Circulating and Salivary NGF and BDNF Levels in SARS-CoV-2 Infection: Potential Predictor Biomarkers of COVID-19 Disease-Preliminary Data.
Filippo BiamonteAgnese ReBijorn Omar BalzaminoGabriele CiascaDaniela SantucciCecilia NapodanoGiuseppina NoccaAntonella FioritaMariapaola MarinoUmberto BasileAlessandra MiceraCinzia Anna Maria CallàPublished in: Journal of personalized medicine (2022)
COVID-19 continues to afflict the global population, causing several pathological diseases and exacerbating co-morbidities due to SARS-CoV-2's high mutation. Recent interest has been devoted to some neuronal manifestations and to increased levels of Nerve Growth Factor (NGF) and Brain-derived Neurotrophic Factor (BDNF) in the bloodstream during SARS-CoV-2 infection, neurotrophins that are well-known for their multifactorial actions on neuro-immune-endocrine and visual functions. Nineteen (19) patients were enrolled in this monocentric prospective study and subjected to anamnesis and biosamples collection (saliva and blood) at hospitalization (acute phase) and 6 months later (remission phase). NGF and BDNF were quantified by ELISA, and biochemical data were related to biostrumental measurements. Increased NGF and BDNF levels were quantified in saliva and serum during the acute phase of SARS-CoV-2 infection (hospitalized patients), and reduced levels were observed in the next 6 months (remission phase), never matching the baseline values. Salivary and circulating data would suggest the possibility of considering sera and saliva as useful matrices for quickly screening neurotrophins, in addition to SARS-CoV2 antigens and RNA. Overall, the findings described herein highlight the importance of NGF and BDNF as dynamic biomarkers for monitoring disease and reinforces the possibility of using saliva and sera for quick, non-invasive COVID-19 screening.
Keyphrases
- growth factor
- sars cov
- respiratory syndrome coronavirus
- coronavirus disease
- stress induced
- electronic health record
- ejection fraction
- newly diagnosed
- prognostic factors
- dendritic cells
- data analysis
- immune response
- climate change
- risk assessment
- disease activity
- artificial intelligence
- brain injury
- human health
- drug induced