A distinguishing profile of chemokines, cytokines and biomarkers in the saliva of children with Sjögren's syndrome.

Autor: Hernandez, M Paula Gomez, Starman, Emily E, Davis, Andrew B, Withanage, Miyuraj Harishchandra Hikkaduwa, Zeng, Erliang, Lieberman, Scott M, Brogden, Kim A, Lanzel, Emily A
Předmět:
Zdroj: Rheumatology; Oct2021, Vol. 60 Issue 10, p4765-4777, 13p
Abstrakt: Objective SS is an autoimmune disease most commonly diagnosed in adults but can occur in children. Our objective was to assess the presence of chemokines, cytokines and biomarkers (CCBMs) in saliva from these children that were associated with lymphocyte and mononuclear cell functions. Methods Saliva was collected from 11 children diagnosed with SS prior to age 18 years and 16 normal healthy children. A total of 105 CCBMs were detected in multiplex microparticle-based immunoassays. ANOVA and t test (0.05 level) were used to detect differences. Ingenuity Pathway Analysis (IPA) was used to assess whether elevated CCBMs were in annotations associated with immune system diseases and select leukocyte activities and functions. Machine learning methods were used to evaluate the predictive power of these CCBMs for SS and were measured by receiver operating characteristic (ROC) curve and area under curve (AUC). Results Of the 105 CCBMs detected, 43 (40.9%) differed in children with SS from those in healthy study controls (P < 0.05) and could differentiate the two groups (P < 0.05). Elevated CCBMs in IPA annotations were associated with autoimmune diseases and with leukocyte chemotaxis, migration, proliferation, and regulation of T cell activation. The best AUC value in ROC analysis was 0.93, indicating that there are small numbers of CCBMs that may be useful for diagnosis of SS. Conclusion While 35 of these 43 CCBMs have been previously reported in SS, 8 CCBMs had not. Additional studies focusing on these CCBMs may provide further insight into disease pathogenesis and may contribute to diagnosis of SS in children. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index