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Digital PCR can augment the interpretation of RT-qPCR Cq values for SARS-CoV-2 diagnostics.

ABSTRACT: Coronavirus disease 2019 (COVID-19) is an infectious, acute respiratory disease caused mainly by person-to-person transmission of the coronavirus SARS-CoV-2. Its emergence has caused a world-wide acute health crisis, intensified by the challenge of reliably identifying individuals likely to transmit the disease. Diagnosis is hampered by the many unknowns surrounding this disease, including those relating to infectious viral burden. This uncertainty is exacerbated by disagreement surrounding the clinical relevance of molecular testing using reverse transcription quantitative PCR (RT-qPCR) for the presence of viral RNA, most often based on the reporting of quantification cycles (Cq), which is also termed the cycle threshold (Ct) or crossing point (Cp). Despite it being common knowledge that Cqs are relative values varying according to a wide range of different parameters, there have been efforts to use them as though they were absolute units, with Cqs below an arbitrarily determined value, deemed to signify a positive result and those above, a negative one. Our results investigated the effects of a range of common variables on Cq values. These data include a detailed analysis of the effect of different carrier molecules on RNA extraction. The impact of sample matrix of buccal swabs and saliva on RNA extraction efficiency was demonstrated in RT-qPCR and the impact of potentially inhibiting compounds in urine along with bile salts were investigated in RT-digital PCR (RT-dPCR). The latter studies were performed such that the impact on the RT step could be separated from the PCR step. In this way, the RT was shown to be more susceptible to inhibitors than the PCR. Together, these studies demonstrate that the consequent variability of test results makes subjective Cq cut-off values unsuitable for the identification of infectious individuals. We also discuss the importance of using reliable control materials for accurate quantification and highlight the substantial role played by dPCR as a method for their development.

SUBMITTER: Whale AS

PROVIDER: S-EPMC8387146 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectivesTo exploit the features of digital PCR for implementing SARS-CoV-2 observational studies by reliably including the viral load factor expressed as copies/μL.MethodsA small cohort of 51 Covid-19 positive samples was assessed by both RT-qPCR and digital PCR assays. A linear regression model was built using a training subset, and its accuracy was assessed in the remaining evaluation subset. The model was then used to convert the stored cycle threshold values of a large dataset of 6208 diagnostic samples into copies/μL of SARS-CoV-2. The calculated viral load was used for a single cohort retrospective study. Finally, the cohort was randomly divided into a training set (n = 3095) and an evaluation set (n = 3113) to establish a logistic regression model for predicting case-fatality and to assess its accuracy.ResultsThe model for converting the Ct values into copies/μL was suitably accurate. The calculated viral load over time in the cohort of Covid-19 positive samples showed very low viral loads during the summer inter-epidemic waves in Italy. The calculated viral load along with gender and age allowed building a predictive model of case-fatality probability which showed high specificity (99.0%) and low sensitivity (21.7%) at the optimal threshold which varied by modifying the threshold (i.e. 75% sensitivity and 83.7% specificity). Alternative models including categorised cVL or raw cycle thresholds obtained by the same diagnostic method also gave the same performance.ConclusionThe modelling of the cycle threshold values using digital PCR had the potential of fostering studies addressing issues regarding Sars-CoV-2; furthermore, it may allow setting up predictive tools capable of early identifying those patients at high risk of case-fatality already at diagnosis, irrespective of the diagnostic RT-qPCR platform in use. Depending upon the epidemiological situation, public health authority policies/aims, the resources available and the thresholds used, adequate sensitivity could be achieved with acceptable low specificity.

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Digital PCR can augment the interpretation of RT-qPCR Cq values for SARS-CoV-2 diagnostics.

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