{"title":"Proteomics of neuropsychiatric disorders.","authors":"Afeng Liu, Lina Sun, Wenshu Meng","doi":"10.1016/j.cca.2024.120093","DOIUrl":null,"url":null,"abstract":"<p><p>The pathogenesis of neuropsychiatric disorders (NDs) remains largely unclear due to the lack of objective and reliable biomarkers. Although proteomics is a powerful tool for identification of biomarkers, this approach has been largely ignored in the field of NDs. This review examines recent use of mass spectrometry-based proteomics in characterizing a number of differentially expressed proteins associated with NDs in various biomatrices including blood, urine, saliva, tear and cerebrospinal fluid as well as brain tissue. While preliminary, these early studies appear promising but require comprehensive validation in multi-center and large-scale clinical cohorts. We also discuss the challenges and prospects of proteomics as applied to NDs. These findings may provide a foundation for developing proteomic-based diagnostics and advancing precision medicine in NDs.</p>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":" ","pages":"120093"},"PeriodicalIF":3.2000,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinica Chimica Acta","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.cca.2024.120093","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICAL LABORATORY TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
The pathogenesis of neuropsychiatric disorders (NDs) remains largely unclear due to the lack of objective and reliable biomarkers. Although proteomics is a powerful tool for identification of biomarkers, this approach has been largely ignored in the field of NDs. This review examines recent use of mass spectrometry-based proteomics in characterizing a number of differentially expressed proteins associated with NDs in various biomatrices including blood, urine, saliva, tear and cerebrospinal fluid as well as brain tissue. While preliminary, these early studies appear promising but require comprehensive validation in multi-center and large-scale clinical cohorts. We also discuss the challenges and prospects of proteomics as applied to NDs. These findings may provide a foundation for developing proteomic-based diagnostics and advancing precision medicine in NDs.
期刊介绍：
The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC)
Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells.
The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.
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