associated with treatment response in schizophrenia, the predictors for TRS remain to be explored. Biomarkers, particularly for peripheral biomarkers, show great potential in predicting TRS in view of their predictive validity, noninvasiveness, ease of testing and low cost that would enable their widespread use. Recent evidence supports that the pathogenesis of TRS may be involved in abnormal neurotransmitter systems, inflammation and stress. Due to the heterogeneity of TRS and the lack of consensus in diagnostic criteria, it is difficult to compare extensive results among different studies. Based on the reported neurobiological mechanisms that may be associated with TRS, this paper narratively reviews the updates of peripheral biomarkers of TRS, from genetic and other related perspectives. Although current evidence regarding biomarkers in TRS remains fragmentary, when taken together, it can help to better understand the neurobiological interface of clinical phenotypes and psychiatric symptoms, which will enable individualized prediction and therapy for TRS in the long run.
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Affiliation(s)
- Shimeng Jiao
- Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China
- Institute of Clinical Pharmacy, Central South University, Changsha, China
- International Research Center for Precision Medicine, Transformative Technology and Software Services, Changsha, Hunan, China
| | - Ting Cao
- Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China
- Institute of Clinical Pharmacy, Central South University, Changsha, China
- International Research Center for Precision Medicine, Transformative Technology and Software Services, Changsha, Hunan, China
| | - Hualin Cai
- Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China
- Institute of Clinical Pharmacy, Central South University, Changsha, China
- International Research Center for Precision Medicine, Transformative Technology and Software Services, Changsha, Hunan, China
- *Correspondence: Hualin Cai,
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Paul KC, Kusters C, Furlong M, Zhang K, Yu Y, Folle AD, Del Rosario I, Keener A, Bronstein J, Sinsheimer JS, Horvath S, Ritz B. Immune system disruptions implicated in whole blood epigenome-wide association study of depression among Parkinson's disease patients. Brain Behav Immun Health 2022; 26:100530. [PMID: 36325427 PMCID: PMC9618774 DOI: 10.1016/j.bbih.2022.100530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 10/01/2022] [Indexed: 11/09/2022] Open
Abstract
Although Parkinson's Disease (PD) is typically described in terms of motor symptoms, depression is a common feature. We explored whether depression influences blood-based genome-wide DNA methylation (DNAm) in 692 subjects from a population-based PD case-control study, using both a history of clinically diagnosed depression and current depressive symptoms measured by the geriatric depression scale (GDS). While PD patients in general had more immune activation and more accelerated epigenetic immune system aging than controls, the patients experiencing current depressive symptoms (GDS≥5) showed even higher levels of both markers than patients without current depressive symptoms (GDS<5). For PD patients with a history of clinical depression compared to those without, we found no differences in immune cell composition. However, a history of clinical depression among patients was associated with differentially methylated CpGs. Epigenome-wide association analysis (EWAS) revealed 35 CpGs associated at an FDR≤0.05 (569 CpGs at FDR≤0.10, 1718 CpGs at FDR≤0.15). Gene set enrichment analysis implicated immune system pathways, including immunoregulatory interactions between lymphoid and non-lymphoid cells (p-adj = 0.003) and cytokine-cytokine receptor interaction (p-adj = 0.004). Based on functional genomics, 25 (71%) of the FDR≤0.05 CpGs were associated with genetic variation at 45 different methylation quantitative trait loci (meQTL). Twenty-six of the meQTLs were also expression QTLs (eQTLs) associated with the abundance of 53 transcripts in blood and 22 transcripts in brain (substantia nigra, putamen basal ganglia, or frontal cortex). Notably, cg15199181 was strongly related to rs823114 (SNP-CpG p-value = 3.27E-310), a SNP identified in a PD meta-GWAS and related to differential expression of PM20D1, RAB29, SLC41A1, and NUCKS1. The entire set of genes detected through functional genomics was most strongly overrepresented for interferon-gamma-mediated signaling pathway (enrichment ratio = 18.8, FDR = 4.4e-03) and T cell receptor signaling pathway (enrichment ratio = 13.2, FDR = 4.4e-03). Overall, the current study provides evidence of immune system involvement in depression among Parkinson's patients. Parkinson's disease (PD) is associated with clinical depression prior to PD onset and depressive symptoms after PD diagnosis. Epigenome-wide analysis revealed CpGs related to current depressive symptoms and a history of clinical depression among PD patients. Patients experiencing current depressive symptoms had the highest epigenetic-based neutrophil-to-lymphocyte ratio on average. Patients with a history of clinical depression had differentially methylated CpGs in genes enriched for immune system pathways. Many of the depression associated CpGs were linked to differential expression through meQTL/eQTLs, which included GWAS variants.
