Longitudinal Immune Profiling of a Severe Acute Respiratory Syndrome Coronavirus 2 Reinfection in a Solid Organ Transplant Recipient

Abstract

Background

The underlying immunologic deficiencies enabling severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfection are currently unknown. We describe deep longitudinal immune profiling of a transplant recipient hospitalized twice for coronavirus disease 2019 (COVID-19).

Methods

A 66-year-old male renal transplant recipient was hospitalized with COVID-19 March 2020 then readmitted to the hospital with COVID-19 233 days after initial diagnosis. Virologic and immunologic investigations were performed on samples from the primary and secondary infections.

Results

Whole viral genome sequencing and phylogenetic analysis revealed that viruses causing both infections were caused by distinct genetic lineages without evidence of immune escape mutations. Longitudinal comparison of cellular and humoral responses during primary SARS-CoV-2 infection revealed that this patient responded to the primary infection with low neutralization titer anti–SARS-CoV-2 antibodies that were likely present at the time of reinfection.

Conclusions

The development of neutralizing antibodies and humoral memory responses in this patient failed to confer protection against reinfection, suggesting that they were below a neutralizing titer threshold or that additional factors may be required for efficient prevention of SARS-CoV-2 reinfection. Development of poorly neutralizing antibodies may have been due to profound and relatively specific reduction in naive CD4 T-cell pools. Seropositivity alone may not be a perfect correlate of protection in immunocompromised patients.

Longitudinal profiling of immune responses for a renal transplant recipient who developed genotypically confirmed SARS-CoV-2 reinfection revealed poor-quality humoral immune responses, low neutralizing antibody presence, and depleted naive T-cell pools insufficient to protect against reinfection and no evidence of viral evasion.

The dynamics and duration of adaptive immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have been described in association with disease severity and the rate of viral clearance, yet the correlates of adaptive immunity responsible for preventing reinfection remain incompletely characterized. In studies of SARS-CoV-2 infection in animal models (mice [1, 2], hamsters [3, 4], and rhesus macaques [5–8]), both vaccine-induced and natural infection–induced immunity are sufficient for protection from SARS-CoV-2 rechallenge. Phase 3 vaccine clinical trials [9], as well as epidemiologic studies of natural infection [10], have also demonstrated robust development of protective immunity in humans. These data unambiguously demonstrate that adaptive immunity confers protection against SARS-CoV-2 infection in the majority of cases. However, cases of SARS-CoV-2 infection after vaccination or reinfection by antigenically similar variants have also been documented as soon as 48 days from primary symptom onset [11–18] (Supplementary Table 1). Whether these reinfections are the direct result of deficient adaptive immune responses to the primary infection, are the result of waning adaptive immunity, or are the result of reinfection with sufficiently variant virus is currently unknown.

Due to the rarity and complexity involved in investigation of human SARS-CoV-2 reinfections, complete immune profiles exploring the magnitude and extent of these adaptive immune responses in paired primary infection and reinfection are lacking. Identifying the deficient features of initial adaptive immune responses that enable subsequent SARS-CoV-2 reinfection will help to further define the correlates of immune protection in humans.

METHODS

Case History

In March 2020, a 66-year-old man who had undergone living-donor renal transplantation 2 years prior, on maintenance immunosuppression with mycophenolate mofetil (MMF, a B- and T-lymphocyte antiproliferative agent) and belatacept (a T-lymphocyte costimulation blocker), was hospitalized with fevers, fatigue, and cough (Figure 1). A diagnosis of SARS-CoV-2 infection was made via reverse-transcription polymerase chain reaction (RT-PCR) performed on a nasopharyngeal swab (NP) specimen. He was subsequently consented and enrolled into the Yale Implementing Medical and Public Health Action Against Coronavirus in Connecticut (IMPACT) study, a biospecimen repository housing clinical and demographic data as well as respiratory, blood, and other tissue samples from patients with confirmed coronavirus disease 2019 (COVID-19) at Yale New Haven Hospital. He developed symptomatic moderate COVID-19 for which he received hydroxychloroquine and atazanavir for 5 days and a single dose of tocilizumab at 8mg/kg. MMF was paused and a reduced dose of belatacept was administered in the setting of acute infection. The oxygen requirement peaked at 4L per minute by nasal cannula; by 13 days from symptom onset (DFSO), the patient was transitioned to room air. Though the patient was asymptomatic thereafter, NP swabs and saliva from the patient remained positive for SARS-CoV-2 by PCR throughout the hospital stay (Supplementary Table 2). The patient was discharged from the hospital on 27 DFSO to the transitional group residential facility after a 14-day period without hypoxia or other clinical signs of infection. MMF was restarted on discharge.

