Evolution of detoxifying systems: the role of environment and population history in shaping genetic diversity at human CYP2D6 locus
Bibliographic record
Abstract
OBJECTIVE: The transition from food collection to food production (FP) modified the nature of selective pressures, and several studies illustrate that genetic adaptation to new lifestyle has occurred in humans since the agricultural revolution. Here we test the hypothesis that high levels of genetic variation at CYP2D6, a locus coding for a detoxifying enzyme of the cytochrome P450 complex, reflect this change. METHODS: We compared DNA sequences and predicted the levels of enzyme activity across 10 African, Asian and European populations, six of which currently rely on hunting and gathering (HG) while four on food production (FP). RESULTS AND CONCLUSION: HG and FP showed similar levels of CYP2D6 diversity, but displayed different substitution patterns at coding DNA sites possibly related to selective differences. Comparison with variation at presumably neutral independent loci confirmed this finding, despite the confounding effects of population history, resulting in higher overall variation in Africans than in Eurasians. The differences between HG and FP populations suggest that new lifestyle and dietary habits acquired in the transition to agriculture affected the variation pattern at CYP2D6, leading to an increase in FP populations of the frequency of alleles that are associated with a slower rate of metabolism. These alleles reached a balanced co-existence with other important and previously selected variants. We suggest that the pronounced substrate-dependent activity of most of these enzymes expanded the spectrum of the metabolic response.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".