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Affiliation(s)
- Kimberly C. Paul
- Department of Neurology, David Geffen School of Medicine, Los Angeles, CA, USA
- Corresponding author. 73-320B CHS, CAMPUS-177220, UCLA, Los Angeles, CA, 90095, USA.
| | - Cynthia Kusters
- Departments of Human Genetics, David Geffen School of Medicine, Los Angeles, CA, USA
| | - Melissa Furlong
- University of Arizona, Mel and Enid Zuckerman College of Public Health, Tucson, AZ, USA
| | - Keren Zhang
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
| | - Yu Yu
- Center for Health Policy Research, UCLA Fielding School of Public Health, Los Angeles, CA, USA
| | - Aline Duarte Folle
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
| | - Irish Del Rosario
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
| | - Adrienne Keener
- Department of Neurology, David Geffen School of Medicine, Los Angeles, CA, USA
| | - Jeff Bronstein
- Department of Neurology, David Geffen School of Medicine, Los Angeles, CA, USA
| | - Janet S. Sinsheimer
- Departments of Human Genetics, David Geffen School of Medicine, Los Angeles, CA, USA
- Department of Biostatistics, UCLA Fielding School of Public Health, Los Angeles, CA, USA
| | - Steve Horvath
- Departments of Human Genetics, David Geffen School of Medicine, Los Angeles, CA, USA
- Department of Biostatistics, UCLA Fielding School of Public Health, Los Angeles, CA, USA
| | - Beate Ritz
- Department of Neurology, David Geffen School of Medicine, Los Angeles, CA, USA
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
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Mott AC, Mott A, Preuß S, Bennewitz J, Tetens J, Falker-Gieske C. eQTL analysis of laying hens divergently selected for feather pecking identifies KLF14 as a potential key regulator for this behavioral disorder. Front Genet 2022; 13:969752. [PMID: 36061196 PMCID: PMC9428588 DOI: 10.3389/fgene.2022.969752] [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: 06/15/2022] [Accepted: 07/25/2022] [Indexed: 02/03/2023] Open
Abstract
Feather pecking in chickens is a damaging behavior, seriously impacting animal welfare and leading to economic losses. Feather pecking is a complex trait, which is partly under genetic control. Different hypotheses have been proposed to explain the etiology of feather pecking and notably, several studies have identified similarities between feather pecking and human mental disorders such as obsessive-compulsive disorder and schizophrenia. This study uses transcriptomic and phenotypic data from 167 chickens to map expression quantitative trait loci and to identify regulatory genes with a significant effect on this behavioral disorder using an association weight matrix approach. From 70 of the analyzed differentially expressed genes, 11,790 genome wide significantly associated variants were detected, of which 23 showed multiple associations (≥15). These were located in proximity to a number of genes, which are transcription regulators involved in chromatin binding, nucleic acid metabolism, protein translation and putative regulatory RNAs. The association weight matrix identified 36 genes and the two transcription factors: SP6 (synonym: KLF14) and ENSGALG00000042129 (synonym: CHTOP) as the most significant, with an enrichment of KLF14 binding sites being detectable in 40 differentially expressed genes. This indicates that differential expression between animals showing high and low levels of feather pecking was significantly associated with a genetic variant in proximity to KLF14. This multiallelic variant was located 652 bp downstream of KLF14 and is a deletion of 1-3 bp. We propose that a deletion downstream of the transcription factor KLF14 has a negative impact on the level of T cells in the developing brain of high feather pecking chickens, which leads to developmental and behavioral abnormalities. The lack of CD4 T cells and gamma-Aminobutyric acid (GABA) receptors are important factors for the increased propensity of laying hens to perform feather pecking. As such, KLF14 is a clear candidate regulator for the expression of genes involved in the pathogenic development. By further elucidating the regulatory pathways involved in feather pecking we hope to take significant steps forward in explaining and understanding other mental disorders, not just in chickens.