Figure 1.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfection clinical timeline. Summary of the patient’s disease course divided into distinct clinical periods: primary infection (green), graft rejection and immunosuppressive therapies (gray), and SARS-CoV-2 reinfection (orange). Clinical annotations are stratified into rows based on content (medications, disease course, diagnostic testing). Arrows indicate specific events; brackets indicate duration of treatment or testing where applicable. Asterisks (∗) indicate annotations specific to SARS-CoV-2 reinfection. Double line breaks (//) indicate condensing of clinical timeline for display. Abbreviations: ACR, acute cellular rejection; ALF, assisted living facility; AMR, antibody-mediated rejection; ATG, antithymocyte globulin; ATV, atazanavir; BID, twice daily; HCQ, hydroxychloroquine; methylpred., methylprednisolone; MMF, mycophenolate mofetil; NP, nasopharyngeal; RT-qPCR, reverse-transcription quantitative polymerase chain reaction; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; SL, saliva; TCMR, T-cell–mediated rejection; TMA, transcription-mediated amplification.

Approximately 10 weeks after discharge, a kidney allograft biopsy was performed because of increasing serum creatinine and was notable for evidence of acute T-cell–mediated rejection and antibody-mediated rejection (AMR) of the transplanted organ (Figure 1). He was treated with 400mg of antithymocyte globulin and 125mg of methylprednisolone. Belatacept was continued, low-dose prednisone was restarted, and the MMF dose was increased. Notably, an NP swab collected at the time was negative for SARS-CoV-2 using a nonquantitative transcription-mediated amplification (TMA) test. He received rituximab 1 week later to address AMR.

Approximately 15 weeks after this hospitalization, the patient underwent repeat renal allograft biopsy for evaluation of polyomavirus-associated nephropathy that demonstrated evidence of mild remnant AMR (Figure 1). Ongoing neutropenia necessitated infusions of filgrastim. NP swab was again negative for SARS-CoV-2 using TMA at 220 DFSO.

Approximately 4 months after the diagnosis of rejection and 7 months from his primary COVID-19 diagnosis, the patient was readmitted to the hospital with fatigue and nonproductive cough (Figure 1). SARS-CoV-2 NP samples returned positive at 236 DFSO/5 days from reinfection symptom onset (DFSO∗). The patient did not develop fevers or hypoxia, had no evidence of pneumonia on chest imaging, and did not require COVID-19–specific therapy. SARS-CoV-2 immunoglobulin G (IgG) was reactive at 5 DFSO∗ via commercial testing. The patient was hospitalized for 10 days, after which he returned to the group living facility where he was maintained on isolation precautions.

Laboratory investigations, specific statistical methods, and results are reported in the relevant figure legends and the Supplementary Methods.

RESULTS

Genome Sequencing Reveals 2 Distinct Lineages of SARS-CoV-2 During Primary Infection and Reinfection

