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Updated: Jul 6, 2025

A High-Throughput Electrochemiluminescence 7-Plex Assay Simultaneously Screening for Type 1 Diabetes and Multiple Autoimmune Diseases
Published on: May 29, 2020
SALIVA-based diagnostic approach for diabetes mellitus: a step towards non-invasive detection - a scoping review
N Cenzato1, F Cazzaniga, C Maspero
1Department of Biomedical, Surgical and Dental Sciences, University of Milan, Milan, Italy. niccolo.cenzato@unimi.it.
Objective:
Diabetes mellitus (DM) is a chronic autoimmune disease whose main feature is chronic hyperglycemia. The causes of DM are impaired insulin secretion, impaired insulin action, or both. Saliva is a biofluid that can be considered as a "mirror" reflecting our body's health status; with the rapid advancement in salivaomics, saliva, being a non-invasive and safe source, could be a substitute for blood in the diagnosis and prognosis of diseases. As there are no precise guidelines about the salivary biomarkers correlated with the diagnosis of diabetes, a review was conducted to verify whether saliva analysis can be feasible and which biomarkers are more reliable, for the diagnosis of this disease.
Materials And Methods:
A literature search was performed through PubMed, Medline, Scopus, Web of Science, LILACS, Open Grey, and Cochrane Library databases. The "PRISMA" guidelines were used for the following review, and thirty-three studies were analyzed.
Results:
Almost all salivary glucose studies suggest that the estimation of this biomarker can be used as a potential indicator. Furthermore, studies that considered other biomarkers such as 1,5-anhydroglucitol, alpha-amylase, N-acetyl-β-D-hexosaminidase, asprosin, resistin, and fructosamine reported that these biomarkers resulted to be potentially useful for diabetes screening and diagnosis, with the exception of the cystatin SA.
Conclusions:
In conclusion, several salivary biomarkers could be useful for monitoring DM, but it would be necessary to further expand the research and define precise values for each marker in order to predict with reasonable confidence if an individual is healthy or suffering from diabetes. Finally, standardized saliva collection and processing techniques are key to minimizing interindividual variability in saliva composition.
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