COVID | Free Full-Text | Chronic False Positive Rapid Plasma Reagin (RPR) Tests Induced by COVID-19 Vaccination
1. Introduction
2. Materials and Methods
Manual RPR card testing was conducted according to the manufacturer’s (Arlington Scientific, Inc® (ASI), Springville, UT, USA) instructions. Samples with reactive results were diluted in series to achieve endpoint titers at a maximum of 1:16. Endpoint titers were considered the highest dilution in which visible aggregation occurred. All reactive results were confirmed via FTA-ABS testing (Labcorp, Tampa, FL, USA). Screen-positive participants underwent screening at additional timepoints, including pre- and post-vaccines or boosters, to examine the potential relationships between antibody magnitude and the persistence of RPR reactivity. Pre-Dose 2 timepoints were analyzed if available.
Among our longitudinal cohort (n = 228), we included a total of 119 participants with relevant timepoints in this analysis. Of the participants, 94% received a 3rd mRNA COVID-19 vaccine, with 41% [39/94] receiving Moderna and 59% [55/94] receiving Pfizer. Biological sex distribution was similar (52% female, 48% male) among individuals who received a 3rd dose. The median age was 59 years (range: 21–93). For the 4th dose, we included 25 participants who provided samples at a median of 29 days following booster vaccination. Overall, 56% percent [14/25] received a Moderna booster, and 44% [11/25] received Pfizer. Again, sex was approximately equal with 12 female and 13 male participants. The median age for the participants receiving the 4th dose was 70 years (range: 46–93), and the median day “post-boost” timepoint from receiving the 3rd and 4th dose was 29.5 (SD: 4.39; range: 23 to 41) and 29 (SD: 5.27; range: 20 to 46) days, respectively.
3. Case Description
Participant 2 was a 58-year-old heterosexual male healthcare worker who identified as White and Hispanic/Latino. He received two doses of the Pfizer BNT162b2 vaccine in early 2021 with a Pfizer booster dose in October 2021. RPR titers were 1:8 at each timepoint tested following vaccination, with the exception of his visit occurring 131 days following the booster dose, in which the titers decreased to 1:4. His post-fourth-dose RPR titer again escalated to 1:8. Participant 2’s FTA-ABS results were reactive at all post-booster time points available, though none were ANA-positive. Curiously, both RPR and FTA-ABS prior to primary vaccine receipt were non-reactive.
4. Discussion
The interesting findings detailed in this case report provide useful information to clinicians and the greater scientific community. In addition to the inherent strengths of following a longitudinal cohort (n = 228), the authors emphasize the non-zero likelihood of chronic RPR false positivity following the administration of the SARS-CoV-2 vaccine and boosters outside of this cohort. This should be considered in the context of routine RPR screening, particularly in individuals with known co-morbidities (i.e., autoimmune diseases). The limitations of this work include the small percentage of false RPR reactivity represented (~2%), though it stands to reason that, if applied to the total population, these serological findings would result in a rather substantial number of affected individuals. Indeed, when applied to all SARS-CoV-2-vaccinated individuals within the global population, this would equate to approximately 94,000,000 people affected worldwide.
5. Conclusions
A greater investigation is needed to look into the underlying mechanisms leading to false RPR assays. Understanding possible mechanisms, including autoimmunization following exaggerated breakdown, high levels of IgM antibodies, anti-PEG antibodies and underlying genetic susceptibility, may aid in avoiding a misdiagnosis of syphilis in COVID-19 vaccination recipients as well as in individuals with various diseases and conditions that have been shown to generate false RPR test results.
Author Contributions
Conceptualization: E.W., S.P. (Suresh Pallikkuth) and S.P. (Savita Pahwa); Investigation: E.W. and J.M.C.; Resources: S.P. (Suresh Pallikkuth), S.P. (Savita Pahwa), M.H. and F.K.; Writing—review and editing: E.W., D.J.K., M.H., J.M.C., F.K., S.P. (Savita Pahwa) and S.P. (Suresh Pallikkuth); Funding: S.P. (Savita Pahwa) and F.K. All authors have read and agreed to the published version of the manuscript.
Funding
This work was partly funded by the NIAID Collaborative Influenza Vaccine Innovation Centers (CIVIC) contract 75N93019C00051 as part of the PARIS/SPARTA studies.
Institutional Review Board Statement
This case report was the result of a sub-set analysis conducted under the COVID-19 Immunity Study (“CITY”), which was IRB approved at the University of Miami (#20201026). All participants provided written informed consent.
Informed Consent Statement
The study participants described herein provided written informed consent for their results to be submitted as a case report.
Data Availability Statement
The dataset generated is not publicly available given the sensitive nature of the information contained within the dataset, including personal and medical details.
Conflicts of Interest
Florian Krammer has consulted for Curevac, Seqirus and Merck and is currently consulting for Pfizer, Third Rock Ventures, Avimex and GSK. He is named on several patents regarding influenza virus and SARS-CoV-2 virus vaccines, influenza virus therapeutics and SARS-CoV-2 serological tests. Some of these technologies have been licensed to commercial entities, and Dr. Krammer is receiving royalties from these entities. Dr. Krammer is also an advisory board member of Castlevax, a spin-off company formed by the Icahn School of Medicine at Mount Sinai to develop SARS-CoV-2 vaccines. The Krammer laboratory has received funding for research projects from Pfizer, GSK and Dynavax, and three of Dr. Krammer’s mentees have recently joined Moderna. All other authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper.
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Table 1.
RPR positive participant characteristics.
Table 1.
RPR positive participant characteristics.
ID | Age | Sex | SARS-CoV-2 Vaccine Manufacturer | Timepoint | RPR Titer | FTA-ABS Result | ANA Result e | Days Elapsed | SARS-CoV-2 Titer |
---|---|---|---|---|---|---|---|---|---|
1 | 72 | Female | Moderna b | Pre 2nd Dose | — | — | — | a | |
Post 2nd Dose | 1:1 | — | 51 d | 1600 | |||||
Pre 4th dose | 1:1 | — | 252 d | 51,200 | |||||
Post 4th dose | 1:1 | Non-Reactive | Negative | 33 d | 25,600 | ||||
Post 4th dose | 1:1 | — | 129 d | 51,200 | |||||
2 | 58 | Male | Pfizer b | Pre-Vaccine | Non-Reactive | Non-Reactive | Negative | — | — |
Post 2nd Dose | 1:8 | Reactive | Negative | 266 c | 3200 | ||||
Pre 3rd Dose | 1:8 | — | — | 273 d | 200 | ||||
Post 3rd dose | 1:8 | Reactive | Negative | 31 d | 25,600 | ||||
Post 3rd Dose | 1:4 | Reactive | Negative | 131 d | 6400 | ||||
Post 4th Dose | 1:8 | Reactive | Negative | 211 d | 1600 |
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