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Letter to the editor: Poor sensitivity of anti‐nucleocapsid antibody in detecting prior COVID‐19 in vaccinated solid organ transplant recipients

Year: 2024

Type: letter

Abstract: Reliable clinical tests to identify prior severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may inform seroprevalence studies, post-acute COVID-19 diagnoses (“Long COVID”), and study eligibility. Although antibody against the nucleocapsid protein of SARS-CoV-2 (anti-N) is a very sensitive biomarker in the unvaccinated general population, anti-N seroconversion rates may be lower following booster vaccination (e.g., 40% vs. ∼90%).1, 2 Among unvaccinated immunosuppressed populations such as solid organ transplant recipients (SOTRs), anti-N levels appear lower,3 though data among vaccinated SOTRs are lacking. It is unclear which subgroups of vaccinated SOTRs might mount anti-N post-infection, and whether these associations are similar to those of anti-spike antibody responses to vaccination (e.g., mycophenolate [MMF] use).4 We, therefore, explored anti-N seroprevalence among vaccinated SOTRs with a history of COVID-19 to determine biomarker sensitivity. SOTRs participating in a national, prospective observational cohort of SARS-CoV-2 vaccination were serially surveyed regarding COVID-19 test results.4 Demographics, transplant characteristics, vaccination history, and COVID-19 diagnosis dates were collected using REDCap survey software hosted at Johns Hopkins. Beginning in October 2021, any participant who ever reported a positive COVID-19 test (PCR or antigen) was offered anti-N testing using the qualitative clinical Roche Elecsys anti-SARS-CoV-2 assay. Sensitivity (true positive %) was calculated as anti-N(+)/all tested for anti-N; this was stratified by time from the infection episode closest to sampling (<2 weeks, 2–12 weeks, 13–24 weeks, >24 weeks). Clinical characteristics were compared among participants who demonstrated anti-N(+) versus anti-N(-) testing. Post-hoc exploratory multivariable Poisson regression was used to assess associations between anti-N(+) status and hospitalization due to COVID-19, lung transplant, mTORi use, MMF use, the interval between COVID-19, and anti-N(+) testing, using the earliest available sample from each participant. Post hoc analyses of anti-N(+) sensitivity among select clinically relevant subgroups (e.g., lung recipients, persons taking MMF, non-hospitalized groups) were explored. Among 2279 participants, 423 (19%) reported ≥1 positive COVID-19 test during follow-up, of whom 121 (29%) provided 139 samples between 12/2021–11/2022. Based on CDC variant proportion data, 11 (9%) of positive COVID-19 tests were reported in the US pre-Delta and 46 (38%) in Delta waves, versus 28 (23%) in the Omicron BA.1, 16 (13%) BA.2, and 20 (17%) BA.5 waves (covid.cdc.gov). Of those, 76/139 (55%) were anti-N(+) at a median (interquartile range; IQR) 62 (32–126) days post-diagnosis. One sample was submitted <2 weeks post-diagnosis and was anti-N(-). Of samples collected 2–12, 13–24, and >24 weeks post-diagnosis, 42/83 (51%), 21/34 (62%), and 13/21 (62%) were anti-N(+). In univariable analysis, anti-N status was not significantly associated with age, sex, number of vaccine doses, or time since diagnosis. However, history of kidney transplant (42% vs. 59%, p = .062) and immunosuppressive regimen (cyclosporine [3% vs. 16%, p = .012] and sirolimus [20% vs. 3%, p = .003]) (Table) appeared associated with anti-N status. In the multivariable model (Table 1), mTOR inhibitor use (risk ratio [95% CI]: 1.56 [1.03, 2.36], p = .036) and hospitalization due to COVID-19 (risk ratio [95% CI]: 1.61 [.99, 2.62], p = .056) appeared positively associated with anti-N(+). Notably, anti-N sensitivity among non-hospitalized SOTRs taking MMF was low (21/50, 42%), particularly among lung and/or kidney recipients (13/35, 37%); in contrast, 7/9 (78%) of hospitalized lung and/or kidney recipients taking MMF were anti-(N+). Multivariable model Risk ratios [95% CI]f In this real-world cohort of vaccinated SOTRs with COVID-19, anti-N sensitivity for prior infection was relatively poor (55%) and only marginally increased with time since diagnosis. Certain