Saliva has emerged as a promising diagnostic fluid for viral infections, enabling the direct analysis of viral genetic material and the detection of infection markers such as proteins, metabolites, microRNAs, and immunoglobulins. This comprehensive review aimed to explore the use of saliva as a diagnostic tool for viral infections, emphasizing its advantages and limitations. Saliva stands out due to its simplicity and safety in collection, along with the convenience of self-collection without the need for healthcare supervision, while potentially being comparable to urine and blood in terms of effectiveness. Herein, we highlighted the significant potential of saliva in assessing viral loads and diagnosing viral infections, such as herpesviruses, HPV, PyV, TTV, SARS-CoV-2, and MPXV. The detection of viral shedding in saliva underscores its utility in early diagnosis, the monitoring of infection progression, and evaluating treatment responses. The non-invasive nature of saliva collection makes it an appealing alternative to more invasive methods, promoting better patient compliance and facilitating large-scale screening and surveillance. As such, we further highlight current evidence on the use of saliva as a prognostic tool. Although a significant amount of data is already available, further investigations are warranted to more comprehensively assess the added benefit from the utilization of salivary biomarkers in the clinics. Salivary biomarkers show great promise for the early detection and prevention of viral infection complications, potentially improving disease management and control at the population level. Integrating these non-invasive tools into routine clinical practice could enhance personalized healthcare strategies and patient outcomes. Future studies should focus on establishing standardization protocols, validating the accuracy of salivary diagnostics, and expanding clinical research to enhance the diagnostic and monitoring capabilities of salivary biomarkers.

Several reports have proposed that the viral load of torque teno virus (TTV) in plasma is a biomarker of immune function in solid organ transplantation (SOT) and in allogeneic hematopoietic stem ce...

Background. Torquetenovirus (TTV) is a small DNA virus constituting the human virome. High levels of TTV-DNA have been shown to be associated with immunosuppression and inflammatory chronic disorders. Aim. To assess the possible association between the salivary viral load of TTV-DNA in patients hospitalised due to COVID-19 and disease severity. Methods. Saliva samples collected from 176 patients infected with SARS-CoV-2 were used to investigate the presence of SARS-CoV-2 and TTV-DNA by use of real-time RT-PCR. Results. The majority of patients were male with severe COVID-19. Presence of SARS-CoV-2 was observed in the saliva of 64.77% of patients, showing TTV-DNA in 55.68% of them. Patients with impaired clinical conditions (p < 0.001), which evolved to death (p = 0.003), showed a higher prevalence of TTV-DNA. The median viral load in patients with severe condition was 4.99 log₁₀ copies/mL, in which those who were discharged and those evolving to death had values of 3.96 log₁₀ copies/mL and 6.27 log₁₀ copies/mL, respectively. A statistically significant association was found between the distribution of TTV-DNA viral load in saliva samples and severity of COVID-19 (p = 0.004) and disease outcomes (p < 0.001). Conclusions. These results indicate that TTV-DNA in saliva could be a useful biomarker of COVID-19 severity and prognosis.

Background: Peri-implantitis is characterized as a pathological change in the tissues around dental implants. Fourier-transform infrared spectroscopy (FTIR) provides molecular information from optical phenomena observed by the vibration of molecules, which is used in biological studies to characterize changes and serves as a form of diagnosis. Aims: this case-control study evaluated the peri-implant disease by using FTIR spectroscopy with attenuated total reflectance in the fingerprint region. Methods: 38 saliva samples were evaluated, 17 from the control group and 21 from the peri-implantitis group. Clinical data such as plaque index (PI), gingival index, probing depth (PS), and attachment level were assessed. Results: The results of clinical parameters showed a statistical difference between the two groups regarding an excess of the PI. In the FTIR-ATR analysis, the main components revealed vibrational modes of fatty acids, histidine, lipid esters, nucleic acids, and tryptophan, with the main molecules contributing to spectral discrimination. The five-component partial least-squares discriminant analysis classification model had an accuracy of 81%, showing differences between healthy and diseased implants. Conclusion: the FTIR spectroscopy provides important molecular characteristics of the samples and the results in association with clinical data show the effectiveness of using this tool for diagnosing the disease.