Longitudinal transcriptomic and epigenetic analysis in astronauts reveals dynamic immune response to spaceflight
Bibliographic record
Abstract
Abstract With the advance of the space industry, the number of astronauts is increasing exponentially. A better understanding of the molecular changes in astronauts in response to spaceflight is required. Here we studied the transcriptomic and epigenetic changes that are subjected to spaceflight. We analyzed the blood samples of two astronauts collected at three timepoints of two weeks before (T0), twenty-four hours after (T2) and three months after (T3) spaceflight. We found monocytes were downregulated at T2 after the spaceflight and reversed to baseline T0 after three months of post-spaceflight at T3. Transcriptomic analysis identified two groups of genes that showed distinct expression patterns, one with transient up-regulation of the expression immediately after spaceflight and another one with transient down-regulation. Pathway analysis of the two groups revealed that protein modification pathway and cell cycle pathway were enriched, possibly supporting the conversion of monocytes to macrophages via autophagy. Epigenetic analysis identified four methylation patterns that showed transient and persistent changes, enriched in the nervous system development pathway and cell apoptosis pathway. Region-level methylation responses point to the genes involved in bone diseases, such as FBLIM1, IHH, and SCAMP2. eQTM analysis suggested a link between RNA transcriptional activity and DNA methylation through transcriptional regulator ZNF684. In conclusion, our longitudinal transcriptomic and epigenetic analysis in astronauts provides a comprehensive view of the physiological impact of spaceflight on human biology that potentially has systemic large short-term and smaller long-term effects on bodily functions.
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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 | 0.000 | 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) | 0.001 | 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".