The Association Between Antibody Responses and Prolonged Viable Severe Acute Respiratory Syndrome Coronavirus 2 Shedding in Immunocompromised Patients: A Prospective Cohort Study

Abstract

Immunocompromised patients with coronavirus disease 2019 were prospectively enrolled from March to November 2022 to understand the association between antibody responses and severe acute respiratory syndrome coronavirus 2 shedding. A total of 62 patients were analyzed, and the results indicated a faster decline in genomic and subgenomic viral RNA in patients with higher neutralizing and S1-specific immunoglobulin G (IgG) antibodies (both P < .001). Notably, high neutralizing antibody levels were associated with a significantly faster decrease in viable virus cultures (P = .04). Our observations suggest the role of neutralizing antibodies in prolonged virus shedding in immunocompromised patients, highlighting the potential benefits of enhancing their humoral immune response through vaccination or monoclonal antibody treatments.

The coronavirus disease 2019 (COVID-19) pandemic has become a worldwide crisis, with millions of confirmed cases and deaths. Despite the development of vaccines, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to spread rapidly, making isolation essential to limit transmission and avoid overwhelming healthcare systems. It seemed likely that the duration of infectious virus shedding was an important influence on the length of time isolation needs to be maintained. Previous studies have shown that about half of immunocompromised patients with SARS-CoV-2 infection shed viable virus for >4 weeks [1]. However, data on the kinetics of the immunological responses in such patients are limited. We therefore investigated whether antibody responses against SARS-CoV-2 are associated with prolonged viable viral shedding in immunocompromised patients.

METHODS

Study Design

This prospective study was conducted at the Asan Medical Center, a 2700-bed tertiary care hospital in Seoul, South Korea, between March 2022 and November 2022. All immunocompromised adult patients, defined as having hematological malignancy or solid organ transplant, who were admitted to our hospital and had SARS-CoV-2 infection confirmed by nasopharyngeal reverse-transcription polymerase chain reaction (RT-PCR), were enrolled. After enrollment, weekly RT-PCR tests of respiratory samples (nasopharyngeal swabs or saliva or sputum) were carried out for up for 12 weeks. If an RT-PCR test was positive after 12 weeks, the test was repeated weekly until 2 consecutive negative results were obtained. Blood samples were also collected weekly. This study was reviewed and approved by the ethics committee of the Institutional Review Board of Asan Medical Center (IRB number 2022-1054), and all participants gave informed consent.

Definitions

Demographic characteristics, underlying diseases, COVID-19 vaccination status, COVID-19 severity, and antiviral agent use were reviewed. Immunocompromised patients were defined as those with hematological malignancy and receiving active chemotherapy or solid organ transplant recipients. B-cell–depleting agents included anti-CD20 monoclonal antibody or bi-specific T-cell engager. The T-cell–depleting agent used was antithymocyte globulin, and the T-cell–nondepleting agent, basiliximab, was considered separately. Antiviral agents were remdesivir, molnupiravir, and nirmatrelvir/ritonavir. Early antiviral agent use was defined as administration of agent within 5 days of COVID-19 diagnosis; fully vaccinated status was defined as 3 doses and partially vaccinated status as 1 or 2 doses.

Measurement of Viral Load From Genomic and Subgenomic RNA

Viral RNA was extracted from the respiratory specimens using a QIAamp viral RNA Mini kit (Qiagen Inc, Hilden, Germany). Multiplex real-time RT-PCR assays targeting the S and N genes were developed and used to determine SARS-CoV-2 genomic and subgenomic RNA copy number as described previously [2, 3]; primer and probe sequences and detailed procedures are provided in Supplementary Table 1. The correlations between cycle threshold value and viral copy numbers [3] are shown in Supplementary Figure 1. Negative RNA values were imputed with 0 log₁₀ copies/mL (Supplementary Materials).

Measurement of Antibody Response

We measured SARS-CoV-2 Wuhan-Hu-1 S1-specific IgG antibody in the blood samples with an in-house–developed enzyme-linked immunosorbent assay as described previously [4], quality-controlled with reference pooled sera from the International Vaccine Institute (Seoul, South Korea). Antibody titers are presented in IU/mL as per World Health Organization international standards. S1-specific IgG assays were considered positive if the results were ≥10 IU/mL, the established cutoff value for this assay.

