Salivary biomarkers as pioneering indicators for diagnosis and severity stratification of pediatric long COVID, 2024, Tyrkalska et al.

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Salivary biomarkers as pioneering indicators for diagnosis and severity stratification of pediatric long COVID
Sylwia D Tyrkalska, Fernando Pérez-Sanz, Lorena Franco-Martínez, Camila P Rubio, Asta Tvarijonaviciute, Silvia Martínez-Subiela, María Méndez-Hernández, Alba González-Aumatell, Clara Carreras-Abad, Èlia Domènech-Marçal, José J Cerón, María L Cayuela, Victoriano Mulero, Sergio Candel

Introduction: Long COVID, or post-acute sequelae of SARS-CoV-2 infection (PASC), manifests as persistent and often debilitating symptoms enduring well beyond the initial COVID-19 infection. This disease is especially worrying in children since it can seriously alter their development. Presently, a specific diagnostic test or definitive biomarker set for confirming long COVID is lacking, relying instead on the protracted presence of symptoms post-acute infection.

Methods: We measured the levels of 13 biomarkers in 105 saliva samples (49 from children with long COVID and 56 controls), and the Pearson correlation coefficient was used to analyse the correlations between the levels of the different salivary biomarkers. Multivariate logistic regression analyses were performed to determine which of the 13 analysed salivary biomarkers were useful to discriminate between children with long COVID and controls, as well as between children with mild and severe long COVID symptoms.

Results: Pediatric long COVID exhibited increased oxidant biomarkers and decreased antioxidant, immune response, and stress-related biomarkers. Correlation analyses unveiled distinct patterns between biomarkers in long COVID and controls. Notably, a multivariate logistic regression pinpointed TOS, ADA2, total proteins, and AOPP as pivotal variables, culminating in a remarkably accurate predictive model distinguishing long COVID from controls. Furthermore, total proteins and ADA1 were instrumental in discerning between mild and severe long COVID symptoms.

Discussion: This research sheds light on the potential clinical utility of salivary biomarkers in diagnosing and categorizing the severity of pediatric long COVID. It also lays the groundwork for future investigations aimed at unravelling the prognostic value of these biomarkers in predicting the trajectory of long COVID in affected individuals.

Link (Frontiers in Cellular and Infection Microbiology)

 

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To further confirm the utility of TOS, ADA2, total proteins, and AOPP, combined, to discriminate between children with long COVID and controls, we elaborated a predictive model with these four salivary biomarkers and tested it. Thus, 85% of all our samples were used to elaborate and train the predictive model, while the remaining 15% of samples were utilized to test it, finding that the model presented very high accuracy, 86.67% (95% CI: 0.5954, 0.9834), with a sensitivity of 0.875 and a specificity of 0.857. Furthermore, this predictive model was also evaluated by performing a receiver operating characteristic (ROC) curve, which is a graphical plot that illustrates the diagnostic ability of a binary classifier system as its discrimination threshold is varied (Fawcett, 2006), resulting in an outstanding area under the curve of 0.906 and, therefore, confirming the strength and potential utility of our predictive model (Figure 3B).

To further confirm the utility of total proteins and ADA1, combined, to discriminate between children with mild and severe long COVID symptoms, we elaborated a predictive model with these two salivary biomarkers and tested it as previously explained. This time, the model presented an accuracy of 71.43% (95% CI: 0.29, 0.96), with a sensitivity of 0.50 and a specificity of 0.80. Finally, the ROC curve for this predictive model showed an area under the curve of 0.796, suggesting that our model has good discriminatory ability (Figure 3E).

Figure 4 Correlations between the salivary biomarkers and the demographic/clinical variables in children with long COVID. Diagram showing the correlations between the salivary biomarkers and the demographic/clinical variables in children with long COVID, according to the Pearson correlation coefficients. Each intersection of the grid refers to the correlation between the two variables faced. The circle sizes show the strength of the correlations according to their P values, while the circle colors refer to the statistical significance of the correlations considering a P value ≤ 0.05 as the threshold.