A comparative proteomic analysis to define the influencing factors on gingival crevicular fluid using LC-MS/MS

Gingival crevicular fluid (GCF) is a promising biofluid for disease identification and biomarker searching in periodontology. This study aimed to investigate the possible influencing factors, including tooth site, sex and age, on the normal GCF proteome. Forty periodontal healthy adults were randomly divided into a training group and a testing group. In the training group, GCF samples from 12 adults were analyzed using the iTRAQ 2D LC-MS/MS method. The influencing factors, tooth site (including periodontitis-susceptible and -insusceptible tooth sites), sex and age, and related differential proteins were defined and functionally annotated. The important differential proteins from 28 adults in the testing group were then validated by PRM analysis. An average of approximately 5 differential proteins were found between tooth sites of periodontitis-susceptible and -insusceptible sites. Eighty-five differentially expressed proteins were obtained between sexes in the young group, while only 7 sex-associated proteins were found in the old group. A total of 203 and 235 age-associated proteins were found in the male and female groups, respectively. The differential protein functional annotation showed that sex-related proteins were mainly related to immune function and metabolism, and age-related proteins were primarily associated with inflammation, lipid metabolism and immune function. In the testing group, a total of 4 sex-related proteins and 12 age-related proteins were validated by PRM analysis. SIGNIFICANCE: The influences of tooth site, sex and age in GCF proteomics in periodontal health were firstly analyzed using LC-MS/MS. Tooth site showed a small influence on the GCF proteome. The sex effect was significant in young adults, but its influence in old adults is small. Age is an important impact factor for the GCF proteome. These findings enrich the knowledge about the normal GCF proteome and might benefit future disease analyses.