We also measured titer of neutralizing antibody against SARS-CoV-2 variants identified from the PCR results (see Supplementary Materials). The 50% neutralization dose (ND₅₀) by plaque reduction neutralization test was calculated based on the plaque counts using the Karber formula [5], determining to be positive for the presence of neutralizing antibodies if the ND₅₀ is ≥20 [6].

In the absence of established criteria, a pragmatic approach was taken to determine the cutoff value for the degree of antibody response, and the 25th and 75th percentiles of the measured IgG and neutralizing antibody levels were used to establish low, medium, and high antibody levels.

Virus Culture

Virus culture was performed on those samples that were positive for genomic RNA by RT-PCR. The detailed methods for virus culture are described in the Supplementary Materials.

Statistical Analysis

A power analysis was conducted with 80% power and a significance level of .05, determining an optimal sample size of 64 for each of the antibody groups. The χ² test or Fisher exact test was used to compare categorical variables and the Mann–Whitney U test or Kruskal–Wallis rank-sum test was used to compare continuous variables, as appropriate. We used a linear mixed model to evaluate interactions between time and antibody group. Days from COVID-19 diagnosis was used as the time scale. In addition, we performed survival analysis to estimate the negative conversion rate of culturable virus using Kaplan–Meier plots and log-rank tests. All tests of significance were 2-tailed and P values <.05 were considered significant. Data were analyzed using R version 4.1.3 software (R Project for Statistical Computing, Vienna, Austria).

RESULTS

Demographic and Clinical Characteristics of the Study Participants

A total of 62 immunocompromised patients with SARS-CoV-2 infection were enrolled between March 2022 and November 2022. The median age was 61 years (interquartile range [IQR], 47–66 years), and 39% were male. Hematologic malignancy accounted for 69.4% of the participants, and 41.9% were fully vaccinated. Of the 62 patients, 46 (74.2%) had high-to-medium S1-IgG antibody levels, and 16 (25.8%) had low levels. Among 53 patients whose neutralizing antibody was measured, 43 (81.1%) showed consistency with the level (high-to-medium or low antibody group) of S1-IgG. There were no significant differences in use of immunosuppressants between the participants with high-to-medium and low S1-IgG antibody except for history of B-cell depletion therapy (P < .001). The severity of COVID-19 and early antiviral agent use were also similar in the 2 antibody groups (P = .50 and P = .25, respectively) (Table 1).

We have additionally enrolled 16 immunocompetent individuals with COVID-19 during our study period for the control group. The median value of the log ND₅₀ of the peak antibody titer in the control group was 3.4 log ND₅₀ (IQR, 1.9–3.8), which was numerically higher than that of the high-to-medium antibody group of immunocompromised patients, with median of 3.0 log ND₅₀ (IQR, 2.7–3.4) (P = .82). Baseline characteristics of the immunocompetent group are presented in Supplementary Table 2.

Genomic and Subgenomic Viral Shedding According to Antibody Level

SARS-CoV-2 genomic viral shedding in saliva according to antibody level is shown in Supplementary Figure 2. It suggests that lower antibody level may be associated with prolonged viral shedding. To investigate further, we categorized antibody levels into high-to-medium and low, and performed an analysis using a linear mixed model. There were no significant differences in viral load at initial diagnosis according to the peak antibody group (Supplementary Figure 3).

The dynamics of SARS-CoV-2 genomic viral shedding according to antibody level are plotted in Figure 1. Genomic viral loads decreased over time after COVID-19 diagnosis in the high-to-medium S1-IgG antibody group (P for time effect <.001) but not in the low S1-IgG antibody group (Figure 1A). There was also a progressive decline of genomic viral loads after COVID-19 diagnosis in the high-to-medium neutralizing antibody group (P for time effect <.001) whereas the low neutralizing antibody group did not show this effect (Figure 1B). As the participants had repeated measures of viral load during the follow-up period in this study, we estimated a linear mixed model to compare whether the viral load is affected by the interaction between the antibody group and the time from the COVID-19 diagnosis. Although viral loads did not differ significantly between the 2 antibody groups (P for S1-IgG group effect = .93, P for neutralizing antibody group effect = .91) in the analysis without considering time interaction, there was a significant group (degree of antibody degree)-by-time interaction effect for both S1-IgG antibody and neutralizing antibody (P for interaction <.001 for both). Similar trends were observed for subgenomic viral shedding (Supplementary Figure 4). A significant group-by-time interaction was detected with respect to both the S1-IgG antibody and neutralizing antibody data (P for interaction <.001 for both). Furthermore, in the subgroup analysis conducted with saliva, the predominant sample type in our study (Supplementary Tables 3 and 4), we observed significant group (antibody degree)-by-time interaction effect for both S1-IgG and neutralizing antibody (P for interaction <.001 for both) (Supplementary Figure 5).

