ABSTRACT
The sudden outbreak and worldwide spread of the SARS-CoV-2 pandemic pushed the scientific community to find fast solutions to cope with the health emergency. COVID-19 complexity, in terms of clinical outcomes, severity, and response to therapy suggested the use of multifactorial strategies, characteristic of the network medicine, to approach the study of the pathobiology. Proteomics and interactomics especially allow to generate datasets that, reduced and represented in the forms of networks, can be analyzed with the tools of systems biology to unveil specific pathways central to virus-human host interaction. Moreover, artificial intelligence tools can be implemented for the identification of druggable targets and drug repurposing. In this review article, we provide an overview of the results obtained so far, from a systems biology perspective, in the understanding of COVID-19 pathobiology and virus-host interactions, and in the development of disease classifiers and tools for drug repurposing.
Subject(s)
COVID-19 , Systems Biology , Animals , Artificial Intelligence , Drug Repositioning , Host Microbial Interactions , HumansSubject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Pandemics , Pneumonia, Viral/epidemiology , COVID-19 , Humans , SARS-CoV-2 , SalivaABSTRACT
OBJECTIVES: This study analyzed salivary samples of COVID-19 patients and compared the results with their clinical and laboratory data. METHODS: Salivary samples of 25 COVID-19 patients were analyzed by rRT-PCR. The following data were collected: age, sex, comorbidities, drugs. Lactate dehydrogenase (LDH) and ultrasensitive reactive C protein (usRCP) values were registered on the same day when a salivary swab was collected. Prevalence of positivity in saliva and association between clinical data and the cycle threshold as a semiquantitative indicator of viral load were considered. RESULTS: Twenty-five subjects were recruited into this study, 17 males and 8 females. The mean age was 61.5 +/- 11.2 years. Cardiovascular and/or dysmetabolic disorders were observed in 65.22% of cases. All the samples tested positive for the presence of SARS-CoV-2, while there was an inverse association between LDH and Ct values. Two patients showed positive salivary results on the same days when their pharyngeal or respiratory swabs showed conversion. CONCLUSIONS: Saliva is a reliable tool to detect SARS-CoV-2. The role of saliva in COVID-19 diagnosis could not be limited to a qualitative detection of the virus, but it may also provide information about the clinical evolution of the disease.