Meta‐Analysis of <scp> <i>CYP1A1</i> MspI </scp> and <scp>Ile462Val</scp> Polymorphisms in Cancer Susceptibility Among Different Ethnic Populations
Bibliographic record
Abstract
The Cytochrome P450 1A1 (CYP1A1) gene plays a crucial role in the production of enzymes involved in the metabolic activation and detoxification of harmful carcinogens, which are essential for genetic susceptibility to cancer. Due to the inconsistent findings obtained from population-based studies, it is crucial to systematically investigate the association between CYP1A1 polymorphisms and diverse ethnic groups. To assess the link between CYP1A1 polymorphisms and cancer risk across different ethnic populations. The studies published in the last decade were searched through PubMed, Cochrane Library, and Embase, based on PRISMA guidelines and eligibility criteria. Meta-analysis includes subgroup analysis based on ethnicity with odds ratio (OR) and 95% confidence intervals through R Studio. Genotypic and allelic data were analyzed under genetic models (allelic, dominant, and recessive) using a random-effects model. The quality of the included case-control studies was assessed using the Newcastle-Ottawa scale. Twenty case-control studies containing various ethnic populations, of which eleven contain the MspI polymorphism, and the other nine contain the Ile462Val polymorphism of the CYP1A1, while none explained both SNPs. The research studies involved 3976 cases and 4891 controls in this meta-analysis. For MspI polymorphisms, the overall pooled analysis revealed a significant association with cancer risk in the Brazilian ethnic group (2.46 [95% CI: 0.00; 305699178.1]) with moderate heterogeneity observed within the genetic models of CYP1A1 polymorphisms. For Ile462Val polymorphisms, the overall pooled effect size was significant among the Asian group (2.11 [95% CI: 1.45; 3.06]). Meanwhile, the subgroup analysis provides some evidence of cancer risk association with polymorphisms among different ethnicities. The results of this meta-analysis indicate that the understanding of CYP1A1 polymorphisms is necessary to determine the etiology of cancer. The significant association among CYP1A1 polymorphisms and cancer can further be studied by selecting studies focused on a particular cancer type and containing a large sample size within a specific ethnic 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".