Arroyo Esteban, Oliveira-Alves Mónica G, Chamorro-Petronacci Cintia M, Marichalar-Mendia Xabier, Bravo-López Susana B, Blanco-Carrión Juan, Pérez-Sayáns Mario
Department of Diagnosis and Surgery, Araraquara, School of Dentistry, Sao Paulo State University (Unesp), Araraquara, SP, Brazil.
Technology Research Center (NPT), Universidade Mogi das Cruzes, Mogi das Cruces, Brazil.
J Taibah Univ Med Sci. 2022 Dec 20;18(4):737-747. doi: 10.1016/j.jtumed.2022.12.004. eCollection 2023 Aug.
This systematic review and meta-analysis was aimed at determining differentially expressed protein-based biomarkers detectable in the saliva for the diagnosis of major periodontal diseases.
A literature review was conducted through January 31, 2022. The methodological quality and risk of bias were assessed with the Newcastle-Ottawa scale for case-control studies. Heterogeneity among studies was analysed with the Q statistical test and the I test. p-values lower than 0.10 and I values higher than 50% indicated high heterogeneity among studies; therefore, the random-effects model was used. The analysis of biological pathways associated with the differentially expressed protein markers was performed with the STITCH integration analysis tool and was limited to interactions with high confidence levels (0.7).
Of all protein-based biomarkers detected, 12 were suitable for meta-analysis: IL-1β, MIP-1α, albumin, TNF-α, ICTP, Ig-A, lactoferrin, MMP-8, IL-6, IL-8, IL-17 and PGE2. The salivary markers with high applicability were IL-1β for differentiating patients with chronic periodontal disease from patients with gingivitis with an OE = 73.5 pg/mL; ICTP for differentiating patients with chronic periodontal disease from healthy control patients with an OE = 0.091 ng/mL; and PGE2 for differentiating patients with chronic periodontal disease from healthy control patients with an OE = 36.3 pg/mL.
The biomarkers with the highest differential expression and the greatest potential for clinical applicability are IL-1β for differentiating periodontitis from gingivitis, and ICTP and PGE2 for differentiating periodontitis from healthy status.
本系统评价和荟萃分析旨在确定可在唾液中检测到的基于蛋白质的差异表达生物标志物，用于诊断主要牙周疾病。
截至2022年1月31日进行了文献综述。采用纽卡斯尔-渥太华病例对照研究量表评估方法学质量和偏倚风险。用Q统计检验和I²检验分析研究间的异质性。p值低于0.10且I²值高于50%表明研究间异质性高；因此，使用随机效应模型。使用STITCH整合分析工具对与差异表达蛋白质标志物相关的生物途径进行分析，并限于高置信水平（0.7）的相互作用。
在所有检测到的基于蛋白质的生物标志物中，有12种适合进行荟萃分析：IL-1β、MIP-1α、白蛋白、TNF-α、ICTP、Ig-A、乳铁蛋白、MMP-8、IL-6、IL-8、IL-17和PGE2。适用性高的唾液标志物为：用于区分慢性牙周炎患者和牙龈炎患者的IL-1β，其最佳区分值（OE）=73.5 pg/mL；用于区分慢性牙周炎患者和健康对照患者的ICTP，其OE = 0.091 ng/mL；以及用于区分慢性牙周炎患者和健康对照患者的PGE2，其OE = 36.3 pg/mL。
差异表达最高且临床适用性潜力最大的生物标志物是用于区分牙周炎和牙龈炎的IL-1β，以及用于区分牙周炎和健康状态的ICTP和PGE2。
