DNA Methylation Changes Are Associated With an Incremental Ascent to High Altitude
Bibliographic record
Abstract
Genetic and non-genetic factors are involved in the individual ability to physiologically acclimatize to high-altitude hypoxia. Increased heart rate and ventilation are associated with response to high-altitude exposure. High-altitude acclimatization is known to have a genetic component. Yet, it is unclear if other factors, such as epigenetic gene regulation, are involved in acclimatization to high-altitude hypoxia in non-acclimatized individuals. We collected saliva samples from a group of healthy adults of European ancestry (n=21) in Kathmandu (1400 m; baseline) and three altitudes during a trek to the Everest Base Camp: Namche (3440 m; day three), Pheriche (4240 m; day seven), and Gorak Shep (5160 m; day 10). We used quantitative bisulfite pyrosequencing to determine changes in DNA methylation, a well-studied epigenetic marker, in LINE-1, EPAS1, EPO, PPARa, and RXRa. We found significantly lower DNA methylation between baseline (1400 m) and high altitudes in LINE-1, EPO (at 4240 m only), and RXRa. We found increased methylation in EPAS1 (at 4240m only) and PPARa. We also found positive associations between EPO methylation and systolic blood pressure and RXRa methylation and hemoglobin. Our results show that incremental exposure to hypoxia can affect the epigenome. Changes to the epigenome, in turn, could underlie the process of altitude acclimatization.
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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".