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Shboul M, Bani Domi A, Abu Zahra A, Khasawneh AG, Darweesh R. Plasma miRNAs as potential biomarkers for schizophrenia in a Jordanian cohort. Noncoding RNA Res 2024; 9:350-358. [PMID: 38511065 PMCID: PMC10950580 DOI: 10.1016/j.ncrna.2024.01.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 01/15/2024] [Accepted: 01/30/2024] [Indexed: 03/22/2024] Open
Abstract
Background Schizophrenia (SZ), a complex and chronic neuropsychiatric disorder affecting approximately 1 % of the general population, presents diagnostic challenges due to the absence of reliable biomarkers, and relying mainly on clinical observations. MicroRNAs (miRNAs) signatures in a wide range of diseases, including psychiatric disorders, hold immense potential for serving as biomarkers. This study aimed to analyze the expression levels of specific microRNAs (miRNAs) namely miR-29b-3p, miR-106b-5p, and miR-199a-3p and explore their diagnostic potential for SZ in Jordanian patients. Methods Small RNAs (miRNAs) were extracted from plasma samples of 30 SZ patients and 35 healthy controls. RNA was reverse transcribed and quantified by real-time polymerase chain reaction (qRT-PCR). The expression levels of three miRNAs (miR-29b-3p, miR-106b-5p and miR-199a-3p) were analyzed. Receiver operating characteristic (ROC) curves analysis was performed to evaluate diagnostic value of these miRNAs. Target genes prediction, functional enrichment and pathway analyses were done using miRWalk and Metascape. STRING database was used to construct protein-protein network and identify hub genes. Results Notably, miR-106b-5p and miR-199a-3p were significantly upregulated (p < 0.0001), while miRNA-29b-3p was downregulated (p < 0.0001) in SZ patients compared to controls. The diagnostic potential was assessed through ROC curves, revealing substantial diagnostic value for miR-199a-3p (AUC: 0.979) followed by miR-106b-5p (AUC: 0.774), with limited diagnostic efficacy for miR-29b-3p. Additionally, bioinformatic analyses for the predicted target genes of the diagnostically significant miRNAs uncovered Gene Ontology (GO) terms related to neurological development, including morphogenesis, which is involved in neuron differentiation, brain development, head development, and neuron projection morphogenesis. These findings highlight a potential connection between the identified miRNAs and SZ pathophysiology in the studied Jordanian population. Furthermore, a protein-protein interaction network from the target genes identified in association with neurological development in the Gene Ontology (GO) terms deepens our comprehension of the molecular landscape of the regulated target genes. Conclusions This comprehensive exploration highlights the promising role of miRNAs in unraveling intricate molecular pathways associated with SZ in the Jordanian cohort and suggests that plasma miRNAs could serve as reliable biomarkers for SZ diagnosis and disease progression. Remarkably, this study represents the first investigation into the role of circulating miRNA expression among Jordanian patients with SZ, providing valuable insights into the diagnostic landscape of this disorder.
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Affiliation(s)
- Mohammad Shboul
- Department of Medical Laboratory Sciences, Faculty of Medical Sciences, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan
| | - Amal Bani Domi
- Department of Medical Laboratory Sciences, Faculty of Medical Sciences, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan
| | - Abdulmalek Abu Zahra
- Department of Medical Laboratory Sciences, Faculty of Medical Sciences, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan
| | - Aws G. Khasawneh
- Department of Neurosciences, Faculty of Medicine, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan
| | - Reem Darweesh
- Department of Medical Laboratory Sciences, Faculty of Medical Sciences, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan
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2
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Quinn TP, Hess JL, Marshe VS, Barnett MM, Hauschild AC, Maciukiewicz M, Elsheikh SSM, Men X, Schwarz E, Trakadis YJ, Breen MS, Barnett EJ, Zhang-James Y, Ahsen ME, Cao H, Chen J, Hou J, Salekin A, Lin PI, Nicodemus KK, Meyer-Lindenberg A, Bichindaritz I, Faraone SV, Cairns MJ, Pandey G, Müller DJ, Glatt SJ. A primer on the use of machine learning to distil knowledge from data in biological psychiatry. Mol Psychiatry 2024; 29:387-401. [PMID: 38177352 PMCID: PMC11228968 DOI: 10.1038/s41380-023-02334-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 09/21/2023] [Accepted: 11/17/2023] [Indexed: 01/06/2024]
Abstract
Applications of machine learning in the biomedical sciences are growing rapidly. This growth has been spurred by diverse cross-institutional and interdisciplinary collaborations, public availability of large datasets, an increase in the accessibility of analytic routines, and the availability of powerful computing resources. With this increased access and exposure to machine learning comes a responsibility for education and a deeper understanding of its bases and bounds, borne equally by data scientists seeking to ply their analytic wares in medical research and by biomedical scientists seeking to harness such methods to glean knowledge from data. This article provides an accessible and critical review of machine learning for a biomedically informed audience, as well as its applications in psychiatry. The review covers definitions and expositions of commonly used machine learning methods, and historical trends of their use in psychiatry. We also provide a set of standards, namely Guidelines for REporting Machine Learning Investigations in Neuropsychiatry (GREMLIN), for designing and reporting studies that use machine learning as a primary data-analysis approach. Lastly, we propose the establishment of the Machine Learning in Psychiatry (MLPsych) Consortium, enumerate its objectives, and identify areas of opportunity for future applications of machine learning in biological psychiatry. This review serves as a cautiously optimistic primer on machine learning for those on the precipice as they prepare to dive into the field, either as methodological practitioners or well-informed consumers.
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Affiliation(s)
- Thomas P Quinn
- Applied Artificial Intelligence Institute (A2I2), Burwood, VIC, 3125, Australia
| | - Jonathan L Hess
- Department of Psychiatry and Behavioral Sciences, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, 13210, USA
| | - Victoria S Marshe
- Institute of Medical Science, University of Toronto, Toronto, ON, M5S 1A1, Canada
- Pharmacogenetics Research Clinic, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, M5S 1A1, Canada
| | - Michelle M Barnett
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, 2308, Australia
- Precision Medicine Research Program, Hunter Medical Research Institute, Newcastle, NSW, 2308, Australia
| | - Anne-Christin Hauschild
- Department of Medical Informatics, Medical University Center Göttingen, Göttingen, Lower Saxony, 37075, Germany
| | - Malgorzata Maciukiewicz
- Hospital Zurich, University of Zurich, Zurich, 8091, Switzerland
- Department of Rheumatology and Immunology, University Hospital Bern, Bern, 3010, Switzerland
- Department for Biomedical Research (DBMR), University of Bern, Bern, 3010, Switzerland
| | - Samar S M Elsheikh
- Pharmacogenetics Research Clinic, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, M5S 1A1, Canada
| | - Xiaoyu Men
- Pharmacogenetics Research Clinic, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, M5S 1A1, Canada
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, M5S 1A1, Canada
| | - Emanuel Schwarz
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Baden-Württemberg, J5 68159, Germany
| | - Yannis J Trakadis
- Department Human Genetics, McGill University Health Centre, Montreal, QC, H4A 3J1, Canada
| | - Michael S Breen
- Psychiatry, Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Eric J Barnett
- Department of Neuroscience and Physiology, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, 13210, USA
| | - Yanli Zhang-James
- Department of Psychiatry and Behavioral Sciences, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, 13210, USA
| | - Mehmet Eren Ahsen
- Department of Business Administration, Gies College of Business, University of Illinois at Urbana-Champaign, Champaign, IL, 61820, USA
- Department of Biomedical and Translational Sciences, Carle-Illinois School of Medicine, University of Illinois at Urbana-Champaign, Champaign, IL, 61820, USA
| | - Han Cao
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Baden-Württemberg, J5 68159, Germany
| | - Junfang Chen
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Baden-Württemberg, J5 68159, Germany
| | - Jiahui Hou
- Department of Psychiatry and Behavioral Sciences, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, 13210, USA
- Department of Neuroscience and Physiology, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, 13210, USA
| | - Asif Salekin
- Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, 13244, USA
| | - Ping-I Lin
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, 2052, Australia
- Mental Health Research Unit, South Western Sydney Local Health District, Liverpool, NSW, 2170, Australia
| | | | - Andreas Meyer-Lindenberg
- Clinical Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Baden-Württemberg, J5 68159, Germany
| | - Isabelle Bichindaritz
- Biomedical and Health Informatics/Computer Science Department, State University of New York at Oswego, Oswego, NY, 13126, USA
- Intelligent Bio Systems Lab, State University of New York at Oswego, Oswego, NY, 13126, USA
| | - Stephen V Faraone
- Department of Psychiatry and Behavioral Sciences, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, 13210, USA
- Department of Neuroscience and Physiology, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, 13210, USA
| | - Murray J Cairns
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, 2308, Australia
- Precision Medicine Research Program, Hunter Medical Research Institute, Newcastle, NSW, 2308, Australia
| | - Gaurav Pandey
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Daniel J Müller
- Pharmacogenetics Research Clinic, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, M5S 1A1, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, M5S 1A1, Canada
- Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, University Hospital of Würzburg, Würzburg, 97080, Germany
| | - Stephen J Glatt
- Department of Psychiatry and Behavioral Sciences, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, 13210, USA.
- Department of Neuroscience and Physiology, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, 13210, USA.
- Department of Public Health and Preventive Medicine, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, 13210, USA.
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Lee J, Xue X, Au E, McIntyre WB, Asgariroozbehani R, Panganiban K, Tseng GC, Papoulias M, Smith E, Monteiro J, Shah D, Maksyutynska K, Cavalier S, Radoncic E, Prasad F, Agarwal SM, Mccullumsmith R, Freyberg Z, Logan RW, Hahn MK. Glucose dysregulation in antipsychotic-naive first-episode psychosis: in silico exploration of gene expression signatures. Transl Psychiatry 2024; 14:19. [PMID: 38199991 PMCID: PMC10781725 DOI: 10.1038/s41398-023-02716-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 12/10/2023] [Accepted: 12/14/2023] [Indexed: 01/12/2024] Open
Abstract
Antipsychotic (AP)-naive first-episode psychosis (FEP) patients display early dysglycemia, including insulin resistance and prediabetes. Metabolic dysregulation may therefore be intrinsic to psychosis spectrum disorders (PSDs), independent of the metabolic effects of APs. However, the potential biological pathways that overlap between PSDs and dysglycemic states remain to be identified. Using meta-analytic approaches of transcriptomic datasets, we investigated whether AP-naive FEP patients share overlapping gene expression signatures with non-psychiatrically ill early dysglycemia individuals. We meta-analyzed peripheral transcriptomic datasets of AP-naive FEP patients and non-psychiatrically ill early dysglycemia subjects to identify common gene expression signatures. Common signatures underwent pathway enrichment analysis and were then used to identify potential new pharmacological compounds via Integrative Library of Integrated Network-Based Cellular Signatures (iLINCS). Our search results yielded 5 AP-naive FEP studies and 4 early dysglycemia studies which met inclusion criteria. We discovered that AP-naive FEP and non-psychiatrically ill subjects exhibiting early dysglycemia shared 221 common signatures, which were enriched for pathways related to endoplasmic reticulum stress and abnormal brain energetics. Nine FDA-approved drugs were identified as potential drug treatments, of which the antidiabetic metformin, the first-line treatment for type 2 diabetes, has evidence to attenuate metabolic dysfunction in PSDs. Taken together, our findings support shared gene expression changes and biological pathways associating PSDs with dysglycemic disorders. These data suggest that the pathobiology of PSDs overlaps and potentially contributes to dysglycemia. Finally, we find that metformin may be a potential treatment for early metabolic dysfunction intrinsic to PSDs.
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Grants
- R01 DK124219 NIDDK NIH HHS
- R01 HL150432 NHLBI NIH HHS
- R01 MH107487 NIMH NIH HHS
- R01 MH121102 NIMH NIH HHS
- Holds the Meighen Family Chair in Psychosis Prevention, the Cardy Schizophrenia Research Chair, a Danish Diabetes Academy Professorship, a Steno Diabetes Center Fellowship, and a U of T Academic Scholar Award, and is funded by operating grants from the Canadian Institutes of Health Research (CIHR), the Banting and Best Diabetes Center, the Miners Lamp U of T award, CIHR and Canadian Psychiatric Association Glenda MacQueen Memorial Award, and the PSI Foundation.
- Hilda and William Courtney Clayton Paediatric Research Fund and Dr. LG Rao/Industrial Partners Graduate Student Award from the University of Toronto, and Meighen Family Chair in Psychosis Prevention
- U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- UofT | Banting and Best Diabetes Centre, University of Toronto (BBDC)
- Canadian Institutes of Health Research (CIHR) Canada Graduate Scholarship-Master’s program
- Cleghorn Award
- University of Toronto (UofT)
- Centre for Addiction and Mental Health (Centre de Toxicomanie et de Santé Mentale)
- U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
- U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes & Digestive & Kidney Diseases)
- U.S. Department of Defense (United States Department of Defense)
- Commonwealth of Pennsylvania Formula Fund, The Pittsburgh Foundation
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Affiliation(s)
- Jiwon Lee
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Xiangning Xue
- Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Emily Au
- Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada
| | - William B McIntyre
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Roshanak Asgariroozbehani
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Kristoffer Panganiban
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - George C Tseng
- Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Emily Smith
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Centre for Addiction and Mental Health, Toronto, ON, Canada
| | | | - Divia Shah
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Kateryna Maksyutynska
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Samantha Cavalier
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Emril Radoncic
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Femin Prasad
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Sri Mahavir Agarwal
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Robert Mccullumsmith
- Department of Neurosciences, University of Toledo, Toledo, OH, USA
- ProMedica, Toledo, OH, USA
| | - Zachary Freyberg
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ryan W Logan
- Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Department of Psychiatry, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Department of Pharmacology, Physiology & Biophysics, Boston University School of Medicine, Boston, MA, USA
| | - Margaret K Hahn
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada.
- Centre for Addiction and Mental Health, Toronto, ON, Canada.
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
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4
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Lee J, Xue X, Au E, McIntyre WB, Asgariroozbehani R, Tseng GC, Papoulias M, Panganiban K, Agarwal SM, Mccullumsmith R, Freyberg Z, Logan RW, Hahn MK. Central insulin dysregulation in antipsychotic-naïve first-episode psychosis: In silico exploration of gene expression signatures. Psychiatry Res 2024; 331:115636. [PMID: 38104424 PMCID: PMC10984627 DOI: 10.1016/j.psychres.2023.115636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 10/18/2023] [Accepted: 11/25/2023] [Indexed: 12/19/2023]
Abstract
Antipsychotic drug (AP)-naïve first-episode psychosis (FEP) patients display premorbid cognitive dysfunctions and dysglycemia. Brain insulin resistance may link metabolic and cognitive disorders in humans. This suggests that central insulin dysregulation represents a component of the pathophysiology of psychosis spectrum disorders (PSDs). Nonetheless, the links between central insulin dysregulation, dysglycemia, and cognitive deficits in PSDs are poorly understood. We investigated whether AP-naïve FEP patients share overlapping brain gene expression signatures with central insulin perturbation (CIP) in rodent models. We systematically compiled and meta-analyzed peripheral transcriptomic datasets of AP-naïve FEP patients along with hypothalamic and hippocampal datasets of CIP rodent models to identify common transcriptomic signatures. The common signatures were used for pathway analysis and to identify potential drug treatments with discordant (reverse) signatures. AP-naïve FEP and CIP (hypothalamus and hippocampus) shared 111 and 346 common signatures respectively, which were associated with pathways related to inflammation, endoplasmic reticulum stress, and neuroplasticity. Twenty-two potential drug treatments were identified, including antidiabetic agents. The pathobiology of PSDs may include central insulin dysregulation, which contribute to dysglycemia and cognitive dysfunction independently of AP treatment. The identified treatments may be tested in early psychosis patients to determine if dysglycemia and cognitive deficits can be mitigated.
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Affiliation(s)
- Jiwon Lee
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.
| | - Xiangning Xue
- Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States.
| | - Emily Au
- Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Pharmacology and Toxicology, University of Toronto, Toronto, Ontario, Canada.
| | - William B McIntyre
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.
| | - Roshanak Asgariroozbehani
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.
| | - George C Tseng
- Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States.
| | - Maria Papoulias
- Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.
| | - Kristoffer Panganiban
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.
| | - Sri Mahavir Agarwal
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.
| | - Robert Mccullumsmith
- Department of Neurosciences, University of Toledo, Toledo, Ohio, United States; ProMedica, Toledo, Ohio, United States.
| | - Zachary Freyberg
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, United States; Department of Cell Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States.
| | - Ryan W Logan
- Department of Psychiatry, University of Massachusetts Chan Medical School, Worcester, Massachusetts, United States; Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, Massachusetts, United States.
| | - Margaret K Hahn
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.
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5
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Fiorito AM, Fakra E, Sescousse G, Ibrahim EC, Rey R. Molecular mapping of a core transcriptional signature of microglia-specific genes in schizophrenia. Transl Psychiatry 2023; 13:386. [PMID: 38092734 PMCID: PMC10719376 DOI: 10.1038/s41398-023-02677-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 11/20/2023] [Accepted: 11/22/2023] [Indexed: 12/17/2023] Open
Abstract
Besides playing a central role in neuroinflammation, microglia regulate synaptic development and is involved in plasticity. Converging lines of evidence suggest that these different processes play a critical role in schizophrenia. Furthermore, previous studies reported altered transcription of microglia genes in schizophrenia, while microglia itself seems to be involved in the etiopathology of the disease. However, the regional specificity of these brain transcriptional abnormalities remains unclear. Moreover, it is unknown whether brain and peripheral expression of microglia genes are related. Thus, we investigated the expression of a pre-registered list of 10 genes from a core signature of human microglia both at brain and peripheral levels. We included 9 independent Gene Expression Omnibus datasets (764 samples obtained from 266 individuals with schizophrenia and 237 healthy controls) from 8 different brain regions and 3 peripheral tissues. We report evidence of a widespread transcriptional alteration of microglia genes both in brain tissues (we observed a decreased expression in the cerebellum, associative striatum, hippocampus, and parietal cortex of individuals with schizophrenia compared with healthy controls) and whole blood (characterized by a mixed altered expression pattern). Our results suggest that brain underexpression of microglia genes may represent a candidate transcriptional signature for schizophrenia. Moreover, the dual brain-whole blood transcriptional alterations of microglia/macrophage genes identified support the model of schizophrenia as a whole-body disorder and lend weight to the use of blood samples as a potential source of biological peripheral biomarkers.
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Affiliation(s)
- Anna M Fiorito
- Lyon Neuroscience Research Center, INSERM U1028, CNRS UMR 5292, PSYR2 Team, University of Lyon, Lyon, France
- Centre Hospitalier Le Vinatier, Bron, France
| | - Eric Fakra
- Lyon Neuroscience Research Center, INSERM U1028, CNRS UMR 5292, PSYR2 Team, University of Lyon, Lyon, France
- Department of Psychiatry, University Hospital of Saint-Etienne, Saint-Etienne, France
| | - Guillaume Sescousse
- Lyon Neuroscience Research Center, INSERM U1028, CNRS UMR 5292, PSYR2 Team, University of Lyon, Lyon, France
- Centre Hospitalier Le Vinatier, Bron, France
| | - El Chérif Ibrahim
- Aix-Marseille Univ, CNRS, INT, Institut de Neurosciences de la Timone, Marseille, France
| | - Romain Rey
- Lyon Neuroscience Research Center, INSERM U1028, CNRS UMR 5292, PSYR2 Team, University of Lyon, Lyon, France.
- Centre Hospitalier Le Vinatier, Bron, France.
- Fondation FondaMental, Créteil, France.
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6
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Mekiten O, Yitzhaky A, Gould N, Rosenblum K, Hertzberg L. Ribosome subunits are upregulated in brain samples of a subgroup of individuals with schizophrenia: A systematic gene expression meta-analysis. J Psychiatr Res 2023; 164:372-381. [PMID: 37413782 DOI: 10.1016/j.jpsychires.2023.06.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 06/05/2023] [Accepted: 06/15/2023] [Indexed: 07/08/2023]
Abstract
One of the new theories accounting for the underlying pathophysiology of schizophrenia is excitation/inhibition imbalance. Interestingly, perturbation in protein synthesis machinery as well as oxidative stress can lead to excitation/inhibition imbalance. We thus performed a systematic meta-analysis of the expression of 79 ribosome subunit genes and two oxidative-stress related genes, HIF1A and NQO1, in brain samples of individuals with schizophrenia vs. healthy controls. We integrated 12 gene expression datasets, following the PRISMA guidelines (overall 511 samples, 253 schizophrenia and 258 controls). Five ribosome subunit genes were significantly upregulated in a subgroup of the patients with schizophrenia, while 24 (30%) showed a tendency for upregulation. HIF1A and NQO1 were also found to be significantly upregulated. Moreover, HIF1A and NQO1 showed positive correlation with the expression of the upregulated ribosome subunit genes. Our results, together with previous findings, suggest a possible role for altered mRNA translation in the pathogenesis of schizophrenia, in association with markers of increased oxidative stress in a subgroup of patients. Further studies should define whether the upregulation of ribosome subunits result in altered mRNA translation, which proteins are modulated and how it characterizes a subgroup of the patients with schizophrenia.
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Affiliation(s)
- Ori Mekiten
- Faculty of Medicine, Tel-Aviv University, Israel
| | - Assif Yitzhaky
- Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel
| | - Nathaniel Gould
- Sagol Department of Neurobiology, University of Haifa, Haifa, Israel
| | - Kobi Rosenblum
- Sagol Department of Neurobiology, University of Haifa, Haifa, Israel; Center for Gene Manipulation in the Brain, University of Haifa, Haifa, Israel
| | - Libi Hertzberg
- Faculty of Medicine, Tel-Aviv University, Israel; Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel; Shalvata Mental Health Center, Israel.
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7
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Yang J, Long Q, Zhang Y, Liu Y, Wu J, Zhao X, You X, Li X, Liu J, Teng Z, Zeng Y, Luo XJ. Whole transcriptome analysis reveals dysregulation of molecular networks in schizophrenia. Asian J Psychiatr 2023; 85:103649. [PMID: 37267675 DOI: 10.1016/j.ajp.2023.103649] [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: 03/09/2023] [Revised: 05/18/2023] [Accepted: 05/22/2023] [Indexed: 06/04/2023]
Abstract
To characterize the regulatory relationships between different types of transcripts and the altered molecular networks in schizophrenia (SCZ), we performed a whole transcriptome study by quantifying mRNAs, long noncoding RNAs (lncRNAs), miRNAs, and circular RNAs (circRNAs) in the same individuals simultaneously. A total of 807 dysregulated genes showed differential expression in SCZ cases compared with controls. Network-based analysis revealed dysregulation of molecular networks in SCZ. Finally, integration of the transcriptome data with published data identified promising SCZ candidate genes. Our study reveals that dysregulated molecular networks and regulatory relationships between different types of transcript may have a role in SCZ.
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Affiliation(s)
- Jinfeng Yang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan 650204, China
| | - Qing Long
- The Second Affiliated Hospital, Kunming Medical University, Kunming, Yunnan 650101, China
| | - Yunqiao Zhang
- The Second Affiliated Hospital, Kunming Medical University, Kunming, Yunnan 650101, China; Honghe Second People's Hospital, Honghe, Yunnan 654399, China; The Sixth Affiliated Hospital, Kunming Medical University, Yuxi, Yunnan 653100, China
| | - Yilin Liu
- The Second Affiliated Hospital, Kunming Medical University, Kunming, Yunnan 650101, China
| | - Jie Wu
- The Affiliated Mental Health Center, Kunming Medical University, Kunming, Yunnan 650224, China
| | - Xinling Zhao
- The Second Affiliated Hospital, Kunming Medical University, Kunming, Yunnan 650101, China
| | - Xu You
- Honghe Second People's Hospital, Honghe, Yunnan 654399, China
| | - Xiaoyan Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
| | - Jiewei Liu
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
| | - Zhaowei Teng
- The Second Affiliated Hospital, Kunming Medical University, Kunming, Yunnan 650101, China.
| | - Yong Zeng
- The Second Affiliated Hospital, Kunming Medical University, Kunming, Yunnan 650101, China.
| | - Xiong-Jian Luo
- Zhongda Hospital, School of Medicine, Advanced Institute for Life and Health, Southeast University, Nanjing 210096, China; Department of Neurology, Zhongda Hospital, School of Medicine, Advanced Institute for Life and Health, Southeast University, Nanjing, China.
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8
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Gu X, Chen A, You M, Guo H, Tan S, He Q, Hu B. Extracellular vesicles: a new communication paradigm of complement in neurological diseases. Brain Res Bull 2023; 199:110667. [PMID: 37192717 DOI: 10.1016/j.brainresbull.2023.110667] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Revised: 03/25/2023] [Accepted: 05/13/2023] [Indexed: 05/18/2023]
Abstract
The complement system is crucial to the innate immune system. It has the function of destroying pathogens by activating the classical, alternative, and lectin pathways. The complement system is important in nervous system diseases such as cerebrovascular and neurodegenerative diseases. Activation of the complement system involves a series of intercellular signaling and cascade reactions. However, research on the source and transport mechanisms of the complement system in neurological diseases is still in its infancy. Studies have increasingly found that extracellular vesicles (EVs), a classic intercellular communication paradigm, may play a role in complement signaling disorders. Here, we systematically review the EV-mediated activation of complement pathways in different neurological diseases. We also discuss the prospect of EVs as future immunotherapy targets.
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Affiliation(s)
- Xinmei Gu
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022
| | - Anqi Chen
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022
| | - Mingfeng You
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022
| | - Hongxiu Guo
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022
| | - Senwei Tan
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022
| | - Quanwei He
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022.
| | - Bo Hu
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022.
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9
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Torsvik A, Brattbakk HR, Trentani A, Holdhus R, Stansberg C, Bartz-Johannessen CA, Hughes T, Steen NE, Melle I, Djurovic S, Andreassen OA, Steen VM. Patients with schizophrenia and bipolar disorder display a similar global gene expression signature in whole blood that reflects elevated proportion of immature neutrophil cells with association to lipid changes. Transl Psychiatry 2023; 13:147. [PMID: 37147304 PMCID: PMC10163263 DOI: 10.1038/s41398-023-02442-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 04/20/2023] [Indexed: 05/07/2023] Open
Abstract
Schizophrenia (SCZ) and bipolar disorder (BD) share clinical characteristics, genetic susceptibility, and immune alterations. We aimed to identify differential transcriptional patterns in peripheral blood cells of patients with SCZ or BD versus healthy controls (HC). We analyzed microarray-based global gene expression data in whole blood from a cohort of SCZ (N = 329), BD (N = 203) and HC (N = 189). In total, 65 genes were significantly differentially expressed in SCZ and 125 in BD, as compared to HC, with similar ratio of up- and downregulated genes in both disorders. Among the top differentially expressed genes, we found an innate immunity signature that was shared between SCZ and BD, consisting of a cluster of upregulated genes (e.g., OLFM4, ELANE, BPI and MPO) that indicate an increased fraction of immature neutrophils. Several of these genes displayed sex differences in the expression pattern, and post-hoc analysis demonstrated a positive correlation with triglyceride and a negative correlation with HDL cholesterol. We found that many of the downregulated genes in SCZ and BD were associated with smoking. These findings of neutrophil granulocyte-associated transcriptome signatures in both SCZ and BD point at altered innate immunity pathways with association to lipid changes and potential for clinical translation.
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Affiliation(s)
- 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.
| | - Hans-Richard Brattbakk
- 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
| | - Andrea Trentani
- 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
| | - Rita Holdhus
- 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
| | - Christine Stansberg
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
| | | | - Timothy Hughes
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Nils Eiel Steen
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Ingrid Melle
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Srdjan Djurovic
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, 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
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10
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Hess JL, Quinn TP, Zhang C, Hearn GC, Chen S, Kong SW, Cairns M, Tsuang MT, Faraone SV, Glatt SJ. BrainGENIE: The Brain Gene Expression and Network Imputation Engine. Transl Psychiatry 2023; 13:98. [PMID: 36949060 PMCID: PMC10033657 DOI: 10.1038/s41398-023-02390-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 02/23/2023] [Accepted: 02/28/2023] [Indexed: 03/24/2023] Open
Abstract
In vivo experimental analysis of human brain tissue poses substantial challenges and ethical concerns. To address this problem, we developed a computational method called the Brain Gene Expression and Network-Imputation Engine (BrainGENIE) that leverages peripheral-blood transcriptomes to predict brain tissue-specific gene-expression levels. Paired blood-brain transcriptomic data collected by the Genotype-Tissue Expression (GTEx) Project was used to train BrainGENIE models to predict gene-expression levels in ten distinct brain regions using whole-blood gene-expression profiles. The performance of BrainGENIE was compared to PrediXcan, a popular method for imputing gene expression levels from genotypes. BrainGENIE significantly predicted brain tissue-specific expression levels for 2947-11,816 genes (false-discovery rate-adjusted p < 0.05), including many transcripts that cannot be predicted significantly by a transcriptome-imputation method such as PrediXcan. BrainGENIE recapitulated measured diagnosis-related gene-expression changes in the brain for autism, bipolar disorder, and schizophrenia better than direct correlations from blood and predictions from PrediXcan. We developed a convenient software toolset for deploying BrainGENIE, and provide recommendations for how best to implement models. BrainGENIE complements and, in some ways, outperforms existing transcriptome-imputation tools, providing biologically meaningful predictions and opening new research avenues.
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Affiliation(s)
- Jonathan L Hess
- Department of Psychiatry & Behavioral Sciences, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, USA
| | - Thomas P Quinn
- Applied Artificial Intelligence Institute (A2I2), Deakin University, Geelong, Australia
| | - Chunling Zhang
- Department of Neuroscience & Physiology, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, USA
| | - Gentry C Hearn
- Department of Neuroscience & Physiology, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, USA
| | - Samuel Chen
- Department of Psychiatry & Behavioral Sciences, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, USA
| | - Sek Won Kong
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Murray Cairns
- School of Biomedical Sciences & Pharmacy, Faculty of Health, The University of Newcastle, New South Wales, Callaghan, New South Wales, Australia
- Hunter Medical Research Institute, Newcastle, Australia
- Centre for Brain & Mental Health Research, The University of Newcastle, Callaghan, Australia
| | - Ming T Tsuang
- Center for Behavioral Genomics, Department of Psychiatry, Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA
- Harvard Institute of Psychiatric Epidemiology and Genetics, Boston, MA, USA
| | - Stephen V Faraone
- Department of Psychiatry & Behavioral Sciences, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, USA
- Department of Neuroscience & Physiology, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, USA
| | - Stephen J Glatt
- Department of Psychiatry & Behavioral Sciences, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, USA.
- Department of Neuroscience & Physiology, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, USA.
