Cross-Sectional Association of Salivary Proteins with Age, Sex, Body Mass Index, Smoking, and Education

Abstract

Whole saliva is gaining more and more attention as a diagnostic tool to study disease-specific changes in human subjects. Prior to the actual disease-related analyses, it is important to understand the influence of various demographic variables and coupled phenotypes on salivary protein signatures. In a cross-sectional approach, we analyzed the influence of age, sex, body mass index (BMI), smoking, and education on salivary protein signatures in whole saliva samples of 187 individuals. Subjects were randomly selected from the population-based Study of Health in Pomerania (SHIP-Trend). Stimulated whole saliva was collected, and proteins were precipitated and proteolytically digested. Samples were analyzed by label-free tandem mass spectrometry. Of the 602 human proteins identified in at least 40% of the saliva samples, we used 304 proteins, which could be identified with at least two unique peptides, for statistical analyses. Univariate and multivariate linear models were used to reveal associations with the phenotypes. The largest number of proteins was associated with smoking status. Moreover, age had a distinct influence on the salivary protein composition. The study discloses the influence of common phenotypes on the salivary protein pattern of human subjects. These results should be considered when studying disease-related proteome signatures in saliva.

Variability Assessment of 90 Salivary Proteins in Intraday and Interday Samples from Healthy Donors by Multiple Reaction Monitoring‐Mass Spectrometry

“…In a recent population‐based approach, Murr et al. used LC‐MS/MS to examine the variation of salivary protein levels in 187 normal individuals and test the correlation of protein levels with age, sex, body mass index (BMI), smoking, and education . They demonstrated that smoking status (54 proteins) and age (12 proteins) were associated with salivary protein abundance and composition among 304 confidentially identified proteins.…”

Functional Specialization of Human Salivary Glands and Origins of Proteins Intrinsic to Human Saliva

“…We used the Human Salivary Proteome Wiki (https://salivaryproteome.nidcr.nih.gov/) to obtain proteome data for the whole saliva, ductal saliva from the PAR, SM, and SL, as well as from blood plasma. The database provides mass-spectrometry-based abundance data for approximately 3,000 proteins compiled from multiple studies (Murr et al, 2017), including those that focused on ductal secretions (Denny et al, 2008). Similar to the comparison approach that we used for integrating GTEx data, we used log transformation (log 10 (1+normalized abundance)) for each dataset.…”

Functional specialization of human salivary glands and origins of proteins intrinsic to human saliva

“…We used the Human Salivary Proteome Wiki ( https://salivaryproteome.nidcr.nih.gov/ ) to obtain proteome data for whole saliva, ductal saliva from the PAR, SM, and SL, as well as from blood plasma. The database provides mass-spectrometry-based abundance data for approximately 3,000 proteins compiled from multiple studies (Murr et al, 2017) , including those that focused on ductal secretions (Denny et al, 2008) . Similar to the comparison approach that we used for integrating GTEx data, we used log transformation (log 10 (1+normalized abundance)) for each dataset.…”