Infrared Based Saliva Screening Test for COVID‐19

Wood, Bayden R.; Kochan, Kamila; Bedolla, Diana E.; Salazar‐Quiroz, Natalia; Grimley, Samantha L.; Pérez-Guaita, David; Baker, Matthew J.; Vongsvivut, Jitraporn; Tobin, Mark J.; Bambery, Keith R.; Christensen, Dale; Pasricha, Shivani; Eden, Anthony K.; McLean, A. R.; Roy, Supti; Roberts, Jason A.; Druce, Julian; Williamson, Deborah A; McAuley, Julie; Catton, Mike; Purcell, Damian F. J.; Godfrey, Dale I.; Heraud, Philip

doi:10.1002/anie.202104453

Cited by 49 publications

(73 citation statements)

References 30 publications

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“…In addition, it also agrees to the results observed in the second derivative of proteins, where a decreased absorption at the range of random coil in the COVID-19 group is observed, as well as an increment of the bands related to nucleic acids. Moreover, Wood et al reported that the band at 1078 cm −1 among others allowed to distinguish the positive from the negative COVID-19 samples 53 ; this band was found at 1076 cm −1 in this research, showing a higher absorbance in the COVID-19 group.…”

Section: Discussionsupporting

confidence: 57%

ATR-FTIR spectrum analysis of saliva samples from COVID-19 positive patients

Martínez-Cuazitl

Vázquez-Zapién

Sánchez-Brito

et al. 2021

Sci Rep

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The coronavirus disease 2019 (COVID-19) is the latest biological hazard for the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Even though numerous diagnostic tests for SARS-CoV-2 have been proposed, new diagnosis strategies are being developed, looking for less expensive methods to be used as screening. This study aimed to establish salivary vibrational modes analyzed by attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy to detect COVID-19 biological fingerprints that allow the discrimination between COVID-19 and healthy patients. Clinical dates, laboratories, and saliva samples of COVID-19 patients (N = 255) and healthy persons (N = 1209) were obtained and analyzed through ATR-FTIR spectroscopy. Then, a multivariate linear regression model (MLRM) was developed. The COVID-19 patients showed low SaO2, cough, dyspnea, headache, and fever principally. C-reactive protein, lactate dehydrogenase, fibrinogen, d-dimer, and ferritin were the most important altered laboratory blood tests, which were increased. In addition, changes in amide I and immunoglobulin regions were evidenced in the FTIR spectra analysis, and the MLRM showed clear discrimination between both groups. Specific salivary vibrational modes employing ATR-FTIR spectroscopy were established; moreover, the COVID-19 biological fingerprint in saliva was characterized, allowing the COVID-19 detection using an MLRM, which could be helpful for the development of new diagnostic devices.

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Section: Discussionsupporting

confidence: 57%

ATR-FTIR spectrum analysis of saliva samples from COVID-19 positive patients

Martínez-Cuazitl

Vázquez-Zapién

Sánchez-Brito

et al. 2021

Sci Rep

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“…Thus, it is urgent to develop reliable and fast methods to accommodate demand for large-scale usage. 1 − 4 , 7 …”

Section: Introductionmentioning

confidence: 99%

“…Since 2020, many research groups have directed their attention to spectroscopy methods to detect the SARS-CoV-2 virus, such as the development of plasmonic biosensors 19 and virus detection in blood samples, 20 oral or pharyngeal cell smears, 21 and saliva. 4 Barauna et al 21 analyzed oral and pharyngeal cell smears in swabs collected from patients with COVID-19 infection-like symptoms. Samples were separated in training (50 positives and 50 negatives) and validation (20 positives and 61 negatives) and classified by GA-LDA with a sensitivity of 95% and a specificity of 89%.…”

Section: Introductionmentioning

confidence: 99%

“…However, they associated only one of the five selected variables with the virus’ RNA, and other selected variables with the organism’s inflammatory responses. Wood et al 4 studied characteristic spectroscopic signals of SARS-CoV-2 biomarkers with synchrotron-Fourier transform infrared (FTIR) and Raman spectra of purified virus. For COVID-19 infection diagnosis, they modeled 57 mean spectra, of which 29 are positive for SARS-CoV-2 infection by RT-qPCR and 28 are negative.…”