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11
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Meta-analysis of brain samples of individuals with schizophrenia detects down-regulation of multiple ATP synthase encoding genes in both females and males. J Psychiatr Res 2023; 158:350-359. [PMID: 36640659 DOI: 10.1016/j.jpsychires.2023.01.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 10/05/2022] [Accepted: 01/03/2023] [Indexed: 01/06/2023]
Abstract
Schizophrenia is a chronic and debilitating mental disorder, with unknown pathophysiology. Converging lines of evidence suggest that mitochondrial functioning may be compromised in schizophrenia. Postmortem brain samples of individuals with schizophrenia showed dysregulated expression levels of genes encoding enzyme complexes comprising the mitochondrial electron transport chain (ETC), including ATP synthase, the fifth ETC complex. However, there are inconsistencies regarding the direction of change, i.e., up- or down-regulation, and differences between female and male patients were hardly examined. We have performed a systematic meta-analysis of the expression of 16 ATP synthase encoding genes in postmortem brain samples of individuals with schizophrenia vs. healthy controls of three regions: Brodmann Area 10 (BA10), BA22/Superior Temporal Gyrus (STG) and the cerebellum. Eight independent datasets were integrated (overall 294brain samples, 145 of individuals with schizophrenia and 149 controls). The meta-analysis was applied to all individuals with schizophrenia vs. the controls, and also to female and male patients vs. age-matched controls, separately. A significant down-regulation of two ATP synthase encoding genes was detected in schizophrenia, ATP5A1 and ATP5H, and a trend towards down-regulation of five further ATP synthase genes. The down-regulation tendency was shown for both females and males with schizophrenia. Our findings support the hypothesis that schizophrenia is associated with reduced ATP synthesis via the oxidative phosphorylation system, which is caused by reduced cellular demand of ATP. Abnormal cellular energy metabolism can lead to alterations in neural function and brain circuitry, and thereby to the cognitive and behavioral aberrations characteristic of schizophrenia.
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12
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Shriebman Y, Yitzhaky A, Kosloff M, Hertzberg L. Gene expression meta-analysis in patients with schizophrenia reveals up-regulation of RGS2 and RGS16 in Brodmann Area 10. Eur J Neurosci 2023; 57:360-372. [PMID: 36443250 DOI: 10.1111/ejn.15876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 09/10/2022] [Accepted: 11/17/2022] [Indexed: 11/30/2022]
Abstract
Regulator of G-protein signalling (RGS) proteins inhibit signalling by G-protein-coupled receptors (GPCRs). GPCRs mediate the functions of several important neurotransmitters and serve as targets of many anti-psychotics. RGS2, RGS4, RGS5 and RGS16 are located on chromosome 1q23.3-31, a locus found to be associated with schizophrenia. Although previous gene expression analysis detected down-regulation of RGS4 expression in brain samples of patients with schizophrenia, the results were not consistent. In the present study, we performed a systematic meta-analysis of differential RGS2, RGS4, RGS5 and RGS16 expression in Brodmann Area 10 (BA10) samples of patients with schizophrenia and from healthy controls. Two microarray datasets met the inclusion criteria (overall, 41 schizophrenia samples and 38 controls were analysed). RGS2 and RGS16 were found to be up-regulated in BA10 samples of individuals with schizophrenia, whereas no differential expression of RGS4 and RGS5 was detected. Analysis of dorso-lateral prefrontal cortex samples of the CommonMind Consortium (258 schizophrenia samples vs. 279 controls) further validated the results. Given their central role in inactivating G-protein-coupled signalling pathways, our results suggest that differential gene expression might lead to enhanced inactivation of G-protein signalling in schizophrenia. This, in turn, suggests that additional studies are needed to further explore the consequences of the differential expression we detected, this time at the protein and functional levels.
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Affiliation(s)
- Yaen Shriebman
- Shalvata Mental Health Center, affiliated with the Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Assif Yitzhaky
- Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel
| | - Mickey Kosloff
- Department of Human Biology, University of Haifa, Haifa, Israel
| | - Libi Hertzberg
- Shalvata Mental Health Center, affiliated with the Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel
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13
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Webster MJ. Infections, Inflammation, and Psychiatric Illness: Review of Postmortem Evidence. Curr Top Behav Neurosci 2023; 61:35-48. [PMID: 35505055 DOI: 10.1007/7854_2022_362] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
While there is an abundance of epidemiological evidence implicating infectious agents in the etiology of severe mental illnesses, postmortem studies have not yet detected an increased incidence of microbial nucleic acid or proteins in the brains of people with mental illness. Nevertheless, abnormally expressed immune and inflammatory markers have consistently been found in the postmortem brain of patients with schizophrenia and mood disorders. Some of these abnormalities may be the result of an infection in utero or early in life that not only impacted the developing immune system but also the developing neurons of the brain. Some of the immune markers that are consistently found to be upregulated in schizophrenia implicate a possible viral infection and the blood brain barrier in the etiology and neuropathology of the disorder.
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14
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Ferguson LB, Mayfield RD, Messing RO. RNA biomarkers for alcohol use disorder. Front Mol Neurosci 2022; 15:1032362. [PMID: 36407766 PMCID: PMC9673015 DOI: 10.3389/fnmol.2022.1032362] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 10/17/2022] [Indexed: 11/06/2022] Open
Abstract
Alcohol use disorder (AUD) is highly prevalent and one of the leading causes of disability in the US and around the world. There are some molecular biomarkers of heavy alcohol use and liver damage which can suggest AUD, but these are lacking in sensitivity and specificity. AUD treatment involves psychosocial interventions and medications for managing alcohol withdrawal, assisting in abstinence and reduced drinking (naltrexone, acamprosate, disulfiram, and some off-label medications), and treating comorbid psychiatric conditions (e.g., depression and anxiety). It has been suggested that various patient groups within the heterogeneous AUD population would respond more favorably to specific treatment approaches. For example, there is some evidence that so-called reward-drinkers respond better to naltrexone than acamprosate. However, there are currently no objective molecular markers to separate patients into optimal treatment groups or any markers of treatment response. Objective molecular biomarkers could aid in AUD diagnosis and patient stratification, which could personalize treatment and improve outcomes through more targeted interventions. Biomarkers of treatment response could also improve AUD management and treatment development. Systems biology considers complex diseases and emergent behaviors as the outcome of interactions and crosstalk between biomolecular networks. A systems approach that uses transcriptomic (or other -omic data, e.g., methylome, proteome, metabolome) can capture genetic and environmental factors associated with AUD and potentially provide sensitive, specific, and objective biomarkers to guide patient stratification, prognosis of treatment response or relapse, and predict optimal treatments. This Review describes and highlights state-of-the-art research on employing transcriptomic data and artificial intelligence (AI) methods to serve as molecular biomarkers with the goal of improving the clinical management of AUD. Considerations about future directions are also discussed.
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Affiliation(s)
- Laura B. Ferguson
- Waggoner Center for Alcohol and Addiction Research, University of Texas at Austin, Austin, TX, United States,Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, TX, United States,Department of Neuroscience, University of Texas at Austin, Austin, TX, United States,*Correspondence: Laura B. Ferguson,
| | - R. Dayne Mayfield
- Waggoner Center for Alcohol and Addiction Research, University of Texas at Austin, Austin, TX, United States,Department of Neuroscience, University of Texas at Austin, Austin, TX, United States
| | - Robert O. Messing
- Waggoner Center for Alcohol and Addiction Research, University of Texas at Austin, Austin, TX, United States,Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, TX, United States,Department of Neuroscience, University of Texas at Austin, Austin, TX, United States
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15
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Seah C, Breen MS, Rusielewicz T, Bader HN, Xu C, Hunter CJ, McCarthy B, Deans PJM, Chattopadhyay M, Goldberg J, Desarnaud F, Makotkine I, Flory JD, Bierer LM, Staniskyte M, Noggle SA, Huckins LM, Paull D, Brennand KJ, Yehuda R. Modeling gene × environment interactions in PTSD using human neurons reveals diagnosis-specific glucocorticoid-induced gene expression. Nat Neurosci 2022; 25:1434-1445. [PMID: 36266471 PMCID: PMC9630117 DOI: 10.1038/s41593-022-01161-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 08/11/2022] [Indexed: 01/13/2023]
Abstract
Post-traumatic stress disorder (PTSD) can develop following severe trauma, but the extent to which genetic and environmental risk factors contribute to individual clinical outcomes is unknown. Here, we compared transcriptional responses to hydrocortisone exposure in human induced pluripotent stem cell (hiPSC)-derived glutamatergic neurons and peripheral blood mononuclear cells (PBMCs) from combat veterans with PTSD (n = 19 hiPSC and n = 20 PBMC donors) and controls (n = 20 hiPSC and n = 20 PBMC donors). In neurons only, we observed diagnosis-specific glucocorticoid-induced changes in gene expression corresponding with PTSD-specific transcriptomic patterns found in human postmortem brains. We observed glucocorticoid hypersensitivity in PTSD neurons, and identified genes that contribute to this PTSD-dependent glucocorticoid response. We find evidence of a coregulated network of transcription factors that mediates glucocorticoid hyper-responsivity in PTSD. These findings suggest that induced neurons represent a platform for examining the molecular mechanisms underlying PTSD, identifying biomarkers of stress response, and conducting drug screening to identify new therapeutics.
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Affiliation(s)
- Carina Seah
- Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry or Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience or Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Departments of Psychiatry and Genetics, Division of Molecular Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Michael S Breen
- Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry or Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tom Rusielewicz
- The New York Stem Cell Foundation Research Institute, New York, NY, USA
| | - Heather N Bader
- Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry or Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
- Center for Psychedelic Psychotherapy and Trauma Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Changxin Xu
- Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry or Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
- Center for Psychedelic Psychotherapy and Trauma Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Barry McCarthy
- The New York Stem Cell Foundation Research Institute, New York, NY, USA
| | - P J Michael Deans
- Departments of Psychiatry and Genetics, Division of Molecular Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Mitali Chattopadhyay
- Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry or Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
- Center for Psychedelic Psychotherapy and Trauma Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jordan Goldberg
- The New York Stem Cell Foundation Research Institute, New York, NY, USA
| | - Frank Desarnaud
- Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry or Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
- Center for Psychedelic Psychotherapy and Trauma Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Iouri Makotkine
- Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry or Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
- Center for Psychedelic Psychotherapy and Trauma Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Janine D Flory
- Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry or Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
- Center for Psychedelic Psychotherapy and Trauma Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Linda M Bierer
- Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry or Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
- Center for Psychedelic Psychotherapy and Trauma Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Migle Staniskyte
- Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry or Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
- Center for Psychedelic Psychotherapy and Trauma Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Scott A Noggle
- The New York Stem Cell Foundation Research Institute, New York, NY, USA
| | - Laura M Huckins
- Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry or Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Departments of Psychiatry and Genetics, Division of Molecular Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Daniel Paull
- The New York Stem Cell Foundation Research Institute, New York, NY, USA.
| | - Kristen J Brennand
- Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry or Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Nash Family Department of Neuroscience or Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Departments of Psychiatry and Genetics, Division of Molecular Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
| | - Rachel Yehuda
- Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry or Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Nash Family Department of Neuroscience or Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA.
- Center for Psychedelic Psychotherapy and Trauma Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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16
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Pergola G, Penzel N, Sportelli L, Bertolino A. Lessons Learned From Parsing Genetic Risk for Schizophrenia Into Biological Pathways. Biol Psychiatry 2022:S0006-3223(22)01701-2. [PMID: 36740470 DOI: 10.1016/j.biopsych.2022.10.009] [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: 04/16/2022] [Revised: 09/10/2022] [Accepted: 10/06/2022] [Indexed: 02/07/2023]
Abstract
The clinically heterogeneous presentation of schizophrenia is compounded by the heterogeneity of risk factors and neurobiological correlates of the disorder. Genome-wide association studies in schizophrenia have uncovered a remarkably high number of genetic variants, but the biological pathways they impact upon remain largely unidentified. Among the diverse methodological approaches employed to provide a more granular understanding of genetic risk for schizophrenia, the use of biological labels, such as gene ontologies, regulome approaches, and gene coexpression have all provided novel perspectives into how genetic risk translates into the neurobiology of schizophrenia. Here, we review the salient aspects of parsing polygenic risk for schizophrenia into biological pathways. We argue that parsed scores, compared to standard polygenic risk scores, may afford a more biologically plausible and accurate physiological modeling of the different dimensions involved in translating genetic risk into brain mechanisms, including multiple brain regions, cell types, and maturation stages. We discuss caveats, opportunities, and pitfalls inherent in the parsed risk approach.
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Affiliation(s)
- Giulio Pergola
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy.
| | - Nora Penzel
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Leonardo Sportelli
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Alessandro Bertolino
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
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17
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Zakutansky PM, Feng Y. The Long Non-Coding RNA GOMAFU in Schizophrenia: Function, Disease Risk, and Beyond. Cells 2022; 11:1949. [PMID: 35741078 PMCID: PMC9221589 DOI: 10.3390/cells11121949] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 06/10/2022] [Accepted: 06/14/2022] [Indexed: 02/05/2023] Open
Abstract
Neuropsychiatric diseases are among the most common brain developmental disorders, represented by schizophrenia (SZ). The complex multifactorial etiology of SZ remains poorly understood, which reflects genetic vulnerabilities and environmental risks that affect numerous genes and biological pathways. Besides the dysregulation of protein-coding genes, recent discoveries demonstrate that abnormalities associated with non-coding RNAs, including microRNAs and long non-coding RNAs (lncRNAs), also contribute to the pathogenesis of SZ. lncRNAs are an actively evolving family of non-coding RNAs that harbor greater than 200 nucleotides but do not encode for proteins. In general, lncRNA genes are poorly conserved. The large number of lncRNAs specifically expressed in the human brain, together with the genetic alterations and dysregulation of lncRNA genes in the SZ brain, suggests a critical role in normal cognitive function and the pathogenesis of neuropsychiatric diseases. A particular lncRNA of interest is GOMAFU, also known as MIAT and RNCR2. Growing evidence suggests the function of GOMAFU in governing neuronal development and its potential roles as a risk factor and biomarker for SZ, which will be reviewed in this article. Moreover, we discuss the potential mechanisms through which GOMAFU regulates molecular pathways, including its subcellular localization and interaction with RNA-binding proteins, and how interruption to GOMAFU pathways may contribute to the pathogenesis of SZ.
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Affiliation(s)
- Paul M. Zakutansky
- Graduate Program in Biochemistry, Cell and Developmental Biology, Emory University, Atlanta, GA 30322, USA;
- Department of Pharmacology and Chemical Biology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Yue Feng
- Department of Pharmacology and Chemical Biology, Emory University School of Medicine, Atlanta, GA 30322, USA
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18
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Hemmings SMJ, Swart P, Womersely JS, Ovenden ES, van den Heuvel LL, McGregor NW, Meier S, Bardien S, Abrahams S, Tromp G, Emsley R, Carr J, Seedat S. RNA-seq analysis of gene expression profiles in posttraumatic stress disorder, Parkinson's disease and schizophrenia identifies roles for common and distinct biological pathways. DISCOVER MENTAL HEALTH 2022; 2:6. [PMID: 37861850 PMCID: PMC10501040 DOI: 10.1007/s44192-022-00009-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 02/14/2022] [Indexed: 10/21/2023]
Abstract
Evidence suggests that shared pathophysiological mechanisms in neuropsychiatric disorders (NPDs) may contribute to risk and resilience. We used single-gene and network-level transcriptomic approaches to investigate shared and disorder-specific processes underlying posttraumatic stress disorder (PTSD), Parkinson's disease (PD) and schizophrenia in a South African sample. RNA-seq was performed on blood obtained from cases and controls from each cohort. Gene expression and weighted gene correlation network analyses (WGCNA) were performed using DESeq2 and CEMiTool, respectively. Significant differences in gene expression were limited to the PTSD cohort. However, WGCNA implicated, amongst others, ribosomal expression, inflammation and ubiquitination as key players in the NPDs under investigation. Differential expression in ribosomal-related pathways was observed in the PTSD and PD cohorts, and focal adhesion and extracellular matrix pathways were implicated in PD and schizophrenia. We propose that, despite different phenotypic presentations, core transdiagnostic mechanisms may play important roles in the molecular aetiology of NPDs.