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Affiliation(s)
| | - Andrea Mott
- Department of Animal Sciences, Georg-August-University, Göttingen, Germany
| | - Siegfried Preuß
- Institute of Animal Science, University of Hohenheim, Stuttgart, Germany
| | - Jörn Bennewitz
- Institute of Animal Science, University of Hohenheim, Stuttgart, Germany
| | - Jens Tetens
- Department of Animal Sciences, Georg-August-University, Göttingen, Germany
- Center for Integrated Breeding Research, Georg-August-University, Göttingen, Germany
| | - Clemens Falker-Gieske
- Department of Animal Sciences, Georg-August-University, Göttingen, Germany
- *Correspondence: Clemens Falker-Gieske,
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Li XW, Zhang MY, Li ZJ, Ai LZ, Jin MD, Jia NN, Xie MT, Yang YQ, Li WZ, Dong L, Yu Q. ABCB9 polymorphism rs61955196 is associated with schizophrenia in a Chinese Han population. World J Psychiatry 2022; 12:904-914. [PMID: 36051605 PMCID: PMC9331447 DOI: 10.5498/wjp.v12.i7.904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 05/02/2022] [Accepted: 06/17/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Schizophrenia (SCZ) is a complex disease which can be affected by both genetic and environmental factors. Prenatal famine exposure may cause changes in DNA methylation levels of genes. Meanwhile, maternal nutrition during pregnancy is a pivotal environmental factor in the development of SCZ. DNA methylation may be an intermediate factor mediating exposure to famine during pregnancy and SCZ, and DNA methylation quantitative trait loci might serve as a promising tool for linking SCZ and prenatal famine.
AIM To analyze the association between prenatal famine exposure and SCZ risk in Northeast Han Chinese through analysis of DNA methylation related loci.
METHODS A total of 954 Han Chinese from Northeast China were recruited, including 443 patients with SCZ and 511 healthy controls. The participants were further divided into famine (born in 1960-1962) and non-famine (born in 1963-1965) groups to investigate the effect of prenatal famine exposure. Four single-nucleotide polymorphisms (SNPs) selected according to the relevant literature were genotyped, namely, rs11917047 in PTPRG, rs2239681 in IGF2, rs3842756 in INSIGF, and rs61955196 in ABCB9. DNA were extracted from peripheral blood samples, and the genotypes of these SNP loci were detected using the improved Multiple Ligase Detection Reaction multiple SNP typing technique. The associations of the DNA methylation related SNPs with SCZ risk and prenatal famine, and their interactions were analyzed using logistic regression analysis and generalized multifactor dimensionality reduction (GMDR) software.
RESULTS Based on the sequencing data, genotype distributions and allele frequencies of the four selected SNPs were determined. All genotype frequencies of the four SNPs in the healthy control group were tested for deviation from Hardy-Weinberg equilibrium (P > 0.05). Logistic regression analysis showed that rs61955196 was significantly associated with SCZ risk in the log-additive model [odds ratio (OR): 1.22; 95% confidence interval (CI): 1.01-1.48; P = 0.040]. We also found that the rs61955196 allele was related with an enhanced risk of SCZ (G>C, OR: 1.22; 95%CI: 1.01-1.47; P = 0.042). However, no associations were observed between rs11917047, rs2239681, or rs3842756 and SCZ risk. Under the optimal genetic model, no significant association of famine with the four SNPs was seen. Though the gene–gene interactions between rs2239681 and rs61955196 were found in GMDR analysis, none of the gene-gene interactions and gene-famine interactions were associated with the risk of SCZ.
CONCLUSION Our study suggested that rs61955196 in ABCB9 is associated with SCZ susceptibility in Northeast Han Chinese, providing insight into genetic effects on SCZ.