Following symptom onset during the primary infection in March 2020, both NP and saliva specimens tested positive by PCR, and NP specimens were whole genome sequenced for phylogenetic analysis [19]. Additional NP and saliva specimens were collected and sequenced during the reinfection episode in November 2020 (Supplementary Table 2). To rule out the possibility of persistent SARS-CoV-2 infection, which has been previously reported [20–23], we compared the virus genomes sequenced from specimens collected 7 DFSO in the primary infection (NP swab), and 5 DFSO∗ during the reinfection (NP swab and saliva). Phylogenetic analysis revealed that viruses from the primary infection and reinfection belong to 2 distinct clades within the SARS-CoV-2 lineage B: clade B0.1 in the primary infection, and B0.1.280 in the reinfection (Figure 2A). Specifically, the virus genome sequenced from the reinfection (Figure 2A and 2C) had 12 mutations not observed in the virus sequenced from the primary infection (Figure 2C): 4 synonymous and 8 nonsynonymous. Among the mutations that alter amino acid identity relative to the SARS-CoV-2 reference genome (Wuhan-Hu-1, GenBank: MN908947), both viruses expressed the spike protein with glycine in position 614 (D614G), but only the virus from the reinfection had an additional polymorphism at spike A1078S, close to the transmembrane connector domain in the S2 subunit [24] (Figure 2B; Supplementary Figure 2). Importantly this mutation is not located within the SARS-CoV-2 spike receptor binding domain, which is the primary target of neutralizing antibodies, nor has it been reported among the SARS-CoV-2 variants of concern B0.1.1.7, B0.1.351, or P0.1 that display variable evasion of humoral immune responses [25].

Figure 2.

Maximum likelihood phylogeny of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) whole genomes. A, Global tree showing the evolutionary relationship of 561 lineage B0.1 SARS-CoV-2 genomes, including 3 samples from the patient’s 2 independent infections as described in this study (green, primary infection; orange, reinfection). These viruses belong to 2 sublineages, which evolved independently of each other since their most recent common ancestors, which circulated in the northeastern United States in March 2020. B, Profile of mutations observed in genomes from both infections, compared with the reference genome (GenBank: MN908947), shown at the top, highlighting the positions of the single-nucleotide polymorphisms (SNPs) shown in the panel. Highlights of the 2 genomic sequences obtained from the reinfection are shown. C, Zoomed view of the clade demonstrating relatedness of viruses in the reinfection group reveals their relatedness to viruses that circulated in the southern United States (state of Florida), the likely origin of that sublineage.

Our phylogenetic analysis also demonstrates that the distinct viral lineages identified from the patient’s primary infection and reinfection diverged from their common ancestor around March 2020 (Supplementary Figure 1), suggesting intrahost evolution in the setting of persistent infection to be an unlikely explanation for this case. The interim negative SARS-CoV-2 testing between episodes of infection further supports a clinical course of independent infections, rather than persistence of initial infection. Various molecular methods have been developed for the diagnosis of SARS-CoV-2 infection, including through nucleic acid amplification via RT-PCR or TMA with both methods having comparable analytical and clinical sensitivity [26–30]. To rule out the remote possibility of the presence of multiple SARS-CoV-2 lineages during reinfection, we sequenced virus genomes from both saliva and NP samples collected during the reinfection (Figure 1C) and found them to be identical. Last, geographic distributions of circulating SARS-CoV-2 lineages indicated that the sublineage of viruses identified from the reinfection first circulated in the southern United States (US) in June 2020 before being reintroduced to the northeast US. The patient reported no travel outside of the northeast US since discharge from his primary SARS-CoV-2 infection in March 2020 (Supplementary Figure 1), supporting that his reinfection was likely the result of a broad geographic reintroduction, rather than an instance of persistent infection. The above findings establish that our case represents a genetically confirmed SARS-CoV-2 reinfection. We next sought to identify the specific immune correlates associated with this susceptibility.

