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Repetto L, Chen J, Yang Z, Zhai R, Timmers PRHJ, Feng X, Li T, Yao Y, Maslov D, Timoshchuk A, Tu F, Twait EL, May-Wilson S, Muckian MD, Prins BP, Png G, Kooperberg C, Johansson Å, Hillary RF, Wheeler E, Pan L, He Y, Klasson S, Ahmad S, Peters JE, Gilly A, Karaleftheri M, Tsafantakis E, Haessler J, Gyllensten U, Harris SE, Wareham NJ, Göteson A, Lagging C, Ikram MA, van Duijn CM, Jern C, Landén M, Langenberg C, Deary IJ, Marioni RE, Enroth S, Reiner AP, Dedoussis G, Zeggini E, Sharapov S, Aulchenko YS, Butterworth AS, Mälarstig A, Wilson JF, Navarro P, Shen X. The genetic landscape of neuro-related proteins in human plasma. Nat Hum Behav 2024:10.1038/s41562-024-01963-z. [PMID: 39210026 DOI: 10.1038/s41562-024-01963-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 07/22/2024] [Indexed: 09/04/2024]
Abstract
Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioural traits and the disease aetiology of neuropsychiatric disorders. Here the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,000 individuals for 184 neuro-related proteins in human plasma. The analysis identified 125 cis-regulatory protein quantitative trait loci (cis-pQTL) and 164 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. At the cis-pQTL, multiple proteins shared a genetic basis with human behavioural traits such as alcohol and food intake, smoking and educational attainment, as well as neurological conditions and psychiatric disorders such as pain, neuroticism and schizophrenia. Integrating with established drug information, the causal inference analysis validated 52 out of 66 matched combinations of protein targets and diseases or side effects with available drugs while suggesting hundreds of repurposing and new therapeutic targets.
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Affiliation(s)
- Linda Repetto
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- Health Data Science Centre, Fondazione Human Technopole, Milan, Italy
| | - Jiantao Chen
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Zhijian Yang
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ranran Zhai
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Paul R H J Timmers
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Xiao Feng
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Ting Li
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Yue Yao
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Denis Maslov
- MSU Institute for Artificial Intelligence, Lomonosov Moscow State University, Moscow, Russia
| | - Anna Timoshchuk
- MSU Institute for Artificial Intelligence, Lomonosov Moscow State University, Moscow, Russia
| | - Fengyu Tu
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Emma L Twait
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, Netherlands
| | - Sebastian May-Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Marisa D Muckian
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Bram P Prins
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Grace Png
- Institute of Translational Genomics, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Technical University of Munich (TUM), TUM School of Medicine and Health, Munich, Germany
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Åsa Johansson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Eleanor Wheeler
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Lu Pan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yazhou He
- Department of Epidemiology and Medical Statistics, Division of Oncology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Sofia Klasson
- Institute of Biomedicine, Department of Laboratory Medicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Shahzad Ahmad
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - James E Peters
- Department of Immunology and Inflammation, Faculty of Medicine, Imperial College London, London, UK
| | - Arthur Gilly
- Institute of Translational Genomics, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | | | | | - Jeffrey Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Ulf Gyllensten
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Sarah E Harris
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, UK
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Andreas Göteson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Cecilia Lagging
- Institute of Biomedicine, Department of Laboratory Medicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Clinical Genetics and Genomics, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
| | | | | | - Christina Jern
- Institute of Biomedicine, Department of Laboratory Medicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Clinical Genetics and Genomics, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Mikael Landén
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Computational Medicine, Berlin Institute of Health (BIH) at Charité-Universitätsmedizin Berlin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Ian J Deary
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Stefan Enroth
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Alexander P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Center and Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - George Dedoussis
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University of Athens, Athens, Greece
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Technical University of Munich (TUM) and Klinikum Rechts der Isar, TUM School of Medicine and Health, Munich, Germany
| | - Sodbo Sharapov
- MSU Institute for Artificial Intelligence, Lomonosov Moscow State University, Moscow, Russia
- Biostatistics Unit-Population and Medical Genomics Programme, Genomics Research Centre, Fondazione Human Technopole, Milan, Italy
| | - Yurii S Aulchenko
- MSU Institute for Artificial Intelligence, Lomonosov Moscow State University, Moscow, Russia
- Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia
| | - Adam S Butterworth
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Behaviour, University of Cambridge, Cambridge, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Anders Mälarstig
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Emerging Science and Innovation, Pfizer Worldwide Research, Development and Medical, Cambridge, UK
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Pau Navarro
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Xia Shen
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China.
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK.
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China.
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
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Smith BJ, Guest PC, Martins-de-Souza D. Maximizing Analytical Performance in Biomolecular Discovery with LC-MS: Focus on Psychiatric Disorders. ANNUAL REVIEW OF ANALYTICAL CHEMISTRY (PALO ALTO, CALIF.) 2024; 17:25-46. [PMID: 38424029 DOI: 10.1146/annurev-anchem-061522-041154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/02/2024]
Abstract
In this review, we discuss the cutting-edge developments in mass spectrometry proteomics and metabolomics that have brought improvements for the identification of new disease-based biomarkers. A special focus is placed on psychiatric disorders, for example, schizophrenia, because they are considered to be not a single disease entity but rather a spectrum of disorders with many overlapping symptoms. This review includes descriptions of various types of commonly used mass spectrometry platforms for biomarker research, as well as complementary techniques to maximize data coverage, reduce sample heterogeneity, and work around potentially confounding factors. Finally, we summarize the different statistical methods that can be used for improving data quality to aid in reliability and interpretation of proteomics findings, as well as to enhance their translatability into clinical use and generalizability to new data sets.
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Affiliation(s)
- Bradley J Smith
- 1Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas, São Paulo, Brazil;
| | - Paul C Guest
- 1Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas, São Paulo, Brazil;
- 2Department of Psychiatry, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
- 3Laboratory of Translational Psychiatry, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
| | - Daniel Martins-de-Souza
- 1Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas, São Paulo, Brazil;
- 4Experimental Medicine Research Cluster, University of Campinas, São Paulo, Brazil
- 5National Institute of Biomarkers in Neuropsychiatry, National Council for Scientific and Technological Development, São Paulo, Brazil
- 6D'Or Institute for Research and Education, São Paulo, Brazil
- 7INCT in Modelling Human Complex Diseases with 3D Platforms (Model3D), São Paulo, Brazil
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Tunset ME, Haslene-Hox H, Van Den Bossche T, Maleki S, Vaaler A, Kondziella D. Blood-borne extracellular vesicles of bacteria and intestinal cells in patients with psychotic disorders. Nord J Psychiatry 2023; 77:686-695. [PMID: 37354486 DOI: 10.1080/08039488.2023.2223572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 05/23/2023] [Accepted: 05/28/2023] [Indexed: 06/26/2023]
Abstract
BACKGROUND Human cells and bacteria secrete extracellular vesicles (EV) which play a role in intercellular communication. EV from the host intestinal epithelium are involved in the regulation of bacterial gene expression and growth. Bacterial EV (bactEV) produced in the intestine can pass to various tissues where they deliver biomolecules to many kinds of cells, including neurons. Emerging data indicate that gut microbiota is altered in patients with psychotic disorders. We hypothesized that the amount and content of blood-borne EV from intestinal cells and bactEV in psychotic patients would differ from healthy controls. METHODS We analyzed for human intestinal proteins by proteomics, for bactEV by metaproteomic analysis, and by measuring the level of lipopolysaccharide (LPS) in blood-borne EV from patients with psychotic disorders (n = 25), tested twice, in the acute phase of psychosis and after improvement, with age- and sex-matched healthy controls (n = 25). RESULTS Patients with psychotic disorders had lower LPS levels in their EV compared to healthy controls (p = .027). Metaproteome analyses confirmed LPS finding and identified Firmicutes and Bacteroidetes as dominating phyla. Total amounts of human intestine proteins in EV isolated from blood was lower in patients compared to controls (p = .02). CONCLUSIONS Our results suggest that bactEV and host intestinal EV are decreased in patients with psychosis and that this topic is worthy of further investigation given potential pathophysiological implications. Possible mechanisms involve dysregulation of the gut microbiota by host EV, altered translocation of bactEV to systemic circulation where bactEV can interact with both the brain and the immune system.
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Affiliation(s)
- Mette Elise Tunset
- Department of Psychosis and Rehabilitation, Psychiatry Clinic, St. Olavs University Hospital, Trondheim, Norway
- Department of Mental Health, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Hanne Haslene-Hox
- Department of Biotechnology and Nanomedicine, SINTEF, Trondheim, Norway
| | - Tim Van Den Bossche
- VIB - UGent Center for Medical Biotechnology, VIB, Ghent, Belgium
- Department of Biomolecular Medicine, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - Susan Maleki
- Department of Biotechnology and Nanomedicine, SINTEF, Trondheim, Norway
| | - Arne Vaaler
- Department of Mental Health, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Department of Acute Psychiatry, Psychiatry Clinic, St. Olavs University Hospital, Trondheim, Norway
| | - Daniel Kondziella
- Department of Neurology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
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4
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Wang LJ, Huang YC, Lin PY, Lee Y, Hung CF, Hsu ST, Huang LH, Li SC. BST-1 as a serum protein biomarker involved in neutrophil infiltration in schizophrenia. World J Biol Psychiatry 2022; 23:537-547. [PMID: 34870552 DOI: 10.1080/15622975.2021.2014151] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
OBJECTIVES Schizophrenia is a serious mental illness. The serum protein biomarkers of schizophrenia were explored using isobaric tags for relative and absolute quantitation (iTRAQ) technology. The underlying function of the identified protein biomarker was also investigated. METHODS We first collected serum samples from 12 schizophrenia patients and 12 healthy control (HC) subjects, followed by global screening with iTRAQ and tandem mass spectrometry (LC-MS/MS). In total, 691 serum proteins were detected and eight proteins, including ZYX, OSCAR, TPM4, SDPR, BST1, ARGHDB, ITIH5 and SH3BGRL3, were selected for further specific validation with enzyme-linked immunosorbent assay (ELISA) on the serum samples from 52 schizophrenia patients and 50 HC subjects. RESULTS Schizophrenia patients had significantly lower serum level of BST1 and higher ITIH5 level than the HC subjects did. Using the levels of BST1, ITIH5 and OSCAR combined with machine learning algorithm, we developed a prediction model of schizophrenia with an auROC value 0.78. Moreover, in vitro cell assay confirmed that BST1 significantly repressed neutrophil infiltration through endothelial layer, highlighted the anti-inflammation nature of BST1. CONCLUSIONS Four novel protein markers (BST1, ITIH5, SDPR, and OSCAR) of schizophrenia were identified, and BST-1 could serve as a serum protein biomarker involved in neutrophil infiltration in schizophrenia.
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Affiliation(s)
- Liang-Jen Wang
- Department of Child and Adolescent Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Yu-Chi Huang
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Pao-Yen Lin
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan.,Institute for Translational Research in Biomedical Sciences, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Yu Lee
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Chi-Fa Hung
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Su-Ting Hsu
- Kaohsiung Municipal Kai-Syuan Psychiatric Hospital, Kaohsiung, Taiwan
| | - Lien-Hung Huang
- Department of Neurosurgery, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Sung-Chou Li
- Center for Mitochondrial Research and Medicine and Genomics and Proteomics Core Laboratory, Department of Medical Research, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
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5
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Rodrigues JE, Martinho A, Santa C, Madeira N, Coroa M, Santos V, Martins MJ, Pato CN, Macedo A, Manadas B. Systematic Review and Meta-Analysis of Mass Spectrometry Proteomics Applied to Human Peripheral Fluids to Assess Potential Biomarkers of Schizophrenia. Int J Mol Sci 2022; 23:ijms23094917. [PMID: 35563307 PMCID: PMC9105255 DOI: 10.3390/ijms23094917] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 04/24/2022] [Accepted: 04/26/2022] [Indexed: 01/27/2023] Open
Abstract
Mass spectrometry (MS)-based techniques can be a powerful tool to identify neuropsychiatric disorder biomarkers, improving prediction and diagnosis ability. Here, we evaluate the efficacy of MS proteomics applied to human peripheral fluids of schizophrenia (SCZ) patients to identify disease biomarkers and relevant networks of biological pathways. Following PRISMA guidelines, a search was performed for studies that used MS proteomics approaches to identify proteomic differences between SCZ patients and healthy control groups (PROSPERO database: CRD42021274183). Nineteen articles fulfilled the inclusion criteria, allowing the identification of 217 differentially expressed proteins. Gene ontology analysis identified lipid metabolism, complement and coagulation cascades, and immune response as the main enriched biological pathways. Meta-analysis results suggest the upregulation of FCN3 and downregulation of APO1, APOA2, APOC1, and APOC3 in SCZ patients. Despite the proven ability of MS proteomics to characterize SCZ, several confounding factors contribute to the heterogeneity of the findings. In the future, we encourage the scientific community to perform studies with more extensive sampling and validation cohorts, integrating omics with bioinformatics tools to provide additional comprehension of differentially expressed proteins. The produced information could harbor potential proteomic biomarkers of SCZ, contributing to individualized prognosis and stratification strategies, besides aiding in the differential diagnosis.
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Affiliation(s)
- João E. Rodrigues
- CNC—Center for Neuroscience and Cell Biology, University of Coimbra, 3004-504 Coimbra, Portugal; (J.E.R.); (A.M.); (C.S.); (M.J.M.)
- CIBB—Centre for Innovative Biomedicine and Biotechnology, University of Coimbra, 3004-504 Coimbra, Portugal; (M.C.); (V.S.)
| | - Ana Martinho
- CNC—Center for Neuroscience and Cell Biology, University of Coimbra, 3004-504 Coimbra, Portugal; (J.E.R.); (A.M.); (C.S.); (M.J.M.)
- CIBB—Centre for Innovative Biomedicine and Biotechnology, University of Coimbra, 3004-504 Coimbra, Portugal; (M.C.); (V.S.)
| | - Catia Santa
- CNC—Center for Neuroscience and Cell Biology, University of Coimbra, 3004-504 Coimbra, Portugal; (J.E.R.); (A.M.); (C.S.); (M.J.M.)
- CIBB—Centre for Innovative Biomedicine and Biotechnology, University of Coimbra, 3004-504 Coimbra, Portugal; (M.C.); (V.S.)
| | - Nuno Madeira
- Faculty of Medicine, University of Coimbra, 3004-504 Coimbra, Portugal;
- Psychiatry Department, Centro Hospitalar e Universitário de Coimbra, 3004-561 Coimbra, Portugal
- CIBIT—Coimbra Institute for Biomedical Imaging and Translational Research, University of Coimbra, 3000-548 Coimbra, Portugal
| | - Manuel Coroa
- CIBB—Centre for Innovative Biomedicine and Biotechnology, University of Coimbra, 3004-504 Coimbra, Portugal; (M.C.); (V.S.)
- Faculty of Medicine, University of Coimbra, 3004-504 Coimbra, Portugal;
- Psychiatry Department, Centro Hospitalar e Universitário de Coimbra, 3004-561 Coimbra, Portugal
| | - Vítor Santos
- CIBB—Centre for Innovative Biomedicine and Biotechnology, University of Coimbra, 3004-504 Coimbra, Portugal; (M.C.); (V.S.)