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Affiliation(s)
- Sian M J Hemmings
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa.
- South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa.
| | - Patricia Swart
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa
- South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa
| | - Jacqueline S Womersely
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa
- South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa
| | - Ellen S Ovenden
- Systems Genetics Working Group, Department of Genetics, Stellenbosch University, Stellenbosch, South Africa
| | - Leigh L van den Heuvel
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa
- South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa
| | - Nathaniel W McGregor
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa
- Systems Genetics Working Group, Department of Genetics, Stellenbosch University, Stellenbosch, South Africa
| | - Stuart Meier
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Stellenbosch University, Cape Town, South Africa
- South African Medical Research Council Centre for Tuberculosis Research, Stellenbosch University, Cape Town, South Africa
- South African Tuberculosis Bioinformatics Initiative, Stellenbosch University, Cape Town, South Africa
| | - Soraya Bardien
- South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa
| | - Shameemah Abrahams
- South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa
| | - Gerard Tromp
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Stellenbosch University, Cape Town, South Africa
- South African Medical Research Council Centre for Tuberculosis Research, Stellenbosch University, Cape Town, South Africa
- South African Tuberculosis Bioinformatics Initiative, Stellenbosch University, Cape Town, South Africa
- Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch, South Africa
| | - Robin Emsley
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa
| | - Jonathan Carr
- Division of Neurology, Department of Medicine, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Soraya Seedat
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa
- South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Stellenbosch University, Cape Town, South Africa
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19
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Epigenome-wide association study of posttraumatic stress disorder identifies novel loci in U.S. military veterans. Transl Psychiatry 2022; 12:65. [PMID: 35177594 PMCID: PMC8854688 DOI: 10.1038/s41398-022-01822-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Revised: 12/26/2021] [Accepted: 01/14/2022] [Indexed: 01/23/2023] Open
Abstract
Posttraumatic stress disorder (PTSD) is a chronic and disabling psychiatric disorder prevalent in military veterans. Epigenetic mechanisms have been implicated in the etiology of PTSD, with DNA methylation being the most studied to identify novel molecular biomarkers associated with this disorder. We performed one of the largest single-sample epigenome-wide association studies (EWAS) of PTSD to date. Our sample included 1135 male European-American U.S. veterans who participated in the National Health and Resilience in Veterans Study (NHRVS). DNA was collected from saliva samples and the Illumina HumanMethylation EPIC BeadChip was used for the methylation analysis. PTSD was assessed using the PTSD Checklist. An EWAS was conducted using linear regression adjusted for age, cell-type proportions, first 10 principal components, and smoking status. After Bonferroni correction, we identified six genome-wide significant (GWS) CpG sites associated with past-month PTSD and three CpGs with lifetime PTSD (prange = 10-10-10-8). These CpG sites map to genes involved in immune function, transcription regulation, axonal guidance, cell signaling, and protein binding. Among these, SENP7, which is involved in transcription regulation and has been linked to risk-taking behavior and alcohol consumption in genome-wide association studies, replicated in an independent veteran cohort and was downregulated in medial orbitofrontal cortex of PTSD postmortem brain tissue. These findings suggest potential epigenetic biomarkers of PTSD that may help inform the pathophysiology of this disorder in veterans and other trauma-affected populations.
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20
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Heurich M, Föcking M, Mongan D, Cagney G, Cotter DR. Dysregulation of complement and coagulation pathways: emerging mechanisms in the development of psychosis. Mol Psychiatry 2022; 27:127-140. [PMID: 34226666 PMCID: PMC8256396 DOI: 10.1038/s41380-021-01197-9] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 06/04/2021] [Accepted: 06/10/2021] [Indexed: 02/06/2023]
Abstract
Early identification and treatment significantly improve clinical outcomes of psychotic disorders. Recent studies identified protein components of the complement and coagulation systems as key pathways implicated in psychosis. These specific protein alterations are integral to the inflammatory response and can begin years before the onset of clinical symptoms of psychotic disorder. Critically, they have recently been shown to predict the transition from clinical high risk to first-episode psychosis, enabling stratification of individuals who are most likely to transition to psychotic disorder from those who are not. This reinforces the concept that the psychosis spectrum is likely a central nervous system manifestation of systemic changes and highlights the need to investigate plasma proteins as diagnostic or prognostic biomarkers and pathophysiological mediators. In this review, we integrate evidence of alterations in proteins belonging to the complement and coagulation protein systems, including the coagulation, anticoagulation, and fibrinolytic pathways and their dysregulation in psychosis, into a consolidated mechanism that could be integral to the progression and manifestation of psychosis. We consolidate the findings of altered blood proteins relevant for progression to psychotic disorders, using data from longitudinal studies of the general population in addition to clinical high-risk (CHR) individuals transitioning to psychotic disorder. These are compared to markers identified from first-episode psychosis and schizophrenia as well as other psychosis spectrum disorders. We propose the novel hypothesis that altered complement and coagulation plasma levels enhance their pathways' activating capacities, while low levels observed in key regulatory components contribute to excessive activation observed in patients. This hypothesis will require future testing through a range of experimental paradigms, and if upheld, complement and coagulation pathways or specific proteins could be useful diagnostic or prognostic tools and targets for early intervention and preventive strategies.
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Affiliation(s)
- Meike Heurich
- School of Pharmacy and Pharmaceutical Sciences, Cardiff University, Cardiff, UK.
| | - Melanie Föcking
- grid.4912.e0000 0004 0488 7120Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - David Mongan
- grid.4912.e0000 0004 0488 7120Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Gerard Cagney
- grid.7886.10000 0001 0768 2743School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Dublin, Ireland
| | - David R. Cotter
- grid.4912.e0000 0004 0488 7120Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
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21
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Wagh VV, Vyas P, Agrawal S, Pachpor TA, Paralikar V, Khare SP. Peripheral Blood-Based Gene Expression Studies in Schizophrenia: A Systematic Review. Front Genet 2021; 12:736483. [PMID: 34721526 PMCID: PMC8548640 DOI: 10.3389/fgene.2021.736483] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 08/31/2021] [Indexed: 12/19/2022] Open
Abstract
Schizophrenia is a disorder that is characterized by delusions, hallucinations, disorganized speech or behavior, and socio-occupational impairment. The duration of observation and variability in symptoms can make the accurate diagnosis difficult. Identification of biomarkers for schizophrenia (SCZ) can help in early diagnosis, ascertaining the diagnosis, and development of effective treatment strategies. Here we review peripheral blood-based gene expression studies for identification of gene expression biomarkers for SCZ. A literature search was carried out in PubMed and Web of Science databases for blood-based gene expression studies in SCZ. A list of differentially expressed genes (DEGs) was compiled and analyzed for overlap with genetic markers, differences based on drug status of the participants, functional enrichment, and for effect of antipsychotics. This literature survey identified 61 gene expression studies. Seventeen out of these studies were based on expression microarrays. A comparative analysis of the DEGs (n = 227) from microarray studies revealed differences between drug-naive and drug-treated SCZ participants. We found that of the 227 DEGs, 11 genes (ACOT7, AGO2, DISC1, LDB1, RUNX3, SIGIRR, SLC18A1, NRG1, CHRNB2, PRKAB2, and ZNF74) also showed genetic and epigenetic changes associated with SCZ. Functional enrichment analysis of the DEGs revealed dysregulation of proline and 4-hydroxyproline metabolism. Also, arginine and proline metabolism was the most functionally enriched pathway for SCZ in our analysis. Follow-up studies identified effect of antipsychotic treatment on peripheral blood gene expression. Of the 27 genes compiled from the follow-up studies AKT1, DISC1, HP, and EIF2D had no effect on their expression status as a result of antipsychotic treatment. Despite the differences in the nature of the study, ethnicity of the population, and the gene expression analysis method used, we identified several coherent observations. An overlap, though limited, of genetic, epigenetic and gene expression changes supports interplay of genetic and environmental factors in SCZ. The studies validate the use of blood as a surrogate tissue for biomarker analysis. We conclude that well-designed cohort studies across diverse populations, use of high-throughput sequencing technology, and use of artificial intelligence (AI) based computational analysis will significantly improve our understanding and diagnostic capabilities for this complex disorder.
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Affiliation(s)
- Vipul Vilas Wagh
- Symbiosis School of Biological Sciences, Symbiosis International (Deemed University), Pune, India
| | - Parin Vyas
- Symbiosis School of Biological Sciences, Symbiosis International (Deemed University), Pune, India
| | - Suchita Agrawal
- The Psychiatry Unit, KEM Hospital and KEM Hospital Research Centre, Pune, India
| | | | - Vasudeo Paralikar
- The Psychiatry Unit, KEM Hospital and KEM Hospital Research Centre, Pune, India
| | - Satyajeet P Khare
- Symbiosis School of Biological Sciences, Symbiosis International (Deemed University), Pune, India
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22
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Rewired Pathways and Disrupted Pathway Crosstalk in Schizophrenia Transcriptomes by Multiple Differential Coexpression Methods. Genes (Basel) 2021; 12:genes12050665. [PMID: 33946654 PMCID: PMC8146818 DOI: 10.3390/genes12050665] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Revised: 04/16/2021] [Accepted: 04/27/2021] [Indexed: 02/03/2023] Open
Abstract
Transcriptomic studies of mental disorders using the human brain tissues have been limited, and gene expression signatures in schizophrenia (SCZ) remain elusive. In this study, we applied three differential co-expression methods to analyze five transcriptomic datasets (three RNA-Seq and two microarray datasets) derived from SCZ and matched normal postmortem brain samples. We aimed to uncover biological pathways where internal correlation structure was rewired or inter-coordination was disrupted in SCZ. In total, we identified 60 rewired pathways, many of which were related to neurotransmitter, synapse, immune, and cell adhesion. We found the hub genes, which were on the center of rewired pathways, were highly mutually consistent among the five datasets. The combinatory list of 92 hub genes was generally multi-functional, suggesting their complex and dynamic roles in SCZ pathophysiology. In our constructed pathway crosstalk network, we found “Clostridium neurotoxicity” and “signaling events mediated by focal adhesion kinase” had the highest interactions. We further identified disconnected gene links underlying the disrupted pathway crosstalk. Among them, four gene pairs (PAK1:SYT1, PAK1:RFC5, DCTN1:STX1A, and GRIA1:MAP2K4) were normally correlated in universal contexts. In summary, we systematically identified rewired pathways, disrupted pathway crosstalk circuits, and critical genes and gene links in schizophrenia transcriptomes.
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23
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Afridi R, Seol S, Kang HJ, Suk K. Brain-immune interactions in neuropsychiatric disorders: Lessons from transcriptome studies for molecular targeting. Biochem Pharmacol 2021; 188:114532. [PMID: 33773976 DOI: 10.1016/j.bcp.2021.114532] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 03/18/2021] [Accepted: 03/18/2021] [Indexed: 12/12/2022]
Abstract
Understanding the pathophysiological mechanisms of neuropsychiatric disorders has been a challenging quest for neurobiologists. Recent years have witnessed enormous technological advances in the field of neuroimmunology, blurring boundaries between the central nervous system and the periphery. Consequently, the discipline has expanded to cover interactions between the nervous and immune systems in health and diseases. The complex interplay between the peripheral and central immune pathways in neuropsychiatric disorders has recently been documented in various studies, but the genetic determinants remain elusive. Recent transcriptome studies have identified dysregulated genes involved in peripheral immune cell activation, blood-brain barrier integrity, glial cell activation, and synaptic plasticity in major depressive disorder, bipolar disorder, autism spectrum disorder, and schizophrenia. Herein, the key transcriptomic techniques applied in investigating differentially expressed genes and pathways responsible for altered brain-immune interactions in neuropsychiatric disorders are discussed. The application of transcriptomics that can aid in identifying molecular targets in various neuropsychiatric disorders is highlighted.
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Affiliation(s)
- Ruqayya Afridi
- Department of Pharmacology, Brain Science & Engineering Institute, BK21 Plus KNU Biomedical Convergence Program, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Sihwan Seol
- Department of Life Science, Chung-Ang University, Seoul, Republic of Korea
| | - Hyo Jung Kang
- Department of Life Science, Chung-Ang University, Seoul, Republic of Korea.
| | - Kyoungho Suk
- Department of Pharmacology, Brain Science & Engineering Institute, BK21 Plus KNU Biomedical Convergence Program, School of Medicine, Kyungpook National University, Daegu, Republic of Korea.
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24
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Prestwood TR, Asgariroozbehani R, Wu S, Agarwal SM, Logan RW, Ballon JS, Hahn MK, Freyberg Z. Roles of inflammation in intrinsic pathophysiology and antipsychotic drug-induced metabolic disturbances of schizophrenia. Behav Brain Res 2021; 402:113101. [PMID: 33453341 PMCID: PMC7882027 DOI: 10.1016/j.bbr.2020.113101] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 12/10/2020] [Accepted: 12/27/2020] [Indexed: 02/06/2023]
Abstract
Schizophrenia is a debilitating psychiatric illness that remains poorly understood. While the bulk of symptomatology has classically been associated with disrupted brain functioning, accumulating evidence demonstrates that schizophrenia is characterized by systemic inflammation and disturbances in metabolism. Indeed, metabolic disease is a major determinant of the high mortality rate associated with schizophrenia. Antipsychotic drugs (APDs) have revolutionized management of psychosis, making it possible to rapidly control psychotic symptoms. This has ultimately reduced relapse rates of psychotic episodes and improved overall quality of life for people with schizophrenia. However, long-term APD use has also been associated with significant metabolic disturbances including weight gain, dysglycemia, and worsening of the underlying cardiometabolic disease intrinsic to schizophrenia. While the mechanisms for these intrinsic and medication-induced metabolic effects remain unclear, inflammation appears to play a key role. Here, we review the evidence for roles of inflammatory mechanisms in the disease features of schizophrenia and how these mechanisms interact with APD treatment. We also discuss the effects of common inflammatory mediators on metabolic disease. Then, we review the evidence of intrinsic and APD-mediated effects on systemic inflammation in schizophrenia. Finally, we speculate about possible treatment strategies. Developing an improved understanding of inflammatory processes in schizophrenia may therefore introduce new, more effective options for treating not only schizophrenia but also primary metabolic disorders.
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Affiliation(s)
- Tyler R Prestwood
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Roshanak Asgariroozbehani
- Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Sciences, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Sally Wu
- Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Sciences, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Sri Mahavir Agarwal
- Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Sciences, Faculty of Medicine, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Banting and Best Diabetes Centre (BBDC), University of Toronto, Toronto, ON, Canada
| | - Ryan W Logan
- Department of Pharmacology and Experimental Therapeutics, Boston University School of Medicine, Boston, MA, USA; Center for Systems Neurogenetics of Addiction, The Jackson Laboratory, Bar Harbor, ME, USA
| | - Jacob S Ballon
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Margaret K Hahn
- Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Sciences, Faculty of Medicine, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Banting and Best Diabetes Centre (BBDC), University of Toronto, Toronto, ON, Canada.
| | - Zachary Freyberg
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA; Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA, USA.
