Deciphering DMET genetic data: comprehensive assessment of Northwestern Han, Tibetan, Uyghur populations and their comparison to eleven 1000 genome populations
Bibliographic record
Abstract
We investigated the allele frequencies of drug absorption, distribution, metabolism and elimination (ADME)-related drug-metabolizing enzymes and transporters (DMET) genes in the Northwestern Han, Tibetan and Uyghur populations and compared the related genes in these three populations with those in eleven 1000 Genome populations. We examined 1936 single nucleotide polymorphisms of 225 DMET genes involved in ADME processes and found 732, 679 and 804 sites were polymorphic in Han, Tibetan and Uyghur. Tibetan differed from Han in only four sites (p < .05), whereas Uyghur differed from Han and Tibetan in 24 and 21 sites, respectively (p < .05). The distributions of 1058 genotyping data of 245 individuals from Han, Tibetan and Uyghur were compared with 1207 other individuals from the eleven 1000 Genomes populations. The top four populations in Han that exhibited the smallest pairwise Fst values were CHB, Tibetan, CHD and JPT; those in Tibetan were Han, CHB, Uyghur and CHD; and those in Uyghur were Han, Tibetan, GIH and CEU. MEGA results revealed that CHB, CHD, JPT, Han, Tibetan and Uyghur were grouped in cluster 1. GIH, MEX, CEU and TSI were grouped in cluster 2. MKK, ASW, LWK and YRI were grouped in cluster 3.
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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 | 0.000 |
| 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".