Comprehensive Summary
The study investigates how gene network analysis and machine learning can uncover molecular drivers of ischemic stroke. Using Weighted Gene Co-expression Network Analysis (WGCNA), the researchers identified two key gene modules strongly linked to stroke pathology and mitochondrial function. Among the mitochondrial-related genes studied, SPTLC2 emerged as a major player. Single-cell RNA sequencing showed that SPTLC2 expression rises in microglia after stroke, promoting inflammation, a metabolic shift toward glycolysis, and altered communication between cells. To test this further, the team used mouse models of stroke, and found that knocking down SPTLC2 improved neurological recovery, reduced infarct volume, and restored mitochondrial health. They also discovered that the transcription factor FLI1 regulates SPTLC2 and that several existing drugs—Nystatin A3, Moxidectin, and Lumacaftor—could potentially target it.
Outcomes and Implications
This work matters because it links microglial metabolism and mitochondrial dysfunction to brain damage after stroke, providing a new target for treatment. By showing that silencing SPTLC2 reduces inflammation and improves recovery, the study highlights a promising path for therapy development. The fact that known drugs may already act on this pathway opens the door to faster clinical translation through drug repurposing. If validated in humans, therapies targeting SPTLC2 could help protect brain tissue, improve long-term outcomes, and reduce the lasting disabilities caused by ischemic stroke.