- Faculty of Medicine, University of Coimbra, 3004-504 Coimbra, Portugal;
- Psychiatry Department, Centro Hospitalar e Universitário de Coimbra, 3004-561 Coimbra, Portugal
| | - Maria J. Martins
- CNC—Center for Neuroscience and Cell Biology, University of Coimbra, 3004-504 Coimbra, Portugal; (J.E.R.); (A.M.); (C.S.); (M.J.M.)
- CIBB—Centre for Innovative Biomedicine and Biotechnology, University of Coimbra, 3004-504 Coimbra, Portugal; (M.C.); (V.S.)
- Medical Services, University of Coimbra, 3004-517 Coimbra, Portugal
| | - Carlos N. Pato
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA;
| | - Antonio Macedo
- Faculty of Medicine, University of Coimbra, 3004-504 Coimbra, Portugal;
- Psychiatry Department, Centro Hospitalar e Universitário de Coimbra, 3004-561 Coimbra, Portugal
- CIBIT—Coimbra Institute for Biomedical Imaging and Translational Research, University of Coimbra, 3000-548 Coimbra, Portugal
- Correspondence: (A.M.); (B.M.)
| | - Bruno Manadas
- CNC—Center for Neuroscience and Cell Biology, University of Coimbra, 3004-504 Coimbra, Portugal; (J.E.R.); (A.M.); (C.S.); (M.J.M.)
- CIBB—Centre for Innovative Biomedicine and Biotechnology, University of Coimbra, 3004-504 Coimbra, Portugal; (M.C.); (V.S.)
- III Institute for Interdisciplinary Research, University of Coimbra (IIIUC), 3030-789 Coimbra, Portugal
- Correspondence: (A.M.); (B.M.)
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6
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Burghardt KJ, Calme G, Caruso M, Howlett BH, Sanders E, Msallaty Z, Mallisho A, Seyoum B, Qi YA, Zhang X, Yi Z. Profiling the Skeletal Muscle Proteome in Patients on Atypical Antipsychotics and Mood Stabilizers. Brain Sci 2022; 12:259. [PMID: 35204022 PMCID: PMC8870450 DOI: 10.3390/brainsci12020259] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 02/09/2022] [Accepted: 02/10/2022] [Indexed: 02/04/2023] Open
Abstract
Atypical antipsychotics (AAP) are used in the treatment of severe mental illness. They are associated with several metabolic side effects including insulin resistance. The skeletal muscle is the primary tissue responsible for insulin-stimulated glucose uptake. Dysfunction of protein regulation within the skeletal muscle following treatment with AAPs may play a role in the associated metabolic side effects. The objective of this study was to measure protein abundance in the skeletal muscle of patients on long-term AAP or mood stabilizer treatment. Cross-sectional muscle biopsies were obtained from patients with bipolar disorder and global protein abundance was measured using stable isotope labeling by amino acid (SILAC) combined with high-performance liquid chromatography-electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS). Sixteen patients completed muscle biopsies and were included in the proteomic analyses. A total of 40 proteins were significantly different between the AAP group and the mood stabilizer group. In-silico pathway analysis identified significant enrichment in several pathways including glucose metabolism, cell cycle, apoptosis, and folate metabolism. Proteome abundance changes also differed based on protein biological processes and function. In summary, significant differences in proteomic profiles were identified in the skeletal muscle between patients on AAPs and mood stabilizers. Future work is needed to validate these findings in prospectively sampled populations.
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Affiliation(s)
- Kyle J. Burghardt
- Department of Pharmacy Practice, University Eugene Applebaum College of Pharmacy and Health Sciences, Wayne State University, 259 Mack Avenue, Suite 2190, Detroit, MI 48201, USA; (G.C.); (B.H.H.); (E.S.)
| | - Griffin Calme
- Department of Pharmacy Practice, University Eugene Applebaum College of Pharmacy and Health Sciences, Wayne State University, 259 Mack Avenue, Suite 2190, Detroit, MI 48201, USA; (G.C.); (B.H.H.); (E.S.)
| | - Michael Caruso
- Department of Pharmaceutical Science, Eugene Applebaum College of Pharmacy and Health Sciences, Wayne State University, 259 Mack Avenue, Detroit, MI 48201, USA; (M.C.); (X.Z.); (Z.Y.)
| | - Bradley H. Howlett
- Department of Pharmacy Practice, University Eugene Applebaum College of Pharmacy and Health Sciences, Wayne State University, 259 Mack Avenue, Suite 2190, Detroit, MI 48201, USA; (G.C.); (B.H.H.); (E.S.)
| | - Elani Sanders
- Department of Pharmacy Practice, University Eugene Applebaum College of Pharmacy and Health Sciences, Wayne State University, 259 Mack Avenue, Suite 2190, Detroit, MI 48201, USA; (G.C.); (B.H.H.); (E.S.)
| | - Zaher Msallaty
- Division of Endocrinology, School of Medicine, Wayne State University, 4201 St Antoine, Detroit, MI 48201, USA; (Z.M.); (A.M.); (B.S.)
| | - Abdullah Mallisho
- Division of Endocrinology, School of Medicine, Wayne State University, 4201 St Antoine, Detroit, MI 48201, USA; (Z.M.); (A.M.); (B.S.)
| | - Berhane Seyoum
- Division of Endocrinology, School of Medicine, Wayne State University, 4201 St Antoine, Detroit, MI 48201, USA; (Z.M.); (A.M.); (B.S.)
| | - Yue A. Qi
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD 20892, USA;
| | - Xiangmin Zhang
- Department of Pharmaceutical Science, Eugene Applebaum College of Pharmacy and Health Sciences, Wayne State University, 259 Mack Avenue, Detroit, MI 48201, USA; (M.C.); (X.Z.); (Z.Y.)
| | - Zhengping Yi
- Department of Pharmaceutical Science, Eugene Applebaum College of Pharmacy and Health Sciences, Wayne State University, 259 Mack Avenue, Detroit, MI 48201, USA; (M.C.); (X.Z.); (Z.Y.)
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7
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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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8
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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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9
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Lee H, Rhee SJ, Kim J, Lee Y, Kim H, Lee J, Lee K, Shin H, Kim H, Lee TY, Kim M, Kim EY, Kim SH, Ahn YM, Kwon JS, Han D, Ha K. Predictive protein markers for depression severity in mood disorders: A preliminary trans-diagnostic approach study. J Psychiatr Res 2021; 142:63-72. [PMID: 34325234 DOI: 10.1016/j.jpsychires.2021.07.041] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 04/01/2021] [Accepted: 07/21/2021] [Indexed: 12/20/2022]
Abstract
Depression is a common symptom of many mental disorders, especially major depressive disorder (MDD) and bipolar disorder (BD). Previous studies have reported that these diseases share common pathophysiological pathways; therefore, this study elucidated whether the plasma levels of protein markers related to common depressive symptoms differed between patients with BD and those with MDD. Plasma samples of 71 patients with mood disorders and clinical manifestations were analyzed in this study. After depleting the abundant proteins, liquid chromatography-tandem mass spectrometry and label-free quantification were performed. Five proteins, viz., cholesteryl ester transfer protein (CETP), apolipoprotein D (APOD), mannan-binding lectin serine protease 2 (MASP2), Ig lambda chain V-II region BO (IGLV2-8) and Ig kappa chain V-III region NG9 (IGKV3-20) were negatively associated with the total scores of the Hamilton depression rating scale (HAM-D), after adjusting for the covariates. CETP and APOD also showed significant negative correlations with the anhedonia/retardation and guilt/agitation scores of the HAM-D. Four proteins, namely, Ig kappa chain V-II region TEW (IGKC; IGKV2D-28), Ig lambda variable 5-45 (IGLV5-45), complement factor H (CFH) and attractin (ATRN), showed significant associations with anhedonia/retardation after adjusting for covariates. Proteins that significantly correlated with the symptoms could predict the remission state of depression (area under the curve [AUC], 0.83) and anhedonia/retardation (AUC, 0.80). Bioinformatics analysis revealed that complement activation, immune response, and lipid metabolism were significantly enriched pathways. Although our study design was cross-sectional and no controls were included, protein markers identified in this preliminary study will be further investigated in our subsequent longitudinal study.
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Affiliation(s)
- Hyunju Lee
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea; Department of Psychiatry and Behavioral Science, Seoul National University College of Medicine, Seoul, Republic of Korea.
| | - Sang Jin Rhee
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.
| | - Jayoun Kim
- Medical Research Collaborating Center, Seoul National University Hospital, Seoul, Republic of Korea.
| | - Yunna Lee
- Department of Neuropsychiatry, Kosin University Gospel Hospital, Busan, Republic of Korea.
| | - Hyeyoung Kim
- Department of Psychiatry, Inha University Hospital, Incheon, Republic of Korea.
| | - Junhee Lee
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.
| | - Kangeun Lee
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.
| | - Hyunsuk Shin
- Proteomics Core Facility, Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea.
| | - Hyeyoon Kim
- Proteomics Core Facility, Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea; Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea.
| | - Tae Young Lee
- Department of Neuropsychiatry, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea.
| | - Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.
| | - Eun Young Kim
- Department of Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.
| | - Se Hyun Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.
| | - Yong Min Ahn
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea; Department of Psychiatry and Behavioral Science, Seoul National University College of Medicine, Seoul, Republic of Korea; Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea.
| | - Jun Soo Kwon
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea; Department of Psychiatry and Behavioral Science, Seoul National University College of Medicine, Seoul, Republic of Korea; Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea; Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea.
| | - Dohyun Han
- Proteomics Core Facility, Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea.
| | - Kyooseob Ha
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea; Department of Psychiatry and Behavioral Science, Seoul National University College of Medicine, Seoul, Republic of Korea; Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea.
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10
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Lin CH, Su H, Hung CC, Lane HY, Shiea J. Characterization of Potential Protein Biomarkers for Major Depressive Disorder Using Matrix-Assisted Laser Desorption Ionization/Time-of-Flight Mass Spectrometry. Molecules 2021; 26:molecules26154457. [PMID: 34361610 PMCID: PMC8348063 DOI: 10.3390/molecules26154457] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 07/21/2021] [Accepted: 07/22/2021] [Indexed: 12/16/2022] Open
Abstract
Matrix-assisted laser desorption ionization/time-of-flight (MALDI-TOF) mass spectrometry is a sensitive analytical tool for characterizing various biomolecules in biofluids. In this study, MALDI-TOF was used to characterize potential plasma biomarkers for distinguishing patients with major depressive disorder (MDD) from patients with schizophrenia and healthy controls. To avoid interference from albumin—the predominant protein in plasma—the plasma samples were pretreated using acid hydrolysis. The results obtained by MALDI-TOF were also validated by electrospray ionization-quadrupole time-of-flight (ESI-QTOF) mass spectrometry. The analytical results were further treated with principal component analysis (PCA), hierarchical clustering analysis (HCA), and receiver operating characteristic (ROC) curve analysis. The statistical analyses showed that MDD patients could be distinguished from schizophrenia patients and healthy controls by the lack of apolipoprotein C1 (Apo C1), which, in fact, was detected in healthy controls and schizophrenia patients. This protein is suggested to be a potential plasma biomarker for distinguishing MDD patients from healthy controls and schizophrenia patients. Since sample preparation for MALDI-TOF is very simple, high-throughput plasma apolipoprotein analysis for clinical purposes is feasible.
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Affiliation(s)
- Chieh-Hsin Lin
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Kaohsiung 833401, Taiwan;
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung 404332, Taiwan
- School of Medicine, Chang Gung University, Taoyuan 333323, Taiwan
| | - Hung Su
- Department of Chemistry, National Sun Yat-Sen University, Kaohsiung 804351, Taiwan;
| | - Chung-Chieh Hung
- Department of Psychiatry & Brain Disease Research Center, China Medical University and Hospital, Taichung 404332, Taiwan;
| | - Hsien-Yuan Lane
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung 404332, Taiwan
- Department of Psychiatry & Brain Disease Research Center, China Medical University and Hospital, Taichung 404332, Taiwan;
- Department of Psychology, College of Medical and Health Sciences, Asia University, Taichung 413305, Taiwan
- Correspondence: (H.-Y.L.); (J.S.)
| | - Jentaie Shiea
- Department of Chemistry, National Sun Yat-Sen University, Kaohsiung 804351, Taiwan;
- Department of Medicinal and Applied Chemistry, Kaohsiung Medical University, Kaohsiung 807378, Taiwan
- Correspondence: (H.-Y.L.); (J.S.)
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11
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Li R, Zhou Y, Liu C, Pei C, Shu W, Zhang C, Liu L, Zhou L, Wan J. Design of Multi‐Shelled Hollow Cr
2
O
3
Spheres for Metabolic Fingerprinting. Angew Chem Int Ed Engl 2021. [DOI: 10.1002/ange.202101007] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Rongxin Li
- School of Chemistry and Molecular Engineering East China Normal University Shanghai 200241 P. R. China
| | - Yongjie Zhou
- Department of Psychiatric Rehabilitation Shenzhen Kangning Hospital Shenzhen Guangdong 518118 P. R. China
| | - Chao Liu
- School of Chemistry and Molecular Engineering East China Normal University Shanghai 200241 P. R. China
| | - Congcong Pei
- School of Chemistry and Molecular Engineering East China Normal University Shanghai 200241 P. R. China
| | - Weikang Shu
- School of Chemistry and Molecular Engineering East China Normal University Shanghai 200241 P. R. China
| | - Chaoqi Zhang
- School of Chemistry and Molecular Engineering East China Normal University Shanghai 200241 P. R. China
| | - Lianzhong Liu
- Wuhan Mental Health Center Tongji Medical College of Huazhong University of Science and Technology Wuhan Hubei 430032 P. R. China
| | - Liang Zhou
- State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of Technology Wuhan Hubei 430070 P. R. China
| | - Jingjing Wan
- School of Chemistry and Molecular Engineering East China Normal University Shanghai 200241 P. R. China
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12
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Li M, Yang X, Sun L, Qing Y, Hu X, Jiang J, Wang D, Cui G, Gao Y, Zhang E, Zhang J, Yang Y, Wan C. Decreased serum apolipoprotein A4 as a potential peripheral biomarker for patients with schizophrenia. J Psychiatr Res 2021; 137:14-21. [PMID: 33640722 DOI: 10.1016/j.jpsychires.2021.02.016] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 01/15/2021] [Accepted: 02/08/2021] [Indexed: 10/22/2022]
Abstract
Recent evidence supports an association between lipid metabolism dysfunction and the pathology of schizophrenia which has led to the search for peripheral blood-based biomarkers. The purpose of this study was to investigate the proteins involved in lipid metabolism (especially apolipoprotein) and to explore their potential as biomarkers for schizophrenia. Using multiple reaction monitoring mass spectrometry (MRM-MS), we quantified 22 proteins in serum samples of 109 healthy controls (HCs) and 111 patients with schizophrenia (SCZ), who were divided into discovery and validation sets. We found serum apolipoprotein A4 (ApoA4) to be significantly decreased in SCZ patients compared to HCs (p=1.61E-05). Moreover, the serum ApoA4 level served as an effective diagnostic tool, achieving area under the receiver operating characteristic curves (AUROC) of 0.840 in the discovery set and 0.791 in the validation set. Additionally, apolipoprotein F (ApoF), angiotensinogen (AGT), and alpha1-antichymotrypsin (ACT) levels were significantly higher in patients with schizophrenia than in healthy controls. These proteins combined with ApoA4, provided higher diagnostic accuracy for schizophrenia in the discovery set (AUROC=0.901) and in the validation set (AUROC=0.879). Our results suggest that the serum level of ApoA4 is a novel potential biomarker for schizophrenia. The proteins identified in this study expand the pool of biomarker candidates for schizophrenia and may be linked to the underlying mechanism of the disease.
