Linking the Metabolic State and Mitochondrial DNA in Chronic Disease, Health, and Aging
Bibliographic record
Abstract
Physical inactivity and overeating leading to obesity and diabetes are both linked to increased risk of age-related chronic diseases. By contrast, caloric restriction and physical activity promote health. However, the cellular mechanisms that link the metabolic state to long-term health outcomes have remained unclear. Damage to mitochondrial DNA (mtDNA), which accumulates with aging in diseased human tissues and with diabetes complications, has been shown in animal models to recapitulate several features of aging. Importantly, mitochondrial morphology, function, and the integrity of mtDNA directly respond to the metabolic state. The oversupply of cells with excess lipids and glucose (i.e., hyperglycemia) fragments mitochondria, increases mitochondrial reactive oxygen species production, and promotes the accumulation of mtDNA damage. In turn, the limited supply of energy substrates promotes fusion and elongation of mitochondria and limits accumulation of mtDNA damage. Here we propose a model in which mitochondrial dynamics (fusion/fission) integrate systemic metabolic information and control the stability of the mitochondrial genome, thus helping to mediate the effects of physical activity, inactivity, and calorie intake on health outcomes. It is well established both epidemiologically and clinically that physical inactivity and behaviors leading to weight gain are associated with elevated risk of most age-related diseases as well as mortality (1). However, the underlying mechanisms mediating these effects are not fully explained. Conversely, the health promoting and life-extending effects of caloric restriction and physical activity are well described (2,3). Nonetheless, the exact mechanisms underlying the health benefits of these interventions, including the reduced risk of most age-related metabolic diseases and diabetes complications, have not been fully elucidated. Here we present a common mechanism that may account for the combined long-term effects of physical activity/inactivity and diet on health outcomes and aging. Improved understanding of the acute cellular events initiated by fluctuations in the metabolic state may …
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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".