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Affiliation(s)
- Xin-Wei Li
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, Jilin Province, China
| | - Ming-Yuan Zhang
- Department of Endemic Diseases and Parasitic Diseases Prevention, Yantai Center for Disease Control and Prevention, Yantai 264003, Shandong Province, China
| | - Zhi-Jun Li
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, Jilin Province, China
| | - Li-Zhe Ai
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, Jilin Province, China
| | - Meng-Di Jin
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, Jilin Province, China
| | - Ning-Ning Jia
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, Jilin Province, China
| | - Meng-Tong Xie
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, Jilin Province, China
| | - Yu-Qing Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, Jilin Province, China
| | - Wei-Zhen Li
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, Jilin Province, China
| | - Lin Dong
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, Jilin Province, China
| | - Qiong Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, Jilin Province, China
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Alameda L, Trotta G, Quigley H, Rodriguez V, Gadelrab R, Dwir D, Dempster E, Wong CCY, Forti MD. Can epigenetics shine a light on the biological pathways underlying major mental disorders? Psychol Med 2022; 52:1645-1665. [PMID: 35193719 PMCID: PMC9280283 DOI: 10.1017/s0033291721005559] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Revised: 11/30/2021] [Accepted: 12/29/2021] [Indexed: 12/27/2022]
Abstract
A significant proportion of the global burden of disease can be attributed to mental illness. Despite important advances in identifying risk factors for mental health conditions, the biological processing underlying causal pathways to disease onset remain poorly understood. This represents a limitation to implement effective prevention and the development of novel pharmacological treatments. Epigenetic mechanisms have emerged as mediators of environmental and genetic risk factors which might play a role in disease onset, including childhood adversity (CA) and cannabis use (CU). Particularly, human research exploring DNA methylation has provided new and promising insights into the role of biological pathways implicated in the aetio-pathogenesis of psychiatric conditions, including: monoaminergic (Serotonin and Dopamine), GABAergic, glutamatergic, neurogenesis, inflammatory and immune response and oxidative stress. While these epigenetic changes have been often studied as disease-specific, similarly to the investigation of environmental risk factors, they are often transdiagnostic. Therefore, we aim to review the existing literature on DNA methylation from human studies of psychiatric diseases (i) to identify epigenetic modifications mapping onto biological pathways either transdiagnostically or specifically related to psychiatric diseases such as Eating Disorders, Post-traumatic Stress Disorder, Bipolar and Psychotic Disorder, Depression, Autism Spectrum Disorder and Anxiety Disorder, and (ii) to investigate a convergence between some of these epigenetic modifications and the exposure to known risk factors for psychiatric disorders such as CA and CU, as well as to other epigenetic confounders in psychiatry research.
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Affiliation(s)
- Luis Alameda
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Departamento de Psiquiatría, Centro Investigación Biomedica en Red de Salud Mental (CIBERSAM), Instituto de Biomedicina de Sevilla (IBIS), Hospital Universitario Virgen del Rocío, Universidad de Sevilla, Sevilla, Spain
| | - Giulia Trotta
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, London, UK
| | - Harriet Quigley
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Victoria Rodriguez
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Romayne Gadelrab
- Centre for Affective Disorders, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Daniella Dwir
- Department of Psychiatry, Center for Psychiatric Neuroscience, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Emma Dempster
- University of Exeter Medical School, University of Exeter, Barrack Road, Exeter, UK
| | - Chloe C. Y. Wong
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, London, UK
| | - Marta Di Forti
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
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Identification of COVID-19-Associated DNA Methylation Variations by Integrating Methylation Array and scRNA-Seq Data at Cell-Type Resolution. Genes (Basel) 2022; 13:genes13071109. [DOI: 10.3390/genes13071109] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 06/16/2022] [Accepted: 06/17/2022] [Indexed: 01/27/2023] Open
Abstract
Single-cell transcriptome studies have revealed immune dysfunction in COVID-19 patients, including lymphopenia, T cell exhaustion, and increased levels of pro-inflammatory cytokines, while DNA methylation plays an important role in the regulation of immune response and inflammatory response. The specific cell types of immune responses regulated by DNA methylation in COVID-19 patients will be better understood by exploring the COVID-19 DNA methylation variation at the cell-type level. Here, we developed an analytical pipeline to explore single-cell DNA methylation variations in COVID-19 patients by transferring bulk-tissue-level knowledge to the single-cell level. We discovered that the methylation variations in the whole blood of COVID-19 patients showed significant cell-type specificity with remarkable enrichment in gamma-delta T cells and presented a phenomenon of hypermethylation and low expression. Furthermore, we identified five genes whose methylation variations were associated with several cell types. Among them, S100A9, AHNAK, and CX3CR1 have been reported as potential COVID-19 biomarkers previously, and the others (TRAF3IP3 and LFNG) are closely associated with the immune and virus-related signaling pathways. We propose that they might serve as potential epigenetic biomarkers for COVID-19 and could play roles in important biological processes such as the immune response and antiviral activity.
