Genetic Variation in the <i>FAS</i> Gene and Associations with Acute Lung Injury
Bibliographic record
Abstract
RATIONALE: Fas (CD95) modulates apoptosis and inflammation and is believed to play an important role in lung injury. OBJECTIVES: To determine if common genetic variation in FAS is associated with acute lung injury (ALI) susceptibility, risk of death, and FAS gene expression. METHODS: We genotyped 14 single nucleotide polymorphisms (tagSNPS) in FAS in samples from healthy white volunteers (control subjects, n = 294) and patients with ALI (cases, n = 324) from the ARDSnet Fluid and Catheter Treatment Trial (FACTT). FAS genotypes associated with ALI in the discovery study were confirmed in a nested case-control validation study of critically ill patients at risk for ALI (n = 657). We also tested for associations between selected tagSNPS and FAS mRNA levels in whole blood from healthy control subjects exposed to media alone or LPS ex vivo. MEASUREMENTS AND MAIN RESULTS: We identified associations between four tagSNPs in FAS (FAS(-11341A>T) [rs17447140], FAS(9325G>A) [rs2147420], FAS(21541C>T) [rs2234978], and FAS(24484A>T) [rs1051070]) and ALI case status. Haplotype-based analyses suggested that three of the tagSNPs (FAS(9325G>A), FAS(21541C>T), and FAS(24484A>T)) function as a unit. The association with this haplotype and ALI was validated in a nested case-control study of at-risk subjects (P = 0.05). This haplotype was also associated with increased FAS mRNA levels in response to LPS stimulation. There was no association between FAS polymorphisms and risk of death among ALI cases. CONCLUSIONS: Common genetic variants in FAS are associated with ALI susceptibility. This is the first genetic evidence supporting a role for FAS in ALI.
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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 | 0.001 | 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".