COVID-19 salivary signature: diagnostic and research opportunities
Sapkota et al.
The finding, in our words
This review summarises the clinical and scientific basis for using saliva as a non-invasive, self-collectable alternative to nasopharyngeal and oropharyngeal swabs for COVID-19 diagnosis and monitoring, and discusses salivary biomarkers including metabolomics that may help identify patients with varying disease severity, including asymptomatic carriers.
A paraphrase to the Library’s standard, never the abstract. The source is one link away and is always the authority.
This review found saliva comparable to blood and urine for detecting viral genetic material and antibodies, supporting patient-centric monitoring and decentralised surveillance. The authors state that standardised protocols and further validation are required for routine clinical use.
This study validated a low-cost 3D-printed smartphone attachment and paper sensor for measuring glucose, uric acid and cholesterol in saliva, demonstrating high correlation with standard ELISA results in a small clinical cohort. The authors suggest this platform offers a scalable solution for decentralised diabetes management by balancing sensitivity with affordability.
Using a synthetic swab for saliva collection gave results closest to no swab for both resting and stimulated samples, indicating minimal pre-analytical interference. The widest metabolite coverage was achieved with ACN:MeOH at 1:1 v/v and a ZIC-HILIC column for polar metabolites plus a C18 column for non-polar metabolites, and resting versus stimulated saliva yielded distinct metabolic profiles that may provide complementary clinical insights.
The study found that self-collected dried saliva on FishburneTabs achieved 92% accuracy for viral RNA detection compared to standard liquid saliva samples. This method supports decentralised testing by enabling reliable sample storage and transport for upper respiratory infections.
This review establishes that microsampling across blood, saliva, urine and stool matrices offers validated workflows and regulatory recognition for human biomonitoring comparable to conventional methods. It finds that these decentralised approaches enhance participant acceptability and enable screening in remote or low-resource settings.