Immunologic Profiling Reveals Naive Lymphocyte Depletion and Poor Humoral Immunity

During the patient’s primary SARS-CoV-2 infection, we performed longitudinal peripheral blood mononuclear cell (PBMC) immunophenotyping by high dimensional flowcytometry at 7, 15, and 23 DFSO (Figure 3; Supplementary Figure 3). In comparison to disease severity– and DFSO-matched patients from our larger IMPACT cohort, we found that the patient differed significantly in both immune cell subtype composition as well as cytokine expression during his primary infection. Notably, during the primary SARS-CoV-2 infection, the patient maintained very high levels of circulating T cells and did not suffer from a T-cell lymphopenia, or specifically CD8⁺ T-cell lymphopenia as is characteristic of symptomatic COVID-19 patients [31–33] (Figure 3A and 3B). With regards to functionality, the patient’s CD8⁺ and CD4⁺ T cells exhibited broad increases in activation markers (CD38⁺, HLA-DR⁺), exhaustion/terminal differentiation markers (PD1⁺, TIM-3⁺), and effector T regulatory cell markers (CD45RA^–, CD25⁺, CD127^–, HLA-DR⁺) (Figure 3B-D). Importantly, we found that the patient also had very low numbers of circulating naive CD4⁺ and CD8⁺ T cells at the time of primary SARS-CoV-2 infection (Figure 3B and 3C), which are required for the generation of potent de novo antiviral response. In comparison to the larger IMPACT cohort, this patient’s immunological profile was uncharacteristic of either moderate or severe SARS-CoV-2 infection, and instead resembled an immunophenotype consistent with chronic antigen exposure. Comparison of the patient’s primary infection to other SARS-CoV-2–infected solid organ transplant (SOT) recipients (Supplementary Table 3) revealed that the patient’s decreases in naive CD4⁺ T cells and increase in activated and exhausted CD4⁺ and CD8⁺ T cells were unique to this patient (Supplementary Figure 7).

Figure 3.

Peripheral lymphocyte profiling of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) primary infection and reinfection demonstrates persistent T-cell exhaustion and loss of B cells. For all graphs, blue linear least squares regression lines and corresponding shading represent the average trend and error bars, respectively, for patients with moderate coronavirus disease 2019 (COVID-19). Red linear least squares regression lines and corresponding shading represent the average trend and error bars, respectively, for patients with severe COVID-19. The dashed green line represents the average value of healthy, uninfected healthcare workers (HCWs) plotted as a constant value across all days for reference. Individual scatter points represent the values for the patient during the primary SARS-CoV-2 infection (green) at 7, 15, and 23 days from symptom onset (DFSO) and the reinfection (orange) at 8 days from reinfection symptom onset. A, Total T cells and B cells isolated from patient whole blood. B, CD8⁺ T-cell subsets plotted as number (top) and relative percentage of parent (bottom). C, CD4⁺ T-cell subsets plotted as number (top) and relative percentage of parent (bottom). D, circulating CD4⁺ T follicular helper cells plotted as number and percentage of parent CD4⁺. E, CD8⁺/ CD4⁺ ratios calculated relative to DFSO.

To assess whether alterations in immune cell composition contributed to reinfection, we again performed multidimensional flow cytometry on PBMCs isolated from the patient at 8 DFSO∗ (Figure 3A-C). In comparison to results from the primary infection (Figure 3A-C), we found a general loss of circulating lymphocytes, whereas myeloid cell subsets remained at similar levels as seen during his primary infection (Supplementary Figure 3). We suspect that this broad depletion of lymphocytes was due to intervening treatment with antithymocyte globulin and rituximab during his episode of graft rejection 3 months prior to his reinfection (Figure 1). Among the patient’s remaining T-cell populations, the patient again presented with largely depleted pools of naive CD4⁺ and CD8⁺ T-cells and with continued expression of activation and exhaustion markers among effector CD4⁺ and CD8⁺ T-cell populations. In contrast to his primary infection, we found an almost complete depletion of CD19⁺ B cells, likely as a result of intervening rituximab treatment (Figure 3A).