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Sánchez-Hidalgo AC, Martín-Cuevas C, Crespo-Facorro B, Garrido-Torres N. Reelin Alterations, Behavioral Phenotypes, and Brain Anomalies in Schizophrenia: A Systematic Review of Insights From Rodent Models. Front Neuroanat 2022; 16:844737. [PMID: 35401125 PMCID: PMC8986979 DOI: 10.3389/fnana.2022.844737] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 02/14/2022] [Indexed: 12/09/2022] Open
Abstract
Reelin is an extracellular matrix glycoprotein reduced in brain regions (the prefrontal cortex and the hippocampus) of patients with schizophrenia. There are diverse rodent models of schizophrenia that mimic patient symptoms based on various causal theories; however, likely shared reelin alterations have not yet been systematically assessed in those models. A systematic review of the literature was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) model. Articles focused on psychotic disorders or schizophrenia and their relationship with reelin in rodent models were selected. Data (first author, publication year, results, both open field and prepulse inhibition test results, and type of reelin alteration) were extracted in duplicate by two independent reviewers. The 37 reviewed articles reported about various schizophrenia models and their reelin alterations, brain morphology, and behavioral defects. We conclude that reelin is an altered preclinical biomarker common to all models included, mainly prenatal or genetic models, and a key protein in schizophrenia disease, making the reelin signaling pathway in prenatal stages a target of special interest for future preclinical and clinical studies. All models presented at least one of the four described reelin alteration types. Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021210568], identifier [CRD42021210568].
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Affiliation(s)
- Ana C. Sánchez-Hidalgo
- Spanish Network for Research in Mental Health (CIBERSAM), Madrid, Spain
- Seville Biomedical Research Centre (IBiS), Seville, Spain
| | - Celia Martín-Cuevas
- Spanish Network for Research in Mental Health (CIBERSAM), Madrid, Spain
- Seville Biomedical Research Centre (IBiS), Seville, Spain
| | - Benedicto Crespo-Facorro
- Spanish Network for Research in Mental Health (CIBERSAM), Madrid, Spain
- Seville Biomedical Research Centre (IBiS), Seville, Spain
- Department of Psychiatry, School of Medicine, University Hospital Virgen del Rocío-IBiS, Seville, Spain
- *Correspondence: Benedicto Crespo-Facorro,
| | - Nathalia Garrido-Torres
- Spanish Network for Research in Mental Health (CIBERSAM), Madrid, Spain
- Seville Biomedical Research Centre (IBiS), Seville, Spain
- Department of Psychiatry, School of Medicine, University Hospital Virgen del Rocío-IBiS, Seville, Spain
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Monroy-Jaramillo N, Martínez-Magaña JJ, Pérez-Aldana BE, Ortega-Vázquez A, Montalvo-Ortiz J, López-López M. The role of alcohol intake in the pharmacogenetics of treatment with clozapine. Pharmacogenomics 2022; 23:371-392. [PMID: 35311547 DOI: 10.2217/pgs-2022-0006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Clozapine (CLZ) is an atypical antipsychotic reserved for patients with refractory psychosis, but it is associated with a significant risk of severe adverse reactions (ADRs) that are potentiated with the concomitant use of alcohol. Additionally, pharmacogenetic studies have explored the influence of several genetic variants in CYP450, receptors and transporters involved in the interindividual response to CLZ. Herein, we systematically review the current multiomics knowledge behind the interaction between CLZ and alcohol intake, and how its concomitant use might modulate the pharmacogenetics. CYP1A2*1F, *1C and other alleles not yet discovered could support a precision medicine approach for better therapeutic effects and fewer CLZ ADRs. CLZ monitoring systems should be amended and include alcohol intake to protect patients from severe CLZ ADRs.
