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Liu H, Wang Z, Li H, Li M, Han B, Qi Y, Wang H, Gao J. Label-free Quantitative Proteomic Analysis of Cerebrospinal Fluid and Serum in Patients With Relapse-Remitting Multiple Sclerosis. Front Genet 2022; 13:892491. [PMID: 35571066 PMCID: PMC9092947 DOI: 10.3389/fgene.2022.892491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 04/05/2022] [Indexed: 11/13/2022] Open
Abstract
Background: The lack of effective serum and cerebrospinal fluid (CSF) biomarkers remains a barrier to early diagnosis and treatment of multiple sclerosis (MS). The study is to identify the diagnostic biomarkers of serum and CSF in patients who suffered MS. Methods: At first, we performed differential analysis of CSF and serum proteomics on control and relapse-remitting multiple sclerosis (RRMS) patients. Secondly, CSF and serum’s differential proteins were compared, in order to identify the significative proteins. Finally, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis were performed on the differential proteins in serum and CSF respectively to clarify their common biological functions and pathways. Results: At the first step, in CSF, 73 proteins were significantly differentially expressed in the RRMS set compared with the controls. In serum, 22 proteins were differentially expressed. Secondly, we found MMP2 C8G and CFH were the same high expression trend in CSF and serum. Finally, we found the differential proteins in serum and CSF are mostly participated in biological processes: immuno-inflammatory response, neuronal development, cell adhesion and signaling. Conclusion: MMP2, C8G and CFH may participate in the pathogenesis of RRMS, which are the potential diagnostic biomarkers of the disease.
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Affiliation(s)
- Haijie Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Ziwen Wang
- Department of Neurology, Baoding No. 1 Central Hospital, Baoding, China
| | - He Li
- Department of Automation, College of Information Science and Engineering, Tianjin Tianshi College, Tianjin, China
| | - Meijie Li
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Bo Han
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yuan Qi
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Huailu Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Juan Gao
- Department of Neurology, Baoding No. 1 Central Hospital, Baoding, China
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Proteomics in Multiple Sclerosis: The Perspective of the Clinician. Int J Mol Sci 2022; 23:ijms23095162. [PMID: 35563559 PMCID: PMC9100097 DOI: 10.3390/ijms23095162] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 04/26/2022] [Accepted: 05/02/2022] [Indexed: 02/08/2023] Open
Abstract
Multiple sclerosis (MS) is the inflammatory demyelinating and neurodegenerative disease of the central nervous system (CNS) that affects approximately 2.8 million people worldwide. In the last decade, a new era was heralded in by a new phenotypic classification, a new diagnostic protocol and the first ever therapeutic guideline, making personalized medicine the aim of MS management. However, despite this great evolution, there are still many aspects of the disease that are unknown and need to be further researched. A hallmark of these research are molecular biomarkers that could help in the diagnosis, differential diagnosis, therapy and prognosis of the disease. Proteomics, a rapidly evolving discipline of molecular biology may fulfill this dire need for the discovery of molecular biomarkers. In this review, we aimed to give a comprehensive summary on the utility of proteomics in the field of MS research. We reviewed the published results of the method in case of the pathogenesis of the disease and for biomarkers of diagnosis, differential diagnosis, conversion of disease courses, disease activity, progression and immunological therapy. We found proteomics to be a highly effective emerging tool that has been providing important findings in the research of MS.
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Rajczewski AT, Jagtap PD, Griffin TJ. An overview of technologies for MS-based proteomics-centric multi-omics. Expert Rev Proteomics 2022; 19:165-181. [PMID: 35466851 PMCID: PMC9613604 DOI: 10.1080/14789450.2022.2070476] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
INTRODUCTION Mass spectrometry-based proteomics reveals dynamic molecular signatures underlying phenotypes reflecting normal and perturbed conditions in living systems. Although valuable on its own, the proteome has only one level of moleclar information, with the genome, epigenome, transcriptome, and metabolome, all providing complementary information. Multi-omic analysis integrating information from one or more of these other domains with proteomic information provides a more complete picture of molecular contributors to dynamic biological systems. AREAS COVERED Here, we discuss the improvements to mass spectrometry-based technologies, focused on peptide-based, bottom-up approaches that have enabled deep, quantitative characterization of complex proteomes. These advances are facilitating the integration of proteomics data with other 'omic information, providing a more complete picture of living systems. We also describe the current state of bioinformatics software and approaches for integrating proteomics and other 'omics data, critical for enabling new discoveries driven by multi-omics. EXPERT COMMENTARY Multi-omics, centered on the integration of proteomics information with other 'omic information, has tremendous promise for biological and biomedical studies. Continued advances in approaches for generating deep, reliable proteomic data and bioinformatics tools aimed at integrating data across 'omic domains will ensure the discoveries offered by these multi-omic studies continue to increase.