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Affiliation(s)
- Minghui Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Xuhan Yang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Liya Sun
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Ying Qing
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Xiaowen Hu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Jie Jiang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Dandan Wang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Gaoping Cui
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Yan Gao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - En Zhang
- The Fourth People's Hospital of Wuhu, Wuhu, China
| | - Juan Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Yong Yang
- Suzhou Guangji Hospital, Affiliated Guangji Hospital of Soochow University, Soochow University, Suzhou, China.
| | - Chunling Wan
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China; Shanghai Mental Health Center, Shanghai Key Laboratory of Psychiatry Disorders, Shanghai Jiao Tong University, Shanghai, China.
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13
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Li R, Zhou Y, Liu C, Pei C, Shu W, Zhang C, Liu L, Zhou L, Wan J. Design of Multi-Shelled Hollow Cr 2 O 3 Spheres for Metabolic Fingerprinting. Angew Chem Int Ed Engl 2021; 60:12504-12512. [PMID: 33721392 DOI: 10.1002/anie.202101007] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 03/08/2021] [Indexed: 12/15/2022]
Abstract
Schizophrenia (SZ) detection enables effective treatment to improve the clinical outcome, but objective and reliable SZ diagnostics are still limited. An ideal diagnosis of SZ suited for robust clinical screening must address detection throughput, low invasiveness, and diagnosis accuracy. Herein, we built a multi-shelled hollow Cr2 O3 spheres (MHCSs) assisted laser desorption/ionization mass spectrometry (LDI MS) platform for the direct metabolic profiling of biofluids towards SZ diagnostics. The MHCSs displayed strong light absorption for enhanced ionization and microscale surface roughness with stability for the effective LDI of metabolites. We profiled urine and serum metabolites (≈1 μL) with the enhanced LDI efficacy in seconds. We discriminated SZ patients (SZs) from healthy controls (HCs) with the highest area under the curve (AUC) value of 1.000 for the blind test. We identified four compounds with optimal diagnostic power as a simplified metabolite panel for SZ and demonstrated the metabolite quantification for clinic use. Our approach accelerates the growth of new platforms toward a precision diagnosis in the near future.
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Affiliation(s)
- Rongxin Li
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, P. R. China
| | - Yongjie Zhou
- Department of Psychiatric Rehabilitation, Shenzhen Kangning Hospital, Shenzhen, Guangdong, 518118, P. R. China
| | - Chao Liu
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, P. R. China
| | - Congcong Pei
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, P. R. China
| | - Weikang Shu
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, P. R. China
| | - Chaoqi Zhang
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, P. R. China
| | - Lianzhong Liu
- Wuhan Mental Health Center, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, 430032, P. R. China
| | - Liang Zhou
- State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology, Wuhan, Hubei, 430070, P. R. China
| | - Jingjing Wan
- School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241, P. R. China
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14
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Santa Cruz EC, Zandonadi FDS, Fontes W, Sussulini A. A pilot study indicating the dysregulation of the complement and coagulation cascades in treated schizophrenia and bipolar disorder patients. BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS 2021; 1869:140657. [PMID: 33839315 DOI: 10.1016/j.bbapap.2021.140657] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 03/23/2021] [Accepted: 03/24/2021] [Indexed: 12/15/2022]
Abstract
A better understanding of the proteome profile after bipolar disorder (BD) and schizophrenia (SCZ) treatment, besides monitoring disease progression, may assist on the development of novel therapeutic strategies with the ability to reduce or control possible side effects. In this pilot study, proteomics analysis employing nano liquid chromatography coupled to mass spectrometry (nLC-MS) and bioinformatic tools were applied to identify differentially abundant proteins in serum of treated BD and SCZ patients. In total, 10 BD patients, 10 SCZ patients, and 14 healthy controls (HC) were included in this study. 24 serum proteins were significantly altered (p < 0.05) in BD and SCZ treated patients and, considering log2FC > 0.58, 8 proteins presented lower abundance in the BD group, while 7 proteins presented higher abundance and 2 lower abundance in SCZ group when compared against HC. Bioinformatics analysis based on these 24 proteins indicated two main altered pathways previously described in the literature; furthermore, it revealed that opposite abundances of the complement and coagulation cascades were the most significant biological processes involved in these pathologies. Moreover, we describe disease-related proteins and pathways associations suggesting the necessity of clinical follow-up improvement besides treatment, as a precaution or safety measure, along with the disease progression. Further biological validation and investigations are required to define whether there is a correlation between complement and coagulation cascade expression for BD and SCZ and cardiovascular diseases.
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Affiliation(s)
- Elisa Castañeda Santa Cruz
- Laboratory of Bioanalytics and Integrated Omics (LaBIOmics), Department of Analytical Chemistry, Institute of Chemistry, University of Campinas (UNICAMP), 13083-970 Campinas, SP, Brazil
| | - Flávia da Silva Zandonadi
- Laboratory of Bioanalytics and Integrated Omics (LaBIOmics), Department of Analytical Chemistry, Institute of Chemistry, University of Campinas (UNICAMP), 13083-970 Campinas, SP, Brazil
| | - Wagner Fontes
- Laboratory of Protein Chemistry and Biochemistry, Department of Cell Biology, Institute of Biology, University of Brasilia (UnB), 70910-900 Brasilia, DF, Brazil
| | - Alessandra Sussulini
- Laboratory of Bioanalytics and Integrated Omics (LaBIOmics), Department of Analytical Chemistry, Institute of Chemistry, University of Campinas (UNICAMP), 13083-970 Campinas, SP, Brazil; National Institute of Science and Technology for Bioanalytics - INCTBio, Institute of Chemistry, University of Campinas (UNICAMP), 13083-970 Campinas, SP, Brazil.
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15
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Föcking M, Sabherwal S, Cates HM, Scaife C, Dicker P, Hryniewiecka M, Wynne K, Rutten BPF, Lewis G, Cannon M, Nestler EJ, Heurich M, Cagney G, Zammit S, Cotter DR. Complement pathway changes at age 12 are associated with psychotic experiences at age 18 in a longitudinal population-based study: evidence for a role of stress. Mol Psychiatry 2021; 26:524-533. [PMID: 30635638 PMCID: PMC6906256 DOI: 10.1038/s41380-018-0306-z] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Revised: 09/06/2018] [Accepted: 10/30/2018] [Indexed: 02/08/2023]
Abstract
The complement cascade is a major component of the immune defence against infection, and there is increasing evidence for a role of dysregulated complement in major psychiatric disorders. We undertook a directed proteomic analysis of the complement signalling pathway (n = 29 proteins) using data-independent acquisition. Participants were recruited from the UK avon longitudinal study of parents and children (ALSPAC) cohort who participated in psychiatric assessment interviews at ages 12 and 18. Protein expression levels at age 12 among individuals who reported psychotic experiences (PEs) at age 18 (n = 64) were compared with age-matched controls (n = 67). Six out of the 29 targeted complement proteins or protein subcomponents were significantly upregulated following correction for multiple comparisons (VTN↑, C1RL↑, C8B↑, C8A↑, CFH↑, and C5↑). We then undertook an unbiased plasma proteomic analysis of mice exposed to chronic social stress and observed dysregulation of 11 complement proteins, including three that were altered in the same direction in individuals with PE (C1R↑, CFH↑, and C5↑). Our findings indicate that dysregulation of the complement protein pathway in blood is associated with incidence of psychotic experiences and that these changes may reflect exposure to stress.
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Affiliation(s)
- Melanie Föcking
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland.
| | - Sophie Sabherwal
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Hannah M Cates
- Friedman Brain Institute and Icahn School of Medicine at Mount Sinai, NY, New York, USA
| | - Caitriona Scaife
- School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin (UCD), Belfield, Dublin 4, Ireland
| | - Patrick Dicker
- Department of Epidemiology and Public Health, Royal College of Surgeons in Ireland, Dublin, Ireland
| | | | - Kieran Wynne
- School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin (UCD), Belfield, Dublin 4, Ireland
| | - Bart P F Rutten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre+, Maastricht, The Netherlands
| | | | - Mary Cannon
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Eric J Nestler
- Friedman Brain Institute and Icahn School of Medicine at Mount Sinai, NY, New York, USA
| | - Meike Heurich
- School of Pharmacy and Pharmaceutical Sciences, Cardiff University, Cardiff, UK
| | - Gerard Cagney
- School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin (UCD), Belfield, Dublin 4, Ireland
| | - Stanley Zammit
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
- Centre for Academic Mental Health, Bristol Medical School, University of Bristol, Bristol, UK
| | - David R Cotter
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland.
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16
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Mongan D, Föcking M, Healy C, Susai SR, Heurich M, Wynne K, Nelson B, McGorry PD, Amminger GP, Nordentoft M, Krebs MO, Riecher-Rössler A, Bressan RA, Barrantes-Vidal N, Borgwardt S, Ruhrmann S, Sachs G, Pantelis C, van der Gaag M, de Haan L, Valmaggia L, Pollak TA, Kempton MJ, Rutten BPF, Whelan R, Cannon M, Zammit S, Cagney G, Cotter DR, McGuire P. Development of Proteomic Prediction Models for Transition to Psychotic Disorder in the Clinical High-Risk State and Psychotic Experiences in Adolescence. JAMA Psychiatry 2021; 78:77-90. [PMID: 32857162 PMCID: PMC7450406 DOI: 10.1001/jamapsychiatry.2020.2459] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
IMPORTANCE Biomarkers that are predictive of outcomes in individuals at risk of psychosis would facilitate individualized prognosis and stratification strategies. OBJECTIVE To investigate whether proteomic biomarkers may aid prediction of transition to psychotic disorder in the clinical high-risk (CHR) state and adolescent psychotic experiences (PEs) in the general population. DESIGN, SETTING, AND PARTICIPANTS This diagnostic study comprised 2 case-control studies nested within the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) and the Avon Longitudinal Study of Parents and Children (ALSPAC). EU-GEI is an international multisite prospective study of participants at CHR referred from local mental health services. ALSPAC is a United Kingdom-based general population birth cohort. Included were EU-GEI participants who met CHR criteria at baseline and ALSPAC participants who did not report PEs at age 12 years. Data were analyzed from September 2018 to April 2020. MAIN OUTCOMES AND MEASURES In EU-GEI, transition status was assessed by the Comprehensive Assessment of At-Risk Mental States or contact with clinical services. In ALSPAC, PEs at age 18 years were assessed using the Psychosis-Like Symptoms Interview. Proteomic data were obtained from mass spectrometry of baseline plasma samples in EU-GEI and plasma samples at age 12 years in ALSPAC. Support vector machine learning algorithms were used to develop predictive models. RESULTS The EU-GEI subsample (133 participants at CHR (mean [SD] age, 22.6 [4.5] years; 68 [51.1%] male) comprised 49 (36.8%) who developed psychosis and 84 (63.2%) who did not. A model based on baseline clinical and proteomic data demonstrated excellent performance for prediction of transition outcome (area under the receiver operating characteristic curve [AUC], 0.95; positive predictive value [PPV], 75.0%; and negative predictive value [NPV], 98.6%). Functional analysis of differentially expressed proteins implicated the complement and coagulation cascade. A model based on the 10 most predictive proteins accurately predicted transition status in training (AUC, 0.99; PPV, 76.9%; and NPV, 100%) and test (AUC, 0.92; PPV, 81.8%; and NPV, 96.8%) data. The ALSPAC subsample (121 participants from the general population with plasma samples available at age 12 years (61 [50.4%] male) comprised 55 participants (45.5%) with PEs at age 18 years and 61 (50.4%) without PEs at age 18 years. A model using proteomic data at age 12 years predicted PEs at age 18 years, with an AUC of 0.74 (PPV, 67.8%; and NPV, 75.8%). CONCLUSIONS AND RELEVANCE In individuals at risk of psychosis, proteomic biomarkers may contribute to individualized prognosis and stratification strategies. These findings implicate early dysregulation of the complement and coagulation cascade in the development of psychosis outcomes.
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Affiliation(s)
- David Mongan
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Melanie Föcking
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Colm Healy
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Subash Raj Susai
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Meike Heurich
- School of Pharmacy and Pharmaceutical Sciences, Cardiff University, Cardiff, United Kingdom
| | - Kieran Wynne
- School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Dublin, Ireland
| | - Barnaby Nelson
- Centre for Youth Mental Health, University of Melbourne, Parkville, Victoria, Australia
| | - Patrick D. McGorry
- Centre for Youth Mental Health, University of Melbourne, Parkville, Victoria, Australia
| | - G. Paul Amminger
- Centre for Youth Mental Health, University of Melbourne, Parkville, Victoria, Australia
| | - Merete Nordentoft
- Mental Health Centre Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark
| | - Marie-Odile Krebs
- University Paris Descartes, Groupe Hospitalier Universitaire (GHU) Paris–Sainte Anne, Evaluation Centre for Young Adults and Adolescents (C’JAAD), Service Hospitalov–Universitaire, Institut National de la Santé et de la Recherche Medicale (INSERM) U1266, Institut de Psychiatrie (Centre National de la Recherche Scientifique [CNRS] 3557), Paris, France
| | | | - Rodrigo A. Bressan
- LiNC–Lab Interdisciplinar Neurociências Clínicas, Depto Psiquiatria, Escola Paulista de Medicina, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil
| | - Neus Barrantes-Vidal
- Departament de Psicologia Clínica i de la Salut (Universitat Autònoma de Barcelona), Fundació Sanitària Sant Pere Claver (Spain), Spanish Mental Health Research Network (Centro de Investigación Biomédica en Red de Salud Mental [CIBERSAM]), Barcelona, Spain
| | - Stefan Borgwardt
- Department of Psychiatry, Medical Faculty, University of Basel, Basel, Switzerland,Department of Psychiatry and Psychotherapy, Translational Psychiatry Unit, University zu Lübeck, Lübeck, Germany
| | - Stephan Ruhrmann
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Gabriele Sachs
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia
| | - Mark van der Gaag
- Faculty of Behavioural and Movement Sciences, Department of Clinical Psychology and EMGO+ Institute for Health and Care Research, Vrije Universiteit (VU) University, Amsterdam, the Netherlands,Department of Psychosis Research, Parnassia Psychiatric Institute, The Hague, the Netherlands
| | - Lieuwe de Haan
- Academic Medical Centre (AMC), Academic Psychiatric Centre, Department Early Psychosis, Amsterdam, the Netherlands
| | - Lucia Valmaggia
- Institute of Psychiatry, Psychology & Neuroscience, Department of Psychology, King’s College London, London, United Kingdom
| | - Thomas A. Pollak
- Institute of Psychiatry, Psychology & Neuroscience, Department of Psychosis Studies, King’s College London, London, United Kingdom
| | - Matthew J. Kempton
- Institute of Psychiatry, Psychology & Neuroscience, Department of Psychosis Studies, King’s College London, London, United Kingdom
| | - Bart P. F. Rutten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Robert Whelan
- Trinity Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Mary Cannon
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Stan Zammit
- Medical Research Council (MRC) Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom,Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Gerard Cagney
- School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Dublin, Ireland
| | - David R. Cotter
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Philip McGuire
- Institute of Psychiatry, Psychology & Neuroscience, Department of Psychosis Studies, King’s College London, London, United Kingdom
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Murtaza N, Uy J, Singh KK. Emerging proteomic approaches to identify the underlying pathophysiology of neurodevelopmental and neurodegenerative disorders. Mol Autism 2020; 11:27. [PMID: 32317014 PMCID: PMC7171839 DOI: 10.1186/s13229-020-00334-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Accepted: 04/06/2020] [Indexed: 12/18/2022] Open
Abstract
Proteomics is the large-scale study of the total protein content and their overall function within a cell through multiple facets of research. Advancements in proteomic methods have moved past the simple quantification of proteins to the identification of post-translational modifications (PTMs) and the ability to probe interactions between these proteins, spatially and temporally. Increased sensitivity and resolution of mass spectrometers and sample preparation protocols have drastically reduced the large amount of cells required and the experimental variability that had previously hindered its use in studying human neurological disorders. Proteomics offers a new perspective to study the altered molecular pathways and networks that are associated with autism spectrum disorders (ASD). The differences between the transcriptome and proteome, combined with the various types of post-translation modifications that regulate protein function and localization, highlight a novel level of research that has not been appropriately investigated. In this review, we will discuss strategies using proteomics to study ASD and other neurological disorders, with a focus on how these approaches can be combined with induced pluripotent stem cell (iPSC) studies. Proteomic analysis of iPSC-derived neurons have already been used to measure changes in the proteome caused by patient mutations, analyze changes in PTMs that resulted in altered biological pathways, and identify potential biomarkers. Further advancements in both proteomic techniques and human iPSC differentiation protocols will continue to push the field towards better understanding ASD disease pathophysiology. Proteomics using iPSC-derived neurons from individuals with ASD offers a window for observing the altered proteome, which is necessary in the future development of therapeutics against specific targets.
