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Shen HP, Dong X, Li ZB, Wu JZ, Zheng CM, Hu XJ, Qian C, Wang SP, Zhao YL, Li JC. Protein Profiles and Novel Molecular Biomarkers of Schizophrenia Based on 4D-DIA Proteomics. J Proteome Res 2024. [PMID: 38856018 DOI: 10.1021/acs.jproteome.4c00040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Schizophrenia is a severe psychological disorder. The current diagnosis mainly relies on clinical symptoms and lacks laboratory evidence, which makes it very difficult to make an accurate diagnosis especially at an early stage. Plasma protein profiles of schizophrenia patients were obtained and compared with healthy controls using 4D-DIA proteomics technology. Furthermore, 79 DEPs were identified between schizophrenia and healthy controls. GO functional analysis indicated that DEPs were predominantly associated with responses to toxic substances and platelet aggregation, suggesting the presence of metabolic and immune dysregulation in patients with schizophrenia. KEGG pathway enrichment analysis revealed that DEPs were primarily enriched in the chemokine signaling pathway and cytokine receptor interactions. A diagnostic model was ultimately established, comprising three proteins, namely, PFN1, GAPDH and ACTBL2. This model demonstrated an AUC value of 0.972, indicating its effectiveness in accurately identifying schizophrenia. PFN1, GAPDH and ACTBL2 exhibit potential as biomarkers for the early detection of schizophrenia. The findings of our studies provide novel insights into the laboratory-based diagnosis of schizophrenia.
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Affiliation(s)
- Hui-Ping Shen
- Department of Psychiatry, Shaoxing Seventh People's Hospital, Shaoxing 312000, China
| | - Xiaotao Dong
- Major Disease Biomarker Research Laboratory, School of Basic Medical Science, Henan University, Kaifeng 475004, China
| | - Zhi-Bin Li
- Major Disease Biomarker Research Laboratory, School of Basic Medical Science, Henan University, Kaifeng 475004, China
| | - Jing-Zhu Wu
- Department of Psychiatry, Shaoxing Seventh People's Hospital, Shaoxing 312000, China
| | - Chun-Mei Zheng
- Department of Psychiatry, Shaoxing Seventh People's Hospital, Shaoxing 312000, China
| | - Xie-Jun Hu
- Department of Psychiatry, Shaoxing Seventh People's Hospital, Shaoxing 312000, China
| | - Chao Qian
- Department of Psychiatry, Shaoxing Seventh People's Hospital, Shaoxing 312000, China
| | - Sheng-Pang Wang
- Department of Psychiatry, Shaoxing Seventh People's Hospital, Shaoxing 312000, China
| | - Yu-Long Zhao
- Department of Psychiatry, Shaoxing Seventh People's Hospital, Shaoxing 312000, China
| | - Ji-Cheng Li
- Major Disease Biomarker Research Laboratory, School of Basic Medical Science, Henan University, Kaifeng 475004, China
- Institute of Cell Biology, Zhejiang University School of Medicine, Hangzhou 310058, China
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Omenn GS, Lane L, Overall CM, Lindskog C, Pineau C, Packer NH, Cristea IM, Weintraub ST, Orchard S, Roehrl MHA, Nice E, Guo T, Van Eyk JE, Liu S, Bandeira N, Aebersold R, Moritz RL, Deutsch EW. The 2023 Report on the Proteome from the HUPO Human Proteome Project. J Proteome Res 2024; 23:532-549. [PMID: 38232391 PMCID: PMC11026053 DOI: 10.1021/acs.jproteome.3c00591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Since 2010, the Human Proteome Project (HPP), the flagship initiative of the Human Proteome Organization (HUPO), has pursued two goals: (1) to credibly identify the protein parts list and (2) to make proteomics an integral part of multiomics studies of human health and disease. The HPP relies on international collaboration, data sharing, standardized reanalysis of MS data sets by PeptideAtlas and MassIVE-KB using HPP Guidelines for quality assurance, integration and curation of MS and non-MS protein data by neXtProt, plus extensive use of antibody profiling carried out by the Human Protein Atlas. According to the neXtProt release 2023-04-18, protein expression has now been credibly detected (PE1) for 18,397 of the 19,778 neXtProt predicted proteins coded in the human genome (93%). Of these PE1 proteins, 17,453 were detected with mass spectrometry (MS) in accordance with HPP Guidelines and 944 by a variety of non-MS methods. The number of neXtProt PE2, PE3, and PE4 missing proteins now stands at 1381. Achieving the unambiguous identification of 93% of predicted proteins encoded from across all chromosomes represents remarkable experimental progress on the Human Proteome parts list. Meanwhile, there are several categories of predicted proteins that have proved resistant to detection regardless of protein-based methods used. Additionally there are some PE1-4 proteins that probably should be reclassified to PE5, specifically 21 LINC entries and ∼30 HERV entries; these are being addressed in the present year. Applying proteomics in a wide array of biological and clinical studies ensures integration with other omics platforms as reported by the Biology and Disease-driven HPP teams and the antibody and pathology resource pillars. Current progress has positioned the HPP to transition to its Grand Challenge Project focused on determining the primary function(s) of every protein itself and in networks and pathways within the context of human health and disease.
