4.7 Review

Systematic Review and Meta-Analysis of Mass Spectrometry Proteomics Applied to Human Peripheral Fluids to Assess Potential Biomarkers of Schizophrenia

期刊

出版社

MDPI
DOI: 10.3390/ijms23094917

关键词

proteomics; mass spectrometry; schizophrenia; biomarkers; human peripheral fluids

资金

  1. FCT-Fundacao para a Ciencia e a Tecnologia, I.P. [POCI-01-0145-FEDER-30943, PTDC/MEC-PSQ/30943/2017, POCI-010145-FEDER-016428, SAICTPAC/0010/2015, POCI-01-0145-FEDER-016795, PTDC/NEUSCC/7051/2014, UIDB/04539/2020, UIDP/04539/2020]
  2. European Social Fund (ESF) through the POCH-Programa Operacional do Capital Humano
  3. European Regional Development Fund (ERDF), through the COMPETE 2020-Operational Programme for Competitiveness and Internationalisation
  4. FCT
  5. [SFRH/BD/88419/2012]
  6. Fundação para a Ciência e a Tecnologia [SFRH/BD/88419/2012, PTDC/MEC-PSQ/30943/2017] Funding Source: FCT

向作者/读者索取更多资源

Mass spectrometry (MS)-based proteomics can effectively identify biomarkers and relevant biological pathways in schizophrenia (SCZ) patients, providing potential targets for prediction and diagnosis improvement. This study identified 217 differentially expressed proteins in SCZ patients through meta-analysis of 19 articles using MS proteomics approaches. Enriched biological pathways included lipid metabolism, complement and coagulation cascades, and immune response. The upregulation of FCN3 and downregulation of APO1, APOA2, APOC1, and APOC3 were suggested as potential biomarkers for SCZ. However, heterogeneity in the findings and confounding factors should be taken into account for future studies to enhance the understanding of differentially expressed proteins.
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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