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Affiliation(s)
- Nadeem Murtaza
- Stem Cell and Cancer Research Institute, Department of Biochemistry and Biomedical Sciences, McMaster University, 1280 Main Street West, Hamilton, ON, L8N 3Z5, Canada
| | - Jarryll Uy
- Stem Cell and Cancer Research Institute, Department of Biochemistry and Biomedical Sciences, McMaster University, 1280 Main Street West, Hamilton, ON, L8N 3Z5, Canada
| | - Karun K Singh
- Stem Cell and Cancer Research Institute, Department of Biochemistry and Biomedical Sciences, McMaster University, 1280 Main Street West, Hamilton, ON, L8N 3Z5, Canada.
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18
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Rodrigues-Amorim D, Rivera-Baltanás T, Vallejo-Curto MDC, Rodriguez-Jamardo C, de las Heras E, Barreiro-Villar C, Blanco-Formoso M, Fernández-Palleiro P, Álvarez-Ariza M, López M, García-Caballero A, Olivares JM, Spuch C. Proteomics in Schizophrenia: A Gateway to Discover Potential Biomarkers of Psychoneuroimmune Pathways. Front Psychiatry 2019; 10:885. [PMID: 31849731 PMCID: PMC6897280 DOI: 10.3389/fpsyt.2019.00885] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2019] [Accepted: 11/11/2019] [Indexed: 12/17/2022] Open
Abstract
Schizophrenia is a severe and disabling psychiatric disorder with a complex and multifactorial etiology. The lack of consensus regarding the multifaceted dysfunction of this ailment has increased the need to explore new research lines. This research makes use of proteomics data to discover possible analytes associated with psychoneuroimmune signaling pathways in schizophrenia. Thus, we analyze plasma of 45 patients [10 patients with first-episode schizophrenia (FES) and 35 patients with chronic schizophrenia] and 43 healthy subjects by label-free liquid chromatography-tandem mass spectrometry. The analysis revealed a significant reduction in the levels of glia maturation factor beta (GMF-β), the brain-derived neurotrophic factor (BDNF), and the 115-kDa isoform of the Rab3 GTPase-activating protein catalytic subunit (RAB3GAP1) in patients with schizophrenia as compared to healthy volunteers. In conclusion, GMF-β, BDNF, and 115-kDa isoform of RAB3GAP1 showed significantly reduced levels in plasma of patients with schizophrenia, thus making them potential biomarkers in schizophrenia.
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Affiliation(s)
- Daniela Rodrigues-Amorim
- Translational Neuroscience Research Group, Galicia Sur Health Research Institute, University of Vigo, CIBERSAM, Vigo, Spain
| | - Tania Rivera-Baltanás
- Translational Neuroscience Research Group, Galicia Sur Health Research Institute, University of Vigo, CIBERSAM, Vigo, Spain
| | - María del Carmen Vallejo-Curto
- Translational Neuroscience Research Group, Galicia Sur Health Research Institute, University of Vigo, CIBERSAM, Vigo, Spain
| | - Cynthia Rodriguez-Jamardo
- Translational Neuroscience Research Group, Galicia Sur Health Research Institute, University of Vigo, CIBERSAM, Vigo, Spain
| | - Elena de las Heras
- Translational Neuroscience Research Group, Galicia Sur Health Research Institute, University of Vigo, CIBERSAM, Vigo, Spain
| | - Carolina Barreiro-Villar
- Translational Neuroscience Research Group, Galicia Sur Health Research Institute, University of Vigo, CIBERSAM, Vigo, Spain
| | - María Blanco-Formoso
- Translational Neuroscience Research Group, Galicia Sur Health Research Institute, University of Vigo, CIBERSAM, Vigo, Spain
| | - Patricia Fernández-Palleiro
- Translational Neuroscience Research Group, Galicia Sur Health Research Institute, University of Vigo, CIBERSAM, Vigo, Spain
| | - María Álvarez-Ariza
- Translational Neuroscience Research Group, Galicia Sur Health Research Institute, University of Vigo, CIBERSAM, Vigo, Spain
| | - Marta López
- Translational Neuroscience Research Group, Galicia Sur Health Research Institute, University of Vigo, CIBERSAM, Vigo, Spain
| | - Alejandro García-Caballero
- Translational Neuroscience Research Group, Galicia Sur Health Research Institute, University of Vigo, CIBERSAM, Vigo, Spain
- Department of Psychiatry, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - José Manuel Olivares
- Translational Neuroscience Research Group, Galicia Sur Health Research Institute, University of Vigo, CIBERSAM, Vigo, Spain
| | - Carlos Spuch
- Translational Neuroscience Research Group, Galicia Sur Health Research Institute, University of Vigo, CIBERSAM, Vigo, Spain
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19
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Smirnova L, Seregin A, Boksha I, Dmitrieva E, Simutkin G, Kornetova E, Savushkina O, Letova A, Bokhan N, Ivanova S, Zgoda V. The difference in serum proteomes in schizophrenia and bipolar disorder. BMC Genomics 2019; 20:535. [PMID: 31291891 PMCID: PMC6620192 DOI: 10.1186/s12864-019-5848-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Purpose of study is revealing significant differences in serum proteomes in schizophrenia and bipolar disorder (BD). RESULTS Quantitative mass-spectrometry based proteomic analysis was used to quantify proteins in the blood serum samples after the depletion of six major blood proteins. Comparison of proteome profiles of different groups revealed 27 proteins being specific for schizophrenia, and 18 - for BD. Protein set in schizophrenia was mostly associated with immune response, cell communication, cell growth and maintenance, protein metabolism and regulation of nucleic acid metabolism. Protein set in BD was mostly associated with immune response, regulating transport processes across cell membrane and cell communication, development of neurons and oligodendrocytes and cell growth. Concentrations of ankyrin repeat domain-containing protein 12 (ANKRD12) and cadherin 5 in serum samples were determined by ELISA. Significant difference between three groups was revealed in ANKRD12 concentration (p = 0.02), with maximum elevation of ANKRD12 concentration (median level) in schizophrenia followed by BD. Cadherin 5 concentration differed significantly (p = 0.035) between schizophrenic patients with prevailing positive symptoms (4.78 [2.71, 7.12] ng/ml) and those with prevailing negative symptoms (1.86 [0.001, 4.11] ng/ml). CONCLUSIONS Our results are presumably useful for discovering the new pathways involved in endogenous psychotic disorders.
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Affiliation(s)
- Liudmila Smirnova
- Mental Health Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, Tomsk, Russia
| | - Alexander Seregin
- Mental Health Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, Tomsk, Russia
| | | | - Elena Dmitrieva
- Mental Health Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, Tomsk, Russia
- Siberian State Medical University, Tomsk, Russia
| | - German Simutkin
- Mental Health Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, Tomsk, Russia
| | - Elena Kornetova
- Mental Health Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, Tomsk, Russia
- Siberian State Medical University, Tomsk, Russia
| | | | | | - Nikolay Bokhan
- Mental Health Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, Tomsk, Russia
| | - Svetlana Ivanova
- Mental Health Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, Tomsk, Russia
- Siberian State Medical University, Tomsk, Russia
| | - Victor Zgoda
- Institute of Biomedical Chemistry, Moscow, Russia
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20
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Madrid-Gambin F, Föcking M, Sabherwal S, Heurich M, English JA, O'Gorman A, Suvitaival T, Ahonen L, Cannon M, Lewis G, Mattila I, Scaife C, Madden S, Hyötyläinen T, Orešič M, Zammit S, Cagney G, Cotter DR, Brennan L. Integrated Lipidomics and Proteomics Point to Early Blood-Based Changes in Childhood Preceding Later Development of Psychotic Experiences: Evidence From the Avon Longitudinal Study of Parents and Children. Biol Psychiatry 2019; 86:25-34. [PMID: 30878195 PMCID: PMC6579334 DOI: 10.1016/j.biopsych.2019.01.018] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Revised: 01/17/2019] [Accepted: 01/17/2019] [Indexed: 01/08/2023]
Abstract
BACKGROUND The identification of early biomarkers of psychotic experiences (PEs) is of interest because early diagnosis and treatment of those at risk of future disorder is associated with improved outcomes. The current study investigated early lipidomic and coagulation pathway protein signatures of later PEs in subjects from the Avon Longitudinal Study of Parents and Children cohort. METHODS Plasma of 115 children (12 years of age) who were first identified as experiencing PEs at 18 years of age (48 cases and 67 controls) were assessed through integrated and targeted lipidomics and semitargeted proteomics approaches. We assessed the lipids, lysophosphatidylcholines (n = 11) and phosphatidylcholines (n = 61), and the protein members of the coagulation pathway (n = 22) and integrated these data with complement pathway protein data already available on these subjects. RESULTS Twelve phosphatidylcholines, four lysophosphatidylcholines, and the coagulation protein plasminogen were altered between the control and PEs groups after correction for multiple comparisons. Lipidomic and proteomic datasets were integrated into a multivariate network displaying a strong relationship between most lipids that were significantly associated with PEs and plasminogen. Finally, an unsupervised clustering approach identified four different clusters, with one of the clusters presenting the highest case-control ratio (p < .01) and associated with a higher concentration of smaller low-density lipoprotein cholesterol particles. CONCLUSIONS Our findings indicate that the lipidome and proteome of subjects who report PEs at 18 years of age are already altered at 12 years of age, indicating that metabolic dysregulation may contribute to an early vulnerability to PEs and suggesting crosstalk between these lysophosphatidylcholines, phosphatidylcholines, and coagulation and complement proteins.
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Affiliation(s)
- Francisco Madrid-Gambin
- Department of Psychiatry, Royal College of Surgeons in Ireland, Beaumont Hospital, Dublin, Ireland; Institute of Food and Health, UCD School of Agriculture and Food Science, Dublin, Ireland
| | - Melanie Föcking
- Department of Psychiatry, Royal College of Surgeons in Ireland, Beaumont Hospital, Dublin, Ireland
| | - Sophie Sabherwal
- Department of Psychiatry, Royal College of Surgeons in Ireland, Beaumont Hospital, Dublin, Ireland
| | - Meike Heurich
- School of Pharmacy and Pharmaceutical Sciences, Cardiff University, Cardiff, United Kingdom
| | - Jane A English
- Department of Psychiatry, Royal College of Surgeons in Ireland, Beaumont Hospital, Dublin, Ireland
| | - Aoife O'Gorman
- Institute of Food and Health, UCD School of Agriculture and Food Science, Dublin, Ireland
| | | | - Linda Ahonen
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Mary Cannon
- Department of Psychiatry, Royal College of Surgeons in Ireland, Beaumont Hospital, Dublin, Ireland
| | - Glyn Lewis
- Faculty of Brain Sciences, Division of Psychiatry, University College London, London, United Kingdom
| | - Ismo Mattila
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Caitriona Scaife
- Department of Psychiatry, Royal College of Surgeons in Ireland, Beaumont Hospital, Dublin, Ireland
| | - Sean Madden
- Department of Psychiatry, Royal College of Surgeons in Ireland, Beaumont Hospital, Dublin, Ireland
| | | | - Matej Orešič
- School of Medical Sciences, Örebro University, Örebro, Sweden; Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland
| | - Stanley Zammit
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom; Centre for Academic Mental Health, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Gerard Cagney
- Conway Institute, UCD School of Biomolecular and Biomedical Science, University College Dublin, Dublin, Ireland
| | - David R Cotter
- Department of Psychiatry, Royal College of Surgeons in Ireland, Beaumont Hospital, Dublin, Ireland.
| | - Lorraine Brennan
- Institute of Food and Health, UCD School of Agriculture and Food Science, Dublin, Ireland
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21
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Sabherwal S, Föcking M, English JA, Fitzsimons S, Hryniewiecka M, Wynne K, Scaife C, Healy C, Cannon M, Belton O, Zammit S, Cagney G, Cotter DR. ApoE elevation is associated with the persistence of psychotic experiences from age 12 to age 18: Evidence from the ALSPAC birth cohort. Schizophr Res 2019; 209:141-147. [PMID: 31080155 DOI: 10.1016/j.schres.2019.05.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Revised: 03/04/2019] [Accepted: 05/01/2019] [Indexed: 11/24/2022]
Abstract
Apolipoproteins, which play important roles in lipid metabolism, innate immunity and synaptic signalling, have been implicated in first episode psychosis and schizophrenia. This is the first study to investigate plasma apolipoprotein expression in children with psychotic experiences that persist into adulthood. Here, using semi-targeted proteomic analysis we compared plasma apolipoprotein expression levels in age 12 subjects who reported psychotic experiences at both age 12 and age 18 (n = 37) with age-matched subjects who only experienced psychotic experiences (PEs) at age 12 (n = 38). Participants were recruited from the UK Avon Longitudinal Study of Parents and Children (ALSPAC) cohort who participated in psychiatric assessment interviews at ages 12 and 18. We identified apoE, a protein with significant regulatory activity on cholesterol metabolism in the brain, to be significantly up regulated (p < 0.003) in those with persistent psychotic experiences. We confirmed this finding in these samples using ELISA. Our findings indicate elevated plasma apoE in age 12 children who experience PEs is associated with persistence psychotic experiences.
