Rizal Muhammad Ihsan, Soeroso Yuniarti, Sulijaya Benso, Assiddiq Bobby F, Bachtiar Endang W, Bachtiar Boy M
Oral Science Research Center, Faculty of Dentistry, Universitas Indonesia, Jakarta, Indonesia.
Department of Periodontology, Faculty of Dentistry, Universitas Indonesia, Jakarta, Indonesia.
Heliyon. 2020 Jun 4;6(6):e04022. doi: 10.1016/j.heliyon.2020.e04022. eCollection 2020 Jun.
Quantitative proteomic workflow based on mass spectrometry (MS) is recently developed by the researchers to screen for biomarkers in periodontal diseases comprising periodontitis. Periodontitis is known for chronic inflammatory disease characterized by progressive destruction of the tooth-supporting apparatus, yet has a lack of clear pathobiology based on a discrepancy between specified categories and diagnostic vagueness. The objective of this review was to outlined the accessible information related to proteomics studies on periodontitis. The Preferred Reporting Items for Systematical Reviews and Meta-Analysis (PRISMA) statement guides to acquaint proteomic analysis on periodontal diseases was applied. Three databases were used in this study, such as Pubmed, ScienceDirect and Biomed Central from 2009 up to November 2019. Proteomics analysis platforms that used in the studies were outlined. Upregulated and downregulated proteins findings data were found, in which could be suitable as candidate biomarkers for this disease.
研究人员最近开发了基于质谱(MS)的定量蛋白质组学工作流程,以筛选包括牙周炎在内的牙周疾病中的生物标志物。牙周炎是以牙齿支持组织进行性破坏为特征的慢性炎症性疾病,但由于特定类别之间存在差异且诊断模糊,其病理生物学尚不清楚。本综述的目的是概述与牙周炎蛋白质组学研究相关的可获取信息。应用了系统评价和Meta分析的首选报告项目(PRISMA)声明来指导牙周疾病的蛋白质组学分析。本研究使用了三个数据库,如2009年至2019年11月的PubMed、ScienceDirect和生物医学中心。概述了研究中使用的蛋白质组学分析平台。发现了上调和下调蛋白质的研究结果数据,这些数据可能适合作为该疾病的候选生物标志物。