Microbiota and Xenobiotics Reveal Links between Myopathy, Inflammaging and Glycolytic Metabolism
Bibliographic record
Abstract
Environmental cues influence the risk and severity of myopathy and sarcopenia. Increased inflammation during ageing (i.e. inflammaging) has been proposed as a contributor sarcopenia. The source of age‐related inflammation is ill‐defined. Xenobiotics, including therapeutic drugs, can also promote inflammation that contributes to myopathy. However, the participatory immune components that link either of these stressors to functional decline in skeletal muscle are unknown. The intestinal microbiota has emerged as an environmental factor that can alter xenobiotic metabolism, inflammation and host metabolism. We sought to define aspects of the microbiota and specific innate immune components that connect triggers of inflammation during ageing or xenobiotic exposure. We used statins as a xenobiotic given well documented statin myopathy. Despite the widespread anti‐inflammatory effects, statins actually increase a very specific immune response that is propagated by an inflammasome that acts as a metabolic danger sensor. Statins activate the NOD‐like receptor family, pryin domain containing 3 (NLRP3) inflammasome. In order to implicate the microbiota, we used aged germ free mice and mice lacking bacterial cell wall sensors to test how the entire microbiota alters sarcopenia. We hypothesized that NLRP3‐null mice would be protected from statin‐induced myopathy and sarcopenia compared to wild type (WT) mice. We hypothesized that germ free mice (devoid of any bacteria) and Nod1‐null would be partially protected from age‐related inflammation and sarcopenia. We found that NLRP3‐null mice had an attenuation of statin myopathy and sarcopenic indicators compared to WT mice. A common mechanism between sarcopenia and statin myopathy was lower glycolysis in muscle cells. Further, specific bacterial ligands such as lipopolysaccharide exposure magnified statin myopathy. However, we found that germ free mice had worse indicators of sarcopenia compared to conventional mice. We found that Nod1‐null mice had worse indicators of sarcopenia compared to WT mice. Our results show that xenobiotics and aging alter glycolytic metabolism, which is a common mechanism linking inflammasome responses to myopathy from various stressors. Specific bacterial components play a role in augmenting statin‐induced myopathy via the NLRP3 inflammasome. However, the totality of the bacterial community and bacterial cell wall sensing actually protects against sarcopenia. Support or Funding Information Funded by Natural Sciences and Engineering Research Council of Canada (NSERC) and the Canadian Institutes of Health Research (CIHR). This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".