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Affiliation(s)
- Sophie Sabherwal
- Department of Psychiatry, Royal College of Surgeons in Ireland (RCSI), Beaumont Hospital, Dublin, Ireland.
| | - Melanie Föcking
- Department of Psychiatry, Royal College of Surgeons in Ireland (RCSI), Beaumont Hospital, Dublin, Ireland
| | - Jane A English
- Department of Psychiatry, Royal College of Surgeons in Ireland (RCSI), Beaumont Hospital, Dublin, Ireland
| | - Stephen Fitzsimons
- School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Dublin, Ireland
| | - Magdalena Hryniewiecka
- Department of Psychiatry, Royal College of Surgeons in Ireland (RCSI), Beaumont Hospital, Dublin, Ireland
| | - Kieran Wynne
- School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Dublin, Ireland
| | - Caitriona Scaife
- School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Dublin, Ireland
| | - Colm Healy
- Department of Psychiatry, Royal College of Surgeons in Ireland (RCSI), Beaumont Hospital, Dublin, Ireland
| | - Mary Cannon
- Department of Psychiatry, Royal College of Surgeons in Ireland (RCSI), Beaumont Hospital, Dublin, Ireland
| | - Orina Belton
- School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Dublin, Ireland
| | - Stanley Zammit
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK; Centre for Academic Mental Health, Bristol Medical School, University of Bristol, Bristol, UK
| | - Gerard Cagney
- School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Dublin, Ireland
| | - David R Cotter
- Department of Psychiatry, Royal College of Surgeons in Ireland (RCSI), Beaumont Hospital, Dublin, Ireland.
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22
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Cooper JD, Han SYS, Tomasik J, Ozcan S, Rustogi N, van Beveren NJM, Leweke FM, Bahn S. Multimodel inference for biomarker development: an application to schizophrenia. Transl Psychiatry 2019; 9:83. [PMID: 30745560 PMCID: PMC6370882 DOI: 10.1038/s41398-019-0419-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Revised: 12/14/2018] [Accepted: 01/24/2019] [Indexed: 02/06/2023] Open
Abstract
In the present study, to improve the predictive performance of a model and its reproducibility when applied to an independent data set, we investigated the use of multimodel inference to predict the probability of having a complex psychiatric disorder. We formed training and test sets using proteomic data (147 peptides from 77 proteins) from two-independent collections of first-onset drug-naive schizophrenia patients and controls. A set of prediction models was produced by applying lasso regression with repeated tenfold cross-validation to the training set. We used feature extraction and model averaging across the set of models to form two prediction models. The resulting models clearly demonstrated the utility of a multimodel based approach to make good (training set AUC > 0.80) and reproducible predictions (test set AUC > 0.80) for the probability of having schizophrenia. Moreover, we identified four proteins (five peptides) whose effect on the probability of having schizophrenia was modified by sex, one of which was a novel potential biomarker of schizophrenia, foetal haemoglobin. The evidence of effect modification suggests that future schizophrenia studies should be conducted in males and females separately. Future biomarker studies should consider adopting a multimodel approach and going beyond the main effects of features.
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Affiliation(s)
- Jason D. Cooper
- 0000000121885934grid.5335.0Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK
| | - Sung Yeon Sarah Han
- 0000000121885934grid.5335.0Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK
| | - Jakub Tomasik
- 0000000121885934grid.5335.0Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK
| | - Sureyya Ozcan
- 0000000121885934grid.5335.0Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK ,0000 0001 1881 7391grid.6935.9Present Address: Department of Chemistry, Middle East Technical University, Ankara, Turkey
| | - Nitin Rustogi
- 0000000121885934grid.5335.0Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK
| | - Nico J. M. van Beveren
- 000000040459992Xgrid.5645.2Department of Neuroscience, Erasmus Medical Centre, Rotterdam, Netherlands ,000000040459992Xgrid.5645.2Department of Psychiatry, Erasmus Medical Centre, Rotterdam, Netherlands ,Department “Nieuwe Kennis”, Delta Centre, for Mental Health Care, Rotterdam, Netherlands
| | - F. Markus Leweke
- 0000 0004 1936 834Xgrid.1013.3Brain and Mind Centre, University of Sydney, Sydney, Australia
| | - Sabine Bahn
- 0000000121885934grid.5335.0Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK
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23
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Proteomic Studies of Psychiatric Disorders. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2019; 1735:59-89. [PMID: 29380307 DOI: 10.1007/978-1-4939-7614-0_4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Many diseases result from programming effects in utero. This chapter describes recent advances in proteomic studies which have improved our understanding of the underlying pathophysiological pathways in the major psychiatric disorders, resulting in the development of potential novel biomarker tests. Such tests should be based on measurement of blood-based proteins given the ease of accessibility of this medium and the known connections between the periphery and the central nervous system. Most importantly, emerging biomarker tests should be developed on lab-on-a-chip and other handheld devices to enable point-of-care use. This should help to identify individuals with psychiatric disorders much sooner than ever before, which will allow more rapid treatment options for the best possible patient outcomes.
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Xu R, Liang J, Luo Y, Wan X, Li K, Qi L, Yuan W, Chen J, Wu Z, Wang M, Zhou J, Xie Y, Zhou S, He F. Mass spectrometry identification of potential biomarker proteins in the 150-kD electrophoretic band in patients with schizophrenia. Medicine (Baltimore) 2018; 97:e13553. [PMID: 30572456 PMCID: PMC6320177 DOI: 10.1097/md.0000000000013553] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Diagnosing schizophrenia is primarily based on the presentation of defined signs and symptoms, none of which is pathognomonic for this group of syndromes. However, few significant genome-wide associations between schizophrenia and individual have detected. Protein profiling of candidate serum biomarkers in schizophrenia is therefore an area of great interest. METHODS In the present study, we used a combination of 7% polyethylene glycol (PEG) enrichment of immune complexes and sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) to separate abnormal band, then analyse the band with liquid chromatography mass spectrometry (LC-MS). RESULTS There is a special 150-kD electrophoretic band in patients with schizophrenia, bipolar disorder, or depression relative to healthy controls (each 30 samples). Analysis of the band using LC-MS resulted in the identification of 11 serum proteins whose abundance was altered between patients and controls. Among them, 8 proteins (CFH, CFB, cDNA FLJ75416, zinc finger protein 729, isoform 2 of nidogen-1, diaphanous-1, cDNA FLJ77762, and cDNA FLJ58411) were up regulated, while one protein (isoform 1 of collagen alpha-1 (II) was down regulated in patients with schizophrenia, but only zinc finger protein 729 has statistics significance (P < .05). No differences were noted with regard to thrombospondin-1 or collagen alpha-2 (I) among the 3 groups. These proteins take part in several biological functions such as focal adhesion, complement cascades, ECM-receptor interaction, and Staphylococcus aureus infection. CONCLUSIONS The 150-kD electrophoretic band or zinc finger protein 729 may become biomarkers in patients with schizophrenia. In the future increasing sample size and function research of zinc finger protein 729 should be executed continuously.
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Affiliation(s)
- Ruihuan Xu
- Clinical Laboratory, Longgang Central Hospital of Shenzhen
| | - Jingwen Liang
- Clinical Laboratory, Longgang Central Hospital of Shenzhen
| | - Yi Luo
- Clinical Laboratory, Longgang Central Hospital of Shenzhen
| | - Xing Wan
- Clinical Laboratory, Longhua People's Hospital of Shenzhen
| | - Kang Li
- Clinical Laboratory, Longhua People's Hospital of Shenzhen
| | - Liguo Qi
- Acute Intervention Division at Kangning Hosptial, Shenzhen
| | - Wenbin Yuan
- Administrative Management, Longgang Central Hospital of Shenzhen
| | - Jianxia Chen
- Clinical Laboratory, Longgang Central Hospital of Shenzhen
| | - Ze Wu
- Clinical Laboratory, Longgang Hand Surgery Hospital of Shenzhen, Guangdong
| | - Mingbang Wang
- Xiamen branch, Children's Hospital of Fudan University/Xiamen Children's Hospital, Xiamen, Fujian, China; Key Laboratory of Birth Defects, Children's Hospital of Fudan University, Shanghai, China
| | - Jiaxiu Zhou
- Division of Psychology, Shenzhen Children's Hospital, Shenzhen, Guangdong
| | - Yingjun Xie
- Key Laboratory for Major Obstetric Diseases of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University
| | - Shaoming Zhou
- Division of Gastroenterology, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
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Comes AL, Papiol S, Mueller T, Geyer PE, Mann M, Schulze TG. Proteomics for blood biomarker exploration of severe mental illness: pitfalls of the past and potential for the future. Transl Psychiatry 2018; 8:160. [PMID: 30115926 PMCID: PMC6095863 DOI: 10.1038/s41398-018-0219-2] [Citation(s) in RCA: 58] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Accepted: 07/16/2018] [Indexed: 12/18/2022] Open
Abstract
Recent improvements in high-throughput proteomic approaches are likely to constitute an essential advance in biomarker discovery, holding promise for improved personalized care and drug development. These methodologies have been applied to study multivariate protein patterns and provide valuable data of peripheral tissues. To highlight findings of the last decade for three of the most common psychiatric disorders, namely schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD), we queried PubMed. Here we delve into the findings from thirty studies, which used proteomics and multiplex immunoassay approaches for peripheral blood biomarker exploration. In an explorative approach, we ran enrichment analyses in peripheral blood according to these results and ascertained the overlap between proteomic findings and genetic loci identified in genome-wide association studies (GWAS). The studies we appraised demonstrate that proteomics for psychiatric research has been heterogeneous in aims and methods and limited by insufficient sample sizes, poorly defined case definitions, methodological inhomogeneity, and confounding results constraining the conclusions that can be extracted from them. Here, we discuss possibilities for overcoming methodological challenges for the implementation of proteomic signatures in psychiatric diagnosis and offer an outlook for future investigations. To fulfill the promise of proteomics in mental disease diagnostics, future research will need large, well-defined cohorts in combination with state-of-the-art technologies.
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Affiliation(s)
- Ashley L. Comes
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital Munich, LMU, 80336 Munich, Germany ,International Max Planck Research School for Translational Psychiatry (IMPRS-TP), 80804 Munich, Germany
| | - Sergi Papiol
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital Munich, LMU, 80336 Munich, Germany ,Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University, 80336 Munich, Germany
| | - Thorsten Mueller
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital Munich, LMU, 80336 Munich, Germany
| | - Philipp E. Geyer
- 0000 0004 0491 845Xgrid.418615.fDepartment of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany ,0000 0001 0674 042Xgrid.5254.6NNF Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Matthias Mann
- 0000 0004 0491 845Xgrid.418615.fDepartment of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany ,0000 0001 0674 042Xgrid.5254.6NNF Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Thomas G. Schulze
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital Munich, LMU, 80336 Munich, Germany
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26
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English JA, Lopez LM, O’Gorman A, Föcking M, Hryniewiecka M, Scaife C, Sabherwal S, Wynne K, Dicker P, Rutten BPF, Lewis G, Zammit S, Cannon M, Cagney G, Cotter DR. Blood-Based Protein Changes in Childhood Are Associated With Increased Risk for Later Psychotic Disorder: Evidence From a Nested Case-Control Study of the ALSPAC Longitudinal Birth Cohort. Schizophr Bull 2018; 44:297-306. [PMID: 29036721 PMCID: PMC5814944 DOI: 10.1093/schbul/sbx075] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The identification of early biological changes associated with the psychotic disorder (PD) is important as it may provide clues to the underlying pathophysiological mechanisms. We undertook the first proteomic profiling of blood plasma samples of children who later develop a PD. Participants were recruited from the UK Avon Longitudinal Study of Parents and Children (ALSPAC) cohort who also participated in psychiatric assessment interviews at age 18. Protein expression levels at age 11 were compared between individuals who developed PD at age 18 (n = 37) with population-based age-matched controls (n = 38). Sixty out of 181 plasma proteins profiled were found to be differentially expressed (P < .05) in children with an outcome of the PD. Thirty-four of these proteins were found to be differentially expressed following correction for multiple comparisons. Pathway analysis implicated the complement and coagulation cascade. A second, targeted proteomic approach was used to verify these findings in age 11 plasma from subjects who reported psychotic experiences at age 18 (n = 40) in comparison to age-matched controls (n = 66). Our findings indicate that the complement and coagulation system is dysregulated in the blood during childhood before the development of the PD.
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Affiliation(s)
- Jane A English
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Lorna M Lopez
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Aoife O’Gorman
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Melanie Föcking
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | | | - Caitriona Scaife
- School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin (UCD), Dublin, Ireland
| | - Sophie Sabherwal
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Kieran Wynne
- School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin (UCD), Dublin, Ireland
| | - Patrick Dicker
- Department of Epidemiology and Public Health, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Bart P F Rutten
- Department of Psychiatry & Neuropsychology, School for Mental Health and Neuroscience, Division of Neuroscience, Maastricht University, Maastricht, The Netherlands
| | | | - Stanley Zammit
- MRC Centre for Neuropsychiatric Genetics & Genomics, Cardiff University, Cardiff, UK
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Mary Cannon
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Gerard Cagney
- School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin (UCD), Dublin, Ireland
| | - David R Cotter
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
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Kupniewska A, Szymanska K, Demkow U. Proteomics in the Diagnosis of Inborn Encephalopathies of Unknown Origin: A Myth or Reality. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2018; 1040:83-99. [PMID: 28983862 DOI: 10.1007/5584_2017_104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2023]
Abstract
Synaptopathy underlies a great variety of neurological or neurodevelopmental disorders, including neurodegenerative diseases and the highly complex neuropsychiatric syndromes. Standard diagnostic assays in the majority of synaptopathies are insufficient to make an appropriate and fast diagnosis, which has spurred a search for more accurate diagnostic methods using recent technological advances. As synaptopathy phenotypes strictly depend on genetics and environmental factors, the best way to approach these diseases is the investigation of entire sets of protein characteristics. Thus, proteomics has emerged as a mainstay in the studies on synaptopathies, with mass spectrometry as a technology of choice. This review is an update on the proteomic methods and achievements in the understanding, diagnostics, and novel biomarkers of synaptopathies. The article also provides a critical point of view and future perspectives on the application of neuroproteomics in clinical practice.
