Genetic Modifiers of Cystic Fibrosis–Related Diabetes
Bibliographic record
Abstract
Diabetes is a common age-dependent complication of cystic fibrosis (CF) that is strongly influenced by modifier genes. We conducted a genome-wide association study in 3,059 individuals with CF (644 with CF-related diabetes [CFRD]) and identified single nucleotide polymorphisms (SNPs) within and 5' to the SLC26A9 gene that associated with CFRD (hazard ratio [HR] 1.38; P = 3.6 × 10(-8)). Replication was demonstrated in 694 individuals (124 with CFRD) (HR, 1.47; P = 0.007), with combined analysis significant at P = 9.8 × 10(-10). SLC26A9 is an epithelial chloride/bicarbonate channel that can interact with the CF transmembrane regulator (CFTR), the protein mutated in CF. We also hypothesized that common SNPs associated with type 2 diabetes also might affect risk for CFRD. A previous association of CFRD with SNPs in TCF7L2 was replicated in this study (P = 0.004; combined analysis P = 3.8 × 10(-6)), and type 2 diabetes SNPs at or near CDKAL1, CDKN2A/B, and IGF2BP2 were associated with CFRD (P < 0.004). These five loci accounted for 8.3% of the phenotypic variance in CFRD onset and had a combined population-attributable risk of 68%. Diabetes is a highly prevalent complication of CF, for which susceptibility is determined in part by variants at SLC26A9 (which mediates processes proximate to the CF disease-causing gene) and at four susceptibility loci for type 2 diabetes in the general population.
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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 | 0.000 | 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) | 0.001 | 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".