AI Insight
This bioinformatics and network toxicology study investigated the molecular mechanisms by which two widely used anesthetics, sevoflurane and propofol, may influence the progression of type 2 diabetes mellitus (T2DM). Using public databases, machine learning algorithms, and molecular docking, the researchers identified two core molecular targets, MMP9 (Matrix Metallopeptidase 9) and HPSE (Heparanase), as shared interaction points between these anesthetics and T2DM-related pathways. Additional analyses revealed associations with autophagy, immune cell infiltration changes (notably increased neutrophils and decreased NK cells), and regulatory networks involving 16 microRNAs and 12 transcription factors.
Why it matters
Patients with T2DM frequently undergo surgery and require anesthesia, yet the metabolic and molecular consequences of anesthetic choice remain poorly understood. Identifying MMP9 and HPSE as candidate targets could inform more personalized anesthetic strategies for diabetic patients and open avenues for experimental validation and therapeutic intervention.
Understand the Science
by Lili Bai, Ping Li, Lina Zhao
Background
Sevoflurane and propofol are commonly used anesthetics that may exert pronounced effects on glucose metabolism and cardiovascular function in patients with type 2 diabetes mellitus (T2DM). This study aimed to elucidate the molecular mechanisms underlying the association of sevoflurane and propofol with T2DM progression.
Methods
Targets associated with sevoflurane, propofol, and T2DM were predicted using public databases. Core targets were identified and validated through differential expression analysis, machine learning algorithms, and expression level verification. Functional enrichment analysis was conducted to characterize related biological processes. Immune cell infiltration was assessed using the CIBERSORT algorithm, and regulatory networks involving microRNAs and transcription factors were constructed. Molecular docking was performed to evaluate the binding affinities between the anesthetics and the core targets.
Results
Two core targets, MMP9 (Matrix Metallopeptidase 9) and HPSE (Heparanase), were identified as significantly associated with sevoflurane and propofol in T2DM. Supplementary sensitivity analyses across multiple fold-change thresholds and permutation tests demonstrated that MMP9 and HPSE were retained as candidate targets across a range of analytical choices, supporting the robustness of their identification. These targets were enriched in pathways related to receptor catabolic processes, cellular responses to abiotic stimuli, and autophagy. Immune infiltration analysis indicated increased neutrophil abundance and decreased levels of activated natural killer (NK) cells. In addition, 16 microRNAs and 12 transcription factors were associated with the core targets. Molecular docking demonstrated potential interactions of sevoflurane and propofol with MMP9 and HPSE.
Conclusion
These findings provide novel insights into the potential association between exposure to sevoflurane and propofol and the progression of T2DM, and identify candidate therapeutic targets. Further experimental and clinical validation is required to support evidence-based selection of personalized anesthetic strategies for patients with T2DM.