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25
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Schizophrenia-associated SLC39A8 polymorphism is a loss-of-function allele altering glutamate receptor and innate immune signaling. Transl Psychiatry 2021; 11:136. [PMID: 33608496 PMCID: PMC7895948 DOI: 10.1038/s41398-021-01262-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Accepted: 02/02/2021] [Indexed: 11/08/2022] Open
Abstract
Schizophrenia is a complex and heterogenous disease that presents with abnormalities in glutamate signaling and altered immune and inflammatory signals. Genome-wide association studies have indicated specific genes and pathways that may contribute to schizophrenia. We assessed the impact of the functional missense variant SLC39A8 (ZIP8)-A391T (ZIP8A391T) on zinc transport, glutamate signaling, and the neuroinflammatory response. The ZIP8A391T mutation resulted in reduced zinc transport into the cell, suggesting a loss in the tight control of zinc in the synaptic cleft. Electrophysiological recordings from perturbed neurons revealed a significant reduction in NMDA- and AMPA-mediated spontaneous EPSCs (sEPSCs) and a reduction in GluN2A and GluA1/2/3 receptor surface expression. All phenotypes were rescued by re-expression of wild-type ZIP8 (ZIP8WT) or application of the membrane-impermeable zinc chelator ZX1. ZIP8 reduction also resulted in decreased BBB integrity, increased IL-6/IL-1β protein expression, and increased NFκB following TNFα stimulation, indicating that ZIP8 loss-of-function may exacerbate immune and inflammatory signals. Together, our findings demonstrate that the A391T missense mutation results in alterations in glutamate and immune function and provide novel therapeutic targets relevant to schizophrenia.
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26
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Krall RF, Tzounopoulos T, Aizenman E. The Function and Regulation of Zinc in the Brain. Neuroscience 2021; 457:235-258. [PMID: 33460731 DOI: 10.1016/j.neuroscience.2021.01.010] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 01/05/2021] [Accepted: 01/08/2021] [Indexed: 12/31/2022]
Abstract
Nearly sixty years ago Fredrich Timm developed a histochemical technique that revealed a rich reserve of free zinc in distinct regions of the brain. Subsequent electron microscopy studies in Timm- stained brain tissue found that this "labile" pool of cellular zinc was highly concentrated at synaptic boutons, hinting a possible role for the metal in synaptic transmission. Although evidence for activity-dependent synaptic release of zinc would not be reported for another twenty years, these initial findings spurred decades of research into zinc's role in neuronal function and revealed a diverse array of signaling cascades triggered or regulated by the metal. Here, we delve into our current understanding of the many roles zinc plays in the brain, from influencing neurotransmission and sensory processing, to activating both pro-survival and pro-death neuronal signaling pathways. Moreover, we detail the many mechanisms that tightly regulate cellular zinc levels, including metal binding proteins and a large array of zinc transporters.
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Affiliation(s)
- Rebecca F Krall
- Department of Neurobiology, University of Pittsburgh School of Medicine, USA; Department of Otolaryngology, University of Pittsburgh School of Medicine, USA; Pittsburgh Hearing Research Center, University of Pittsburgh School of Medicine, USA; Pittsburgh Institute for Neurodegenerative Diseases, University of Pittsburgh School of Medicine, USA
| | - Thanos Tzounopoulos
- Department of Otolaryngology, University of Pittsburgh School of Medicine, USA; Pittsburgh Hearing Research Center, University of Pittsburgh School of Medicine, USA.
| | - Elias Aizenman
- Department of Neurobiology, University of Pittsburgh School of Medicine, USA; Pittsburgh Hearing Research Center, University of Pittsburgh School of Medicine, USA; Pittsburgh Institute for Neurodegenerative Diseases, University of Pittsburgh School of Medicine, USA.
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27
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Khavari B, Mahmoudi E, Geaghan MP, Cairns MJ. Oxidative Stress Impact on the Transcriptome of Differentiating Neuroblastoma Cells: Implication for Psychiatric Disorders. Int J Mol Sci 2020; 21:ijms21239182. [PMID: 33276438 PMCID: PMC7731408 DOI: 10.3390/ijms21239182] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 11/27/2020] [Accepted: 11/27/2020] [Indexed: 01/06/2023] Open
Abstract
Prenatal environmental exposures that have been shown to induce oxidative stress (OS) during pregnancy, such as smoking and alcohol consumption, are risk factors for the onset of schizophrenia and other neurodevelopmental disorders (NDDs). While the OS role in the etiology of neurodegenerative diseases is well known, its contribution to the genomic dysregulation associated with psychiatric disorders is less well defined. In this study we used the SH-SY5Y cell line and applied RNA-sequencing to explore transcriptomic changes in response to OS before or during neural differentiation. We observed differential expression of many genes, most of which localised to the synapse and were involved in neuronal differentiation. These genes were enriched in schizophrenia-associated signalling pathways, including PI3K/Akt, axon guidance, and signalling by retinoic acid. Interestingly, circulatory system development was affected by both treatments, which is concordant with observations of increased prevalence of cardiovascular disease in patients with NDDs. We also observed a very significant increase in the expression of immunity-related genes, supporting current hypotheses of immune system involvement in psychiatric disorders. While further investigation of this influence in other cell and animal models is warranted, our data suggest that early life exposure to OS has a disruptive influence on neuronal gene expression that may perturb normal differentiation and neurodevelopment, thereby contributing towards overall risk for developing psychiatric diseases.
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Affiliation(s)
- Behnaz Khavari
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, NSW 2308, Australia; (B.K.); (E.M.); (M.P.G.)
- Centre for Brain and Mental Health Research, University of Newcastle and the Hunter Medical Research Institute, Newcastle, NSW 2305, Australia
| | - Ebrahim Mahmoudi
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, NSW 2308, Australia; (B.K.); (E.M.); (M.P.G.)
- Centre for Brain and Mental Health Research, University of Newcastle and the Hunter Medical Research Institute, Newcastle, NSW 2305, Australia
| | - Michael P. Geaghan
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, NSW 2308, Australia; (B.K.); (E.M.); (M.P.G.)
- Centre for Brain and Mental Health Research, University of Newcastle and the Hunter Medical Research Institute, Newcastle, NSW 2305, Australia
| | - Murray J. Cairns
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, NSW 2308, Australia; (B.K.); (E.M.); (M.P.G.)
- Centre for Brain and Mental Health Research, University of Newcastle and the Hunter Medical Research Institute, Newcastle, NSW 2305, Australia
- Correspondence: ; Tel.: +61-02-4921-8670
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28
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Krebs CE, Ori APS, Vreeker A, Wu T, Cantor RM, Boks MPM, Kahn RS, Olde Loohuis LM, Ophoff RA. Whole blood transcriptome analysis in bipolar disorder reveals strong lithium effect. Psychol Med 2020; 50:2575-2586. [PMID: 31589133 DOI: 10.1017/s0033291719002745] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
BACKGROUND Bipolar disorder (BD) is a highly heritable mood disorder with complex genetic architecture and poorly understood etiology. Previous transcriptomic BD studies have had inconsistent findings due to issues such as small sample sizes and difficulty in adequately accounting for confounders like medication use. METHODS We performed a differential expression analysis in a well-characterized BD case-control sample (Nsubjects = 480) by RNA sequencing of whole blood. We further performed co-expression network analysis, functional enrichment, and cell type decomposition, and integrated differentially expressed genes with genetic risk. RESULTS While we observed widespread differential gene expression patterns between affected and unaffected individuals, these effects were largely linked to lithium treatment at the time of blood draw (FDR < 0.05, Ngenes = 976) rather than BD diagnosis itself (FDR < 0.05, Ngenes = 6). These lithium-associated genes were enriched for cell signaling and immune response functional annotations, among others, and were associated with neutrophil cell-type proportions, which were elevated in lithium users. Neither genes with altered expression in cases nor in lithium users were enriched for BD, schizophrenia, and depression genetic risk based on information from genome-wide association studies, nor was gene expression associated with polygenic risk scores for BD. CONCLUSIONS These findings suggest that BD is associated with minimal changes in whole blood gene expression independent of medication use but emphasize the importance of accounting for medication use and cell type heterogeneity in psychiatric transcriptomic studies. The results of this study add to mounting evidence of lithium's cell signaling and immune-related mechanisms.
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Affiliation(s)
- Catharine E Krebs
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University California Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, University California Los Angeles, Los Angeles, CA, USA
| | - Anil P S Ori
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University California Los Angeles, Los Angeles, CA, USA
| | - Annabel Vreeker
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University California Los Angeles, Los Angeles, CA, USA
- Department of Medical Genetics, University Medical Center Utrecht, Utrecht, Netherlands
| | - Timothy Wu
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University California Los Angeles, Los Angeles, CA, USA
| | - Rita M Cantor
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University California Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, University California Los Angeles, Los Angeles, CA, USA
| | - Marco P M Boks
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, Netherlands
| | - Rene S Kahn
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Loes M Olde Loohuis
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University California Los Angeles, Los Angeles, CA, USA
| | - Roel A Ophoff
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University California Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, University California Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
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29
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Hess JL, Nguyen NH, Suben J, Meath RM, Albert AB, Van Orman S, Anders KM, Forken PJ, Roe CA, Schulze TG, Faraone SV, Glatt SJ. Gene co-expression networks in peripheral blood capture dimensional measures of emotional and behavioral problems from the Child Behavior Checklist (CBCL). Transl Psychiatry 2020; 10:328. [PMID: 32968041 PMCID: PMC7511314 DOI: 10.1038/s41398-020-01007-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Revised: 05/29/2020] [Accepted: 09/03/2020] [Indexed: 12/21/2022] Open
Abstract
The U.S. National Institute of Mental Health (NIMH) introduced the research domain criteria (RDoC) initiative to promote the integration of information across multiple units of analysis (i.e., brain circuits, physiology, behavior, self-reports) to better understand the basic dimensions of behavior and cognitive functioning underlying normal and abnormal mental conditions. Along those lines, this study examined the association between peripheral blood gene expression levels and emotional and behavioral problems in school-age children. Children were chosen from two age- and sex-matched groups: those with or without parental reports of any prior or current psychiatric diagnosis. RNA-sequencing was performed on whole blood from 96 probands aged 6-12 years who were medication-free at the time of assessment. Module eigengenes were derived using weighted gene co-expression network analysis (WGCNA). Associations were tested between module eigengene expression levels and eight syndrome scales from parent ratings on the Child Behavior Checklist (CBCL). Nine out of the 36 modules were significantly associated with at least one syndrome scale measured by the CBCL (i.e., aggression, social problems, attention problems, and/or thought problems) after accounting for covariates and correcting for multiple testing. Our study demonstrates that variation in peripheral blood gene expression relates to emotional and behavioral profiles in children. If replicated and validated, our results may help in identifying problem or at-risk behavior in pediatric populations, and in elucidating the biological pathways that modulate complex human behavior.
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Affiliation(s)
- Jonathan L Hess
- Department of Psychiatry & Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Nicholas H Nguyen
- Department of Psychiatry & Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Jesse Suben
- Department of Psychiatry & Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Ryan M Meath
- Department of Psychiatry & Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Avery B Albert
- Department of Psychiatry & Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
- Department of Psychology, Syracuse University, Syracuse, NY, USA
| | - Sarah Van Orman
- Department of Psychiatry & Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Kristin M Anders
- Department of Psychiatry & Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Patricia J Forken
- Department of Psychiatry & Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Cheryl A Roe
- Department of Public Health and Preventive Medicine, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Thomas G Schulze
- Institute of Psychiatric Phenomics and Genomics, Medical Center of the University of Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University, Baltimore, MD, USA
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Mannheim, Germany
| | - Stephen V Faraone
- Department of Psychiatry & Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
- Department of Neuroscience & Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Stephen J Glatt
- Department of Psychiatry & Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA.
- Department of Neuroscience & Physiology, SUNY Upstate Medical University, Syracuse, NY, USA.
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30
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Zhao Y, Wong L, Goh WWB. How to do quantile normalization correctly for gene expression data analyses. Sci Rep 2020; 10:15534. [PMID: 32968196 PMCID: PMC7511327 DOI: 10.1038/s41598-020-72664-6] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Accepted: 08/03/2020] [Indexed: 02/07/2023] Open
Abstract
Quantile normalization is an important normalization technique commonly used in high-dimensional data analysis. However, it is susceptible to class-effect proportion effects (the proportion of class-correlated variables in a dataset) and batch effects (the presence of potentially confounding technical variation) when applied blindly on whole data sets, resulting in higher false-positive and false-negative rates. We evaluate five strategies for performing quantile normalization, and demonstrate that good performance in terms of batch-effect correction and statistical feature selection can be readily achieved by first splitting data by sample class-labels before performing quantile normalization independently on each split (“Class-specific”). Via simulations with both real and simulated batch effects, we demonstrate that the “Class-specific” strategy (and others relying on similar principles) readily outperform whole-data quantile normalization, and is robust-preserving useful signals even during the combined analysis of separately-normalized datasets. Quantile normalization is a commonly used procedure. But when carelessly applied on whole datasets without first considering class-effect proportion and batch effects, can result in poor performance. If quantile normalization must be used, then we recommend using the “Class-specific” strategy.
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Affiliation(s)
- Yaxing Zhao
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China
| | - Limsoon Wong
- Department of Computer Science, National University of Singapore, Singapore, Singapore.,Department of Pathology, National University of Singapore, Singapore, Singapore
| | - Wilson Wen Bin Goh
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore.
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31
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Epigenomic Dysregulation in Schizophrenia: In Search of Disease Etiology and Biomarkers. Cells 2020; 9:cells9081837. [PMID: 32764320 PMCID: PMC7463953 DOI: 10.3390/cells9081837] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 07/27/2020] [Accepted: 07/31/2020] [Indexed: 12/13/2022] Open
Abstract
Schizophrenia is a severe psychiatric disorder with a complex array of signs and symptoms that causes very significant disability in young people. While schizophrenia has a strong genetic component, with heritability around 80%, there is also a very significant range of environmental exposures and stressors that have been implicated in disease development and neuropathology, such as maternal immune infection, obstetric complications, childhood trauma and cannabis exposure. It is postulated that epigenetic factors, as well as regulatory non-coding RNAs, mediate the effects of these environmental stressors. In this review, we explore the most well-known epigenetic marks, including DNA methylation and histone modification, along with emerging RNA mediators of epigenomic state, including miRNAs and lncRNAs, and discuss their collective potential for involvement in the pathophysiology of schizophrenia implicated through the postmortem analysis of brain tissue. Given that peripheral tissues, such as blood, saliva, and olfactory epithelium have the same genetic composition and are exposed to many of the same environmental exposures, we also examine some studies supporting the application of peripheral tissues for epigenomic biomarker discovery in schizophrenia. Finally, we provide some perspective on how these biomarkers may be utilized to capture a signature of past events that informs future treatment.
