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Osterman A, Krenn F, Iglhaut M, Badell I, Lehner A, Späth PM, Stern M, Both H, Bender S, Muenchhoff M, Graf A, Krebs S, Blum H, Grimmer T, Durner J, Czibere L, Dächert C, Grzimek-Koschewa N, Protzer U, Kaderali L, Baldauf HM, Keppler OT. Automated antigen assays display a high heterogeneity for the detection of SARS-CoV-2 variants of concern, including several Omicron sublineages. Med Microbiol Immunol 2023; 212:307-322. [PMID: 37561226 PMCID: PMC10501957 DOI: 10.1007/s00430-023-00774-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 07/11/2023] [Indexed: 08/11/2023]
Abstract
Diagnostic tests for direct pathogen detection have been instrumental to contain the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) pandemic. Automated, quantitative, laboratory-based nucleocapsid antigen (Ag) tests for SARS-CoV-2 have been launched alongside nucleic acid-based test systems and point-of-care (POC) lateral-flow Ag tests. Here, we evaluated four commercial Ag tests on automated platforms for the detection of different sublineages of the SARS-CoV-2 Omicron variant of concern (VoC) (B.1.1.529) in comparison with "non-Omicron" VoCs. A total of 203 Omicron PCR-positive respiratory swabs (53 BA.1, 48 BA.2, 23 BQ.1, 39 XBB.1.5 and 40 other subvariants) from the period February to March 2022 and from March 2023 were examined. In addition, tissue culture-expanded clinical isolates of Delta (B.1.617.2), Omicron-BA.1, -BF.7, -BN.1 and -BQ.1 were studied. These results were compared to previously reported data from 107 clinical "non-Omicron" samples from the end of the second pandemic wave (February to March 2021) as well as cell culture-derived samples of wildtype (wt) EU-1 (B.1.177), Alpha VoC (B.1.1.7) and Beta VoC (B.1.351)). All four commercial Ag tests were able to detect at least 90.9% of Omicron-containing samples with high viral loads (Ct < 25). The rates of true-positive test results for BA.1/BA.2-positive samples with intermediate viral loads (Ct 25-30) ranged between 6.7% and 100.0%, while they dropped to 0 to 15.4% for samples with low Ct values (> 30). This heterogeneity was reflected also by the tests' 50%-limit of detection (LoD50) values ranging from 44,444 to 1,866,900 Geq/ml. Respiratory samples containing Omicron-BQ.1/XBB.1.5 or other Omicron subvariants that emerged in 2023 were detected with enormous heterogeneity (0 to 100%) for the intermediate and low viral load ranges with LoD50 values between 23,019 and 1,152,048 Geq/ml. In contrast, detection of "non-Omicron" samples was more sensitive, scoring positive in 35 to 100% for the intermediate and 1.3 to 32.9% of cases for the low viral loads, respectively, corresponding to LoD50 values ranging from 6181 to 749,792 Geq/ml. All four assays detected cell culture-expanded VoCs Alpha, Beta, Delta and Omicron subvariants carrying up to six amino acid mutations in the nucleocapsid protein with sensitivities comparable to the non-VoC EU-1. Overall, automated quantitative SARS-CoV-2 Ag assays are not more sensitive than standard rapid antigen tests used in POC settings and show a high heterogeneity in performance for VoC recognition. The best of these automated Ag tests may have the potential to complement nucleic acid-based assays for SARS-CoV-2 diagnostics in settings not primarily focused on the protection of vulnerable groups. In light of the constant emergence of new Omicron subvariants and recombinants, most recently the XBB lineage, these tests' performance must be regularly re-evaluated, especially when new VoCs carry mutations in the nucleocapsid protein or immunological and clinical parameters change.
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Affiliation(s)
- Andreas Osterman
- Max von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Franziska Krenn
- Max von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Maximilian Iglhaut
- Max von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Irina Badell
- Max von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Andreas Lehner
- Max von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Patricia M Späth
- Max von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Marcel Stern
- Max von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Hanna Both
- Max von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Sabine Bender
- Max von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Maximilian Muenchhoff
- Max von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site, Munich, Germany
- COVID‑19 Registry of the LMU Munich (CORKUM), University Hospital, LMU München, Munich, Germany
| | - Alexander Graf
- Laboratory for Functional Genome Analysis, Gene Center, LMU München, Munich, Germany
| | - Stefan Krebs
- Laboratory for Functional Genome Analysis, Gene Center, LMU München, Munich, Germany
| | - Helmut Blum
- Laboratory for Functional Genome Analysis, Gene Center, LMU München, Munich, Germany
| | - Timo Grimmer
- Department of Psychiatry and Psychotherapy, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Jürgen Durner
- Labor Becker MVZ GbR, Munich, Germany
- Department of Conservative Dentistry and Periodontology, University Hospital, LMU München, Munich, Germany
| | | | - Christopher Dächert
- Max von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Natascha Grzimek-Koschewa
- Max von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site, Munich, Germany
| | - Ulrike Protzer
- German Center for Infection Research (DZIF), Partner Site, Munich, Germany
- Institute of Virology, Technical University of Munich/Helmholtz Zentrum München, Munich, Germany
| | - Lars Kaderali
- Institute of Bioinformatics, University Medicine Greifswald, Greifswald, Germany
| | - Hanna-Mari Baldauf
- Max von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany.
| | - Oliver T Keppler
- Max von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany.
