Interethnic diversity of NAT2 polymorphisms in Brazilian admixed populations
Bibliographic record
Abstract
BACKGROUND: N-acetyltransferase type 2 (Nat2) is a phase II drug- metabolizing enzyme that plays a key role in the bioactivation of aromatic and heterocyclic amines. Its relevance in drug metabolism and disease susceptibility remains a central theme for pharmacogenetic research, mainly because of its genetic variability among human populations. In fact, the evolutionary and ethnic-specific SNPs on the NAT2 gene remain a focus for the potential discoveries in personalized drug therapy and genetic markers of diseases. Despite the wide characterization of NAT2 SNPs frequency in established ethnic groups, little data are available for highly admixed populations. In this context, five common NAT2 SNPs (G191A, C481T, G590A, A803G and G857A) were investigated in a highly admixed population comprised of Afro-Brazilians, Whites, and Amerindians in northeastern Brazil. Thus, we sought to determine whether the distribution of NAT2 polymorphism is different among these three ethnic groups. RESULTS: Overall, there were no statistically significant differences in the distribution of NAT2 polymorphism when Afro-Brazilian and White groups were compared. Even the allele frequency of 191A, relatively common in African descendents, was not different between the Afro-Brazilian and White groups. However, allele and genotype frequencies of G590A were significantly higher in the Amerindian group than either in the Afro-Brazilian or White groups. Interestingly, a haplotype block between G590A and A803G was verified exclusively among Amerindians. CONCLUSIONS: Our results indicate that ethnic admixture might contribute to a particular pattern of genetic diversity in the NAT2 gene and also offer new insights for the investigation of possible new NAT2 gene-environment effects in admixed populations.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".