Metagenomic analysis reveals the signature of gut microbiota associated with human chronotypes
Bibliographic record
Abstract
Patterns of diurnal activity differ substantially between individuals, with early risers and late sleepers being examples of opposite chronotypes. Growing evidence suggests that the late chronotype significantly impacts the risk of developing mood disorders, obesity, diabetes, and other chronic diseases. Despite the vast potential of utilizing chronotype information for precision medicine, those factors that shape chronotypes remain poorly understood. Here, we assessed whether the various chronotypes are associated with different gut microbiome compositions. Using metagenomic sequencing analysis, we established a distinct signature associated with chronotype based on two bacterial genera, Alistipes (elevated in "larks") and Lachnospira (elevated in "owls"). We identified three metabolic pathways associated with the early chronotype, and linked distinct dietary patterns with different chronotypes. Our work demonstrates an association between the gut microbiome and chronotype and may represent the first step towards developing dietary interventions aimed at ameliorating the deleterious health correlates of the late chronotype.
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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 | 0.001 | 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".