- German Center for Infection Research (DZIF), Partner Site, Munich, Germany.
- COVID‑19 Registry of the LMU Munich (CORKUM), University Hospital, LMU München, Munich, Germany.
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Osterman A, Iglhaut M, Lehner A, Späth P, Stern M, Autenrieth H, Muenchhoff M, Graf A, Krebs S, Blum H, Baiker A, Grzimek-Koschewa N, Protzer U, Kaderali L, Baldauf HM, Keppler OT. Comparison of four commercial, automated antigen tests to detect SARS-CoV-2 variants of concern. Med Microbiol Immunol 2021; 210:263-275. [PMID: 34415422 PMCID: PMC8377707 DOI: 10.1007/s00430-021-00719-0] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Accepted: 08/13/2021] [Indexed: 12/23/2022]
Abstract
A versatile portfolio of diagnostic tests is essential for the containment of the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) pandemic. Besides nucleic acid-based test systems and point-of-care (POCT) antigen (Ag) tests, quantitative, laboratory-based nucleocapsid Ag tests for SARS-CoV-2 have recently been launched. Here, we evaluated four commercial Ag tests on automated platforms and one POCT to detect SARS-CoV-2. We evaluated PCR-positive (n = 107) and PCR-negative (n = 303) respiratory swabs from asymptomatic and symptomatic patients at the end of the second pandemic wave in Germany (February–March 2021) as well as clinical isolates EU1 (B.1.117), variant of concern (VOC) Alpha (B.1.1.7) or Beta (B.1.351), which had been expanded in a biosafety level 3 laboratory. The specificities of automated SARS-CoV-2 Ag tests ranged between 97.0 and 99.7% (Lumipulse G SARS-CoV-2 Ag (Fujirebio): 97.03%, Elecsys SARS-CoV-2 Ag (Roche Diagnostics): 97.69%; LIAISON® SARS-CoV-2 Ag (Diasorin) and SARS-CoV-2 Ag ELISA (Euroimmun): 99.67%). In this study cohort of hospitalized patients, the clinical sensitivities of tests were low, ranging from 17.76 to 52.34%, and analytical sensitivities ranged from 420,000 to 25,000,000 Geq/ml. In comparison, the detection limit of the Roche Rapid Ag Test (RAT) was 9,300,000 Geq/ml, detecting 23.58% of respiratory samples. Receiver-operating-characteristics (ROCs) and Youden’s index analyses were performed to further characterize the assays’ overall performance and determine optimal assay cutoffs for sensitivity and specificity. VOCs carrying up to four amino acid mutations in nucleocapsid were detected by all five assays with characteristics comparable to non-VOCs. In summary, automated, quantitative SARS-CoV-2 Ag tests show variable performance and are not necessarily superior to a standard POCT. The efficacy of any alternative testing strategies to complement nucleic acid-based assays must be carefully evaluated by independent laboratories prior to widespread implementation.
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Affiliation(s)
- Andreas Osterman
- Max Von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Maximilian Iglhaut
- Max Von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Andreas Lehner
- Max Von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Patricia Späth
- Max Von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Marcel Stern
- Max Von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Hanna Autenrieth
- Max Von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
| | - Maximilian Muenchhoff
- Max Von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site, Munich, Germany
- COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, LMU Munich, Munich, Germany
| | - Alexander Graf
- Laboratory for Functional Genome Analysis, Gene Center, LMU München, Munich, Germany
| | - Stefan Krebs
- Laboratory for Functional Genome Analysis, Gene Center, LMU München, Munich, Germany
| | - Helmut Blum
- Laboratory for Functional Genome Analysis, Gene Center, LMU München, Munich, Germany
| | - Armin Baiker
- Public Health Microbiology Unit, Bavarian Health and Food Safety Authority, Oberschleißheim, Germany
| | - Natascha Grzimek-Koschewa
- Max Von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany
- German Center for Infection Research (DZIF), Partner Site, Munich, Germany
| | - Ulrike Protzer
- German Center for Infection Research (DZIF), Partner Site, Munich, Germany
- Institute of Virology, Technical University of Munich/Helmholtz Zentrum München, Munich, Germany
| | - Lars Kaderali
- Institute of Bioinformatics, University Medicine Greifswald, Greifswald, Germany
| | - Hanna-Mari Baldauf
- Max Von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany.
- Max Von Pettenkofer Institute, Virology, National Reference Center for Retroviruses, LMU München, Feodor-Lynen-Str. 23, 81377, Munich, Germany.
| | - Oliver T Keppler
- Max Von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany.
- German Center for Infection Research (DZIF), Partner Site, Munich, Germany.
- COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, LMU Munich, Munich, Germany.
- Max Von Pettenkofer Institute, Virology, National Reference Center for Retroviruses, LMU München, Pettenkoferstr. 9a, 80336, Munich, Germany.
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