To further investigate the immunological dysfunction present in the patient during the primary SARS-CoV-2 infection, we performed multiplex cytokine analysis from the patient’s serum. We found that the patient had globally elevated cytokines (Supplementary Figure 4) including interleukin (IL)–10, interferon (IFN)–α, IFN-λ, IL-1α, tumor necrosis factor–α, tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), and IL-27 at all sampled points during primary infection. Other markers of T-cell functionality, including secreted cytokine IFN-γ and T-cell activating cytokines IL-18 and IL-12, remained elevated through the patient’s course of infection even after improvement in COVID-19 symptoms (Figure 4A). In contrast to this patient, a disease severity–matched COVID-19 cohort showed either no elevation, or conversely, a reduction in levels of these cytokines over their course of infection. Persistent elevations in these cytokines were not seen in 2 other SARS-CoV-2–infected SOT recipients, again suggesting a unique degree of immunological dysfunction in this patient (Supplementary Figure 8). Additionally, the patient’s IL-15 and IL-7 levels, required for maintenance of naive T-cell pools, were also persistently elevated (Figure 4B). Elevated IL-7 levels were also seen in other SOT recipients, possibly reflecting chronic antigen engagement in these patients. Overall, these data suggest that persistent utilization of T cells, possibly a result of continual response to the patient’s allograft, and rather than poor production of cytokines, may be responsible for low numbers of naive T cells at the time of primary infection.

Figure 4.

Peripheral cytokine profiling demonstrates broad increases in activation markers suggestive of chronic immune engagement. For all graphs, blue linear least squares regression lines and corresponding shading represent the average trend and error bars, respectively, for patients with moderate coronavirus disease 2019 (COVID-19). Red linear least squares regression lines and corresponding shading represent the average trend and error bars, respectively, for patients with severe COVID-19. The dashed green line represents the average value of healthy, uninfected healthcare workers plotted as a constant value across all days for reference. Individual scatter points represent the values for the patient during the primary severe acute respiratory syndrome coronavirus 2 infection (green) at 7, 15, and 23 days from symptom onset (DFSO). A, Serial measurements of various cytokines plotted against DFSO. B, Select cytokines responsible for naive T-cell proliferation and maintenance. Abbreviations: HCWs, healthcare workers; IFN, interferon; IL, interleukin; TNF, tumor necrosis factor; TRAIL, tumor necrosis factor-related apoptosis-inducing ligand.

To assess whether the above alterations in immune cell composition resulted in deficient humoral immunity, we first assessed anti–SARS-CoV-2 IgG and immunoglobulin M (IgM) levels by enzyme-linked immunosorbent assay during primary infection and found that the patient produced typical levels of SARS-CoV-2–specific antibodies (S1 and receptor binding domain) compared with other hospitalized COVID-19 patients (Figure 5A). Relative to 2 other SARS-CoV-2–infected SOT patients, the IgG antibody response in this patient was delayed and reduced in overall in magnitude (Supplementary Figure 9). Given the patient’s loss of B cells prior to reinfection (Figures 1 and 3), we initially hypothesized that SARS-CoV-2 reinfection may have also been the result of iatrogenic loss of humoral immunity. However, this was not the cases, as upon admission to the hospital at 5 DFSO∗ the patient tested positive for SARS-CoV-2 IgG by commercial laboratory testing. Furthermore, we found accelerated S1 IgG kinetics, suggestive of a memory response upon pathogen rechallenge (Figure 5B and 5C). Moreover, there was a complete absence of S1-specific IgM during reinfection, consistent with a memory response to SARS-CoV-2 infection (Figure 5B). These results suggest that antiviral antibodies were not lost during rituximab treatment as initially hypothesized, and furthermore that the source of S1-specific IgG during the reinfection was likely due to long-lived plasma cells (which are not depleted by rituximab [34]) generated during initial SARS-CoV-2 infection rather than a de novo response to the reinfection.

Figure 5.

