Longitudinal Innate and Heterologous Adaptive Immune Responses to SARS‐CoV‐2 JN.1 in Transplant Recipients With Prior Omicron Infection: Limited Neutralization but Robust CD4 <sup>+</sup> T‐Cell Activity
Bibliographic record
Abstract
BACKGROUND: Solid organ transplant (SOT) recipients are at increased risk for severe COVID-19 and often exhibit reduced vaccine efficacy due to chronic immunosuppression. As new SARS-CoV-2 variants emerge, understanding immune responses following natural infection remains critical for informing protection strategies in this vulnerable population. We conducted a longitudinal study of SOT recipients who had recovered from Omicron BA.1 or BA.2 infection, evaluating immune responses to the JN.1 subvariant at 4-6 weeks and 1 year postinfection. METHODS: Neutralizing antibodies to JN.1 were measured using a pseudovirus neutralization assay, and JN.1-specific T-cell responses were assessed by flow cytometry. Frequencies of bulk T-cells and innate immune cells, identified via flow cytometry, and their correlation with adaptive responses were also analyzed. RESULTS: At 4-6 weeks, 30% of participants had detectable JN.1-neutralizing antibodies, rising to 43% at one year, although titers remained low. In contrast, CD4⁺ T-cell responses were robust and detected in 75%-83% of participants at 4-6 weeks, increasing to 75%-93% by 1 year. CD8⁺ T-cell responses were observed less frequently. Exploratory correlations between innate and bulk T-cell subsets with heterologous adaptive immune responses were investigated but did not reveal statistically significant relationships. CONCLUSION: T-cell responses may help mitigate severe disease following exposure to JN.1-derived variants, which continue to dominate the SARS-CoV-2 landscape.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".