Sex-specific immune responses to COVID-19 vaccination in end-stage renal disease patients
Bibliographic record
Abstract
Abstract Background End-stage renal disease (ESRD) patients have muted memory B cell formation and reduced humoral responses to COVID-19 vaccination; however, early innate immune responses have yet to be characterized. Sex-stratification is also limited in COVID-19 vaccination research. Methods We collected blood before (BD1) and 1-4 days post-dose 1 (PD1) of BNT162b2 vaccination for RNA-sequencing in ESRD patients (n = 35 BD1; 18 PD1) and healthy controls (HC) (n = 31 BD1; 30 PD1). Additionally, 20 plasma cytokines were quantified in ESRD patients (n = 39 BD1, 35 PD1) and HC (34 BD1, 15 PD1). Results Transcriptional profiling of vaccine responses identified 125 significantly differentially expressed genes (DEG) (padj<0.04) in ESRD patients and 107 DEGs (padj<0.05) in HC. 71 DEGs were shared, 54 unique to ESRD, and 36 unique to HC. DEG, pathway analyses, and cytokine responses in the combined dataset showed ESRD patients were more inflamed than HC at baseline, with an elevated inflammatory cytokine profile compared to HC. These results were driven by female ESRD patients where IL-2, IL-10, and IP-10 were more significant in females (p < 0.001) compared to males (p < 0.01). While IL-6, IFN-γ, IL-13, eotaxin, were exclusively associated in females (p < 0.05). Healthy females also had a stronger immunological response to vaccination compared to healthy males. Conclusions Despite baseline inflammation, ESRD patients were able to mount similar early immune responses to vaccination as HC, with females in both populations more reactogenic than males. Sex-stratification is recommended for ongoing immunological research to better understand unique responses to COVID-19 vaccination. Key messages • End-stage renal disease patients have similar early innate immune responses to COVID-19 vaccination as healthy controls. • Sex-stratification is important to identify unique immunological responses that may be leveraged for sex-specific vaccination strategies.
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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 | 0.016 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.001 | 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 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".