Metabolomic profiling of skeletal muscle in GSDMD-knockout mice reveals distinct metabolic alterations in sepsis-induced myopathy.
Summary
Using GSDMD-knockout and wild-type mice in a sepsis model, non-targeted UHPLC-QE-MS metabolomics revealed substantial alterations in muscle metabolites and pathways (taurine/hypotaurine, amino acid, bile acid, oxidative stress, nucleotide metabolism). The study proposes metabolite panels as potential biomarkers and implicates GSDMD in regulating energy, amino-acid, lipid and redox metabolism in sepsis-associated myopathy.
Key Findings
- GSDMD knockout significantly altered skeletal muscle metabolome in septic mice, affecting taurine/hypotaurine, amino acid, bile acid, oxidative stress, and nucleotide metabolism.
- A panel of differential metabolites was identified that could serve as candidate biomarkers for sepsis-associated myopathy.
- Findings suggest GSDMD regulates energy, amino-acid, lipid and redox metabolic pathways in skeletal muscle during sepsis.
Clinical Implications
Identified metabolites could be developed as diagnostic markers for sepsis-associated myopathy and may point to metabolic pathways amenable to therapeutic modulation to preserve muscle function in sepsis survivors.
Why It Matters
Provides mechanistic insight into how pyroptosis effector GSDMD modulates muscle metabolism during sepsis and identifies metabolite biomarkers with translational potential for sepsis-associated myopathy.
Limitations
- Study performed in mice; translational validity to human sepsis-associated myopathy requires confirmation.
- Sample size and time-course dynamics not detailed in abstract; longitudinal validation and mechanistic follow-up needed.
Future Directions
Validate identified metabolite panels in human sepsis cohorts, perform time-course studies, and test interventions targeting implicated metabolic pathways to preserve muscle function.
Study Information
- Study Type
- Cohort
- Research Domain
- Pathophysiology
- Evidence Level
- V - Preclinical mechanistic study in animal models (basic science).
- Study Design
- OTHER