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Affiliation(s)
- Nancy Monroy-Jaramillo
- Department of Genetics, National Institute of Neurology & Neurosurgery, Manuel Velasco Suárez, La Fama, Tlalpan, Mexico City, 14269, Mexico
| | - José Jaime Martínez-Magaña
- Department of Psychiatry, Division of Human Genetics, Yale University School of Medicine, Orange, West Haven, CT 06477, USA
| | - Blanca Estela Pérez-Aldana
- Doctorado en Ciencias Biológicas y de la Salud, Metropolitan Autonomous University, Campus Xochimilco, Villa Quietud, Coyoacán, Mexico City, 04960, Mexico
| | - Alberto Ortega-Vázquez
- Metropolitan Autonomous University, Campus Xochimilco, Villa Quietud, Coyoacán, Mexico City, 04960, Mexico
| | - Janitza Montalvo-Ortiz
- Department of Psychiatry, Division of Human Genetics, Yale University School of Medicine, Orange, West Haven, CT 06477, USA
| | - Marisol López-López
- Metropolitan Autonomous University, Campus Xochimilco, Villa Quietud, Coyoacán, Mexico City, 04960, Mexico
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Miller CL. The Epigenetics of Psychosis: A Structured Review with Representative Loci. Biomedicines 2022; 10:561. [PMID: 35327363 PMCID: PMC8945330 DOI: 10.3390/biomedicines10030561] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 02/24/2022] [Accepted: 02/26/2022] [Indexed: 02/04/2023] Open
Abstract
The evidence for an environmental component in chronic psychotic disorders is strong and research on the epigenetic manifestations of these environmental impacts has commenced in earnest. In reviewing this research, the focus is on three genes as models for differential methylation, MCHR1, AKT1 and TDO2, each of which have been investigated for genetic association with psychotic disorders. Environmental factors associated with psychotic disorders, and which interact with these model genes, are explored in depth. The location of transcription factor motifs relative to key methylation sites is evaluated for predicted gene expression results, and for other sites, evidence is presented for methylation directing alternative splicing. Experimental results from key studies show differential methylation: for MCHR1, in psychosis cases versus controls; for AKT1, as a pre-existing methylation pattern influencing brain activation following acute administration of a psychosis-eliciting environmental stimulus; and for TDO2, in a pattern associated with a developmental factor of risk for psychosis, in all cases the predicted expression impact being highly dependent on location. Methylation induced by smoking, a confounding variable, exhibits an intriguing pattern for all three genes. Finally, how differential methylation meshes with Darwinian principles is examined, in particular as it relates to the "flexible stem" theory of evolution.
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Pérez-Aldana BE, Martínez-Magaña JJ, Mayén-Lobo YG, Dávila-Ortiz de Montellano DJ, Aviña-Cervantes CL, Ortega-Vázquez A, Genis-Mendoza AD, Sarmiento E, Soto-Reyes E, Juárez-Rojop IE, Tovilla-Zarate CA, González-Castro TB, Nicolini H, López-López M, Monroy-Jaramillo N. Clozapine Long-Term Treatment Might Reduce Epigenetic Age Through Hypomethylation of Longevity Regulatory Pathways Genes. Front Psychiatry 2022; 13:870656. [PMID: 35664466 PMCID: PMC9157596 DOI: 10.3389/fpsyt.2022.870656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 03/29/2022] [Indexed: 11/13/2022] Open
Abstract
Long-term studies have shown significantly lower mortality rates in patients with continuous clozapine (CLZ) treatment than other antipsychotics. We aimed to evaluate epigenetic age and DNA methylome differences between CLZ-treated patients and those without psychopharmacological treatment. The DNA methylome was analyzed using the Infinium MethylationEPIC BeadChip in 31 CLZ-treated patients with psychotic disorders and 56 patients with psychiatric disorders naive to psychopharmacological treatment. Delta age (Δage) was calculated as the difference between predicted epigenetic age and chronological age. CLZ-treated patients were stratified by sex, age, and years of treatment. Differential methylation sites between both groups were determined using linear regression models. The Δage in CLZ-treated patients was on average lower compared with drug-naive patients for the three clocks analyzed; however, after data-stratification, this difference remained only in male patients. Additional differences were observed in Hannum and Horvath clocks when comparing chronological age and years of CLZ treatment. We identified 44,716 differentially methylated sites, of which 87.7% were hypomethylated in CLZ-treated patients, and enriched in the longevity pathway genes. Moreover, by protein-protein interaction, AMPK and insulin signaling pathways were found enriched. CLZ could promote a lower Δage in individuals with long-term treatment and modify the DNA methylome of the longevity-regulating pathways genes.
