Altered baseline immunological state and impaired immune response to SARS-CoV-2 mRNA vaccination in lung transplant recipients
Bibliographic record
Abstract
The effectiveness of COVID-19 mRNA vaccines is diminished in organ transplant patients. Using a multi-omics approach, we investigate the immunological state of lung transplant (LTX) recipients at baseline and after SARS-CoV-2 mRNA vaccination compared to healthy controls (HCs). LTX patients exhibit a baseline immune profile resembling severe COVID-19 and sepsis, characterized by elevated pro-inflammatory cytokines (e.g., EN-RAGE [also known as S100A12], interleukin [IL]-6), reduced human leukocyte antigen (HLA)-DR expression on monocytes and dendritic cells, impaired cytokine production, and increased plasma microbial products. Single-cell RNA sequencing identifies an enriched monocyte cluster in LTX patients marked by high S100A family expression and reduced cytokine and antigen presentation genes. Post vaccination, LTX patients show diminished antibody, B cell, and T cell responses, along with blunted innate immune signatures. Integrative analysis links these altered baseline immunological features to impaired vaccine responses. These findings provide critical insights into the immunosuppressed condition of LTX recipients and their reduced vaccine-induced adaptive and innate immune responses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".