Decoding neuron-specific lineage to identify diagnostic biomarkers and therapeutic targets for ischemic stroke

Ischemic stroke (IS) imposes a major global health burden. To uncover new diagnostic and therapeutic targets, we profiled neuronal heterogeneity during IS using single-cell RNA sequencing. Our analysis decoded neuronal lineage trajectories, identified a critical cell-cell communication network, and pinpointed key gene modules. By integrating multiple machine learning algorithms, we constructed a highly accurate diagnostic model based on the hub genes Il18 and Cherp. This model was rigorously validated across multi-omics datasets and species. We further confirmed that Cherp promotes neuronal repair by regulating calcium homeostasis, while Il18 serves as a potential early blood biomarker. This work provides effective targets and translatable tools for advancing IS precision medicine.