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Affiliation(s)
| | - José Jaime Martínez-Magaña
- Laboratorio de Genómica de Enfermedades Psiquiátricas y Neurodegenerativas, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Yerye Gibrán Mayén-Lobo
- Departamento de Sistemas Biológicos, Universidad Autónoma Metropolitana, Mexico City, Mexico
| | | | - Carlos Luis Aviña-Cervantes
- Departamento de Psiquiatría, Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suárez, Mexico City, Mexico
| | - Alberto Ortega-Vázquez
- Departamento de Sistemas Biológicos, Universidad Autónoma Metropolitana, Mexico City, Mexico
| | - Alma Delia Genis-Mendoza
- Laboratorio de Genómica de Enfermedades Psiquiátricas y Neurodegenerativas, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Emmanuel Sarmiento
- Dirección General, Hospital Psiquiátrico Infantil Juan N Navarro, Mexico City, Mexico
| | - Ernesto Soto-Reyes
- Departamento de Ciencias Naturales, Universidad Autónoma Metropolitana, Unidad Cuajimalpa, Mexico City, Mexico
| | - Isela Esther Juárez-Rojop
- División Académica de Ciencias de la Salud, Universidad Juárez Autónoma de Tabasco, Villahermosa, Mexico
| | | | - Thelma Beatriz González-Castro
- División Académica Multidisciplinaria de Jalpa de Méndez, Universidad Juárez Autónoma de Tabasco, Jalpa de Méndez, Mexico
| | - Humberto Nicolini
- Laboratorio de Genómica de Enfermedades Psiquiátricas y Neurodegenerativas, Instituto Nacional de Medicina Genómica, Mexico City, Mexico.,Grupo de Estudios Médicos y Familiares Carracci, Mexico City, Mexico
| | - Marisol López-López
- Departamento de Sistemas Biológicos, Universidad Autónoma Metropolitana, Mexico City, Mexico
| | - Nancy Monroy-Jaramillo
- Departamento de Genética, Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suárez, Mexico City, Mexico
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Iftimovici A, Kebir O, Jiao C, He Q, Krebs MO, Chaumette B. Dysmaturational Longitudinal Epigenetic Aging During Transition to Psychosis. SCHIZOPHRENIA BULLETIN OPEN 2022; 3:sgac030. [PMID: 39144766 PMCID: PMC11206049 DOI: 10.1093/schizbullopen/sgac030] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/16/2024]
Abstract
Psychosis frequently occurs during adolescence and young adulthood, possibly as a result of gene-environment interactions, mediated by epigenetic mechanisms such as DNA methylation. Methylation patterns can be leveraged to predict epigenetic age in order to identify anomalies in aging trajectories that may be associated with the emergence of psychosis. Thus, epigenetic age may provide a measurable surrogate of psychotic risk or psychosis' emergence, and shed light on the neurodevelopmental model of psychosis. In this study, we present the first longitudinal analysis of epigenetic age trajectory during conversion to psychosis in a population at ultra-high-risk, with available genome-wide methylation DNA at two time points, at baseline and after one year of follow-up (N = 38 × 2). After predicting epigenetic age, we computed epigenetic age gap as the cross-sectional difference between real age and predicted age, and (longitudinal) epigenetic age acceleration as the derivative of predicted age with respect to time. At baseline, future converters were 2.7 years younger than nonconverters and this difference disappeared at follow-up, when some converted to psychosis. This is because during conversion to psychosis, the epigenetic age of converters accelerated by 2.8 years/year compared to nonconverters. This acceleration was robust with a strictly positive 95% confidence interval, and held its significance after adjustment for age, sex, and cannabis intake. The methylation sites most associated with aging were on genes also linked with schizophrenia and neurodevelopmental disorders. This accelerated age trajectory, following a previous deceleration, may therefore reflect dysmaturational processes.
