Detecting zoonotic Influenza A using QIAstat-Dx Respiratory SARS-CoV-2 panel for pandemic preparedness.

Recent reports from the World Health Organization regarding Influenza A cases of zoonotic origin in humans (H1v and H9N2) and publications describing emergence swine Influenza A cases in humans together with "G4" Eurasian avian-like H1N1 Influenza A virus have drawn global attention to Influenza A pandemic threat. Additionally, the current COVID-19 epidemic has stressed the importance of surveillance and preparedness to prevent potential outbreaks. One feature of the QIAstat-Dx Respiratory SARS-CoV-2 panel is the double target approach for Influenza A detection of seasonal strains affecting humans using a generic Influenza A assay plus the three specific human subtype assays. This work explores the potential use of this double target approach in the QIAstat-Dx Respiratory SARS-Co-V-2 Panel as a tool to detect zoonotic Influenza A strains. A set of recently recorded H9 and H1 spillover strains and the G4 EA Influenza A strains as example of recent zoonotic Flu A strains were subjected to detection prediction with QIAstat-Dx Respiratory SARS-CoV-2 Panel using commercial synthetic dsDNA sequences. In addition, a large set of available commercial human and non-human influenza A strains were also tested using QIAstat-Dx Respiratory SARS-CoV-2 Panel for a better understanding of detection and discrimination of Influenza A strains. Results show that QIAstat-Dx Respiratory SARS-CoV-2 Panel generic Influenza A assay detects all the recently recorded H9, H5 and H1 zoonotic spillover strains and all the G4 EA Influenza A strains. Additionally, these strains yielded negative results for the three-human seasonal IAV (H1, H3 and H1N1 pandemic) assays. Additional non-human strains corroborated those results of Flu A detection with no subtype discrimination, whereas human Influenza strains were positively discriminated. These results indicate that QIAstat-Dx Respiratory SARS-CoV-2 Panel could be a useful tool to diagnose zoonotic Influenza A strains and differentiate them from the seasonal strains commonly affecting humans.

Ct values as a diagnostic tool for monitoring SARS-CoV-2 viral load using the QIAstat-Dx® Respiratory SARS-CoV-2 Panel.

OBJECTIVES: Qualitative real-time polymerase chain reaction tests are not designed to provide quantitative or semiquantitative results because cycle threshold (Ct) values are not normalized to standardized controls of known concentration. The aim of this study was to characterize SARS-CoV-2 viral loads based on Ct values, using the QIAstat-Dx® Respiratory SARS-CoV-2 Panel. METHODS: Different lineages of SARS-CoV-2 clinical samples and the World Health Organization international standard were used to assess the linearity of the QIAstat-Dx Respiratory SARS-CoV-2 Panel. Limit of detection for the different lineages was characterized. RESULTS: Comparable efficiencies and linearity for all samples resulted in R2 ≥0.99, covering a dynamic range of 1,000,000-100 copies/mL for the SARS-CoV-2 assay, showing linear correlation between Ct values and viral load down to 300 copies/mL. CONCLUSION: The SARS-CoV-2 Ct values provided by the QIAstat-Dx® Respiratory SARS-CoV-2 Panel could be used as a surrogate for viral load given the linear correlation between Ct values and viral concentration down to limit of detection. This panel allows to obtain reproducible Ct values for SARS-CoV-2 ribonucleic acid downstream of the sample collection, reducing the sample-to-Ct workflow variability. Ct values can help provide a reliable assessment and comparison of viral loads in patients when tested with the QIAstat-Dx Respiratory SARS-CoV-2 Panel.

Systematic review on the association between respiratory virus real-time PCR cycle threshold values and clinical presentation or outcomes.

