Research Information System University of Greifswald

Andörfer L*¹, Holtfreter B¹, Weiß S², Matthes R¹, Pitchika V¹, Schmidt C³, Samietz S⁴, Kastenmüller G, Nauck M⁵, Völker U², Völzke H³, Csonka L, Suhre K, Pietzner M⁵, Kocher T¹

1 - Zentrum für Zahn-, Mund- und Kieferheilkunde / Poliklinik für Zahnerhaltung,Parodontologie, Endodontologie; Präventive Zahnmedizin und Kinderzahnheilkunde

2 - Interfakultäres Institut für Genetik und Funktionelle Genomforschung / Abt. Funktionelle Genomforschung

3 - Institut für Community Medicine / Abt. SHIP KEF

4 - Zentrum für Zahn-, Mund- und Kieferheilkunde / Poliklinik für Zahnärztliche Prothetik, Alterszahnheilkunde und Medizinische Werkstoffkunde

5 - Institut für Klinische Chemie und Laboratoriumsmedizin

Background: Periodontitis is among the most common chronic diseases worldwide, and it is one of the main reasons for tooth loss. Comprehensive profiling of the metabolite content of the saliva can enable the identification of novel pathways associated with periodontitis and highlight non-invasive markers to facilitate time and cost-effective screening efforts for the presence of periodontitis and the prediction of tooth loss. Methods: We first investigated cross-sectional associations of 13 oral health variables with saliva levels of 562 metabolites, measured by untargeted mass spectrometry among a sub-sample (n = 938) of the Study of Health in Pomerania (SHIP-2) using linear regression models adjusting for common confounders. We took forward any candidate metabolite associated with at least two oral variables, to test for an association with a 5-year tooth loss over and above baseline oral health status using negative binomial regression models. Results: We identified 84 saliva metabolites that were associated with at least one oral variable cross-sectionally, for a subset of which we observed robust replication in an independent study. Out of 34 metabolites associated with more than two oral variables, baseline saliva levels of nine metabolites were positively associated with a 5-year tooth loss. Across all analyses, the metabolites 2-pyrrolidineacetic acid and butyrylputrescine were the most consistent candidate metabolites, likely reflecting oral dysbiosis. Other candidate metabolites likely reflected tissue destruction and cell proliferation. Conclusions: Untargeted metabolic profiling of saliva replicated metabolic signatures of periodontal status and revealed novel metabolites associated with periodontitis and future tooth loss. Keywords: 2-Pyrrolidineacetic acid; Butyrylputrescine; Cohort study; Metabolomics; Periodontitis; Progression; Tooth loss.