Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Saliva for Diabetes’ Complications: Non-Invasive Diagnostics and Monitoring

Version 1 : Received: 13 September 2023 / Approved: 14 September 2023 / Online: 14 September 2023 (11:51:43 CEST)

How to cite: Esteves, E.; Mendes, V.; Manadas, B.; Lemos, A.; Alves, D.; Bernardino, L.; Correia, M. J.; Barros, M.; Esteves, A. C.; Rosa, N. Saliva for Diabetes’ Complications: Non-Invasive Diagnostics and Monitoring. Preprints 2023, 2023090994. https://doi.org/10.20944/preprints202309.0994.v1 Esteves, E.; Mendes, V.; Manadas, B.; Lemos, A.; Alves, D.; Bernardino, L.; Correia, M. J.; Barros, M.; Esteves, A. C.; Rosa, N. Saliva for Diabetes’ Complications: Non-Invasive Diagnostics and Monitoring. Preprints 2023, 2023090994. https://doi.org/10.20944/preprints202309.0994.v1

Abstract

Type 2 Diabetes Mellitus is a chronic metabolic disease that poses a significant long-term health risk due to its debilitating complications. While the diagnosis and monitoring of diabetes are well-established, the monitoring of its numerous complications presents a challenge, which can compromise patients' prognosis and quality of life. We analyzed the proteome of ten saliva samples, five from healthy individuals and five from patients with Type 2 Diabetes Mellitus. The aim was to identify potential biomarkers of Type 2 Diabetes Mellitus and its complications. We used PANTHER and FUNRICH tools to conduct a functional analysis and enrichment approach. Our findings revealed 622 proteins involved in 16 disrupted biological processes, which are linked to Type 2 Diabetes Mellitus. Metabolic processes, response to stimuli, processes of the immune system, and signaling are notable due to their known relation with Type 2 Diabetes Mellitus. Enrichment analysis has revealed that there are eleven biological processes that have been deregulated. These processes involve twenty different salivary proteins that are associated with multiple complications in diabetes. Our findings demonstrate that saliva is a dependable source of possible biomarkers that can be used to monitor diabetes and its complications.

Keywords

Saliva; Proteomics; Biomarkers

Subject

Biology and Life Sciences, Biochemistry and Molecular Biology

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