organ and immunosuppressive characteristics appear to affect anti-N status, particularly mTOR inhibitors, which in adjusted analysis appeared associated with a higher rate of anti-N(+); this may be related to differential cellular activation or metabolism with the use of this drug class,5 relative to that of calcineurin inhibitors. Additionally, disease severity (marked by hospitalization) was associated with higher anti-N(+), which may be due to greater viral exposure and/or endogenous immune response in the setting of the lower respiratory tract or systemic infection. These data indicate that a negative clinical anti-N test is not sufficient to rule out prior SARS-CoV-2 infection in SOTRs, particularly among more immunosuppressed groups and those who experienced milder disease. Therefore, seroprevalence studies using this assay are not likely accurate reflections of prior SARS-CoV-2 exposure in this population. Limitations of this study include its small sample size, response rates, and self-reported COVID-19 episodes and therapies received owing to its observational design. Additionally, we did not capture detailed immunosuppressive dosing or treatment of rejection, such as use of lymphodepleting medications, which might further reduce sensitivity of antibody assays. Concept and design: Jennifer L. Alejo, Teresa Chiang, Sarah Frey, Goutham A. Nair, William A. Werbel. Acquisition, analysis, or interpretation of data: Teresa Chiang, Jennifer L. Alejo, Sarah Frey, Aura T. Abedon, Zeba Nauroz, Allan B. Massie, William A. Werbel. Drafting of the manuscript: Jennifer L. Alejo, Teresa Chiang, Sarah Frey, Goutham A. Nair, William A. Werbel. Critical review of the manuscript for important intellectual content: all authors. Statistical analysis: Teresa Chiang, Sarah Frey, Zeba Nauroz, Allan B. Massie, William A. Werbel. Obtained funding: Jacqueline M. Garonzik-Wang, Dorry L. Segev, Allan B. Massie, William A. Werbel. Administrative technical or material support: Jennifer L. Alejo, Aura T. Abedon, Andrew H. Karaba, Aaron A. R. Tobian, William A. Clarke, Robin K. Avery, Jacqueline M. Garonzik-Wang, William A. Werbel. Supervision: Jennifer L. Alejo, Andrew H. Karaba, Aaron A. R. Tobian, William A. Clarke, Robin K. Avery, Jacqueline M. Garonzik-Wang, Dorry L. Segev, Allan B. Massie, William A. Werbel. The authors thank the participants of the Johns Hopkins COVID-19 Transplant Vaccine Study, without whom this research could not be possible. They also thank the members of the study team, including Brian J. Boyarsky MD, PhD; Alexa Jefferis, BS; Nicole Fortune Hernandez, BS; Letitia Thomas; Rivka Abedon; Chunyi Xia; Kim Hall; Alex Philip. They also thank Ms. Yolanda Eby for project support and guidance. This work was supported by the Ben-Dov family, the Trokhan Patterson family, grants T32DK007713 (Dr. Alejo), K23DK115908 (Dr. Garonzik-Wang), R01DK132395 (Dr. Massie) from the National Institute of Diabetes and Digestive and Kidney Diseases; grants U01AI138897-S04 and K24AI144954 (Dr. Segev), and K23AI157893 (Dr. Werbel) from the National Institute of Allergy and Infectious Diseases. The funding entities had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Dr. Avery has received grant/research support from Aicuris, Astellas, Chimerix, Merck, Oxford Immunotec, Qiagen, Regeneron, and Takeda/Shire. Dr. Karaba has received consulting fees from Roche. DL Segev has the following financial disclosures: consulting and speaking honoraria from Sanofi, Novartis, CLS Behring, Jazz Pharmaceuticals, Veloxis, Mallinckrodt, Thermo Fisher Scientific, Regeneron, Novavax, and AstraZeneca. Dr. Karaba has received consulting fees from Roche. Dr. Werbel has received consulting and advisory board fees from AstraZeneca, advisory board fees from Novavax, consulting fees from GlobalData, and consulting fees from the IDSA/CDC COVID-19 Real-Time Learning Network. The remaining authors of this manuscript have no financial disclosures or conflicts of interest to disclose as described by Clinical Transplantation. Drs. Chiang and Werbel had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Identifiable patient-level information will not be made available.

Source: Clinical Transplantation

DOI: 10.1111/ctr.15233