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Affiliation(s)
- Anton Iftimovici
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, GDR 3557-Institut de Psychiatrie, Pathophysiology of psychiatric disorders, Paris, France
- NeuroSpin, Atomic Energy Commission, Gif-sur Yvette, France
| | - Oussama Kebir
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, GDR 3557-Institut de Psychiatrie, Pathophysiology of psychiatric disorders, Paris, France
- GHU Paris Psychiatrie et Neurosciences, Pôle PEPIT, Paris, France
| | - Chuan Jiao
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, GDR 3557-Institut de Psychiatrie, Pathophysiology of psychiatric disorders, Paris, France
| | - Qin He
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, GDR 3557-Institut de Psychiatrie, Pathophysiology of psychiatric disorders, Paris, France
| | - Marie-Odile Krebs
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, GDR 3557-Institut de Psychiatrie, Pathophysiology of psychiatric disorders, Paris, France
- GHU Paris Psychiatrie et Neurosciences, Pôle PEPIT, Paris, France
| | - Boris Chaumette
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, GDR 3557-Institut de Psychiatrie, Pathophysiology of psychiatric disorders, Paris, France
- GHU Paris Psychiatrie et Neurosciences, Pôle PEPIT, Paris, France
- Department of Psychiatry, McGill University, Montréal, Québec, Canada
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50
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Berdenis van Berlekom A, Notman N, Sneeboer MAM, Snijders GJLJ, Houtepen LC, Nispeling DM, He Y, Dracheva S, Hol EM, Kahn RS, de Witte LD, Boks MP. DNA methylation differences in cortical grey and white matter in schizophrenia. Epigenomics 2021; 13:1157-1169. [PMID: 34323598 PMCID: PMC8386513 DOI: 10.2217/epi-2021-0077] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 07/09/2021] [Indexed: 01/27/2023] Open
Abstract
Aim: Identify grey- and white-matter-specific DNA-methylation differences between schizophrenia (SCZ) patients and controls in postmortem brain cortical tissue. Materials & methods: Grey and white matter were separated from postmortem brain tissue of the superior temporal and medial frontal gyrus from SCZ (n = 10) and control (n = 11) cases. Genome-wide DNA-methylation analysis was performed using the Infinium EPIC Methylation Array (Illumina, CA, USA). Results: Four differentially methylated regions associated with SCZ status and tissue type (grey vs white matter) were identified within or near KLF9, SFXN1, SPRED2 and ALS2CL genes. Gene-expression analysis showed differential expression of KLF9 and SFXN1 in SCZ. Conclusion: Our data show distinct differences in DNA methylation between grey and white matter that are unique to SCZ, providing new leads to unravel the pathogenesis of SCZ.
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Affiliation(s)
- Amber Berdenis van Berlekom
- Department of Psychiatry, Brain Center University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Department of Translational Neuroscience, Brain Center University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Nina Notman
- Department of Psychiatry, Brain Center University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Marjolein AM Sneeboer
- Department of Psychiatry, Brain Center University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Department of Translational Neuroscience, Brain Center University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Gijsje JLJ Snijders
- Department of Psychiatry, Brain Center University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Lotte C Houtepen
- Department of Psychiatry, Brain Center University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Danny M Nispeling
- Department of Psychiatry, Brain Center University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Yujie He
- Department of Psychiatry, Brain Center University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Department of Translational Neuroscience, Brain Center University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | | | - Stella Dracheva
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mental Illness Research, Education, & Clinical Center (VISN 2 South), James J Peters VA Medical Center, Bronx, NY, 10468, USA
| | - Elly M Hol
- Department of Translational Neuroscience, Brain Center University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - René S Kahn
- Department of Psychiatry, Brain Center University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mental Illness Research, Education, & Clinical Center (VISN 2 South), James J Peters VA Medical Center, Bronx, NY, 10468, USA
| | - Lot D de Witte
- Department of Psychiatry, Brain Center University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Marco P Boks
- Department of Psychiatry, Brain Center University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
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