Section: Introductionmentioning

confidence: 99%

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Noninvasive Diagnostic for COVID-19 from Saliva Biofluid via FTIR Spectroscopy and Multivariate Analysis

et al. 2022

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the worst global health crisis in living memory. The reverse transcription polymerase chain reaction (RT-qPCR) is considered the gold standard diagnostic method, but it exhibits limitations in the face of enormous demands. We evaluated a mid-infrared (MIR) data set of 237 saliva samples obtained from symptomatic patients (138 COVID-19 infections diagnosed via RT-qPCR). MIR spectra were evaluated via unsupervised random forest (URF) and classification models. Linear discriminant analysis (LDA) was applied following the genetic algorithm (GA-LDA), successive projection algorithm (SPA-LDA), partial least squares (PLS-DA), and a combination of dimension reduction and variable selection methods by particle swarm optimization (PSO-PLS-DA). Additionally, a consensus class was used. URF models can identify structures even in highly complex data. Individual models performed well, but the consensus class improved the validation performance to 85% accuracy, 93% sensitivity, 83% specificity, and a Matthew’s correlation coefficient value of 0.69, with information at different spectral regions. Therefore, through this unsupervised and supervised framework methodology, it is possible to better highlight the spectral regions associated with positive samples, including lipid (∼1700 cm –1 ), protein (∼1400 cm –1 ), and nucleic acid (∼1200–950 cm –1 ) regions. This methodology presents an important tool for a fast, noninvasive diagnostic technique, reducing costs and allowing for risk reduction strategies.

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“…Another recent study (n = 29 for COVID positive volunteers) determined infrared spectroscopy could be used to discriminate between COVID-infected and non-infected saliva with 93% sensitivity and 82% specificity. 40 As for the previous study, both the COVID-positive and negative cohorts consisted of hospitalized, symptomatic patients requiring treatment. Most labelfree tests would be aimed at screening non-hospitalized people who may be symptomatic or asymptomatic with different levels of severity of COVID-19 infection.…”

Section: Point-of-care Rapid Screeningmentioning

confidence: 99%

Saliva-based detection of COVID-19 infection in a real-world setting using reagent-free Raman spectroscopy and machine learning

Ember

Daoust

Mahfoud

et al. 2021

Preprint

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Significance: The primary method of COVID-19 detection is reverse transcription polymerase chain reaction (RT-PCR) testing. PCR test sensitivity may decrease as more variants of concern arise. Aim: We aimed to develop a reagent-free way to detect COVID-19 in a real-world setting with minimal constraints on sample acquisition. Approach: We present a workflow for collecting, preparing and imaging dried saliva supernatant droplets using a non-invasive, label-free technique known as Raman spectroscopy to detect changes in the molecular profile of saliva associated with COVID-19 infection. Results: Using machine learning and droplet segmentation, amongst all confounding factors, we discriminated between COVID-positive and negative individuals yielding receiver operating coefficient (ROC) curves with an area under curve (AUC) of 0.8 in both males (79% sensitivity, 75% specificity) and females (84% sensitivity, 64% specificity). Taking the sex of the saliva donor into account increased the AUC by 5%. Conclusion:These findings may pave the way for new rapid Raman spectroscopic screening tools for COVID-19 and other infectious diseases.

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Infrared Based Saliva Screening Test for COVID‐19

Cited by 49 publications

References 30 publications

ATR-FTIR spectrum analysis of saliva samples from COVID-19 positive patients

ATR-FTIR spectrum analysis of saliva samples from COVID-19 positive patients

Noninvasive Diagnostic for COVID-19 from Saliva Biofluid via FTIR Spectroscopy and Multivariate Analysis

Saliva-based detection of COVID-19 infection in a real-world setting using reagent-free Raman spectroscopy and machine learning

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