Dataset Information

COVID-19 salivary Raman fingerprint: innovative approach for the detection of current and past SARS-CoV-2 infections.

ABSTRACT: The pandemic of COVID-19 is continuously spreading, becoming a worldwide emergency. Early and fast identification of subjects with a current or past infection must be achieved to slow down the epidemiological widening. Here we report a Raman-based approach for the analysis of saliva, able to significantly discriminate the signal of patients with a current infection by COVID-19 from healthy subjects and/or subjects with a past infection. Our results demonstrated the differences in saliva biochemical composition of the three experimental groups, with modifications grouped in specific attributable spectral regions. The Raman-based classification model was able to discriminate the signal collected from COVID-19 patients with accuracy, precision, sensitivity and specificity of more than 95%. In order to translate this discrimination from the signal-level to the patient-level, we developed a Deep Learning model obtaining accuracy in the range 89-92%. These findings have implications for the creation of a potential Raman-based diagnostic tool, using saliva as minimal invasive and highly informative biofluid, demonstrating the efficacy of the classification model.

SUBMITTER: Carlomagno C

PROVIDER: S-EPMC7925543 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

COVID-19 salivary Raman fingerprint: innovative approach for the detection of current and past SARS-CoV-2 infections.

Carlomagno C C Bertazioli D D Gualerzi A A Picciolini S S Banfi P I PI Lax A A Messina E E Navarro J J Bianchi L L Caronni A A Marenco F F Monteleone S S Arienti C C Bedoni M M

Scientific reports 20210302 1

The pandemic of COVID-19 is continuously spreading, becoming a worldwide emergency. Early and fast identification of subjects with a current or past infection must be achieved to slow down the epidemiological widening. Here we report a Raman-based approach for the analysis of saliva, able to significantly discriminate the signal of patients with a current infection by COVID-19 from healthy subjects and/or subjects with a past infection. Our results demonstrated the differences in saliva biochemi ...[more]

PMID: 33654146

Similar Datasets

Project description:Objective: To assess the predictive value of symptoms, sociodemographic characteristics, and SARS-CoV-2 exposure in household, school, and community setting for SARS-CoV-2 seropositivity in Swiss schoolchildren at two time points in 2020. Design: Serological testing of children in primary and secondary schools (aged 6-13 and 12-16 years, respectively) took place in June-July (T1) and October-November (T2) 2020, as part of the longitudinal, school-based study Ciao Corona in the canton of Zurich, Switzerland. Information on sociodemographic characteristics and clinical history was collected with questionnaires to parents; information on school-level SARS-CoV-2 infections was collected with questionnaires to school principals. Community-level cumulative incidence was obtained from official statistics. We used logistic regression to identify individual predictors of seropositivity and assessed the predictive performance of symptom- and exposure-based prediction models. Results: A total of 2,496 children (74 seropositive) at T1 and 2,152 children (109 seropositive) at T2 were included. Except for anosmia (odds ratio 15.4, 95% confidence interval [3.4-70.7]) and headache (2.0 [1.03-3.9]) at T2, none of the individual symptoms were significantly predictive of seropositivity at either time point. Of all the exposure variables, a reported SARS-CoV-2 case in the household was the strongest predictor for seropositivity at T1 (12.4 [5.8-26.7]) and T2 (10.8 [4.5-25.8]). At both time points, area under the receiver operating characteristic curve was greater for exposure-based (T1, 0.69; T2, 0.64) than symptom-based prediction models (T1, 0.59; T2, 0.57). Conclusions: In children, retrospective identification of past SARS-CoV-2 infections based on symptoms is imprecise. SARS-CoV-2 seropositivity is better predicted by factors of SARS-CoV-2 exposure, especially reported SARS-CoV-2 cases in the household. Predicting SARS-CoV-2 seropositivity in children in general is challenging, as few reliable predictors could be identified. For an accurate retrospective identification of SARS-CoV-2 infections in children, serological tests are likely indispensable. Trial registration number: NCT04448717.

Project description:The diagnosis of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection relies on the detection of viral RNA by real-time reverse transcription polymerase chain reaction (rRT-PCR) performed with respiratory specimens, especially nasopharyngeal swabs. However, this procedure requires specialized medical personnel, centralized laboratory facilities, and time to provide results (from several hours up to 1 d). In addition, there is a non-negligible risk of viral transmission for the operator who performs the procedure. For these reasons, several studies have suggested the use of other body fluids, including saliva, for the detection of SARS-CoV-2. The use of saliva as a diagnostic specimen has numerous advantages: it is easily self-collected by the patient with almost no discomfort, it does not require specialized health care personnel for its management, and it reduces the risks for the operator. In the past few months, several scientific papers, media, and companies have announced the development of new salivary tests to detect SARS-CoV-2 infection. Posterior oropharyngeal saliva should be distinguished from oral saliva, since the former is a part of respiratory secretions, while the latter is produced by the salivary glands, which are outside the respiratory tract. Saliva can be analyzed through standard (rRT-PCR) or rapid molecular biology tests (direct rRT-PCR without extraction), although, in a hospital setting, these procedures may be performed only in addition to nasopharyngeal swabs to minimize the incidence of false-negative results. Conversely, the promising role of saliva in the diagnosis of SARS-CoV-2 infection is highlighted by the emergence of point-of-care technologies and, most important, point-of-need devices. Indeed, these devices can be directly used in workplaces, airports, schools, cinemas, and shopping centers. An example is the recently described Rapid Salivary Test, an antigen test based on the lateral flow assay, which detects the presence of the virus by identifying the spike protein in the saliva within a few minutes.

Dataset Information

COVID-19 salivary Raman fingerprint: innovative approach for the detection of current and past SARS-CoV-2 infections.

Publications

COVID-19 salivary Raman fingerprint: innovative approach for the detection of current and past SARS-CoV-2 infections.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets