Phenotypic associations with the HMOX1 GT(n) promoter repeat in European populations
Bibliographic record
Abstract
AbstractHO-1 is a key enzyme in the management of heme in humans. A GT(n) repeat length in the gene HMOX1, has previously been widely associated with a variety of phenotypes, including susceptibility and outcomes in diabetes, cancer, infections, and neonatal jaundice. However, studies are generally small and results inconsistent. In this study, we imputed the GT(n) repeat length in two European cohorts (UK Biobank, n = 463,005; and Avon Longitudinal Study of Parents and Children (ALSPAC n = 937), with the reliability of imputation tested in other cohorts (1000 Genomes, HGDP, and UK-PGP). Subsequently, we measured the relationship between repeat length and previously identified associations (diabetes, COPD, pneumonia and infection related mortality in UK Biobank; neonatal jaundice in ALSPAC) and performed a phenome-wide association study (PheWAS) in UK Biobank. Despite high quality imputation (correlation between true repeat length and imputed repeat length >0.9 in test cohorts), no clinical associations were identified in either the PheWAS or specific association studies. These findings were robust to definitions of repeat length and sensitivity analyses. Despite multiple smaller studies identifying associations across a variety of clinical settings; we could not replicate or identify any relevant phenotypic associations with the HMOX1 GT(n) repeat.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".