OBJECTIVES: It is unclear whether real-time (rt)-PCR cycle threshold (Ct) values can be utilized to guide clinical and infection-control decisions. This systematic review assesses the association between respiratory pathogen rt-PCR Ct values and clinical presentation or outcomes. METHODS: We searched MEDLINE, EMBASE and Cochrane library databases on 14-17 January 2020 for studies reporting the presence or absence of an association between Ct values and clinical presentation or outcomes, excluding animal studies, reviews, meta-analyses, and non-English language studies. RESULTS: Among 33 studies identified (reporting on between 9 and 4918 participants by pathogen), influenza (n = 11 studies; 4918 participants), human rhinovirus (HRV, n = 11; 2012) and respiratory syncytial virus (RSV, n = 8; 3290) were the most-studied pathogens. Low influenza Ct values were associated with mortality in 1/3 studies, with increased disease severity/duration or ICU admission in 3/9, and with increased hospitalization or length of hospital stay (LOS) in 1/6. Low HRV Ct values were associated with increased disease severity/duration or ICU admission in 3/10 studies, and with increased hospitalization or LOS in 1/3. Low RSV Ct values were associated with increased disease severity/duration or ICU admission in 3/6 studies, and with increased hospitalization or LOS in 4/4. Contradictory associations were also identified for other respiratory pathogens. CONCLUSIONS: Respiratory infection Ct values may inform clinical and infection-control decisions. However, the study heterogeneity observed in this review highlights the need for standardized workflows to utilize Ct values as a proxy of genomic load and confirm their value for respiratory infection management.

Performance evaluation of the QIAstat-Dx® Respiratory SARS-CoV-2 Panel.

OBJECTIVE: The aim of this study was to evaluate the QIAstat-Dx® Respiratory SARS-CoV-2 Panel (QIAstat-SARS-CoV-2), which is a closed, fully automated, multiplex polymerase chain reaction (PCR) assay that detects severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and 21 other pathogens that cause respiratory disease. METHODS: Nasopharyngeal swabs from patients with or suspected of having coronavirus disease 2019 were collected and tested at Bichat-Claude Bernard Hospital, Paris, France. Using the World Health Organisation-approved real-time-PCR assay developed by the Charité Institute of Virology as the reference, positive percent agreement (PPA) and negative percent agreement (NPA) were calculated. RESULTS: In total, 189 negative and 88 positive samples were analyzed. QIAstat-SARS-CoV-2 had an NPA of 90.48% (95% confidence interval (CI), 85.37%, 94.26%) and a PPA of 94.32% (95% CI, 87.24%, 98.13%). Co-infections were detected by QIAstat-SARS-CoV-2 in 4/277 specimens. The methods exhibited comparable failure rates (23/307 [7.5%] vs. 6/298 [2.0%] for QIAstat-SARS-CoV-2 and reference methods, respectively). The turnaround time was shorter for QIAstat-SARS-CoV-2 compared with the reference method (difference in mean -14:30 h [standard error, 0:03:23; 95% CI, -14:37, -14:24]; P < 0.001). CONCLUSIONS: QIAstat-SARS-CoV-2 shows good agreement with the reference assay, providing faster and accurate results for detecting SARS-CoV-2.

A Systematic Review of the Clinical Utility of Cycle Threshold Values in the Context of COVID-19.

BACKGROUND: The ability to predict likely prognosis and infectiousness for patients with COVID-19 would aid patient management decisions. Diagnosis is usually via real-time PCR, and it is unclear whether the semi-quantitative capability of this method, determining viral load through cycle threshold (Ct) values, can be leveraged. OBJECTIVES: We aim to review available knowledge on correlations between SARS-COV-2 Ct values and patient- or healthcare-related outcomes to determine whether Ct values provide useful clinical information. SOURCES: A PubMed search was conducted on 1 June 2020 based on a search strategy of (Ct value OR viral load) AND SARS-CoV-2. Data were extracted from studies reporting on the presence or absence of an association between Ct values, or viral loads determined via Ct value, and clinical outcomes. CONTENT: Data from 18 studies were relevant for inclusion. One study reported on the correlation between Ct values and mortality and one study reported on the correlation between Ct values and progression to severe disease; both reported a significant association (p < 0.001 and p = 0.008, respectively). Fourteen studies reported on the correlation between Ct value or viral loads determined via Ct value and disease severity, and an association was observed in eight (57%) studies. Studies reporting on the correlation of viral load with biochemical and haematological markers showed an association with at least one marker, including increased lactate dehydrogenase (n = 4), decreased lymphocytes (n = 3) and increased high-sensitivity troponin I (n = 2). Two studies reporting on the correlation with infectivity showed that lower Ct values were associated with higher viral culture positivity. IMPLICATIONS: Data suggest that lower Ct values may be associated with worse outcomes and that Ct values may be useful in predicting the clinical course and prognosis of patients with COVID-19; however, further studies are warranted to confirm clinical value.