Humoral responses to primary and recurrent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. A, SARS-CoV-2 spike S1 (S1) and receptor binding domain (RBD) enzyme-linked immunosorbent assay (ELISA) values, measured at optical density (OD) 450, as observed during the patient’s primary SARS-CoV-2 infection. Values are plotted against days from symptom onset (DFSO). Cycle threshold (CT) reverse-transcription quantitative polymerase chain reaction (RT-qPCR) values are shown in black (left y-axis) and corresponding ELISA data are shown in red (immunoglobulin G [IgG]) and blue (immunoglobulin M [IgM]) (right y-axis, red). Solid lines correspond to S1, dashed lines correspond to RBD. B, S1 ELISA values from the patient’s SARS-CoV-2 reinfection in November 2020. CT qPCR values are shown in black (left axis) and corresponding ELISA data are shown in red (IgG) and blue (IgM) (right axis). Values are plotted against reinfection days from symptom onset (DFSO∗) C, ELISA S1 IgG trajectories plotted from primary infection and reinfection. D and E, Longitudinal plaque reduction neutralization test 50% neutralization potency estimate (PRNT₅₀) assays for each sample collected during the patient’s SARS-CoV-2 primary (top, green) and reinfection (bottom, orange) episodes. Dots represent neutralization of the patient’s serum relative to healthy, uninfected healthcare workers. Solid lines represent the best fit of a generalized linear model for estimating serum half-maximal inhibitory concentration (IC₅₀) values. Condensed clinical timeline (above) shows timing of PRNT₅₀ assays relative to days from symptom onset. F, Protein-based immunome wide association study tiling data representing binding locations of patient’s antibodies against spike protein. Samples are ordered longitudinally by rows (primary infection, green; reinfection, orange) to track humoral dynamics. Shared peaks and respective peak heights between the primary infection and reinfection are annotated (black arrows). A map of SARS-CoV-2 spike domains is provided for reference against antibody binding locations (bottom).

To assess the neutralizing capacity of anti–SARS-CoV-2 antibodies present during both the primary and recurrent SARS-CoV-2 infections, we performed longitudinal plaque reduction neutralization test 50% neutralization potency estimate (PRNT₅₀) assays (Figure 5D and 5E). While the patient developed neutralizing antibodies by 15 DFSO, they were transient in nature and significantly declined in potency by 23 DFSO. This atypical neutralizing antibody response is not consistent with other large-scale studies that show persistence of neutralization capacity (half-life=90 days [95% confidence interval, 70–125 days]). Furthermore, the neutralization capacity was notably reduced in comparison to other hospitalized COVID-19 patients of matched disease severity (Supplementary Figure 5A and 5B). Longitudinal analysis of serum samples was not performed during the intervening period between primary infection and reinfection; however, early hospital clinical laboratory serologic assays showed persistence of anti–SARS-CoV-2 IgG at 5 DFSO∗. We were able to assess neutralizing antibodies during the reinfection, and found that neutralizing antibodies were present at 8 DFSO∗ and increased slightly by 12 DFSO∗. Similar to the primary infection, they were of poor neutralizing capacity relative to other COVID-19 patients (Supplementary Figures 5A and 6).

Given that the patient was depleted of naive circulating B cells, had no IgM response, and had detectable circulating antibodies as early as 5 DFSO∗, we hypothesized that neutralizing antibodies observed during the reinfection reflected antibodies generated during primary infection, rather than a new humoral response to the reinfection. To examine whether these neutralizing antibodies targeted the same regions within the SARS-CoV-2 spike protein, we performed linear epitope mapping of this patient’s antibody binding using serum epitope repertoire analysis—a random bacterial display peptide library—coupled with a recently described bioinformatic method that enriches for antigen-specific antibody binding signals (protein-based immunome wide association study [PIWAS]) [35]. Using this approach, we found 2 characteristic PIWAS peaks—signifying locations of patient antibody binding—at identical locations in both the primary infection and reinfection (Figure 5F). These peaks of antibody binding were centered on amino acid 141 in the N-terminal domain of S1 and on amino acid 1112 in the S2 domain of spike. The high degree of concordance in peak locations between primary infection and reinfection suggests that the same antibody-secreting population responded to both infections. Importantly, this peak is distinct from the spike amino acid mutation at 1078 that was found only in the reinfection isolate (Supplementary Figure 2), suggesting that viral evasion of the antibody response generated during the primary infection was unlikely to be responsible for reinfection.

