Association of Interferon Regulatory Factor-4 Polymorphism rs12203592 With Divergent Melanoma Pathways
Bibliographic record
Abstract
BACKGROUND: Solar elastosis and neval remnants are histologic markers characteristic of divergent melanoma pathways linked to differences in age at onset, host phenotype, and sun exposure. However, the association between these pathway markers and newly identified low-penetrance melanoma susceptibility loci remains unknown. METHODS: In the Genes, Environment and Melanoma (GEM) Study, 2103 Caucasian participants had first primary melanomas that underwent centralized pathology review. For 47 single-nucleotide polymorphisms (SNPs) previously identified as low-penetrant melanoma risk variants, we used multinomial logistic regression to compare melanoma with solar elastosis and melanoma with neval remnants simultaneously to melanoma with neither of these markers, excluding melanomas with both markers. All statistical tests were two-sided. RESULTS: IRF4 rs12203592 was the only SNP to pass the false discovery threshold in baseline models adjusted for age, sex, and study center. rs12203592*T was associated positively with melanoma with solar elastosis (odds ratio [OR] = 1.47, 95% confidence interval [CI] = 1.18 to 1.82) and inversely with melanoma with neval remnants (OR = 0.65, 95% CI = 0.48 to 0.87) compared with melanoma with neither marker (P global = 3.78 x 10(-08)). Adjusting for phenotypic characteristics and total sun exposure hours did not materially affect rs12203592's associations. Distinct early- and late-onset age distributions were observed in patients with IRF4 rs12203592 [CC] and [TT] genotypes, respectively. CONCLUSIONS: Our findings suggest a role of IRF4 rs12203592 in pathway-specific risk for melanoma development. We hypothesize that IRF4 rs12203592 could underlie in part the bimodal age distribution reported for melanoma and linked to the divergent pathways.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".