Salivary proteins serve multifaceted roles in maintaining oral health and hold significant potential for diagnosing and monitoring diseases due to the non-invasive nature of saliva sampling. However, the clinical utility of current saliva biomarker studies is limited by the lack of reference intervals (RIs) to correctly interpret the testing result. Here, we developed a rapid and robust saliva proteome profiling workflow, obtaining coverage of >1,200 proteins from a 50-µL unstimulated salivary flow with 30 min gradients. With the workflow, we investigated protein variation in a cohort of 1,743 healthy individuals. The significant differences in non-linear saliva proteomes among age groups resulted in the establishment of age-related RIs covering 1,123 salivary protein variations. We then utilized a cohort of 30 epilepsy patients as a case study to illustrate the practical application of RIs in identifying disease-enriched outlier proteins, elucidating their cellular origins, determining disease diagnosis, and visualizing outlier proteins in each epilepsy patient. Our study showed the classification model based on the RI achieved PR-AUC of 0.815 (95%CI: 0.813-0.826). Additionally, we validated these results in an independent test set. Furthermore, the epilepsy cohort could be further stratified into 2 major subtypes, with one subtype characterized by disrupted metabolic proteins and containing mostly Focal Cortical Dysplasia (FCD) type III epilepsy patients. Overall, our study provided a proof-of-principle workflow for the use of salivary proteome for health monitoring, epilepsy diagnosis and subtyping.
Keywords: biomarker; disease subtypes; epilepsy; reference intervals; saliva proteomics.
© 2024. Science China Press.