DISCUSSION

We have described a case of symptomatic SARS-CoV-2 reinfection in a SOT recipient and profiled the unique immunological dysfunctions present during both initial SARS-CoV-2 infection and reinfection. Through extensive clinical investigation and phylogenetic analysis of virus sequences, we confirmed that the patient was reinfected with a genetically distinct lineage of SARS-CoV-2, which was neither the result of persistent infection nor the result of infection by an antigenically distinct SARS-CoV-2 variant. Accordingly, we investigated the potential mechanistic causes of this patient’s multiple SARS-CoV-2 infections by performing longitudinal immunologic profiling during both primary infection and reinfection.

To address the underlying cellular defects that may have led to a poor neutralizing antibody response, we performed flow cytometry of PBMCs during primary infection and reinfection. We found significant differences in the patient’s T-cell composition relative to other hospitalized COVID-19 patients. Rather than T-cell lymphopenia, which is common in COVID-19 patients, this patient presented with a profound and specific reduction in naive T cells, most significantly in his CD4⁺ compartment. Reduced naive T cells are a characteristic feature of aging and are suspected to contribute to the impaired adaptive immune responses observed in elderly individuals [36]. Depletions in naive T cells, and the corresponding deficits in adaptive immune responses, have also been reported in inflammatory states like chronic hepatitis C infection [37] and chronic granulomatous disease [38]; however, this phenomenon has been less well documented in SOT. It has been consistently observed that SOT recipients develop poor adaptive response to either immunization or new infections—including SARS-CoV-2 mRNA vaccination [39–41]. It is unlikely that the patient’s immunosuppression prior to primary infection led to naive T-cell–specific lymphopenia as MMF, a purine biosynthesis inhibitor, would be expected to inhibit both T- and B-cell proliferation nonspecifically, and belatacept, a co-stimulatory inhibitor, would also be expected to inhibit T-cell activation and differentiation. These medications would be expected to lead to increased naive T-cell pools and decreased activation, which were not present in this patient who was found to have high levels of activation, terminal differentiation, and exhaustion in both CD4⁺ and CD8⁺ pools. We also found that other SOT recipients on similar immunosuppressive agents did not possess these same immunologic abnormalities. We suspect that this immune phenotype was the result of chronic antigen exposure from the transplanted organ [42], rather than the patient’s immunosuppression. We suspect that this lack of naive T cells contributed to a deficient humoral immune response during primary SARS-CoV-2 infection. Whether similar impaired cellular dynamics may lead to impaired humoral immunity to SARS-CoV-2 or other infections in other SOT recipients, or other populations with aspects of repeated antigen exposure such as chronic infection and cancer, warrants further investigation.

While antibodies against SARS-CoV-2 spike likely represent a correlate of protection, to what extent and the level required for protection remains unknown. This patient had developed SARS-CoV-2–specific IgG antibodies that were detected as early as 5 DFSO∗ during reinfection, suggesting a memory response. This is supported by the accelerated antibody kinetics relative to first infection and the lack of IgM production. These antibodies were likely produced by SARS-CoV-2–specific plasma cells, which are resistant to rituximab. Linear epitope profiling of spike antibodies from primary infection and reinfection revealed identical amino acid binding peaks, suggesting that this memory response was generated during the patient’s primary infection and present during reinfection. Unfortunately for this patient these 2 spike binding sites, which corresponded to amino acids 141 and 1112, do not correspond to areas of high antigenicity or neutralization when compared to our greater IMPACT cohort (Supplementary Figure 6), We hypothesize that the patient’s underlying immunodeficiencies (low naive CD4 pools) led to poor neutralizing antibody quality (PRNT₅₀ titers approximately 1:10–1:30), which were insufficient to protect against SARS-CoV-2 reinfection.

