Mechanisms of Mitochondrial Disease and the Role of Exercise: A Symposium
Bibliographic record
Abstract
Mitochondrial biogenesis is a process characterized by an increase of mitochondrial mass in the cell. The rate of organelle synthesis must exceed its rate of degradation for an accumulation of mitochondria to occur. Mitochondrial biogenesis can occur in any cell type with preexisting mitochondria, and it usually results when the energy demand of the tissue is augmented over a period of time. A prime example of this is in skeletal muscle. An endurance training program that produces regular, periodic increases in energy demand, results in well-documented increases in mitochondrial content within recruited muscle fibers (1). This is especially evident within fibers with a low initial content. In contrast to situations involving increased patterns of muscle use, reductions in energy demand provoked by limb immobilization or other models of muscle disuse are accompanied by decrements in mitochondrial volume, likely a result of augmented mitochondrial degradation that exceeds the rate of organelle synthesis. This degradation process is less well understood than that involving mitochondrial biogenesis. As expected for the synthesis of an organelle as complex as the mitochondrion, biogenesis involves multiple sequential events, including an upregulation of DNA transcription, cytosolic translation, and posttranslational events, including protein import and multisubunit holoenzyme assembly. Biogenesis is further complicated by the presence of a small, but vital genome within the organelle itself, denoted mitochondrial DNA (mtDNA). As noted in the articles that follow, defects in mtDNA are the most common causes of mitochondrial dysfunction and disease. The adaptations observed in muscle and other tissues in response to deficits in specific, and essential, mitochondrial components are less straightforward than those observed in response to muscle use or disuse. For example, it is well documented that deficiencies in iron intake can result in mitochondrial dysfunction, despite measured increases in mitochondrial volume within the cell (4). Iron is a vital component of the heme prosthetic group, an important part of cytochromes within the electron transport chain. Thus, oxygen consumption rates of isolated mitochondria are reduced, but the muscle cell adapts to this through an apparent stimulation of other mitochondrial constituents as a compensatory response. Similar phenomena appear to occur in mitochondrial diseases, where cellular adaptations to mtDNA defects are variable, depending on the extent of the mtDNA defect (5). Mitochondrial diseases began to be recognized in the 1980s (3,6) and, as a group, they have gained increasing attention at a rate commensurate with our ability to appreciate their existence, and our ability to diagnose them. Disorders of mitochondrial function are now commonly associated with a wide variety of diseases, some of which are illustrated in Figure 1. These diseases are mainly affiliated with tissues that are very sensitive to decrements in mitochondrially derived adenosine triphosphate (ATP), such as brain (and other neural tissues), heart, and muscle.FIGURE 1—The spectrum of mitochondrial disorders. A wide range of diseases and conditions have been associated with impaired mitochondrial function and altered mitochondrial gene expression, some of which are illustrated above. Mitochondrial disorders primarily affect tissues with a high energy demand such as the brain, muscle, and heart. Several of these disorders, particularly the mitochondrial myopathies, have been classified into different categories based on the clinical phenotype of the disease. Senescence is a condition in which cellular functions are affected based in part on altered rates of apoptosis and mitochondrial DNA (mtDNA) mutations. More information on mitochondrial diseases can be found in (: 2,7,8 ) and http://www.mitomap.org. MELAS, mitochondrial encephalomyopathy, lactic acidosis, and strokelike episodes; CPEO, chronic, progressive external ophthalmoplegia; MERFF, myoclonic epilepsy ragged red muscle fibers; KSS, Kearns–Sayre syndrome.This symposium was organized with the goal of improving the understanding of the exercise science community to mitochondrial diseases. The article by Tarnopolsky and Raha introduces the complexity and variety of mitochondrial diseases in detail, including their diagnosis and treatment. Several examples will be highlighted to illustrate these concepts in case presentation format. The goal of the article is to provide a primer for exercise scientists and practitioners to emphasize the important role that mitochondrial dysfunction plays in physiology and human disease. An additional goal of the symposium was to highlight both the spectrum of exercise limitation associated with mitochondrial dysfunction in skeletal muscle of patients with mitochondrial disease, and the therapeutic potential of exercise training in ameliorating this often disabling disease. Thus, the article by Taivassalo and Haller presents the variable range of exercise intolerance attributable to the combined effects of impaired mitochondrial oxidative phosphorylation and habitual physical inactivity. It also documents the few existing studies in which endurance and resistance exercise training have been used to induce physiologic and molecular adaptations within muscle in an attempt to both reverse the effects of muscle disuse and increase the levels of functional mitochondria in patients with defects in mtDNA. Finally, in the article by Chabi et al., information is provided on the overall process of mitochondrial biogenesis in muscle, including the role of important transcription factors, the post translational events involved in mitochondrial assembly, the effects of exercise on these events, and how they can be affected by mitochondrial disease.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".