Variation in genes controlling warfarin disposition and response in American Indian and Alaska Native people: CYP2C9, VKORC1, CYP4F2, CYP4F11, GGCX
Bibliographic record
Abstract
Objectives Pharmacogenetic testing is projected to improve health outcomes and reduce the cost of care by increasing therapeutic efficacy and minimizing drug toxicity. American Indian and Alaska Native (AI/AN) people historically have been excluded from pharmacogenetic research and its potential benefits, a deficiency we sought to address. The vitamin K antagonist warfarin is prescribed for prevention of thromboembolic events, although its narrow therapeutic index and wide interindividual variability necessitate close monitoring of drug response. Therefore, we were interested in variation in CYP2C9, VKORC1, CYP4F2, CYP4F11, and GGCX, which encode enzymes important for the activity of warfarin and synthesis of vitamin K-dependent blood clotting factors. Methods We resequenced these genes in 188 AI/AN people in partnership with Southcentral Foundation in Anchorage, Alaska and 94 Yup'ik people living in the Yukon-Kuskokwim Delta of southwest Alaska to identify known or novel function-disrupting variation. We conducted genotyping for specific single nucleotide polymorphisms in larger cohorts of each study population (380 and 350, respectively). Results We identified high frequencies of the lower-warfarin dose VKORC1 haplotype (-1639G > A and 1173C > T) and the higher-warfarin dose CYP4F2*3 variant. We also identified two relatively common, novel, and potentially function-disrupting variants in CYP2C9 (M1L and N218I), which, along with CYP2C9*3, CYP2C9*2, and CYP2C9*29, predict that a significant proportion of AI/AN people will have decreased CYP2C9 activity. Conclusion Overall, we predict a lower average warfarin dose requirement in AI/AN populations in Alaska than that seen in non-AI/AN populations of the USA, a finding consistent with clinical experience in Alaska.
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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) | 0.000 | 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".