Culturable Virus Shedding According to Antibody Level

We also compared the proportion of positive SARS-CoV-2 cultures with time from COVID-19 diagnosis as a function of antibody level. The median time to negative conversion of culturable virus was 3.5 weeks (95% confidence interval [CI], 3–6 weeks) in the high-to-medium antibody group and 6.5 weeks (95% CI, 3–∞ weeks) in the low S1-antibody group, though this difference was not statistically significant (P by log-rank test = .061) (Figure 1C). However, in the case of neutralizing antibody, the time to negative conversion in the high-to-medium neutralizing antibody group (median, 3 weeks [95% CI, 3–7 weeks]) was significantly shorter than in the low neutralizing antibody group (median, 5 weeks [95% CI, 3–∞ weeks]) (P by log-rank test = .042) (Figure 1D). Additionally, the median time to negative conversion of culturable virus was 2 weeks (95% CI, 1.43–not available), which was significantly faster negative conversion of infectious virus shedding compared with immunocompromised patients. The viral load and culturable virus shedding in immunocompetent control group are shown in Supplementary Figure 6.

DISCUSSION

In this prospective cohort study, we demonstrated that prolonged shedding of culturable SARS-CoV-2 in immunocompromised patients was significantly associated with the level of the neutralizing antibody response. Shedding of viable SARS-CoV-2 was significantly prolonged in patients with low neutralizing antibody levels, implying that neutralizing antibodies are a key factor influencing infectious virus shedding in immunocompromised COVID-19 patients.

In a previous study conducted with a preliminary cohort of the one used in this research, viable virus shedding in immunocompromised patients was found to persist for a median of approximately 4 weeks, and use of B-cell–depleting agents was identified as a clinical risk factor for prolonged viral shedding [1]. The present study consolidated our previous epidemiologic findings by demonstrating an association between low neutralizing antibody levels and prolonged viral shedding. These findings are consistent with the previous hypothesis that CD8⁺ T cells play a critical role in the antiviral response during acute viral infections, while B cells are responsible for prevention of infection and eventual viral clearance [7]. Furthermore, the present findings support the idea that augmenting the humoral immune response in immunocompromised patients by vaccination or monoclonal antibody use could shorten the period of viable viral shedding; this in turn could reduce the tissue damage caused by the virus itself as well as the collateral damage due to prolonged patient isolation such as delayed appropriate chemotherapy. However, as the coordination of virus-specific CD4⁺ T cells, CD8⁺ T cells, and antibodies [8, 9] is recognized as crucial for effective viral clearance, further studies in this area such as additional in-depth experiments on T-cell responses are warranted.

The small sample size of our study and the presence of censored data may limit the conclusions that may be drawn from our results. Also, VeroE6 cells, not VeroTPRSS2 or VeroACE2/TMPRSS2 cells, were utilized in this study. However, recent reports have indicated that Omicron variants, unlike pre-Omicron SARS-CoV-2 variants, do not require TMPRSS2 for cell entry [10–13]. As such, we believe that the use of VeroE6 cells did not impact the measurement of virus neutralization and isolation. In addition, T-cell responses were not evaluated. However, given that the antibody response in most of the enrolled patients seemed to be potentially associated with the duration of viable viral shedding, it might be worth considering the use of this immunologic parameter as a potential mechanistic (or nonmechanistic) correlate of the duration of viral shedding. Therefore, despite these limitations, our study may offer valuable insights for guiding future research.

In conclusion, our findings indicate a potential association between the neutralizing antibody response and the prediction of viral clearance in immunocompromised patients with SARS-CoV-2 infection. These preliminary results also suggest the need for further investigation into strategies to enhance humoral immune responses against COVID-19 in immunocompromised individuals.

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

Financial support. This work was supported by grants from the Korea National Institute of Health (grant number 2022-ER1609-00, 2022-NI-043-00, and 6634-325-210), and the National Research Foundation of Korea from the Ministry of Science and ICT, South Korea (grant number RS-2023-00219002).

References

Author notes