Nrf2 deficiency in muscle attenuates experimental autoimmune myositis‐induced muscle weakness
Bibliographic record
Abstract
Abstract Idiopathic inflammatory myopathies (IIMs) are systemic autoimmune diseases characterised by muscle weakness. Although multiple physiological and pathological processes are associated with IIMs, T‐lymphocyte infiltration into muscle plays a key role in the development and exacerbation of IIMs. Nuclear factor erythroid 2‐related factor 2 (Nrf2) is a key transcription factor that regulates inflammatory responses; therefore, muscle Nrf2 may serve an important role in the development of IIMs. In this study, we demonstrated that experimental autoimmune myositis (EAM) causes loss of muscle mass and function in oxidative and glycolytic muscles in C57BL/6 mice. EAM increased CD4 + and CD8 + T‐lymphocyte infiltration, as well as interferon‐gamma (IFN‐γ) and tumour necrosis factor‐alpha (TNF‐α) mRNA expression in oxidative soleus and glycolytic extensor digitorum longus muscles, along with elevated chemokine mRNA levels (i.e. CCL3, CCL5, CXCL9, CXCL10 and CXCL16). IFN‐γ and TNF‐α treatments increased the mRNA expression levels of these chemokines in C2C12 myotubes. EAM also increased phosphorylated Nrf2 at Ser40 in soleus and glycolytic white vastus lateralis muscle. Although the expression of several chemokines was affected by Nrf2 activation following tert‐butylhydroquinone treatment or Keap1 knockdown, CCL5 mRNA expression significantly increased in C2C12 myotubes and mouse skeletal muscle. Moreover, muscle‐specific Nrf2 knockout in mice attenuates EAM‐induced loss of muscle mass and function, which was associated with the inhibition of CCL5 mRNA expression, CD8 + T‐lymphocyte infiltration and IFN‐γ mRNA expression. Collectively, these findings reveal that regulating Nrf2 activity is a promising therapeutic approach for treating IIM‐mediated muscle weakness. image Key points Experimental autoimmune myositis (EAM) causes loss of muscle mass and function. Loss of muscle mass and function in EAM were associated with increased chemokine mRNA expression (i.e. CCL3, CCL5, CXCL9, CXCL10 and CXCL16), T‐lymphocyte infiltration and inflammatory cytokine mRNA expression (i.e. IFN‐γ and TNF‐α) in the skeletal muscle. EAM activated Nrf2 in muscle and increased Nrf2 activity in vivo and in vitro increased CCL5 mRNA expression. Muscle‐specific Nrf2 knockout in mice attenuated EAM‐induced muscle weakness by inhibiting CCL5 mRNA expression, CD8 + T‐lymphocyte migration and IFN‐γ mRNA expression in muscles. These results provide further evidence for the potential therapeutic targeting of Nrf2 to mitigate EAM‐induced muscle weakness.
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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".