Gene-centric association study of acute chest syndrome and painful crisis in sickle cell disease patients
Bibliographic record
Abstract
Patients with sickle cell disease (SCD) present with a wide range of clinical complications. Understanding this clinical heterogeneity offers the prospects to tailor the right treatments to the right patients and also guide the development of novel therapies. Several environmental (eg, nutrition) and nonenvironmental (eg, fetal hemoglobin levels, α-thalassemia status) factors are known to modify SCD severity. To find new genetic modifiers of SCD severity, we performed a gene-centric association study in 1514 African American participants from the Cooperative Study of Sickle Cell Disease (CSSCD) for acute chest syndrome (ACS) and painful crisis. From the initial results, we selected 36 single nucleotide polymorphism (SNPs) and genotyped them for replication in 387 independent patients from the CSSCD, 318 SCD patients recruited at Georgia Health Sciences University, and 449 patients from the Duke SCD cohort. In the combined analysis, an association between ACS and rs6141803 reached array-wide significance (P = 4.1 × 10(-7)). This SNP is located 8.2 kilobases upstream of COMMD7, a gene highly expressed in the lung that interacts with nuclear factor-κB signaling. Our results provide new leads to gaining a better understanding of clinical variability in SCD, a "simple" monogenic disease.
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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 | 0.001 | 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 | 0.000 |
| 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".