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Affiliation(s)
- Anna Kupniewska
- Department of Laboratory Diagnostics and Clinical Immunology of Developmental Age, Medical University of Warsaw, 63A Zwirki and Wigury Street, 02-091, Warsaw, Poland.
| | - Krystyna Szymanska
- Department of Clinical and Experimental Neuropathology, The Mossakowski Medical Research Centre, Polish Academy of Sciences, 5 Pawińskiego Street, 02-106, Warsaw, Poland
- Department of Child Psychiatry, Warsaw Medical University, Warsaw, 24 Marszalkowska Street, 00-576, Warsaw, Poland
| | - Urszula Demkow
- Department of Laboratory Diagnostics and Clinical Immunology of Developmental Age, Medical University of Warsaw, 63A Zwirki and Wigury Street, 02-091, Warsaw, Poland
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Cooper JD, Ozcan S, Gardner RM, Rustogi N, Wicks S, van Rees GF, Leweke FM, Dalman C, Karlsson H, Bahn S. Schizophrenia-risk and urban birth are associated with proteomic changes in neonatal dried blood spots. Transl Psychiatry 2017; 7:1290. [PMID: 29249827 PMCID: PMC5802534 DOI: 10.1038/s41398-017-0027-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2017] [Revised: 07/12/2017] [Accepted: 08/20/2017] [Indexed: 12/22/2022] Open
Abstract
In the present study, we tested whether there were proteomic differences in blood between schizophrenia patients after the initial onset of the disorder and controls; and whether those differences were also present at birth among neonates who later developed schizophrenia compared to those without a psychiatric admission. We used multiple reaction monitoring mass spectrometry to quantify 77 proteins (147 peptides) in serum samples from 60 first-onset drug-naive schizophrenia patients and 77 controls, and 96 proteins (152 peptides) in 892 newborn blood-spot (NBS) samples collected between 1975 and 1985. Both serum and NBS studies showed significant alterations in protein levels. Serum results revealed that Haptoglobin and Plasma protease C1 inhibitor were significantly upregulated in first-onset schizophrenia patients (corrected P < 0.05). Alpha-2-antiplasmin, Complement C4-A and Antithrombin-III were increased in first-onset schizophrenia patients (uncorrected P-values 0.041, 0.036 and 0.013, respectively) and also increased in newborn babies who later develop schizophrenia (P-values 0.0058, 0.013 and 0.044, respectively). We also tested whether protein abundance at birth was associated with exposure to an urban environment during pregnancy and found highly significant proteomic differences at birth between urban and rural environments. The prediction model for urbanicity had excellent predictive performance in both discovery (area under the receiver operating characteristic curve (AUC) = 0.90) and validation (AUC = 0.89) sample sets. We hope that future biomarker studies based on stored NBS samples will identify prognostic disease indicators and targets for preventive measures for neurodevelopmental conditions, particularly those with onset during early childhood, such as autism spectrum disorder.
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Affiliation(s)
- Jason D. Cooper
- 0000000121885934grid.5335.0Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK
| | - Sureyya Ozcan
- 0000000121885934grid.5335.0Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK
| | - Renee M. Gardner
- 0000 0004 1937 0626grid.4714.6Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
| | - Nitin Rustogi
- 0000000121885934grid.5335.0Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK
| | - Susanne Wicks
- 0000 0004 1937 0626grid.4714.6Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden ,0000 0001 2326 2191grid.425979.4Centre for Epidemiology and Community Medicine, Stockholm County Council, Stockholm, Sweden
| | - Geertje F. van Rees
- 0000000121885934grid.5335.0Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK
| | - F. Markus Leweke
- 0000 0004 1936 834Xgrid.1013.3Brain and Mind Centre, University of Sydney, Sydney, Australia
| | - Christina Dalman
- 0000 0004 1937 0626grid.4714.6Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden ,0000 0001 2326 2191grid.425979.4Centre for Epidemiology and Community Medicine, Stockholm County Council, Stockholm, Sweden
| | - Håkan Karlsson
- 0000 0004 1937 0626grid.4714.6Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
| | - Sabine Bahn
- Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK.
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Ren J, Zhao G, Sun X, Liu H, Jiang P, Chen J, Wu Z, Peng D, Fang Y, Zhang C. Identification of plasma biomarkers for distinguishing bipolar depression from major depressive disorder by iTRAQ-coupled LC-MS/MS and bioinformatics analysis. Psychoneuroendocrinology 2017; 86:17-24. [PMID: 28910601 DOI: 10.1016/j.psyneuen.2017.09.005] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Revised: 08/28/2017] [Accepted: 09/03/2017] [Indexed: 10/18/2022]
Abstract
It is important to differentiate between bipolar disorder (BD) and major depressive disorder (MDD) in the first depressive episode because of the potential treatment implications. Previous studies have mainly focused on the different clinical features or pathological biomarkers to distinguish these two diseases; however, a better understanding of the proteomics profiling of BD may help aid future therapeutic strategies. Here, we applied isobaric tags for relative and absolute quantification (iTRAQ) technology combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify differentially expressed proteins between MDD and bipolar depression (BP). In total, 30 MDD, 30 BP and 30 healthy subjects were included. Proteins from depleted plasma samples were digested into peptides, individually labeled with iTRAQ reagents, combined and subjected to LC-MS/MS and further bioinformatics analyses. Our results showed that 9 proteins were significantly altered between MDD and BP. Briefly, B2RAN2, B4E1B2, APOA1, ENG, SBSN and QSOX2 were up-regulated, whereas ORM1, MRC2 and SLPI were down-regulated. Most identified proteins were related to the immune system. The bioinformatics analysis showed that B2RAN2 (highly similar to vanin-1) was involved in the significantly enriched KEGG pathways "pantothenate and CoA biosynthesis" (P=0.009). B2RAN2 and ENG may play important roles in depression. They may serve as candidate biomarkers for distinguishing MDD and BP. Further validation and investigation are required to illuminate the roles of B2RAN2 and ENG in MDD and BP. The current study provided a potential and novel biomarker panel that may, in turn, aid the diagnosis of BD.
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Affiliation(s)
- Juanjuan Ren
- Department of Biochemistry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Guoqing Zhao
- Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiujia Sun
- Department of Biochemistry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hongmei Liu
- Department of Biochemistry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ping Jiang
- Department of Biochemistry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jun Chen
- Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhiguo Wu
- Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Daihui Peng
- Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yiru Fang
- Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Chen Zhang
- Department of Biochemistry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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Schmitt A, Martins-de-Souza D, Akbarian S, Cassoli JS, Ehrenreich H, Fischer A, Fonteh A, Gattaz WF, Gawlik M, Gerlach M, Grünblatt E, Halene T, Hasan A, Hashimoto K, Kim YK, Kirchner SK, Kornhuber J, Kraus TFJ, Malchow B, Nascimento JM, Rossner M, Schwarz M, Steiner J, Talib L, Thibaut F, Riederer P, Falkai P. Consensus paper of the WFSBP Task Force on Biological Markers: Criteria for biomarkers and endophenotypes of schizophrenia, part III: Molecular mechanisms. World J Biol Psychiatry 2017; 18:330-356. [PMID: 27782767 DOI: 10.1080/15622975.2016.1224929] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
OBJECTIVES Despite progress in identifying molecular pathophysiological processes in schizophrenia, valid biomarkers are lacking for both the disease and treatment response. METHODS This comprehensive review summarises recent efforts to identify molecular mechanisms on the level of protein and gene expression and epigenetics, including DNA methylation, histone modifications and micro RNA expression. Furthermore, it summarises recent findings of alterations in lipid mediators and highlights inflammatory processes. The potential that this research will identify biomarkers of schizophrenia is discussed. RESULTS Recent studies have not identified clear biomarkers for schizophrenia. Although several molecular pathways have emerged as potential candidates for future research, a complete understanding of these metabolic pathways is required to reveal better treatment modalities for this disabling condition. CONCLUSIONS Large longitudinal cohort studies are essential that pair a thorough phenotypic and clinical evaluation for example with gene expression and proteome analysis in blood at multiple time points. This approach might identify biomarkers that allow patients to be stratified according to treatment response and ideally also allow treatment response to be predicted. Improved knowledge of molecular pathways and epigenetic mechanisms, including their potential association with environmental influences, will facilitate the discovery of biomarkers that could ultimately be effective tools in clinical practice.
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Affiliation(s)
- Andrea Schmitt
- a Department of Psychiatry and Psychotherapy , LMU Munich , Germany.,b Laboratory of Neuroscience (LIM27) , Institute of Psychiatry, University of Sao Paulo , Sao Paulo , Brazil
| | - Daniel Martins-de-Souza
- b Laboratory of Neuroscience (LIM27) , Institute of Psychiatry, University of Sao Paulo , Sao Paulo , Brazil.,c Laboratory of Neuroproteomics, Department of Biochemistry , Institute of Biology University of Campinas (UNICAMP), Campinas , SP , Brazil
| | - Schahram Akbarian
- d Division of Psychiatric Epigenomics, Departments of Psychiatry and Neuroscience , Mount Sinai School of Medicine , New York , USA
| | - Juliana S Cassoli
- c Laboratory of Neuroproteomics, Department of Biochemistry , Institute of Biology University of Campinas (UNICAMP), Campinas , SP , Brazil
| | - Hannelore Ehrenreich
- e Clinical Neuroscience , Max Planck Institute of Experimental Medicine, DFG Centre for Nanoscale Microscopy & Molecular Physiology of the Brain , Göttingen , Germany
| | - Andre Fischer
- f Research Group for Epigenetics in Neurodegenerative Diseases , German Centre for Neurodegenerative Diseases (DZNE), Göttingen , Germany.,g Department of Psychiatry and Psychotherapy , University Medical Centre Göttingen , Germany
| | - Alfred Fonteh
- h Neurosciences , Huntington Medical Research Institutes , Pasadena , CA , USA
| | - Wagner F Gattaz
- b Laboratory of Neuroscience (LIM27) , Institute of Psychiatry, University of Sao Paulo , Sao Paulo , Brazil
| | - Michael Gawlik
- i Department of Psychiatry and Psychotherapy , University of Würzburg , Germany
| | - Manfred Gerlach
- j Centre for Mental Health, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy , University of Würzburg , Germany
| | - Edna Grünblatt
- i Department of Psychiatry and Psychotherapy , University of Würzburg , Germany.,k Department of Child and Adolescent Psychiatry and Psychotherapy , Psychiatric Hospital, University of Zürich , Switzerland.,l Neuroscience Centre Zurich , University of Zurich and the ETH Zurich , Switzerland.,m Zurich Centre for Integrative Human Physiology , University of Zurich , Switzerland
| | - Tobias Halene
- d Division of Psychiatric Epigenomics, Departments of Psychiatry and Neuroscience , Mount Sinai School of Medicine , New York , USA
| | - Alkomiet Hasan
- a Department of Psychiatry and Psychotherapy , LMU Munich , Germany
| | - Kenij Hashimoto
- n Division of Clinical Neuroscience , Chiba University Centre for Forensic Mental Health , Chiba , Japan
| | - Yong-Ku Kim
- o Department of Psychiatry , Korea University, College of Medicine , Republic of Korea
| | | | - Johannes Kornhuber
- p Department of Psychiatry and Psychotherapy , Friedrich-Alexander-University Erlangen-Nuremberg , Erlangen , Germany
| | | | - Berend Malchow
- a Department of Psychiatry and Psychotherapy , LMU Munich , Germany
| | - Juliana M Nascimento
- c Laboratory of Neuroproteomics, Department of Biochemistry , Institute of Biology University of Campinas (UNICAMP), Campinas , SP , Brazil
| | - Moritz Rossner
- r Department of Psychiatry, Molecular and Behavioural Neurobiology , LMU Munich , Germany.,s Research Group Gene Expression , Max Planck Institute of Experimental Medicine , Göttingen , Germany
| | - Markus Schwarz
- t Institute for Laboratory Medicine, LMU Munich , Germany
| | - Johann Steiner
- u Department of Psychiatry , University of Magdeburg , Magdeburg , Germany
| | - Leda Talib
- b Laboratory of Neuroscience (LIM27) , Institute of Psychiatry, University of Sao Paulo , Sao Paulo , Brazil
| | - Florence Thibaut
- v Department of Psychiatry , University Hospital Cochin (site Tarnier), University of Paris-Descartes, INSERM U 894 Centre Psychiatry and Neurosciences , Paris , France
| | - Peter Riederer
- w Center of Psychic Health; Department of Psychiatry, Psychosomatics and Psychotherapy , University Hospital of Würzburg , Germany
| | - Peter Falkai
- a Department of Psychiatry and Psychotherapy , LMU Munich , Germany
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Zamanian-Azodi M, Rezaei-Tavirani M, Nejadi N, Arefi Oskouie A, Zayeri F, Hamdieh M, Safaei A, Rezaei-Tavirani M, Ahmadzadeh A, Amouzandeh-Nobaveh A, Okhovatian F. Serum Proteomic Profiling of Obsessive-Compulsive Disorder, Washing Subtype: A Preliminary Study. Basic Clin Neurosci 2017; 8:307-316. [PMID: 29158881 PMCID: PMC5683688 DOI: 10.18869/nirp.bcn.8.4.307] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Introduction: Obsessive-Compulsive Disorder (OCD) is a disabling mental condition that its proteomic profiling is not yet investigated. Proteomics is a valuable tool to discover biomarker approaches. It can be helpful to detect protein expression changes in complex disorders such as OCD. Methods: Here, by the application of 2D gel electrophoresis (2DE), a pilot study of serum proteome profile of females with washing subtype of OCD was performed. Serum samples were obtained from females with washing subtype of OCD. Following the protein extraction from the serum with acetone perception, the samples were subjected to 2DE for separation based on pI and molecular weight (MW) with triple replications. Finally, the protein spots were visualized using Coomassie blue staining method and analyzed by Progenesis SameSpots software. Furthermore, protein-protein interaction (PPI) network analysis was handled by the application of Cytoscape software. Results: The results suggested that 41 matched spots demonstrated significant expression alterations among which 5 proteins including immunoglobulin heavy constant alpha-1 (IGHA1), apolipoprotein A-4 (APOA4), haptoglobin (HP), protein α-1-antitrypsin (SERPINA1), and component 3 (C3) were identified by database query. Additionally, PPI network analysis indicated the central role of SERPINA1 and C3 in the network integrity. However, albumin (ALB), amyloid precursor protein (APP), and protein α-1-antitrypsin (APOA1) proteins were important in OCD PPI network as well. The identified proteins were related to 3 processes: acute-phase response, hydrogen peroxide catabolic process, and regulation of triglyceride metabolic process. Conclusion: It was concluded that these proteins may have a fundamental role in OCD pathogenesis. Moreover, the dysregulation of inflammatory and antioxidant systems in OCD risk was suggested by the current study. However, evaluation of bigger sample sizes and application of mass spectrometry are essential requirements to confirm this preliminary evaluation.
