A Significant Increasing Risk Association between Cigarette Smoking and XPA and XPC Genes Polymorphisms
Bibliographic record
Abstract
Cigarette smoking (CS) is a major cause of various serious diseases due to tobacco chemicals. There is evidence suggesting that CS has been linked with the DNA damage repair system, as it can affect genomic stability, inducing genetic changes in the genes involved in the repair system, specifically the nucleotide excision repair (NER) pathway, affecting the function and/or regulation of these genes. Single nucleotide polymorphism (SNP), along with CS, can affect the work of the NER pathway and, therefore, could lead to different diseases. This study explored the association of four SNPs in both XPA and XPC genes with CS in the Saudi population. The Taq Man genotyping assay was used for 220 healthy non-smokers (control) and 201 healthy smokers to evaluate four SNPs in the XPA gene named rs10817938, rs1800975, rs3176751, and rs3176752 and four SNPs in the XPC gene called rs1870134, rs2228000, rs2228001, and rs2607775. In the XPA gene, SNP rs3176751 showed a high-risk association with CS-induced diseases with all clinical parameters, including CS duration, CS intensity, gender, and age of smokers. On the other hand, SNP rs1800975 showed a statistically significant low-risk association with all clinical parameters. In addition, rs10817938 showed a high-risk association only with long-term smokers and a low-risk association only with younger smokers. A low-risk association was found in SNP rs3176752 with older smokers. In the XPC gene, SNP rs2228001 showed a low-risk association only with female smokers. SNP rs2607775 revealed a statistically significant low-risk association with CS-induced diseases, concerning all parameters, except for male smokers. However, SNP rs2228000 and rs1870134 showed no association with CS. Overall, the study results demonstrated possible significant associations (effector/and protector) between CS and SNPs polymorphisms in DNA repair genes, such as XPA and XPC, except for rs2228000 and rs1870134 polymorphisms.
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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 | 0.000 | 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".