MICBG406A polymorphism reduces risk of mechanical ventilation and death during viral acute lung injury
Bibliographic record
Abstract
MHC class I polypeptide-related sequence B (MICB) is a ligand for NKG2D. We have shown NK cells are central to lung transplant acute lung injury (ALI) via NKG2D activation, and increased MICB in bronchoalveolar lavage predicts ALI severity. Separately, we found a MICB polymorphism (MICBG406A) is associated with decreased ALI risk. We hypothesized this polymorphism would protect against severe SARS-CoV-2 respiratory disease. We analyzed 1,036 patients hospitalized with SARS-CoV-2 infection from IMPACC. Associations between MICBG406A and outcomes were determined by linear regression or Cox proportional hazards models. We also measured immune profiles of peripheral blood and the upper and lower airway. We identified 560 major allele homozygous patients, and 426 and 50 with 1 or 2 copies of the variant allele, respectively. MICBG406A conferred reduced odds of severe COVID-19. MICBG406A homozygous participants demonstrated 34% reduced cumulative odds for mechanical ventilation or death and 43% reduced risk for mortality. Patients with MICBG406A variant alleles had reduced soluble inflammatory mediators and differential regulation of multiple immune pathways. These findings demonstrate a potentially novel association between increasing MICBG406A variant allele copies and reduced COVID-19 severity, independent of SARS-CoV-2 viral burden and humoral immunity, suggesting the NKG2D-ligand pathway as an intervention target.
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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 | 0.001 |
| 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) | 0.002 | 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".