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Affiliation(s)
- Mona Zamanian-Azodi
- Student Research Committee, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mostafa Rezaei-Tavirani
- Proteomics Research Center, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Naser Nejadi
- Department of Biochemistry, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Afsaneh Arefi Oskouie
- Proteomics Research Center, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Faird Zayeri
- Student Research Committee, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mostafa Hamdieh
- Taleghani Hospital, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Akram Safaei
- Proteomics Research Center, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Majid Rezaei-Tavirani
- Department of Surgery, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Alireza Ahmadzadeh
- Proteomics Research Center, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | | | - Farshad Okhovatian
- Physiotherapy Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Tan XT, Amran FB, Thayan R, Ahmad N, Jaafar R, Haron R, Abdullah R, bin Shamsuddin SR, Md. Riffin NSB, Abdul-Rahman PS. Potential serum biomarkers associated with mild and severe leptospirosis infection: A cohort study in the Malaysian population. Electrophoresis 2017; 38:2141-2149. [DOI: 10.1002/elps.201600471] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2016] [Revised: 04/22/2017] [Accepted: 05/12/2017] [Indexed: 11/09/2022]
Affiliation(s)
- Xue Ting Tan
- Bacteriology Unit; Institute for Medical Research; Kuala Lumpur Malaysia
- Department of Molecular Medicine, Faculty of Medicine; University of Malaya; Kuala Lumpur Malaysia
| | - Fairuz binti Amran
- Bacteriology Unit; Institute for Medical Research; Kuala Lumpur Malaysia
| | - Ravindran Thayan
- Virology Unit; Institute for Medical Research; Kuala Lumpur Malaysia
| | - Norazah Ahmad
- Bacteriology Unit; Institute for Medical Research; Kuala Lumpur Malaysia
| | - Roslinda Jaafar
- Microbiology Unit; Hospital Sultan Haji Ahmad Shah; Pahang Malaysia
| | - Rahimah Haron
- Department of Anesthesiology; Hospital Sultan Haji Ahmad Shah; Pahang Malaysia
| | - Rafidah Abdullah
- Department of Medical; Hospital Sultan Haji Ahmad Shah; Pahang Malaysia
| | | | | | - Puteri Shafinaz Abdul-Rahman
- Department of Molecular Medicine, Faculty of Medicine; University of Malaya; Kuala Lumpur Malaysia
- University of Malaya Centre for Proteomics Research; University of Malaya; Kuala Lumpur Malaysia
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Sabherwal S, English JA, Föcking M, Cagney G, Cotter DR. Blood biomarker discovery in drug-free schizophrenia: the contribution of proteomics and multiplex immunoassays. Expert Rev Proteomics 2016; 13:1141-1155. [DOI: 10.1080/14789450.2016.1252262] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Affiliation(s)
- Sophie Sabherwal
- Department of Psychiatry, Royal College of Surgeons in Ireland, ERC Beaumont Hospital, Dublin, Ireland
| | - Jane A. English
- Department of Psychiatry, Royal College of Surgeons in Ireland, ERC Beaumont Hospital, Dublin, Ireland
| | - Melanie Föcking
- Department of Psychiatry, Royal College of Surgeons in Ireland, ERC Beaumont Hospital, Dublin, Ireland
| | - Gerard Cagney
- Proteome Research Centre, UCD Conway Institute of Biomolecular and Biomedical Research, School of Medicine, and Medical Sciences, University College Dublin, Dublin, Ireland
| | - David R. Cotter
- Department of Psychiatry, Royal College of Surgeons in Ireland, ERC Beaumont Hospital, Dublin, Ireland
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Giusti L, Ciregia F, Mazzoni MR, Lucacchini A. Proteomics insight into psychiatric disorders: an update on biological fluid biomarkers. Expert Rev Proteomics 2016; 13:941-950. [DOI: 10.1080/14789450.2016.1230499] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Affiliation(s)
- Laura Giusti
- Department of Pharmacy, University of Pisa, Pisa, Italy
| | - Federica Ciregia
- Department of Pharmacy, University of Pisa, Pisa, Italy
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
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Davalieva K, Maleva Kostovska I, Dwork AJ. Proteomics Research in Schizophrenia. Front Cell Neurosci 2016; 10:18. [PMID: 26909022 PMCID: PMC4754401 DOI: 10.3389/fncel.2016.00018] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2015] [Accepted: 01/18/2016] [Indexed: 11/29/2022] Open
Abstract
Despite intense scientific efforts, the neuropathology and pathophysiology of schizophrenia are poorly understood. Proteomic studies, by testing large numbers of proteins for associations with disease, may contribute to the understanding of the molecular mechanisms of schizophrenia. They may also indicate the types and locations of cells most likely to harbor pathological alterations. Investigations using proteomic approaches have already provided much information on quantitative and qualitative protein patterns in postmortem brain tissue, peripheral tissues and body fluids. Different proteomic technologies such as 2-D PAGE, 2-D DIGE, SELDI-TOF, shotgun proteomics with label-based (ICAT), and label-free (MSE) quantification have been applied to the study of schizophrenia for the past 15 years. This review summarizes the results, mostly from brain but also from other tissues and bodily fluids, of proteomics studies in schizophrenia. Emphasis is given to proteomics platforms, varying sources of material, proposed candidate biomarkers emerging from comparative proteomics studies, and the specificity of the putative markers in terms of other mental illnesses. We also compare proteins altered in schizophrenia with reports of protein or mRNA sequences that are relatively enriched in specific cell types. While proteomic studies of schizophrenia find abnormalities in the expression of many proteins that are not cell type-specific, there appears to be a disproportionate representation of proteins whose synthesis and localization are highly enriched in one or more brain cell type compared with other types of brain cells. Two of the three proteins most commonly altered in schizophrenia are aldolase C and glial fibrillary acidic protein, astrocytic proteins with entirely different functions, but the studies are approximately evenly divided with regard to the direction of the differences and the concordance or discordance between the two proteins. Alterations of common myelin-associated proteins were also frequently observed, and in four studies that identified alterations in at least two, all differences were downwards in schizophrenia, consistent with earlier studies examining RNA or targeting myelin-associated proteins.
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Affiliation(s)
- Katarina Davalieva
- Research Centre for Genetic Engineering and Biotechnology "Georgi D Efremov," Macedonian Academy of Sciences and Arts Skopje, Republic of Macedonia
| | - Ivana Maleva Kostovska
- Research Centre for Genetic Engineering and Biotechnology "Georgi D Efremov," Macedonian Academy of Sciences and Arts Skopje, Republic of Macedonia
| | - Andrew J Dwork
- Department of Molecular Imaging and Neuropathology, New York State Psychiatric InstituteNew York, NY, USA; Departments of Psychiatry and Pathology and Cell Biology, College of Physicians and Surgeons of Columbia UniversityNew York, NY, USA; Macedonian Academy of Sciences and ArtsSkopje, Republic of Macedonia
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Chaubey K, Rao MK, Alam SI, Waghmare C, Bhattacharya BK. Increased expression of immune modulator proteins and decreased expression of apolipoprotein A-1 and haptoglobin in blood plasma of sarin exposed rats. Chem Biol Interact 2016; 246:36-44. [DOI: 10.1016/j.cbi.2016.01.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2015] [Revised: 01/06/2016] [Accepted: 01/07/2016] [Indexed: 12/28/2022]
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Commercialisation of Biomarker Tests for Mental Illnesses: Advances and Obstacles. Trends Biotechnol 2015; 33:712-723. [DOI: 10.1016/j.tibtech.2015.09.010] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2015] [Revised: 08/14/2015] [Accepted: 09/17/2015] [Indexed: 12/28/2022]
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Häggmark A, Schwenk JM, Nilsson P. Neuroproteomic profiling of human body fluids. Proteomics Clin Appl 2015; 10:485-502. [PMID: 26286680 DOI: 10.1002/prca.201500065] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2015] [Revised: 07/17/2015] [Accepted: 08/12/2015] [Indexed: 12/11/2022]
Abstract
Analysis of protein expression and abundance provides a possibility to extend the current knowledge on disease-associated processes and pathways. The human brain is a complex organ and dysfunction or damage can give rise to a variety of neurological diseases. Although many proteins potentially reflecting disease progress are originating from brain, the scarce availability of human tissue material has lead to utilization of body fluids such as cerebrospinal fluid and blood in disease-related research. Within the most common neurological disorders, much effort has been spent on studying the role of a few hallmark proteins in disease pathogenesis but despite extensive investigation, the signatures they provide seem insufficient to fully understand and predict disease progress. In order to expand the view the field of neuroproteomics has lately emerged alongside developing technologies, such as affinity proteomics and mass spectrometry, for multiplexed and high-throughput protein profiling. Here, we provide an overview of how such technologies have been applied to study neurological disease and we also discuss some important considerations concerning discovery of disease-associated profiles.
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Affiliation(s)
- Anna Häggmark
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Jochen M Schwenk
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Peter Nilsson
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology, Stockholm, Sweden
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Song YR, Wu B, Yang YT, Chen J, Zhang LJ, Zhang ZW, Shi HY, Huang CL, Pan JX, Xie P. Specific alterations in plasma proteins during depressed, manic, and euthymic states of bipolar disorder. ACTA ACUST UNITED AC 2015; 48:973-82. [PMID: 26375446 PMCID: PMC4671523 DOI: 10.1590/1414-431x20154550] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2014] [Accepted: 04/14/2015] [Indexed: 12/22/2022]
Abstract
Bipolar disorder (BD) is a common psychiatric mood disorder affecting more than 1-2%
of the general population of different European countries. Unfortunately, there is no
objective laboratory-based test to aid BD diagnosis or monitor its progression, and
little is known about the molecular basis of BD. Here, we performed a comparative
proteomic study to identify differentially expressed plasma proteins in various BD
mood states (depressed BD, manic BD, and euthymic BD) relative to healthy controls. A
total of 10 euthymic BD, 20 depressed BD, 15 manic BD, and 20 demographically matched
healthy control subjects were recruited. Seven high-abundance proteins were
immunodepleted in plasma samples from the 4 experimental groups, which were then
subjected to proteome-wide expression profiling by two-dimensional electrophoresis
and matrix-assisted laser desorption/ionization-time-of-flight/time-of-flight tandem
mass spectrometry. Proteomic results were validated by immunoblotting and
bioinformatically analyzed using MetaCore. From a total of 32 proteins identified
with 1.5-fold changes in expression compared with healthy controls, 16 proteins were
perturbed in BD independent of mood state, while 16 proteins were specifically
associated with particular BD mood states. Two mood-independent differential
proteins, apolipoprotein (Apo) A1 and Apo L1, suggest that BD pathophysiology may be
associated with early perturbations in lipid metabolism. Moreover, down-regulation of
one mood-dependent protein, carbonic anhydrase 1 (CA-1), suggests it may be involved
in the pathophysiology of depressive episodes in BD. Thus, BD pathophysiology may be
associated with early perturbations in lipid metabolism that are independent of mood
state, while CA-1 may be involved in the pathophysiology of depressive episodes.
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Affiliation(s)
- Y R Song
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - B Wu
- Chongqing Key Laboratory of Neurobiology, Chongqing, China
| | - Y T Yang
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - J Chen
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - L J Zhang
- Chongqing Key Laboratory of Neurobiology, Chongqing, China
| | - Z W Zhang
- Chongqing Key Laboratory of Neurobiology, Chongqing, China
| | - H Y Shi
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - C L Huang
- Chongqing Key Laboratory of Neurobiology, Chongqing, China
| | - J X Pan
- Chongqing Key Laboratory of Neurobiology, Chongqing, China
| | - P Xie
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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Sanjurjo L, Aran G, Roher N, Valledor AF, Sarrias MR. AIM/CD5L: a key protein in the control of immune homeostasis and inflammatory disease. J Leukoc Biol 2015; 98:173-84. [PMID: 26048980 DOI: 10.1189/jlb.3ru0215-074r] [Citation(s) in RCA: 87] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2015] [Accepted: 04/12/2015] [Indexed: 01/16/2023] Open
Abstract
CD5L, a soluble protein belonging to the SRCR superfamily, is expressed mostly by macrophages in lymphoid and inflamed tissues. The expression of this protein is transcriptionally controlled by LXRs, members of the nuclear receptor family that play major roles in lipid homeostasis. Research undertaken over the last decade has uncovered critical roles of CD5L as a PRR of bacterial and fungal components and in the control of key mechanisms in inflammatory responses, with involvement in processes, such as infection, atherosclerosis, and cancer. In this review, we summarize the current knowledge of CD5L, its roles at the intersection between lipid homeostasis and immune response, and its potential use as a diagnostic biomarker in a variety of diseases, such as TB and liver cirrhosis.
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Affiliation(s)
- Lucía Sanjurjo
- *Innate Immunity Group, Health Sciences Research Institute Germans Trias i Pujol, Badalona, Spain; Evolutive Immunology Group, Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Barcelona, Spain; Nuclear Receptor Group, Department of Physiology and Immunology, School of Biology, University of Barcelona, Barcelona, Spain; and Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas, Barcelona, Spain
| | - Gemma Aran
- *Innate Immunity Group, Health Sciences Research Institute Germans Trias i Pujol, Badalona, Spain; Evolutive Immunology Group, Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Barcelona, Spain; Nuclear Receptor Group, Department of Physiology and Immunology, School of Biology, University of Barcelona, Barcelona, Spain; and Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas, Barcelona, Spain
| | - Nerea Roher
- *Innate Immunity Group, Health Sciences Research Institute Germans Trias i Pujol, Badalona, Spain; Evolutive Immunology Group, Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Barcelona, Spain; Nuclear Receptor Group, Department of Physiology and Immunology, School of Biology, University of Barcelona, Barcelona, Spain; and Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas, Barcelona, Spain
| | - Annabel F Valledor
- *Innate Immunity Group, Health Sciences Research Institute Germans Trias i Pujol, Badalona, Spain; Evolutive Immunology Group, Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Barcelona, Spain; Nuclear Receptor Group, Department of Physiology and Immunology, School of Biology, University of Barcelona, Barcelona, Spain; and Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas, Barcelona, Spain
| | - Maria-Rosa Sarrias
- *Innate Immunity Group, Health Sciences Research Institute Germans Trias i Pujol, Badalona, Spain; Evolutive Immunology Group, Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Barcelona, Spain; Nuclear Receptor Group, Department of Physiology and Immunology, School of Biology, University of Barcelona, Barcelona, Spain; and Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas, Barcelona, Spain
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Nascimento JM, Martins-de-Souza D. The proteome of schizophrenia. NPJ SCHIZOPHRENIA 2015; 1:14003. [PMID: 27336025 PMCID: PMC4849438 DOI: 10.1038/npjschz.2014.3] [Citation(s) in RCA: 82] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/19/2014] [Revised: 10/28/2014] [Accepted: 10/30/2014] [Indexed: 12/24/2022]
Abstract
On observing schizophrenia from a clinical point of view up to its molecular basis, one may conclude that this is likely to be one of the most complex human disorders to be characterized in all aspects. Such complexity is the reflex of an intricate combination of genetic and environmental components that influence brain functions since pre-natal neurodevelopment, passing by brain maturation, up to the onset of disease and disease establishment. The perfect function of tissues, organs, systems, and finally the organism depends heavily on the proper functioning of cells. Several lines of evidence, including genetics, genomics, transcriptomics, neuropathology, and pharmacology, have supported the idea that dysfunctional cells are causative to schizophrenia. Together with the above-mentioned techniques, proteomics have been contributing to understanding the biochemical basis of schizophrenia at the cellular and tissue level through the identification of differentially expressed proteins and consequently their biochemical pathways, mostly in the brain tissue but also in other cells. In addition, mass spectrometry-based proteomics have identified and precisely quantified proteins that may serve as biomarker candidates to prognosis, diagnosis, and medication monitoring in peripheral tissue. Here, we review all data produced by proteomic investigation in the last 5 years using tissue and/or cells from schizophrenic patients, focusing on postmortem brain tissue and peripheral blood serum and plasma. This information has provided integrated pictures of the biochemical systems involved in the pathobiology, and has suggested potential biomarkers, and warrant potential targets to alternative treatment therapies to schizophrenia.
