RT-PCR genotyping assays to identify SARS-CoV-2 variants in England in 2021: a design and retrospective evaluation study

Bray, Neil, Sopwith, Will, Edmunds, Matt, Vansteenhouse, Harper, Feenstra, Jelena D. M., Jacobs, Peter, Rajput, Kamal, O'Connell, Anne Marie, Smith, Melanie L., Blomquist, Paula, Hatziioanou, Diane, Elson, Richard ORCID: https://orcid.org/0000-0001-6350-5274, Vivancos, Roberto, Gallagher, Eileen, Wigglesworth, Mark J., Dominiczak, Anna, Hopkins, Susan and Lake, Iain R. ORCID: https://orcid.org/0000-0003-4407-5357 (2024) RT-PCR genotyping assays to identify SARS-CoV-2 variants in England in 2021: a design and retrospective evaluation study. The Lancet Microbe. ISSN 2666-5247

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Background – Identifying known and emerging pathogen mutations (variants) is important to understand disease transmission and may assist in risk assessment where variants confer increased infectivity or illness severity. Whole genome sequencing (WGS) is the gold standard diagnostic tool for identifying and genetically characterizing variants, but where large populations need rapidly assessing, cost, capacity and timeliness limit its utility. We aimed to assess the potential of genotyping assays to provide accurate and timely variant information at scale by retrospectively examining surveillance for SARS-CoV-2 variants in England between March and September 2021 when genotyping assays were used widely for variant detection.   Methods – We chose a panel of four reverse transcription polymerase chain reaction (RT-PCR) genotyping assays to detect circulating variants of SARS-COV-2 in England and developed a decision-algorithm (DA) to assign a probable SARS-CoV-2 variant to samples using the assay results. We extracted surveillance data from UKHSA databases for >115,000 SARS-CoV-2 positive samples (March 1 2021 and September 6 2021) where variant information was available from both genotyping and WGS. By comparing the genotyping and WGS variant result, we calculated accuracy metrics alongside the time difference between the sample collection date and the availability of variant information. We assessed the number of samples with a variant assigned from genotyping and/or WGS over time.   Findings – From May 2021 to September 2021 variant assignment through genotyping assays and the DAs was accurate for key variants (sensitivity compared to WGS; Beta 91% (95% CI 74 - 100%), Delta 98% (95% CI 98 – 99%), Gamma 93% (95% CI 81 – 100%)). Genotyping produced variant information a median of 3 days (IQR 2– 4) after the sample collection date, faster than WGS (median 9 days; IQR 8 - 11). Genotyping was less costly, and its flexibility enabled a nine-fold increase in the quantity of samples tested for variants by this method.   Interpretation – RT-PCR genotyping assays are suitable for high-throughput variant surveillance, and, once established, genotyping assays may complement WGS though enabling larger scale testing for known variants and timelier results which are important for effective public health response. However, the choice of panels of RT-PCR assays is highly dependent on WGS-generated database information on circulating variants, and hence they are particularly useful in situations where variants are not rapidly changing.   Genotyping assays have a huge potential for guiding disease control globally, especially in settings with limited WGS capacity.

Item Type: Article
Additional Information: Data sharing: The UKHSA welcomes applications from organisations looking to use these data, and all applications will be rigorously reviewed using an objective, standards-based process. Potential applicants should contact DataAccess@ukhsa.gov.uk. Acknowledgments: This work was made possible by the UK Lighthouse Laboratories, their staff members (>6000 people), and Department of Health and Social Care (DHSC) funding between 2020 and 2021. We thank all members of the UKHSA Outbreak Surveillance Team who acted as a central information point to produce timely, accurate, and detailed surveillance reports to support the UK’s COVID-19 response and were central to much of the data used in this paper. We acknowledge the University of Glasgow for supporting in cash and kind the Glasgow Lighthouse Laboratory, which piloted the genotyping assays. RV is affiliated to the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Emerging and Zoonotic Infections and the NIHR HPRU in Gastrointestinal Infections. SH is affiliated to the NIHR HPRU in Health Care Acquired Infections and Antimicrobial Resistance. IRL is funded by the NIHR HPRU in Emergency Preparedness and Response. AD was Director of the Lighthouse Laboratories and was co-funded by the DHSC then UKHSA and the University of Glasgow. The views expressed in this article are those of the author(s) and are not necessarily those of UK Health Security Agency, the Department of Health and Social Care, the National Health Service, or the National Institute for Health Research.
Uncontrolled Keywords: sdg 3 - good health and well-being,4* ,/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being
Faculty \ School: Faculty of Science > School of Environmental Sciences
University of East Anglia Research Groups/Centres > Theme - ClimateUEA
UEA Research Groups: Faculty of Science > Research Groups > Environmental Social Sciences
University of East Anglia Schools > Faculty of Science > Tyndall Centre for Climate Change Research
Faculty of Science > Research Centres > Tyndall Centre for Climate Change Research
Depositing User: LivePure Connector
Date Deposited: 02 Dec 2023 03:32
Last Modified: 02 Feb 2024 02:17
URI: https://ueaeprints.uea.ac.uk/id/eprint/93849
DOI: 10.1016/S2666-5247(23)00320-8

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