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32
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Kotov R, Jonas KG, Carpenter WT, Dretsch MN, Eaton NR, Forbes MK, Forbush KT, Hobbs K, Reininghaus U, Slade T, South SC, Sunderland M, Waszczuk MA, Widiger TA, Wright A, Zald DH, Krueger RF, Watson D. Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): I. Psychosis superspectrum. World Psychiatry 2020; 19:151-172. [PMID: 32394571 PMCID: PMC7214958 DOI: 10.1002/wps.20730] [Citation(s) in RCA: 131] [Impact Index Per Article: 32.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
The Hierarchical Taxonomy of Psychopathology (HiTOP) is a scientific effort to address shortcomings of traditional mental disorder diagnoses, which suffer from arbitrary boundaries between psychopathology and normality, frequent disorder co-occurrence, heterogeneity within disorders, and diagnostic instability. This paper synthesizes evidence on the validity and utility of the thought disorder and detachment spectra of HiTOP. These spectra are composed of symptoms and maladaptive traits currently subsumed within schizophrenia, other psychotic disorders, and schizotypal, paranoid and schizoid personality disorders. Thought disorder ranges from normal reality testing, to maladaptive trait psychoticism, to hallucinations and delusions. Detachment ranges from introversion, to maladaptive detachment, to blunted affect and avolition. Extensive evidence supports the validity of thought disorder and detachment spectra, as each spectrum reflects common genetics, environmental risk factors, childhood antecedents, cognitive abnormalities, neural alterations, biomarkers, and treatment response. Some of these characteristics are specific to one spectrum and others are shared, suggesting the existence of an overarching psychosis superspectrum. Further research is needed to extend this model, such as clarifying whether mania and dissociation belong to thought disorder, and explicating processes that drive development of the spectra and their subdimensions. Compared to traditional diagnoses, the thought disorder and detachment spectra demonstrated substantially improved utility: greater reliability, larger explanatory and predictive power, and higher acceptability to clinicians. Validated measures are available to implement the system in practice. The more informative, reliable and valid characterization of psychosis-related psychopathology offered by HiTOP can make diagnosis more useful for research and clinical care.
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Affiliation(s)
- Roman Kotov
- Department of PsychiatryStony Brook UniversityStony BrookNYUSA
| | | | | | - Michael N. Dretsch
- Walter Reed Army Institute of Research, US Army Medical Research Directorate ‐ WestSilver SpringMDUSA
| | | | | | | | - Kelsey Hobbs
- Department of PsychologyUniversity of MinnesotaMinneapolisMNUSA
| | - Ulrich Reininghaus
- Department of Public Mental Health, Central Institute of Mental Health, Medical Faculty MannheimUniversity of HeidelbergGermany,ESRC Centre for Society and Mental HealthKing's College LondonLondonUK,Centre for Epidemiology and Public HealthInstitute of Psychiatry, Psychology & Neuroscience, King's College LondonLondonUK
| | - Tim Slade
- Matilda Centre for Research in Mental Health and Substance AbuseUniversity of SydneySydneyNSWAustralia
| | - Susan C. South
- Department of Psychological SciencesPurdue UniversityWest LafayetteINUSA
| | - Matthew Sunderland
- Matilda Centre for Research in Mental Health and Substance AbuseUniversity of SydneySydneyNSWAustralia
| | | | | | | | - David H. Zald
- Department of PsychologyVanderbilt UniversityNashvilleTNUSA
| | | | - David Watson
- Department of PsychologyUniversity of Notre DameSouth BendINUSA
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33
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Mazza MG, Lucchi S, Rossetti A, Clerici M. Neutrophil-lymphocyte ratio, monocyte-lymphocyte ratio and platelet-lymphocyte ratio in non-affective psychosis: A meta-analysis and systematic review. World J Biol Psychiatry 2020; 21:326-338. [PMID: 30806142 DOI: 10.1080/15622975.2019.1583371] [Citation(s) in RCA: 83] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Objectives: Neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR) and monocyte/lymphocyte ratio (MLR) are inexpensive and reproducible biomarkers of inflammation. This is the first meta-analysis exploring the role of NLR, MLR and PLR in non-affective psychosis.Methods: Eight studies have been identified from the main electronic databases. Meta-analyses based on random-effects models have been carried out generating pooled standardised mean differences (SMDs) between non-affective psychotic patients and healthy controls (HCs).Results: Subjects with non-affective psychosis had a significant higher NLR and MLR as compared with HC (respectively SMD = 0.715; P < 0.001; I2=57.565% and SMD = 0.417; P = 0.001; I2=65.754%), confirmed by heterogeneity-based sensitivity analysis. Subgroup analyses showed no differences in effect size across different study characteristics, including drug treatment status, diagnosis, and setting. Meta-regression showed that age influenced the relationship between non-affective psychosis and MLR. A trend of significance, not confirmed by heterogeneity-based sensitivity analysis, was observed in PLR with patients showing higher PLR than HC.Conclusions: Our meta-analysis supports the hypothesis that an inflammatory activation occurs in non-affective psychosis and inflammatory ratios, especially NLR and MLR, may be useful to detect this activation.
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Affiliation(s)
- Mario Gennaro Mazza
- Department of Medicine and Surgery, University of Milano Bicocca, Monza, Italy
| | - Sara Lucchi
- Department of Medicine and Surgery, University of Milano Bicocca, Monza, Italy
| | - Aurora Rossetti
- Department of Medicine and Surgery, University of Milano Bicocca, Monza, Italy
| | - Massimo Clerici
- Department of Medicine and Surgery, University of Milano Bicocca, Monza, Italy
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34
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Hess JL, Tylee DS, Barve R, de Jong S, Ophoff RA, Kumarasinghe N, Tooney P, Schall U, Gardiner E, Beveridge NJ, Scott RJ, Yasawardene S, Perera A, Mendis J, Carr V, Kelly B, Cairns M, Tsuang MT, Glatt SJ. Transcriptomic abnormalities in peripheral blood in bipolar disorder, and discrimination of the major psychoses. Schizophr Res 2020; 217:124-135. [PMID: 31391148 PMCID: PMC6997041 DOI: 10.1016/j.schres.2019.07.036] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 07/20/2019] [Accepted: 07/23/2019] [Indexed: 02/07/2023]
Abstract
We performed a transcriptome-wide meta-analysis and gene co-expression network analysis to identify genes and gene networks dysregulated in the peripheral blood of bipolar disorder (BD) cases relative to unaffected comparison subjects, and determined the specificity of the transcriptomic signatures of BD and schizophrenia (SZ). Nineteen genes and 4 gene modules were significantly differentially expressed in BD cases. Thirteen gene modules were shown to be differentially expressed in a combined case-group of BD and SZ subjects called "major psychosis", including genes biologically linked to apoptosis, reactive oxygen, chromatin remodeling, and immune signaling. No modules were differentially expressed between BD and SZ cases. Machine-learning classifiers trained to separate diagnostic classes based solely on gene expression profiles could distinguish BD cases from unaffected comparison subjects with an area under the curve (AUC) of 0.724, as well as BD cases from SZ cases with AUC = 0.677 in withheld test samples. We introduced a novel and straightforward method called "polytranscript risk scoring" that could distinguish BD cases from unaffected subjects (AUC = 0.672) and SZ cases (AUC = 0.607) significantly better than expected by chance. Taken together, our results highlighted gene expression alterations common to BD and SZ that involve biological processes of inflammation, oxidative stress, apoptosis, and chromatin regulation, and highlight disorder-specific changes in gene expression that discriminate the major psychoses.
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Affiliation(s)
- Jonathan L. Hess
- Psychiatric Genetic Epidemiology & Neurobiology Laboratory (PsychGENe Lab); Departments of Psychiatry and Behavioral Sciences & Neuroscience and Physiology; SUNY Upstate Medical University; Syracuse, NY, U.S.A
| | - Daniel S. Tylee
- Psychiatric Genetic Epidemiology & Neurobiology Laboratory (PsychGENe Lab); Departments of Psychiatry and Behavioral Sciences & Neuroscience and Physiology; SUNY Upstate Medical University; Syracuse, NY, U.S.A
| | - Rahul Barve
- Psychiatric Genetic Epidemiology & Neurobiology Laboratory (PsychGENe Lab); Departments of Psychiatry and Behavioral Sciences & Neuroscience and Physiology; SUNY Upstate Medical University; Syracuse, NY, U.S.A
| | - Simone de Jong
- MRC Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, UK
| | - Roel A. Ophoff
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Behavior, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, California, U.S.A.,Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Nishantha Kumarasinghe
- School of Medicine & Public Health, The University of Newcastle, Callaghan, Newcastle, Australia.,Department of Anatomy, Faculty of Medical Sciences, University of Sri Jayawardenepura, Nugegoda, Sri Lanka,Faculty of Medicine, Sir John Kotelawala Defence University, Ratmalana, Sri Lanka
| | - Paul Tooney
- School of Biomedical Sciences & Pharmacy, Faculty of Health, The University of Newcastle, New South Wales, Australia,Hunter Medical Research Institute, Newcastle, Australia
| | - Ulrich Schall
- School of Medicine & Public Health, The University of Newcastle, Callaghan, Newcastle, Australia.,Priority Centre for Brain & Mental Health Research, The University of Newcastle, Callaghan, Newcastle, Australia
| | - Erin Gardiner
- School of Biomedical Sciences & Pharmacy, Faculty of Health, The University of Newcastle, New South Wales, Australia,Priority Centre for Brain & Mental Health Research, The University of Newcastle, Callaghan, Newcastle, Australia
| | - Natalie Jane Beveridge
- School of Medicine & Public Health, The University of Newcastle, Callaghan, Newcastle, Australia.,Hunter Medical Research Institute, Newcastle, Australia,Priority Centre for Brain & Mental Health Research, The University of Newcastle, Callaghan, Newcastle, Australia
| | - Rodney J. Scott
- School of Biomedical Sciences & Pharmacy, Faculty of Health, The University of Newcastle, New South Wales, Australia,Hunter Medical Research Institute, Newcastle, Australia
| | - Surangi Yasawardene
- Department of Anatomy, Faculty of Medical Sciences, University of Sri Jayawardenepura, Nugegoda, Sri Lanka
| | - Antionette Perera
- Department of Anatomy, Faculty of Medical Sciences, University of Sri Jayawardenepura, Nugegoda, Sri Lanka
| | - Jayan Mendis
- Department of Anatomy, Faculty of Medical Sciences, University of Sri Jayawardenepura, Nugegoda, Sri Lanka
| | - Vaughan Carr
- School of Psychiatry, University of New South Wales, Kensington, New South Wales, Australia
| | - Brian Kelly
- School of Medicine & Public Health, The University of Newcastle, Callaghan, Newcastle, Australia.,Hunter Medical Research Institute, Newcastle, Australia,Priority Centre for Brain & Mental Health Research, The University of Newcastle, Callaghan, Newcastle, Australia
| | - Murray Cairns
- School of Biomedical Sciences & Pharmacy, Faculty of Health, The University of Newcastle, New South Wales, Australia,Hunter Medical Research Institute, Newcastle, Australia,Priority Centre for Brain & Mental Health Research, The University of Newcastle, Callaghan, Newcastle, Australia
| | | | - Ming T. Tsuang
- Center for Behavioral Genomics, Department of Psychiatry, Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA; Harvard Institute of Psychiatric Epidemiology and Genetics, Boston, USA
| | - Stephen J. Glatt
- Psychiatric Genetic Epidemiology & Neurobiology Laboratory (PsychGENe Lab); Departments of Psychiatry and Behavioral Sciences & Neuroscience and Physiology; SUNY Upstate Medical University; Syracuse, NY, U.S.A.,Please address correspondence to: Dr. Stephen J. Glatt, 3710 Neuroscience Research Building, Institute for Human Performance, 505 Irving Avenue, Syracuse, NY 13202, , Phone: 1 (315) 464-7742
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35
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van Mierlo HC, Schot A, Boks MPM, de Witte LD. The association between schizophrenia and the immune system: Review of the evidence from unbiased 'omic-studies'. Schizophr Res 2020; 217:114-123. [PMID: 31130400 DOI: 10.1016/j.schres.2019.05.028] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 05/17/2019] [Accepted: 05/18/2019] [Indexed: 01/04/2023]
Abstract
A role for immune processes in the pathogenesis of schizophrenia has been suggested by genetic and epidemiological studies, as well as cross-sectional studies on blood and brain samples. However, results are heterogeneous, which is likely caused by low samples sizes, insufficient control of confounders that influence immune processes, and potentially publication bias. Large hypothesis-free 'omic' studies partially circumvent these problems and could provide further evidence for a role of immune pathways in schizophrenia. In this review we assessed whether the largest genome, transcriptome and methylome studies in schizophrenia to date support a link with the immune system. We constructed an overview of the schizophrenia-associated genes and transcripts that were identified in these large 'omic' studies. We then performed a hypothesis-driven analysis to examine the association and enrichment of immune system-related genes and transcripts in these datasets. Additionally, we reviewed secondary analyses that were previously performed on these 'omic' studies. Except for the link between complement factor 4 (C4), we found limited evidence for a role of microglia and immune processes among genetic risk variants. Transcriptome and methylome studies point towards alterations in immune system related genes, pathways and cells. This includes changes in microglia, as well as complement, nuclear factor-κB, toll-like receptor and interferon signaling pathways. Many of these associated immune-related genes and pathways have been shown to be involved in neurodevelopment and neuronal functioning. Additional replication of these findings is needed, but once further conformation is provided, these findings could be a potentially interesting target for future therapies.
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Affiliation(s)
- Hans C van Mierlo
- Department of Psychiatry, UMC Utrecht Brain Center, 3508GA Utrecht, the Netherlands
| | - Aron Schot
- Department of Psychiatry, UMC Utrecht Brain Center, 3508GA Utrecht, the Netherlands
| | - Marco P M Boks
- Department of Psychiatry, UMC Utrecht Brain Center, 3508GA Utrecht, the Netherlands
| | - Lot D de Witte
- Department of Psychiatry, Icahn School of Medicine, New York, United States of America; Mental Illness Research, Education and Clinical Center (MIRECC), James J Peters VA Medical Center, Bronx, NY, United States of America.
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36
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Santarelli DM, Carroll AP, Cairns HM, Tooney PA, Cairns MJ. Schizophrenia-associated MicroRNA-Gene Interactions in the Dorsolateral Prefrontal Cortex. GENOMICS PROTEOMICS & BIOINFORMATICS 2020; 17:623-634. [PMID: 32006661 PMCID: PMC7212302 DOI: 10.1016/j.gpb.2019.10.003] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Revised: 10/01/2019] [Accepted: 10/23/2019] [Indexed: 12/14/2022]
Abstract
Schizophrenia-associated anomalies in gene expression in postmortem brain can be attributed to a combination of genetic and environmental influences. Given the small effect size of common variants, it is likely that we may only see the combined impact of some of these at the pathway level in small postmortem studies. At the gene level, however, there may be more impact from common environmental exposures mediated by influential epigenomic modifiers, such as microRNA (miRNA). We hypothesise that dysregulation of miRNAs and their alteration of gene expression have significant implications in the pathophysiology of schizophrenia. In this study, we integrate changes in cortical gene and miRNA expression to identify regulatory interactions and networks associated with the disorder. Gene expression analysis in post-mortem prefrontal dorsolateral cortex (BA 46) (n = 74 matched pairs of schizophrenia, schizoaffective, and control samples) was integrated with miRNA expression in the same cohort to identify gene-miRNA regulatory networks. A significant gene-miRNA interaction network was identified, including miR-92a, miR-495, and miR-134, which converged with differentially expressed genes in pathways involved in neurodevelopment and oligodendrocyte function. The capacity for miRNA to directly regulate gene expression through respective binding sites in BCL11A, PLP1, and SYT11 was also confirmed to support the biological relevance of this integrated network model. The observations in this study support the hypothesis that miRNA dysregulation is an important factor in the complex pathophysiology of schizophrenia.
