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. 2020 Oct 10;21(20):7477.
doi: 10.3390/ijms21207477.

Salivary Biomarkers for Diagnosis of Inflammatory Bowel Diseases: A Systematic Review

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Salivary Biomarkers for Diagnosis of Inflammatory Bowel Diseases: A Systematic Review

Kacper Nijakowski et al. Int J Mol Sci. .

Abstract

Saliva as a biological fluid has a remarkable potential in the non-invasive diagnostics of several systemic disorders. Inflammatory bowel diseases are chronic inflammatory disorders of the gastrointestinal tract. This systematic review was designed to answer the question "Are salivary biomarkers reliable for the diagnosis of inflammatory bowel diseases?". Following the inclusion and exclusion criteria, eleven studies were included (according to PRISMA statement guidelines). Due to their heterogeneity, the potential salivary markers for IBD were divided into four groups: oxidative status markers, inflammatory cytokines, microRNAs and other biomarkers. Active CD patients manifest decreased activity of antioxidants (e.g., glutathione, catalase) and increased lipid peroxidation. Therefore, malondialdehyde seems to be a good diagnostic marker of CD. Moreover, elevated concentrations of proinflammatory cytokines (such as interleukin 1β, interleukin 6 or tumour necrosis factor α) are associated with the activity of IBD. Additionaly, selected miRNAs are altered in saliva (overexpressed miR-101 in CD; overexpressed miR-21, miR-31, miR-142-3p and underexpressed miR-142-5p in UC). Among other salivary biomarkers, exosomal PSMA7, α-amylase and calprotectin are detected. In conclusion, saliva contains several biomarkers which can be used credibly for the early diagnosis and regular monitoring of IBD. However, further investigations are necessary to validate these findings, as well as to identify new reliable salivary biomarkers.

Keywords: biomarkers; inflammatory bowel disease; saliva.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
PRISMA flow diagram presenting the detailed search strategy.
Figure 2
Figure 2
Quality assessment, including the main potential risk of bias (risk level: green—low, yellow—unspecified, red—high; quality score: green—good, yellow—intermediate, red—poor).

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