Correction to: A Systematic Review of the Clinical Utility of Cycle Threshold Values in the Context of COVID-19.

The original article can be found online.

Multiple assays in a real-time RT-PCR SARS-CoV-2 panel can mitigate the risk of loss of sensitivity by new genomic variants during the COVID-19 outbreak.

OBJECTIVES: In this study, five SARS-CoV-2 PCR assay panels were evaluated against the accumulated genetic variability of the virus to assess the effect on sensitivity of the individual assays. DESIGN OR METHODS: As of week 21, 2020, the complete set of available SARS-CoV-2 genomes from GISAID and GenBank databases were used in this study. SARS-CoV-2 primer sequences from publicly available panels (WHO, CDC, NMDC, and HKU) and QIAstat-Dx were included in the alignment, and accumulated genetic variability affecting any oligonucleotide annealing was annotated. RESULTS: A total of 11,627 (34.38%) genomes included single mutations affecting annealing of any PCR assay. Variations in 8,773 (25.94%) genomes were considered as high risk, whereas additional 2,854 (8.43%) genomes presented low frequent single mutations and were predicted to yield no impact on sensitivity. In case of the QIAstat-Dx SARS-CoV-2 Panel, 99.11% of the genomes matched with a 100% coverage all oligonucleotides, and critical variations were tested in vitro corroborating no loss of sensitivity. CONCLUSIONS: This analysis stresses the importance of targeting more than one region in the viral genome for SARS-CoV-2 detection to mitigate the risk of loss of sensitivity due to the unknown mutation rate during this SARS-CoV-2 outbreak.

Multicenter Evaluation of the QIAstat-Dx Respiratory Panel for Detection of Viruses and Bacteria in Nasopharyngeal Swab Specimens.

The QIAstat-Dx Respiratory Panel (QIAstat-Dx RP) is a multiplex in vitro diagnostic test for the qualitative detection of 20 pathogens directly from nasopharyngeal swab (NPS) specimens. The assay is performed using a simple sample-to-answer platform with results available in approximately 69 min. The pathogens identified are adenovirus, coronavirus 229E, coronavirus HKU1, coronavirus NL63, coronavirus OC43, human metapneumovirus A and B, influenza A, influenza A H1, influenza A H3, influenza A H1N1/2009, influenza B, parainfluenza virus 1, parainfluenza virus 2, parainfluenza virus 3, parainfluenza virus 4, rhinovirus/enterovirus, respiratory syncytial virus A and B, Bordetella pertussis, Chlamydophila pneumoniae, and Mycoplasma pneumoniae This multicenter evaluation provides data obtained from 1,994 prospectively collected and 310 retrospectively collected (archived) NPS specimens with performance compared to that of the BioFire FilmArray Respiratory Panel, version 1.7. The overall percent agreement between QIAstat-Dx RP and the comparator testing was 99.5%. In the prospective cohort, the QIAstat-Dx RP demonstrated a positive percent agreement of 94.0% or greater for the detection of all but four analytes: coronaviruses 229E, NL63, and OC43 and rhinovirus/enterovirus. The test also demonstrated a negative percent agreement of ≥97.9% for all analytes. The QIAstat-Dx RP is a robust and accurate assay for rapid, comprehensive testing for respiratory pathogens.