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Affiliation(s)
- Andrew T. Rajczewski
- Department of Biochemistry, Molecular and Cell Biology Building, University of Minnesota, 420 Washington Ave SE 7-129, Minneapolis, MN, 55455, USA
| | - Pratik D. Jagtap
- Department of Biochemistry, Molecular and Cell Biology Building, University of Minnesota, 420 Washington Ave SE 7-129, Minneapolis, MN, 55455, USA,Coauthor, Research Department of Biochemistry, Molecular and Cell Biology Building, University of Minnesota, 420 Washington Ave SE 7-129, Minneapolis, MN, 55455, USA
| | - Timothy J. Griffin
- Department of Biochemistry, Molecular and Cell Biology Building, University of Minnesota, 420 Washington Ave SE 7-129, Minneapolis, MN, 55455, USA,Department of Biochemistry, Molecular and Cell Biology Building, University of Minnesota, 420 Washington Ave SE 7-129, Minneapolis, MN, 55455, USA
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Salazar IL, Lourenço AST, Manadas B, Baldeiras I, Ferreira C, Teixeira AC, Mendes VM, Novo AM, Machado R, Batista S, Macário MDC, Grãos M, Sousa L, Saraiva MJ, Pais AACC, Duarte CB. Posttranslational modifications of proteins are key features in the identification of CSF biomarkers of multiple sclerosis. J Neuroinflammation 2022; 19:44. [PMID: 35135578 PMCID: PMC8822857 DOI: 10.1186/s12974-022-02404-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 01/26/2022] [Indexed: 12/27/2022] Open
Abstract
Background Multiple sclerosis is an inflammatory and degenerative disease of the central nervous system (CNS) characterized by demyelination and concomitant axonal loss. The lack of a single specific test, and the similarity to other inflammatory diseases of the central nervous system, makes it difficult to have a clear diagnosis of multiple sclerosis. Therefore, laboratory tests that allows a clear and definite diagnosis, as well as to predict the different clinical courses of the disease are of utmost importance. Herein, we compared the cerebrospinal fluid (CSF) proteome of patients with multiple sclerosis (in the relapse–remitting phase of the disease) and other diseases of the CNS (inflammatory and non-inflammatory) aiming at identifying reliable biomarkers of multiple sclerosis. Methods CSF samples from the discovery group were resolved by 2D-gel electrophoresis followed by identification of the protein spots by mass spectrometry. The results were analyzed using univariate (Student’s t test) and multivariate (Hierarchical Cluster Analysis, Principal Component Analysis, Linear Discriminant Analysis) statistical and numerical techniques, to identify a set of protein spots that were differentially expressed in CSF samples from patients with multiple sclerosis when compared with other two groups. Validation of the results was performed in samples from a different set of patients using quantitative (e.g., ELISA) and semi-quantitative (e.g., Western Blot) experimental approaches. Results Analysis of the 2D-gels showed 13 protein spots that were differentially expressed in the three groups of patients: Alpha-1-antichymotrypsin, Prostaglandin-H2-isomerase, Retinol binding protein 4, Transthyretin (TTR), Apolipoprotein E, Gelsolin, Angiotensinogen, Agrin, Serum albumin, Myosin-15, Apolipoprotein B-100 and EF-hand calcium-binding domain—containing protein. ELISA experiments allowed validating part of the results obtained in the proteomics analysis and showed that some of the alterations in the CSF proteome are also mirrored in serum samples from multiple sclerosis patients. CSF of multiple sclerosis patients was characterized by TTR oligomerization, thus highlighting the importance of analyzing posttranslational modifications of the proteome in the identification of novel biomarkers of the disease. Conclusions The model built based on the results obtained upon analysis of the 2D-gels and in the validation phase attained an accuracy of about 80% in distinguishing multiple sclerosis patients and the other two groups. Supplementary Information The online version contains supplementary material available at 10.1186/s12974-022-02404-2.
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Affiliation(s)
- Ivan L Salazar
- CNC-Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal.,Institute for Interdisciplinary Research, University of Coimbra, Coimbra, Portugal
| | - Ana S T Lourenço
- CNC-Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal.,Institute for Interdisciplinary Research, University of Coimbra, Coimbra, Portugal
| | - Bruno Manadas
- CNC-Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal.,Institute for Interdisciplinary Research, University of Coimbra, Coimbra, Portugal
| | - Inês Baldeiras
- CNC-Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal.,Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Cláudia Ferreira
- Coimbra Chemistry Centre, Department of Chemistry, University of Coimbra, Coimbra, Portugal
| | - Anabela Claro Teixeira
- Molecular Neurobiology Group, Instituto de Biologia Molecular e Celular (IBMC), Instituto de Investigação e Inovação em Saúde (i3S), University of Porto, Porto, Portugal
| | - Vera M Mendes
- CNC-Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal
| | - Ana Margarida Novo
- Neurology Department, CHUC-Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Rita Machado
- Neurology Department, CHUC-Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Sónia Batista
- CNC-Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal.,Neurology Department, CHUC-Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Maria do Carmo Macário
- Neurology Department, CHUC-Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Mário Grãos
- CNC-Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal.,Institute for Interdisciplinary Research, University of Coimbra, Coimbra, Portugal.,Biocant-Associação de Transferência de Tecnologia, Cantanhede, Portugal
| | - Lívia Sousa
- Neurology Department, CHUC-Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Maria João Saraiva
- Molecular Neurobiology Group, Instituto de Biologia Molecular e Celular (IBMC), Instituto de Investigação e Inovação em Saúde (i3S), University of Porto, Porto, Portugal
| | - Alberto A C C Pais
- Coimbra Chemistry Centre, Department of Chemistry, University of Coimbra, Coimbra, Portugal
| | - Carlos B Duarte
- CNC-Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal. .,Department of Life Sciences, University of Coimbra, Coimbra, Portugal.
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