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Affiliation(s)
- Juliana M Nascimento
- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Sao Paulo, Brazil
- D’Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
| | - Daniel Martins-de-Souza
- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Sao Paulo, Brazil
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42
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Sajic T, Liu Y, Aebersold R. Using data-independent, high-resolution mass spectrometry in protein biomarker research: perspectives and clinical applications. Proteomics Clin Appl 2015; 9:307-21. [PMID: 25504613 DOI: 10.1002/prca.201400117] [Citation(s) in RCA: 148] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2014] [Revised: 11/13/2014] [Accepted: 12/10/2014] [Indexed: 12/17/2022]
Abstract
In medicine, there is an urgent need for protein biomarkers in a range of applications that includes diagnostics, disease stratification, and therapeutic decisions. One of the main technologies to address this need is MS, used for protein biomarker discovery and, increasingly, also for protein biomarker validation. Currently, data-dependent analysis (also referred to as shotgun proteomics) and targeted MS, exemplified by SRM, are the most frequently used mass spectrometric methods. Recently developed data-independent acquisition techniques combine the strength of shotgun and targeted proteomics, while avoiding some of the limitations of the respective methods. They provide high-throughput, accurate quantification, and reproducible measurements within a single experimental setup. Here, we describe and review data-independent acquisition strategies and their recent use in clinically oriented studies. In addition, we also provide a detailed guide for the implementation of SWATH-MS (where SWATH is sequential window acquisition of all theoretical mass spectra)-one of the data-independent strategies that have gained wide application of late.
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Affiliation(s)
- Tatjana Sajic
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
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Abstract
Patients with psychiatric disorders exhibit several neurobehavioral and neuropsychological alterations compared to healthy controls. However, signature endpoints of these behavioral manifestations have not yet been translated into clinical tests for diagnosis and follow-up measures. Recently, neuroproteomic approaches have been utilized to identify unique signature markers indicative of these disorders. Development of reliable biomarkers has the potential to revolutionize the diagnosis, classification, and monitoring of clinical responses in psychiatric diseases. However, the lack of biological gold standards, the evolving nosology of psychiatric disorders, and the complexity of the nervous system are among the major challenges that have hindered efforts to develop reliable biomarkers in the field of neuropsychiatry and drug abuse. While biomarkers currently have a limited role in the area of neuropsychiatry, several promising biomarkers have been proposed in conditions such as dementia, schizophrenia, depression, suicide, and addiction. One of the primary objectives of this review is to discuss the role of proteomics in the development of biomarkers specific to neuropsychiatry. We discuss and evaluate currently available biomarkers as well as those that are under research for clinical use in the future.
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Zhang W, Xiao MS, Ji S, Tang J, Xu L, Li X, Li M, Wang HZ, Jiang HY, Zhang DF, Wang J, Zhang S, Xu XF, Yu L, Zheng P, Chen X, Yao YG. Promoter variant rs2301228 on the neural cell adhesion molecule 1 gene confers risk of schizophrenia in Han Chinese. Schizophr Res 2014; 160:88-96. [PMID: 25445624 DOI: 10.1016/j.schres.2014.09.036] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2014] [Revised: 09/09/2014] [Accepted: 09/16/2014] [Indexed: 01/15/2023]
Abstract
BACKGROUND Schizophrenia is recognized as a disorder of the brain and neuronal connectivity. The neural cell adhesion molecule 1 (NCAM1) gene plays a crucial role in regulating neuronal connectivity. METHODS We conducted a two-stage association analysis on 17 NCAM1 SNPs in two independent Han Chinese schizophrenia case-control cohorts (discovery sample from Hunan Province: 986 patients and 1040 normal controls; replication sample from Yunnan Province: 564 cases and 547 healthy controls). Allele, genotype and haplotype frequencies were compared between case and control samples. Transcription factor binding site prediction and luciferase reporter assays were employed to assess the potential function of promoter SNPs. We detected developmental changes at the transcriptional level of NCAM1 during neuron differentiation in Macaca mulatta neural progenitor cells (NPC). Serum levels of NCAM1 were measured in 72 cases and 88 controls. RESULTS A promoter variant, rs2301228, was found to be associated with schizophrenia at the allelic level and was validated in a replication cohort. Luciferase reporter assays demonstrated that risk allele rs2301228-A significantly down-regulated NCAM1 gene transcription compared to the G-allele. Concordantly, schizophrenia patients had a significantly lower level of serum NCAM1 compared to healthy donors. During the NPC neuronal differentiation, NCAM1 mRNA was significantly increased, suggesting a critical role of this gene in neural development. CONCLUSIONS Our results provide direct evidence for NCAM1 as a susceptibility gene for schizophrenia, which offers support to a neurodevelopmental model and neuronal connectivity hypothesis in the onset of schizophrenia.
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Affiliation(s)
- Wen Zhang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, China
| | - Mei-Sheng Xiao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, China
| | - Shuang Ji
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Jinsong Tang
- Institute of Mental Health, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Ling Xu
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Xiao Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Ming Li
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Hui-Zhen Wang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, China; School of Life Sciences, University of Science and Technology of China, Hefei, Anhui, China
| | - Hong-Yan Jiang
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Deng-Feng Zhang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Jicai Wang
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Shuliang Zhang
- Coal Mine Mental Hospital of Yunnan Province, Honghe, Yunnan 652402, China
| | - Xiu-Feng Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Li Yu
- Laboratory for Conservation and Utilization of Bio-resource & Key Laboratory for Microbial Resources of the Ministry of Education, Yunnan University, Kunming, Yunnan, China
| | - Ping Zheng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Xiaogang Chen
- Institute of Mental Health, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yong-Gang Yao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, China.
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45
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English JA, Wynne K, Cagney G, Cotter DR. Targeted proteomics for validation of biomarkers in early psychosis. Biol Psychiatry 2014; 76:e7-9. [PMID: 24332930 DOI: 10.1016/j.biopsych.2013.11.016] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2013] [Accepted: 11/06/2013] [Indexed: 11/29/2022]
Affiliation(s)
- Jane A English
- Department of Psychiatry, Royal College of Surgeons in Ireland, ERC Beaumont Hospital, Dublin, Ireland.
| | - Kieran Wynne
- School of Biomolecular and Biomedical Science, University College Dublin, Dublin, Ireland
| | - Gerard Cagney
- School of Biomolecular and Biomedical Science, University College Dublin, Dublin, Ireland
| | - David R Cotter
- Department of Psychiatry, Royal College of Surgeons in Ireland, ERC Beaumont Hospital, Dublin, Ireland
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46
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van Beveren NJM, Schwarz E, Noll R, Guest PC, Meijer C, de Haan L, Bahn S. Evidence for disturbed insulin and growth hormone signaling as potential risk factors in the development of schizophrenia. Transl Psychiatry 2014; 4:e430. [PMID: 25158005 PMCID: PMC4150237 DOI: 10.1038/tp.2014.52] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2013] [Revised: 05/07/2014] [Accepted: 05/21/2014] [Indexed: 01/03/2023] Open
Abstract
Molecular abnormalities in metabolic, hormonal and immune pathways are present in peripheral body fluids of a significant subgroup of schizophrenia patients. The authors have tested whether such disturbances also occur in psychiatrically ill and unaffected siblings of schizophrenia patients with the aim of identifying potential contributing factors to disease vulnerability. The subjects were recruited as part of the Genetic Risk and OUtcome of Psychosis (GROUP) study. The authors used multiplexed immunoassays to measure the levels of 184 molecules in serum from 112 schizophrenia patients, 133 siblings and 87 unrelated controls. Consistent with the findings of previous studies, serum from schizophrenia patients contained higher levels of insulin, C-peptide and proinsulin, decreased levels of growth hormone and altered concentrations of molecules involved in inflammation. In addition, significant differences were found in the levels of some of these proteins in siblings diagnosed with mood disorders (n=16) and in unaffected siblings (n=117). Most significantly, the insulin/growth hormone ratio was higher across all groups compared with the controls. Taken together, these findings suggest the presence of a molecular endophenotype involving disruption of insulin and growth factor signaling pathways as an increased risk factor for schizophrenia.
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Affiliation(s)
- N J M van Beveren
- Department of Neuroscience, Erasmus Medical Center, Rotterdam, The Netherlands,Department of Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands,Department 'Nieuwe Kennis', Delta Center for Mental Health Care, Rotterdam, The Netherlands,Department of Neuroscience, Erasmus University Medical Center, 3000 CA Rotterdam, The Netherlands. E-mail: or
| | - E Schwarz
- Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK
| | - R Noll
- Department of Psychology, DeSales University, Center Valley, PA, USA
| | - P C Guest
- Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK
| | - C Meijer
- Department of Psychiatry, Academic Medical Center, Amsterdam, The Netherlands
| | - L de Haan
- Department of Psychiatry, Academic Medical Center, Amsterdam, The Netherlands
| | - S Bahn
- Department of Neuroscience, Erasmus Medical Center, Rotterdam, The Netherlands,Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK,Department of Neuroscience, Erasmus University Medical Center, 3000 CA Rotterdam, The Netherlands. E-mail: or
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47
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Technological advances for deciphering the complexity of psychiatric disorders: merging proteomics with cell biology. Int J Neuropsychopharmacol 2014; 17:1327-41. [PMID: 24524332 DOI: 10.1017/s146114571400008x] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Proteomic studies have increased our understanding of the molecular pathways affected in psychiatric disorders. Mass spectrometry and two-dimensional gel electrophoresis analyses of post-mortem brain samples from psychiatric patients have revealed effects on synaptic, cytoskeletal, antioxidant and mitochondrial protein networks. Multiplex immunoassay profiling studies have found alterations in hormones, growth factors, transport and inflammation-related proteins in serum and plasma from living first-onset patients. Despite these advances, there are still difficulties in translating these findings into platforms for improved treatment of patients and for discovery of new drugs with better efficacy and side effect profiles. This review describes how the next phase of proteomic investigations in psychiatry should include stringent replication studies for validation of biomarker candidates and functional follow-up studies which can be used to test the impact on physiological function. All biomarker candidates should now be tested in series with traditional and emerging cell biological approaches. This should include investigations of the effects of post-translational modifications, protein dynamics and network analyses using targeted proteomic approaches. Most importantly, there is still an urgent need for development of disease-relevant cellular models for improved translation of proteomic findings into a means of developing novel drug treatments for patients with these life-altering disorders.
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48
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Law KP, Lim YP. Recent advances in mass spectrometry: data independent analysis and hyper reaction monitoring. Expert Rev Proteomics 2014; 10:551-66. [PMID: 24206228 DOI: 10.1586/14789450.2013.858022] [Citation(s) in RCA: 99] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
New mass spectrometry (MS) methods, collectively known as data independent analysis and hyper reaction monitoring, have recently emerged. These methods hold promises to address the shortcomings of data-dependent analysis and selected reaction monitoring (SRM) employed in shotgun and targeted proteomics, respectively. They allow MS analyses of all species in a complex sample indiscriminately, or permit SRM-like experiments conducted with full high-resolution product ion spectra, potentially leading to higher sequence coverage or analytical selectivity. These methods include MS(E), all-ion fragmentation, Fourier transform-all reaction monitoring, SWATH Acquisition, multiplexed MS/MS, pseudo-SRM (pSRM) and parallel reaction monitoring (PRM). In this review, the strengths and pitfalls of these methods are discussed and illustrated with examples. In essence, the suitability of the use of each method is contingent on the biological questions posed. Although these methods do not fundamentally change the shape of proteomics, they are useful additional tools that should expedite biological discoveries.
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Affiliation(s)
- Kai Pong Law
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, MD4, Level 1, 14 Medical Drive, 117599, Singapore
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49
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Hayashi-Takagi A, Vawter MP, Iwamoto K. Peripheral biomarkers revisited: integrative profiling of peripheral samples for psychiatric research. Biol Psychiatry 2014; 75:920-8. [PMID: 24286759 PMCID: PMC4964959 DOI: 10.1016/j.biopsych.2013.09.035] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2013] [Revised: 09/17/2013] [Accepted: 09/24/2013] [Indexed: 12/18/2022]
Abstract
Peripheral samples, such as blood and skin, have been used for decades in psychiatric research as surrogates for central nervous system samples. Although the validity of the data obtained from peripheral samples has been questioned and other state-of-the-art techniques, such as human brain imaging, genomics, and induced pluripotent stem cells, seem to reduce the value of peripheral cells, accumulating evidence has suggested that revisiting peripheral samples is worthwhile. Here, we re-evaluate the utility of peripheral samples and argue that establishing an understanding of the common signaling and biological processes in the brain and peripheral samples is required for the validity of such models. First, we present an overview of the available types of peripheral cells and describe their advantages and disadvantages. We then briefly summarize the main achievements of omics studies, including epigenome, transcriptome, proteome, and metabolome analyses, as well as the main findings of functional cellular assays, the results of which imply that alterations in neurotransmission, metabolism, the cell cycle, and the immune system may be partially responsible for the pathophysiology of major psychiatric disorders such as schizophrenia. Finally, we discuss the future utility of peripheral samples for the development of biomarkers and tailor-made therapies, such as multimodal assays that are used as a battery of disease and trait pathways and that might be potent and complimentary tools for use in psychiatric research.
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Affiliation(s)
- Akiko Hayashi-Takagi
- Laboratory of Structural Physiology, Center for Disease Biology and Integrative Medicine, University of Tokyo, Tokyo; Precursory Research for Embryonic Science and Technology, Japan Science and Technology Agency, Kawaguchi, Saitama, Japan.
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50
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Al Awam K, Haußleiter IS, Dudley E, Donev R, Brüne M, Juckel G, Thome J. Multiplatform metabolome and proteome profiling identifies serum metabolite and protein signatures as prospective biomarkers for schizophrenia. J Neural Transm (Vienna) 2014; 122 Suppl 1:S111-22. [PMID: 24789758 DOI: 10.1007/s00702-014-1224-0] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2014] [Accepted: 04/14/2014] [Indexed: 12/27/2022]
Abstract
Schizophrenia is a severe mental illness with a biological basis. However, the search for reliable biomarkers suitable for clinical routine has been futile so far. Accordingly, there is a need for innovative approaches such as genomics and proteomics to achieve this goal. In the present study, we compared metabolomic and proteomic data from 26 schizophrenia patients as well as from unaffected controls carefully matched for age and gender in a multi-platform approach. The combined analysis identified many signatures with initially good biomarker characteristics. After statistical analysis and comparison of these identified serum metabolites (analysed by Gas Chromatography Mass Spectrometry) and hydrophobic serum proteins (analysed by matrix-assisted laser desorption ionisation mass spectrometry), several markers (e.g., 2-piperidinec carboxylic acid, 6-deoxy-mannofuranose, galactoseoxime and a serum peptide of m/z 3177) were determined as having the best discriminating value between the groups. Our findings represent a proof of principle indicating that metabolomic and proteomic approaches can be successfully used in psychiatric biomarker research, even though the results should be regarded as preliminary with a need for replication in larger samples.
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Affiliation(s)
- Khaled Al Awam
- College of Medicine, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
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