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Affiliation(s)
- Gilbert S. Omenn
- University of Michigan, Ann Arbor, Michigan 48109, United States
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Lydie Lane
- CALIPHO Group, SIB Swiss Institute of Bioinformatics and University of Geneva, 1015 Lausanne, Switzerland
| | - Christopher M. Overall
- University of British Columbia, Vancouver, BC V6T 1Z4, Canada, Yonsei University Republic of Korea
| | | | - Charles Pineau
- University Rennes, Inserm U1085, Irset, 35042 Rennes, France
| | | | | | - Susan T. Weintraub
- University of Texas Health Science Center-San Antonio, San Antonio, Texas 78229-3900, United States
| | | | - Michael H. A. Roehrl
- Department of Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, United States
| | | | - Tiannan Guo
- Westlake Center for Intelligent Proteomics, Westlake Laboratory, Westlake University, Hangzhou 310024, Zhejiang Province, China
| | - Jennifer E. Van Eyk
- Advanced Clinical Biosystems Research Institute, Smidt Heart Institute, Cedars-Sinai Medical Center, 127 South San Vicente Boulevard, Pavilion, 9th Floor, Los Angeles, CA, 90048, United States
| | - Siqi Liu
- BGI Group, Shenzhen 518083, China
| | - Nuno Bandeira
- University of California, San Diego, La Jolla, CA, 92093, United States
| | - Ruedi Aebersold
- Institute of Molecular Systems Biology in ETH Zurich, 8092 Zurich, Switzerland
- University of Zurich, 8092 Zurich, Switzerland
| | - Robert L. Moritz
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Eric W. Deutsch
- Institute for Systems Biology, Seattle, Washington 98109, United States
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Shin D, Lee J, Kim Y, Park J, Shin D, Song Y, Joo EJ, Roh S, Lee KY, Oh S, Ahn YM, Rhee SJ, Kim Y. Evaluation of a Nondepleted Plasma Multiprotein-Based Model for Discriminating Psychiatric Disorders Using Multiple Reaction Monitoring-Mass Spectrometry: Proof-of-Concept Study. J Proteome Res 2024; 23:329-343. [PMID: 38063806 DOI: 10.1021/acs.jproteome.3c00580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2024]
Abstract
Psychiatric evaluation relies on subjective symptoms and behavioral observation, which sometimes leads to misdiagnosis. Despite previous efforts to utilize plasma proteins as objective markers, the depletion method is time-consuming. Therefore, this study aimed to enhance previous quantification methods and construct objective discriminative models for major psychiatric disorders using nondepleted plasma. Multiple reaction monitoring-mass spectrometry (MRM-MS) assays for quantifying 453 peptides in nondepleted plasma from 132 individuals [35 major depressive disorder (MDD), 47 bipolar disorder (BD), 23 schizophrenia (SCZ) patients, and 27 healthy controls (HC)] were developed. Pairwise discriminative models for MDD, BD, and SCZ, and a discriminative model between patients and HC were constructed by machine learning approaches. In addition, the proteins from nondepleted plasma-based discriminative models were compared with previously developed depleted plasma-based discriminative models. Discriminative models for MDD versus BD, BD versus SCZ, MDD versus SCZ, and patients versus HC were constructed with 11 to 13 proteins and showed reasonable performances (AUROC = 0.890-0.955). Most of the shared proteins between nondepleted and depleted plasma models had consistent directions of expression levels and were associated with neural signaling, inflammatory, and lipid metabolism pathways. These results suggest that multiprotein markers from nondepleted plasma have a potential role in psychiatric evaluation.
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Affiliation(s)
- Dongyoon Shin
- Proteomics Research Team, CHA Institute of Future Medicine, Seongnam 13520, Republic of Korea
| | - Jihyeon Lee
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul 03080, Republic of Korea
| | - Yeongshin Kim
- Department of Life Science, General Graduate School, CHA University, Seongnam 13488, Republic of Korea
| | - Junho Park
- Proteomics Research Team, CHA Institute of Future Medicine, Seongnam 13520, Republic of Korea
- Department of Life Science, General Graduate School, CHA University, Seongnam 13488, Republic of Korea
| | - Daun Shin
- Department of Psychiatry, Korea University Anam Hospital, Seoul 02841, Republic of Korea
| | - Yoojin Song
- Department of Psychiatry, Kangwon National University Hospital, Chuncheon 24289, Republic of Korea
| | - Eun-Jeong Joo
- Department of Neuropsychiatry, School of Medicine, Eulji University, Daejeon 34824, Republic of Korea
- Department of Psychiatry, Uijeongbu Eulji Medical Center, Eulji University, Uijeongbu 11759, Republic of Korea
| | - Sungwon Roh
- Department of Psychiatry, Hanyang University Hospital and Hanyang University College of Medicine, Seoul 04763, Republic of Korea
| | - Kyu Young Lee
- Department of Neuropsychiatry, School of Medicine, Eulji University, Daejeon 34824, Republic of Korea
- Department of Psychiatry, Nowon Eulji University Hospital, Seoul 01830, Republic of Korea
| | - Sanghoon Oh
- Department of Neuropsychiatry, School of Medicine, Eulji University, Daejeon 34824, Republic of Korea
- Department of Psychiatry, Uijeongbu Eulji Medical Center, Eulji University, Uijeongbu 11759, Republic of Korea
| | - Yong Min Ahn
- Department of Psychiatry, Seoul National University College of Medicine, Seoul 03080, Republic of Korea
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul 03080, Republic of Korea
- Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul 03080, Republic of Korea
| | - Sang Jin Rhee
- Biomedical Research Institute, Seoul National University Hospital, Seoul 03080, Republic of Korea
| | - Youngsoo Kim
- Proteomics Research Team, CHA Institute of Future Medicine, Seongnam 13520, Republic of Korea
- Department of Life Science, General Graduate School, CHA University, Seongnam 13488, Republic of Korea
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