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Affiliation(s)
- Danielle M Santarelli
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW 2308, Australia; Centre for Brain and Mental Health Research, Hunter Medical Research Institute, Newcastle, NSW 2305, Australia
| | - Adam P Carroll
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW 2308, Australia; Centre for Brain and Mental Health Research, Hunter Medical Research Institute, Newcastle, NSW 2305, Australia
| | - Heath M Cairns
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW 2308, Australia; Centre for Brain and Mental Health Research, Hunter Medical Research Institute, Newcastle, NSW 2305, Australia
| | - Paul A Tooney
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW 2308, Australia; Centre for Brain and Mental Health Research, Hunter Medical Research Institute, Newcastle, NSW 2305, Australia
| | - Murray J Cairns
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW 2308, Australia; Centre for Brain and Mental Health Research, Hunter Medical Research Institute, Newcastle, NSW 2305, Australia.
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37
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Mazza MG, Capellazzi M, Tagliabue I, Lucchi S, Rossetti A, Clerici M. Neutrophil-lymphocyte, monocyte-lymphocyte and platelet-lymphocyte ratio in schizoaffective disorder compared to schizophrenia. Gen Hosp Psychiatry 2019; 61:86-87. [PMID: 31280919 DOI: 10.1016/j.genhosppsych.2019.06.013] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Revised: 06/25/2019] [Accepted: 06/27/2019] [Indexed: 10/26/2022]
Affiliation(s)
- Mario Gennaro Mazza
- Department of Medicine and Surgery, University of Milano Bicocca, Monza, MB, Italy.
| | - Martina Capellazzi
- Department of Medicine and Surgery, University of Milano Bicocca, Monza, MB, Italy
| | - Ilaria Tagliabue
- Department of Medicine and Surgery, University of Milano Bicocca, Monza, MB, Italy
| | - Sara Lucchi
- Department of Medicine and Surgery, University of Milano Bicocca, Monza, MB, Italy
| | - Aurora Rossetti
- Department of Medicine and Surgery, University of Milano Bicocca, Monza, MB, Italy
| | - Massimo Clerici
- Department of Medicine and Surgery, University of Milano Bicocca, Monza, MB, Italy
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Jian X, Chen J, Li Z, Song Z, Zhou J, Xu W, Liu Y, Shen J, Wang Y, Yi Q, Shi Y. SLC39A8 is a risk factor for schizophrenia in Uygur Chinese: a case-control study. BMC Psychiatry 2019; 19:293. [PMID: 31533672 PMCID: PMC6751796 DOI: 10.1186/s12888-019-2240-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Accepted: 08/15/2019] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Schizophrenia is a severe mental disease with high morbidity and heritability. The SLC39A8 gene is located in 4q24 and encodes a protein that transports many metal ions. Multiple previous studies found that one of the most pleiotropic single nucleotide polymorphisms (SNPs) in SLC39A8, rs13107325, is associated with schizophrenia in the European population. However, the polymorphism of this locus is rare in other populations. In China, the Han Chinese and the Uygur Chinese are two ethnic populations that originate from different races. METHODS A case-control study was conducted with 983 schizophrenia cases and 1230 healthy controls of the Chinese Uygur population. To validate the most promising SNP, meta-analyses were conducted with the Han Chinese and the European PGC2 data sets reported previously. RESULTS A susceptible locus, rs10014145 (pallele = 0.014, pallele = 0.098 after correction; pgenotype = 0.004, pgenotype = 0.032 after correction) was identified in case-control study of the Chinese Uygur population. Further, the association between rs10014145 and schizophrenia was supported by a meta-analysis of Han and Uygur Chinese samples (pooled OR [95% CI] =1.10 [1.03-1.17], Z = 2.73, p = 0.006). The association between rs10014145 and schizophrenia was not significant in a meta-analysis of combined Chinese and European samples (pooled OR [95% CI] =1.07 [1.00-1.14], Z = 1.88, and p = 0.06). In addition, the "CCAC" haplotype of rs4698844-rs233814-rs13114343-rs151394 was significantly associated with schizophrenia in Uygur Chinese (P = 0.003, corrected p = 0.012). CONCLUSIONS The results of this study support that SLC39A8 is a susceptible gene for schizophrenia in the populations of Han Chinese and Uygur Chinese in China, further studies are suggested to validate the association.
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Affiliation(s)
- Xuemin Jian
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education) and the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China
| | - Jianhua Chen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education) and the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Zhiqiang Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education) and the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China
- Affiliated Hospital of Qingdao University and Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao, Shandong, 266003, People's Republic of China
| | - Zhijian Song
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education) and the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China
| | - Juan Zhou
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education) and the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China
| | - Wei Xu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education) and the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China
| | - Yahui Liu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education) and the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China
| | - Jiawei Shen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education) and the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China
| | - Yonggang Wang
- Department of Neurology, School of Medicine, Renji Hospital, Shanghai Jiao Tong University, Shanghai, 200127, People's Republic of China.
| | - Qizhong Yi
- Psychological Medicine Center, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, People's Republic of China.
| | - Yongyong Shi
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education) and the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China.
- Shanghai key laboratory of Sleep Disordered Breathing, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University, Shanghai, People's Republic of China.
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China.
- Affiliated Hospital of Qingdao University and Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao, Shandong, 266003, People's Republic of China.
- Institute of Social Cognitive and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China.
- Institute of Neuropsychiatric Science and Systems Biological Medicine, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China.
- Shanghai Changning Mental Health Center, Shanghai, 200030, People's Republic of China.
- Department of Psychiatry, First Teaching Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830054, People's Republic of China.
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Gilabert-Juan J, López-Campos G, Sebastiá-Ortega N, Guara-Ciurana S, Ruso-Julve F, Prieto C, Crespo-Facorro B, Sanjuán J, Moltó MD. Time dependent expression of the blood biomarkers EIF2D and TOX in patients with schizophrenia. Brain Behav Immun 2019; 80:909-915. [PMID: 31078689 DOI: 10.1016/j.bbi.2019.05.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2019] [Revised: 05/05/2019] [Accepted: 05/08/2019] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND During last years, there has been an intensive search for blood biomarkers in schizophrenia to assist in diagnosis, prognosis and clinical management of the disease. METHODS In this study, we first conducted a weighted gene coexpression network analysis to address differentially expressed genes in peripheral blood from patients with chronic schizophrenia (n = 30) and healthy controls (n = 15). The discriminating performance of the candidate genes was further tested in an independent cohort of patients with first-episode schizophrenia (n = 124) and healthy controls (n = 54), and in postmortem brain samples (cingulate and prefrontal cortices) from patients with schizophrenia (n = 34) and healthy controls (n = 35). RESULTS The expression of the Eukaryotic Translation Initiation Factor 2D (EIF2D) gene, which is involved in protein synthesis regulation, was increased in the chronic patients of schizophrenia. On the contrary, the expression of the Thymocyte Selection-Associated High Mobility Group Box (TOX) gene, involved in immune function, was reduced. EIF2D expression was also altered in first-episode schizophrenia patients, but showing reduced levels. Any of the postmortem brain areas studied did not show differences of expression of both genes. CONCLUSIONS EIF2D and TOX are putative blood markers of chronic patients of schizophrenia, which expression change from the onset to the chronic disease, unraveling new biological pathways that can be used for the development of new intervention strategies in the diagnosis and prognosis of schizophrenia disease.
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Affiliation(s)
- Javier Gilabert-Juan
- Department of Genetics, Universitat de València, Valencia, Spain; Neurobiology Unit, Cell Biology Department, Interdisciplinary Research Structure for Biotechnology and Biomedicine (BIOTECMED), Universitat de València, Valencia, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; INCLIVA, Valencia, Spain.
| | | | - Noelia Sebastiá-Ortega
- Department of Genetics, Universitat de València, Valencia, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; INCLIVA, Valencia, Spain
| | | | - Fulgencio Ruso-Julve
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; University Hospital Marqués de Valdecilla, IDIVAL, Department of Psychiatry, School of Medicine, University of Cantabria, Santander, Spain
| | - Carlos Prieto
- Servicio de Bioinformática, Nucleus, Universidad de Salamanca, Salamanca, Spain
| | - Benedicto Crespo-Facorro
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; University Hospital Marqués de Valdecilla, IDIVAL, Department of Psychiatry, School of Medicine, University of Cantabria, Santander, Spain
| | - Julio Sanjuán
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; INCLIVA, Valencia, Spain; Unit of Psychiatry, Universitat de València, Valencia, Spain
| | - María Dolores Moltó
- Department of Genetics, Universitat de València, Valencia, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain; INCLIVA, Valencia, Spain
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Çalışkan M, Manduchi E, Rao HS, Segert JA, Beltrame MH, Trizzino M, Park Y, Baker SW, Chesi A, Johnson ME, Hodge KM, Leonard ME, Loza B, Xin D, Berrido AM, Hand NJ, Bauer RC, Wells AD, Olthoff KM, Shaked A, Rader DJ, Grant SFA, Brown CD. Genetic and Epigenetic Fine Mapping of Complex Trait Associated Loci in the Human Liver. Am J Hum Genet 2019; 105:89-107. [PMID: 31204013 PMCID: PMC6612522 DOI: 10.1016/j.ajhg.2019.05.010] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Accepted: 05/13/2019] [Indexed: 12/14/2022] Open
Abstract
Deciphering the impact of genetic variation on gene regulation is fundamental to understanding common, complex human diseases. Although histone modifications are important markers of gene regulatory elements of the genome, any specific histone modification has not been assayed in more than a few individuals in the human liver. As a result, the effects of genetic variation on histone modification states in the liver are poorly understood. Here, we generate the most comprehensive genome-wide dataset of two epigenetic marks, H3K4me3 and H3K27ac, and annotate thousands of putative regulatory elements in the human liver. We integrate these findings with genome-wide gene expression data collected from the same human liver tissues and high-resolution promoter-focused chromatin interaction maps collected from human liver-derived HepG2 cells. We demonstrate widespread functional consequences of natural genetic variation on putative regulatory element activity and gene expression levels. Leveraging these extensive datasets, we fine-map a total of 74 GWAS loci that have been associated with at least one complex phenotype. Our results reveal a repertoire of genes and regulatory mechanisms governing complex disease development and further the basic understanding of genetic and epigenetic regulation of gene expression in the human liver tissue.
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Affiliation(s)
- Minal Çalışkan
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Elisabetta Manduchi
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Biostatistics, Epidemiology, & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - H Shanker Rao
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Julian A Segert
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Marcia Holsbach Beltrame
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Marco Trizzino
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - YoSon Park
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Samuel W Baker
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Alessandra Chesi
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Matthew E Johnson
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Kenyaita M Hodge
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Michelle E Leonard
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Baoli Loza
- Division of Transplant Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Dong Xin
- Division of Transplant Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Andrea M Berrido
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Nicholas J Hand
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Robert C Bauer
- Division of Cardiology, Columbia University, New York, NY 10032, USA
| | - Andrew D Wells
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Kim M Olthoff
- Division of Transplant Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Abraham Shaked
- Division of Transplant Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Daniel J Rader
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Struan F A Grant
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Christopher D Brown
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
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Leirer DJ, Iyegbe CO, Di Forti M, Patel H, Carra E, Fraietta S, Colizzi M, Mondelli V, Quattrone D, Lally J, Ajnakina O, Lee SH, Curtis CJ, Breen G, Pariante C, Aitchison K, Dazzan P, Murray RM, Dobson RJB, Newhouse SJ. Differential gene expression analysis in blood of first episode psychosis patients. Schizophr Res 2019; 209:88-97. [PMID: 31113746 PMCID: PMC6677921 DOI: 10.1016/j.schres.2019.05.011] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Revised: 02/22/2019] [Accepted: 05/05/2019] [Indexed: 12/26/2022]
Abstract
BACKGROUND Psychosis is a condition influenced by an interaction of environmental and genetic factors. Gene expression studies can capture these interactions; however, studies are usually performed in patients who are in remission. This study uses blood of first episode psychosis patients, in order to characterise deregulated pathways associated with psychosis symptom dimensions. METHODS Peripheral blood from 149 healthy controls and 131 first episode psychosis patients was profiled using Illumina HT-12 microarrays. A case/control differential expression analysis was performed, followed by correlation of gene expression with positive and negative syndrome scale (PANSS) scores. Enrichment analyses were performed on the associated gene lists. We test for pathway differences between first episode psychosis patients who qualify for a Schizophrenia diagnosis against those who do not. RESULTS A total of 978 genes were differentially expressed and enriched for pathways associated to immune function and the mitochondria. Using PANSS scores we found that positive symptom severity was correlated with immune function, while negative symptoms correlated with mitochondrial pathways. CONCLUSIONS Our results identified gene expression changes correlated with symptom severity and showed that key pathways are modulated by positive and negative symptom dimensions.
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Affiliation(s)
- Daniel J Leirer
- MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology and Neuroscience, Box P080, De Crespigny Park, SE5 8AF London, UK.
| | - Conrad O Iyegbe
- Department of Psychosis Studies, Institute of Psychiatry, Kings College London, Box P092, De Crespigny Park, SE5 8AF London, UK
| | - Marta Di Forti
- MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology and Neuroscience, Box P080, De Crespigny Park, SE5 8AF London, UK
| | - Hamel Patel
- MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology and Neuroscience, Box P080, De Crespigny Park, SE5 8AF London, UK; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, Box P080, De Crespigny Park, SE5 8AF London, UK
| | - Elena Carra
- Department of Psychosis Studies, Institute of Psychiatry, Kings College London, Box P092, De Crespigny Park, SE5 8AF London, UK
| | - Sara Fraietta
- Department of Psychosis Studies, Institute of Psychiatry, Kings College London, Box P092, De Crespigny Park, SE5 8AF London, UK
| | - Marco Colizzi
- Department of Psychosis Studies, Institute of Psychiatry, Kings College London, Box P092, De Crespigny Park, SE5 8AF London, UK
| | - Valeria Mondelli
- Department of Psychological Medicine, Institute of Psychiatry, Kings College London, De Crespigny Park, SE5 8AF London, UK
| | - Diego Quattrone
- MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology and Neuroscience, Box P080, De Crespigny Park, SE5 8AF London, UK
| | - John Lally
- Department of Psychosis Studies, Institute of Psychiatry, Kings College London, Box P092, De Crespigny Park, SE5 8AF London, UK
| | - Olesya Ajnakina
- Department of Psychosis Studies, Institute of Psychiatry, Kings College London, Box P092, De Crespigny Park, SE5 8AF London, UK
| | - Sang Hyuck Lee
- MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology and Neuroscience, Box P080, De Crespigny Park, SE5 8AF London, UK; NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London
| | - Charles J Curtis
- MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology and Neuroscience, Box P080, De Crespigny Park, SE5 8AF London, UK; NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London
| | - Gerome Breen
- MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology and Neuroscience, Box P080, De Crespigny Park, SE5 8AF London, UK; NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London
| | - Carmine Pariante
- Department of Psychological Medicine, Institute of Psychiatry, Kings College London, De Crespigny Park, SE5 8AF London, UK
| | - Katherine Aitchison
- Departments of Psychiatry and Medical Genetics, University of Alberta, 11361-87 Avenue, AB T6G 2E1, Edmonton, Canada
| | - Paola Dazzan
- MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology and Neuroscience, Box P080, De Crespigny Park, SE5 8AF London, UK; Department of Psychological Medicine, Institute of Psychiatry, Kings College London, De Crespigny Park, SE5 8AF London, UK
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Kings College London, Box P092, De Crespigny Park, SE5 8AF London, UK
| | - Richard J B Dobson
- NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, Box P080, De Crespigny Park, SE5 8AF London, UK
| | - Stephen J Newhouse
- MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology and Neuroscience, Box P080, De Crespigny Park, SE5 8AF London, UK; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, Box P080, De Crespigny Park, SE5 8AF London, UK
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Abstract
BACKGROUND This paper aims to synthesise the literature on machine learning (ML) and big data applications for mental health, highlighting current research and applications in practice. METHODS We employed a scoping review methodology to rapidly map the field of ML in mental health. Eight health and information technology research databases were searched for papers covering this domain. Articles were assessed by two reviewers, and data were extracted on the article's mental health application, ML technique, data type, and study results. Articles were then synthesised via narrative review. RESULTS Three hundred papers focusing on the application of ML to mental health were identified. Four main application domains emerged in the literature, including: (i) detection and diagnosis; (ii) prognosis, treatment and support; (iii) public health, and; (iv) research and clinical administration. The most common mental health conditions addressed included depression, schizophrenia, and Alzheimer's disease. ML techniques used included support vector machines, decision trees, neural networks, latent Dirichlet allocation, and clustering. CONCLUSIONS Overall, the application of ML to mental health has demonstrated a range of benefits across the areas of diagnosis, treatment and support, research, and clinical administration. With the majority of studies identified focusing on the detection and diagnosis of mental health conditions, it is evident that there is significant room for the application of ML to other areas of psychology and mental health. The challenges of using ML techniques are discussed, as well as opportunities to improve and advance the field.