The discrepancy between frequent, durable protective immune responses generated during most SARS-CoV-2 infections and rare cases of reported reinfection by antigenically similar variants is currently unexplained. While the protective capacity of humoral responses against SARS-CoV-2 infection is clear, large variability in magnitude of responses during natural infection or vaccination has been shown in multiple longitudinal studies. We identified that a patient’s humoral immune response was not sufficient to prevent SARS-CoV-2 reinfection. We investigated both the dynamics of antibody production, as well as the general quality of antibodies produced, and found that although total anti–SARS-CoV-2 antibodies were not particularly hampered, the neutralizing capacity of these antibodies was defective. This case highlights that the mere presence of antibodies may not be sufficient to protect against reinfection if the neutralization titer is below a certain threshold. This is particularly important given the emergence of variants of concern such as P0.1, B0.1.351, and B0.1.617 that show evasion of antibody mediated protection, and suggests that people who develop low neutralization titers, irrespective of antibody titer, will be at higher risk for reinfection.

As with all case studies, generalizability of our findings to wider patient populations is a limitation. Also, while the lack of humoral responses to vaccination or acute infection in immunosuppressed and SOT populations is well documented, there are likely additional mechanisms than those discussed in this manuscript. Our analysis of the immunophenotype of the patient was limited to surveys of circulating immune dynamics; however, numerous studies have also described perturbations in immunity at tissue sites not easily amenable to direct interrogation. We also did not analyze antigen specific T-cell responses, which may reveal additional dysfunction. Future studies should investigate not only the circulating and systemic adaptive immune responses during SARS-CoV-2 reinfections, but also the possibility that local defects in immune responsiveness among barrier tissue sites may also enable recurrent SARS-CoV-2 infection.

Supplementary Data

Supplementary materials are available at The Journal of Infectious Diseases online (http://jid.oxfordjournals.org/). Supplementary materials consist of data provided by the author that are published to benefit the reader. The posted materials are not copyedited. The contents of all supplementary data are the sole responsibility of the authors. Questions or messages regarding errors should be addressed to the author.

Notes

Author contributions. A. I., B. I., M. M. A., and N. D. G. conceived the study. J. K., A. F. B., P. T., M. M. A., B. I., and A. I. drafted the manuscript. P. T., B. I., and M. M. A. constructed the patient’s clinical narrative. T. A., C. B. F. V., J. R. F., A. W. L., M. E. P., C. C. K., and IMPACT team members performed RNA extractions, polymerase chain reaction, and virus sequencing from patient samples. A. F. B. performed phylogenetic analysis. J. K., C. L., T. M., J. O., J. S., and IMPACT team members performed sample collection and peripheral blood mononuclear cell isolation. P. W. and P. L. performed flow cytometry and analyzed data. F. L. performed enzyme-linked immunosorbent assays on patient samples. J. K., M. P. H., and C. L. performed plaque reduction neutralization test 50% neutralization potency estimate assays. All authors helped to edit the manuscript. A. I. and N. D. G. secured funds and supervised the project.

Acknowledgments. We thank M. Linehan for technical and logistical assistance; C. Wilen for kindly providing the SARS-CoV-2; and J. Jaycox for helpful insight and discussion. We also give special recognition of the services of B. Fontes, D. Scoville, and the Yale Environmental Health and Safety Department for their ongoing assistance in safely conducting biosafety level 3 research.

Financial support. This work was supported by the Women’s Health Research at Yale Pilot Project Program (to A. I.); Fast Grant from Emergent Ventures at the Mercatus Center (to A. I. and N. D. G.); the Mathers Foundation; the Ludwig Family Foundation; the Department of Internal Medicine at the Yale School of Medicine; Yale School of Public Health; the Beatrice Kleinberg Neuwirth Fund; and the Centers for Disease Control and Prevention (contract number 75D30120C09570 to N. D. G.). IMPACT received support from the Yale COVID-19 Research Resource Fund. A. I. is an investigator of the Howard Hughes Medical Institute. J. K. received support from the National Institutes of Health T32 MSTP training grant. B. I. received support from the National Institute of Allergy and Infectious Diseases (grant number 2T32AI007517-16). T. A. and M. E. P. were supported by a Clinical and Translational Science Award (number TL1 TR001864).

Potential conflicts of interest. A. I. has served as a consultant for Spring Discovery, Boehringer Ingelheim, and Adaptive Biotechnologies. All other authors report no potential conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.