Genome-wide Association Study of Postburn Scarring Identifies a Novel Protective Variant
Bibliographic record
Abstract
OBJECTIVE: To identify genetic variants associated with the severity of postburn hypertrophic scarring (HTS) using a genome-wide approach. BACKGROUND: Risk of severe postburn HTS is known to depend on race, but the genetic determinants of HTS are unknown. METHODS: We conducted a genome-wide association study (GWAS) in a prospective cohort of adults admitted with deep-partial-thickness burns from 2007 through 2014. Scar severity was assessed over time using the Vancouver Scar Scale (VSS), and DNA was genotyped with a >500,000-marker array. We performed association testing of single-nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) >0.01 using linear regression of VSS height score on genotype adjusted for patient and injury characteristics as well as population genetic structure. Array-wide significance was based on Bonferroni correction for multiple testing. RESULTS: Of 538 patients (median age 40 years, median burn size 6.0% of body surface area), 71% were men and 76% were White. The mean VSS height score was 1.2 (range: 0-3). Of 289,639 SNPs tested, a variant in the CUB and Sushi multiple domains 1 (CSMD1) gene (rs11136645; MAF = 0.49), was significantly associated with decreased scar height (regression coefficient = -0.23, P = 7.9 × 10). CONCLUSIONS: In the first published GWAS of HTS, we report that a common intronic variant in the CSMD1 gene is associated with reduced severity of postburn HTS. If this association is confirmed in an independent cohort, investigating the potential role of CSMD1 in wound healing may elucidate HTS pathophysiology.
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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 | 0.001 | 0.002 |
| 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) | 0.000 | 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".