Cigarette Smoking and Intracranial Aneurysms: A Pilot Analysis of SNPs in the CYP2A6 Gene in the Italian Population
Bibliographic record
Abstract
BACKGROUND: Cigarette smoking is a modifiable risk factor associated with formation and rupture of intracranial aneurysms (IAs). Cytochrome P450 2A6 (CYP2A6) is the main enzyme implied in catabolism of nicotine and xenobiotics, giving rise to oxidative stress products. Our study investigated the associations between specific single-nucleotide polymorphisms (SNPs) in the CYP2A6 gene and the presence of sporadic IAs in a cluster of Italian patients, as well as their rupture regarding cigarette smoking habit. METHODS: Three hundred and thirty-one Italian patients with sporadic IAs were recruited in a single institution. We recorded data on clinical onset with subarachnoid hemorrhage (SAH) and smoking habit. Genetic analysis was performed with a standard procedure on peripheral blood samples: CYP2A6 ∗1B2, CYP2A6 ∗2, and CYP2A6 ∗14 SNPs were analyzed in the study group along with 150 healthy control subjects. Statistical analysis was conducted according to genetic association study guidelines. RESULTS: In the patient cohort, the frequency of aSAH was significantly higher in current smokers (P < 0.001; OR=17.45), regardless of the pattern of CYP2A6 SNPs. There was a correlation between IA rupture and cigarette smoking in patients with the heterozygous CYP2A6 ∗1B2 allele (P < 0.001; OR=15.47). All patients carrying the heterozygous CYP2A6 ∗14 allele had an aSAH event (100%), regardless of smoking habit, although this correlation was not statistically significant (P = 1). CONCLUSIONS: According to our findings, a cigarette smoker carrying a fully active CYP2A6 enzyme (heterozygous ∗1B2 allele) may have an increased risk of IA rupture compared to those with functionally less active variants: further investigation on a larger sample is needed to verify this result. The role of the heterozygous CYP2A6 ∗14 allele in aSAH is yet to be clarified.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| 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".