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Affiliation(s)
- Adrian B R Shatte
- Federation University, School of Science, Engineering & Information Technology,Melbourne,Australia
| | - Delyse M Hutchinson
- Deakin University, Centre for Social and Early Emotional Development, School of Psychology, Faculty of Health,Geelong,Australia
| | - Samantha J Teague
- Deakin University, Centre for Social and Early Emotional Development, School of Psychology, Faculty of Health,Geelong,Australia
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Dysregulation of a specific immune-related network of genes biologically defines a subset of schizophrenia. Transl Psychiatry 2019; 9:156. [PMID: 31150013 PMCID: PMC6544656 DOI: 10.1038/s41398-019-0486-6] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2018] [Revised: 03/22/2019] [Accepted: 04/29/2019] [Indexed: 12/31/2022] Open
Abstract
Currently, the clinical diagnosis of schizophrenia relies solely on self-reporting and clinical interview, and likely comprises heterogeneous biological subsets. Such subsets may be defined by an underlying biology leading to solid biomarkers. A transgenic rat model modestly overexpressing the full-length, non-mutant Disrupted-in-Schizophrenia 1 (DISC1) protein (tgDISC1 rat) was generated that defines such a subset, inspired by our previous identification of insoluble DISC1 protein in post mortem brains from patients with chronic mental illness. Besides specific phenotypes such as DISC1 protein pathology, abnormal dopamine homeostasis, and changes in neuroanatomy and behavior, this animal model also shows subtle disturbances in overarching signaling pathways relevant for schizophrenia. In a reverse-translational approach, assuming that both the animal model and a patient subset share common disturbed signaling pathways, we identified differentially expressed transcripts from peripheral blood mononuclear cells of tgDISC1 rats that revealed an interconnected set of dysregulated genes, led by decreased expression of regulator of G-protein signaling 1 (RGS1), chemokine (C-C) ligand 4 (CCL4), and other immune-related transcripts enriched in T-cell and macrophage signaling and converging in one module after weighted gene correlation network analysis. Testing expression of this gene network in two independent cohorts of patients with schizophrenia versus healthy controls (n = 16/50 and n = 54/45) demonstrated similar expression changes. The two top markers RGS1 and CCL4 defined a subset of 27% of patients with 97% specificity. Thus, analogous aberrant signaling pathways can be identified by a blood test in an animal model and a corresponding schizophrenia patient subset, suggesting that in this animal model tailored pharmacotherapies for this patient subset could be achieved.
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Postmortem transcriptional profiling reveals widespread increase in inflammation in schizophrenia: a comparison of prefrontal cortex, striatum, and hippocampus among matched tetrads of controls with subjects diagnosed with schizophrenia, bipolar or major depressive disorder. Transl Psychiatry 2019; 9:151. [PMID: 31123247 PMCID: PMC6533277 DOI: 10.1038/s41398-019-0492-8] [Citation(s) in RCA: 109] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 05/03/2019] [Indexed: 11/30/2022] Open
Abstract
Psychiatric disorders such as schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) arise from complex interactions between genetic and environmental factors. Common genetic variants associated with multiple psychiatric disorders suggest that shared genetic architecture could contribute to divergent clinical syndromes. To evaluate shared transcriptional alterations across connected brain regions, Affymetrix microarrays were used to profile postmortem dorsolateral prefrontal cortex (DLPFC), hippocampus, and associative striatum from 19 well-matched tetrads of subjects with SCZ, BD, MDD, or unaffected controls. SCZ subjects showed a substantial burden of differentially expressed genes across all examined brain regions with the greatest effects in hippocampus, whereas BD and MDD showed less robust alterations. Pathway analysis of transcriptional profiles compared across diagnoses demonstrated commonly enriched pathways between all three disorders in hippocampus, significant overlap between SCZ and BD in DLPFC, but no significant overlap of enriched pathways between disorders in striatum. SCZ samples showed increased expression of transcripts associated with inflammation across all brain regions examined, which was not evident in BD or MDD, or in rat brain following chronic dosing with antipsychotic drugs. Several markers of inflammation were confirmed by RT-PCR in hippocampus, including S100A8/9, IL-6, MAFF, APOLD1, IFITM3, and BAG3. A cytokine ELISA panel showed significant increases in IL-2 and IL-12p70 protein content in hippocampal tissue collected from same SCZ subjects when compared to matched control subjects. These data suggest an overlapping subset of dysregulated pathways across psychiatric disorders; however, a widespread increase in inflammation appears to be a specific feature of the SCZ brain and is not likely to be attributable to chronic antipsychotic drug treatment.
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Wu M, Fang K, Wang W, Lin W, Guo L, Wang J. Identification of key genes and pathways for Alzheimer’s disease via combined analysis of genome-wide expression profiling in the hippocampus. BIOPHYSICS REPORTS 2019. [DOI: 10.1007/s41048-019-0086-2] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
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Kim S, Jo Y, Webster MJ, Lee D. Shared co-expression networks in frontal cortex of the normal aged brain and schizophrenia. Schizophr Res 2019; 204:253-261. [PMID: 30224231 DOI: 10.1016/j.schres.2018.09.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Revised: 08/17/2018] [Accepted: 09/11/2018] [Indexed: 11/25/2022]
Abstract
Previous studies on the brain of people with schizophrenia have identified structural changes and gene expression changes, suggesting that brain aging maybe accelerated in people with schizophrenia. To better characterize gene expression profiles in schizophrenia and in the aged population we constructed co-expression networks using RNA-Seq data from frontal cortex. The first data set analysed was from 62 subjects with schizophrenia and 51 unaffected controls ranging in age from 19 to 63 years. The second separate data set was from normal control individuals ranging in age from 29 to 106 years. In the first data set, we found two co-expression modules significantly associated with schizophrenia. One was a downregulated co-expression module enriched for neuron function related genes and the other was an upregulated immune/inflammation-related module. In the second data set of normal individuals, we found seven co-expression modules significantly correlated with age. A comparison of the co-expression modules from the two data sets revealed a significant consensus in nodes associated with schizophrenia and those associated with normal aging. The results indicate that a co-expression module related to neuronal function is downregulated and an immune/inflammation related co-expression module is upregulated, and associated with cells of the blood vessels, in both schizophrenia and in normal aging. This finding adds further support to the hypothesis that there may be accelerated brain aging in schizophrenia.
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Affiliation(s)
- Sanghyeon Kim
- Stanley Brain Research Laboratory, Stanley Medical Research Institute, 9800 Medical Center Drive, Rockville, MD 20850, United States of America.
| | - Yousang Jo
- Department of Bio and Brain Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea
| | - Maree J Webster
- Stanley Brain Research Laboratory, Stanley Medical Research Institute, 9800 Medical Center Drive, Rockville, MD 20850, United States of America
| | - Doheon Lee
- Department of Bio and Brain Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea.
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Zimmermann CA, Arloth J, Santarelli S, Löschner A, Weber P, Schmidt MV, Spengler D, Binder EB. Stress dynamically regulates co-expression networks of glucocorticoid receptor-dependent MDD and SCZ risk genes. Transl Psychiatry 2019; 9:41. [PMID: 30696808 PMCID: PMC6351530 DOI: 10.1038/s41398-019-0373-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Revised: 11/16/2018] [Accepted: 01/01/2019] [Indexed: 01/04/2023] Open
Abstract
Early-life adversity is an important risk factor for major depressive disorder (MDD) and schizophrenia (SCZ) that interacts with genetic factors to confer disease risk through mechanisms that are still insufficiently understood. One downstream effect of early-life adversity is the activation of glucocorticoid receptor (GR)-dependent gene networks that drive acute and long-term adaptive behavioral and cellular responses to stress. We have previously shown that genetic variants that moderate GR-induced gene transcription (GR-response eSNPs) are significantly enriched among risk variants from genome-wide association studies (GWASs) for MDD and SCZ. Here, we show that the 63 transcripts regulated by these disease-associated functional genetic variants form a tight glucocorticoid-responsive co-expression network (termed GCN). We hypothesized that changes in the correlation structure of this GCN may contribute to early-life adversity-associated disease risk. Therefore, we analyzed the effects of different qualities of social support and stress throughout life on GCN formation across distinct brain regions using a translational mouse model. We observed that different qualities of social experience substantially affect GCN structure in a highly brain region-specific manner. GCN changes were predominantly found in two functionally interconnected regions, the ventral hippocampus and the hypothalamus, two brain regions previously shown to be of relevance for the stress response, as well as psychiatric disorders. Overall, our results support the hypothesis that a subset of genetic variants may contribute to risk for MDD and SCZ by altering circuit-level effects of early and adult social experiences on GCN formation and structure.
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Affiliation(s)
- Christoph A. Zimmermann
- 0000 0000 9497 5095grid.419548.5Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | - Janine Arloth
- 0000 0000 9497 5095grid.419548.5Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | - Sara Santarelli
- 0000 0000 9497 5095grid.419548.5Department of Stress Neurobiology and Neurogenetics, Max Planck Institute of Psychiatry, Munich, Germany
| | - Anne Löschner
- 0000 0000 9497 5095grid.419548.5Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | - Peter Weber
- 0000 0000 9497 5095grid.419548.5Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | - Mathias V. Schmidt
- 0000 0000 9497 5095grid.419548.5Department of Stress Neurobiology and Neurogenetics, Max Planck Institute of Psychiatry, Munich, Germany
| | - Dietmar Spengler
- 0000 0000 9497 5095grid.419548.5Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | - Elisabeth B. Binder
- 0000 0000 9497 5095grid.419548.5Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany ,Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
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48
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Misiak B, Frydecka D, Stanczykiewicz B, Samochowiec J. Editorial: Peripheral Markers of Immune Response in Major Psychiatric Disorders: Where Are We Now and Where Do We Want to Be? Front Psychiatry 2019; 10:5. [PMID: 30723427 PMCID: PMC6349819 DOI: 10.3389/fpsyt.2019.00005] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2018] [Accepted: 01/04/2019] [Indexed: 11/25/2022] Open
Affiliation(s)
- Błazej Misiak
- Department of Genetics, Wroclaw Medical University, Wrocław, Poland
| | - Dorota Frydecka
- Department of Psychiatry, Wroclaw Medical University, Wrocław, Poland
| | | | - Jerzy Samochowiec
- Department of Psychiatry, Pomeranian Medical University, Szczecin, Poland
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49
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Dopamine perturbation of gene co-expression networks reveals differential response in schizophrenia for translational machinery. Transl Psychiatry 2018; 8:278. [PMID: 30546022 PMCID: PMC6293320 DOI: 10.1038/s41398-018-0325-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Accepted: 11/13/2018] [Indexed: 12/02/2022] Open
Abstract
The dopaminergic hypothesis of schizophrenia (SZ) postulates that positive symptoms of SZ, in particular psychosis, are due to disturbed neurotransmission via the dopamine (DA) receptor D2 (DRD2). However, DA is a reactive molecule that yields various oxidative species, and thus has important non-receptor-mediated effects, with empirical evidence of cellular toxicity and neurodegeneration. Here we examine non-receptor-mediated effects of DA on gene co-expression networks and its potential role in SZ pathology. Transcriptomic profiles were measured by RNA-seq in B-cell transformed lymphoblastoid cell lines from 514 SZ cases and 690 controls, both before and after exposure to DA ex vivo (100 μM). Gene co-expression modules were identified using Weighted Gene Co-expression Network Analysis for both baseline and DA-stimulated conditions, with each module characterized for biological function and tested for association with SZ status and SNPs from a genome-wide panel. We identified seven co-expression modules under baseline, of which six were preserved in DA-stimulated data. One module shows significantly increased association with SZ after DA perturbation (baseline: P = 0.023; DA-stimulated: P = 7.8 × 10-5; ΔAIC = -10.5) and is highly enriched for genes related to ribosomal proteins and translation (FDR = 4 × 10-141), mitochondrial oxidative phosphorylation, and neurodegeneration. SNP association testing revealed tentative QTLs underlying module co-expression, notably at FASTKD2 (top P = 2.8 × 10-6), a gene involved in mitochondrial translation. These results substantiate the role of translational machinery in SZ pathogenesis, providing insights into a possible dopaminergic mechanism disrupting mitochondrial function, and demonstrates the utility of disease-relevant functional perturbation in the study of complex genetic etiologies.
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Karpiński P, Samochowiec J, Frydecka D, Sąsiadek MM, Misiak B. Further evidence for depletion of peripheral blood natural killer cells in patients with schizophrenia: A computational deconvolution study. Schizophr Res 2018; 201:243-248. [PMID: 29681501 DOI: 10.1016/j.schres.2018.04.026] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2018] [Revised: 03/20/2018] [Accepted: 04/14/2018] [Indexed: 11/16/2022]
Abstract
Dysregulation of innate and adaptive immunity is increasingly being recognized as one of core characteristics of schizophrenia pathophysiology. Several studies have revealed that patients with schizophrenia present various alterations in the levels of distinct leukocyte subpopulations. However, studies addressing this point have provided mixed results. Therefore, in this study we translated a computational deconvolution algorithm in order to estimate counts of distinct leukocyte subpopulations in peripheral blood of patients with schizophrenia. Our analysis was based on publicly available data from peripheral blood DNA methylation profiling in 711 schizophrenia patients and 713 healthy controls (2 independent samples). In both datasets, there were significantly lower levels of CD8 and NK cells together with significantly higher levels of granulocytes. However, the levels of CD8 cells were insignificant after controlling for age and sex differences in one dataset. Our results indicate that patients with schizophrenia present innate immunity dysregulation in terms of NK cells depletion and increased levels of granulocytes. Longitudinal studies of various clinical subgroups of schizophrenia patients are required in order to disentangle whether our findings reflect trait- or state-dependent alterations.
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Affiliation(s)
- Paweł Karpiński
- Department of Genetics, Wroclaw Medical University, Marcinkowskiego 1 Street, 50-368 Wroclaw, Poland
| | - Jerzy Samochowiec
- Department of Psychiatry, Pomeranian Medical University, Broniewskiego 26 Street, 71-460 Szczecin, Poland
| | - Dorota Frydecka
- Department of Psychiatry, Wroclaw Medical University, Pasteura 10 Street, 50-367 Wroclaw, Poland
| | - Maria M Sąsiadek
- Department of Genetics, Wroclaw Medical University, Marcinkowskiego 1 Street, 50-368 Wroclaw, Poland
| | - Błażej Misiak
- Department of Genetics, Wroclaw Medical University, Marcinkowskiego 1 Street, 50-368 Wroclaw, Poland.
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