Inhibition of Mer exacerbates early brain injury by regulating microglia/macrophage phenotype after subarachnoid hemorrhage in mice

The pivotal role of microglia in injury and the prognosis of subarachnoid hemorrhage

Subarachnoid hemorrhage leads to a series of pathological changes, including vascular spasm, cellular apoptosis, blood-brain barrier damage, cerebral edema, and white matter injury. Microglia, which are the key immune cells in the central nervous system, maintain homeostasis in the neural environment, support neurons, mediate apoptosis, participate in immune regulation, and have neuroprotective effects. Increasing evidence has shown that microglia play a pivotal role in the pathogenesis of subarachnoid hemorrhage and affect the process of injury and the prognosis of subarachnoid hemorrhage. Moreover, microglia play certain neuroprotective roles in the recovery phase of subarachnoid hemorrhage. Several approaches aimed at modulating microglia function are believed to attenuate subarachnoid hemorrhage injury. This provides new targets and ideas for the treatment of subarachnoid hemorrhage. However, an in-depth and comprehensive summary of the role of microglia after subarachnoid hemorrhage is still lacking. This review describes the activation of microglia after subarachnoid hemorrhage and their roles in the pathological processes of vasospasm, neuroinflammation, neuronal apoptosis, blood-brain barrier disruption, cerebral edema, and cerebral white matter lesions. It also discusses the neuroprotective roles of microglia during recovery from subarachnoid hemorrhage and therapeutic advances aimed at modulating microglial function after subarachnoid hemorrhage. Currently, microglia in subarachnoid hemorrhage are targeted with TLR inhibitors, nuclear factor-κB and STAT3 pathway inhibitors, glycine/tyrosine kinases, NLRP3 signaling pathway inhibitors, Gasdermin D inhibitors, vincristine receptor α receptor agonists, ferroptosis inhibitors, genetic modification techniques, stem cell therapies, and traditional Chinese medicine. However, most of these are still being evaluated at the laboratory stage. More clinical studies and data on subarachnoid hemorrhage are required to improve the treatment of subarachnoid hemorrhage.

Mesenchymal Stem Cell-Derived Extracellular Vesicles Alleviate Brain Damage Following Subarachnoid Hemorrhage via the Interaction of miR-140-5p and HDAC7

Subarachnoid hemorrhage (SAH) triggers severe neuroinflammation and cognitive impairment, where microglial M1 polarization exacerbates the injury and M2 polarization mitigates damage. Mesenchymal stem cell-derived extracellular vesicles (MSC-EVs), carrying microRNA (miR)-140-5p, offer therapeutic promise by targeting the cAMP/PKA/CREB pathway and modulating microglial responses, demonstrating a novel approach for addressing SAH-induced brain injury. This research explored the role of miR-140-5p delivered by MSC-EVs in mitigating brain damage following SAH. Serum from SAH patients and healthy individuals was analyzed for miR-140-5p and cAMP levels. The association between miR-140-5p levels, brain injury severity, and patient survival was examined, along with the target relationship between miR-140-5p and histone deacetylases 7 (HDAC7). MSC-EVs were characterized for their ability to cross the blood-brain barrier and modulate the HDAC7/AKAP12/cAMP/PKA/CREB axis, reducing M1 polarization and inflammation. The therapeutic effect of MSC-EV-miR-140-5p was demonstrated in an SAH mouse model, showing reduced neuronal apoptosis and improved neurological function. This study highlights the potential of MSC-EV-miR-140-5p in mitigating SAH-induced neuroinflammation and brain injury, providing a foundation for developing MSC-EV-based treatments for SAH.

Machine learning and deep learning to identifying subarachnoid haemorrhage macrophage-associated biomarkers by bulk and single-cell sequencing

We investigated subarachnoid haemorrhage (SAH) macrophage subpopulations and identified relevant key genes for improving diagnostic and therapeutic strategies. SAH rat models were established, and brain tissue samples underwent single-cell transcriptome sequencing and bulk RNA-seq. Using single-cell data, distinct macrophage subpopulations, including a unique SAH subset, were identified. The hdWGCNA method revealed 160 key macrophage-related genes. Univariate analysis and lasso regression selected 10 genes for constructing a diagnostic model. Machine learning algorithms facilitated model development. Cellular infiltration was assessed using the MCPcounter algorithm, and a heatmap integrated cell abundance and gene expression. A 3 × 3 convolutional neural network created an additional diagnostic model, while molecular docking identified potential drugs. The diagnostic model based on the 10 selected genes achieved excellent performance, with an AUC of 1 in both training and validation datasets. The heatmap, combining cell abundance and gene expression, provided insights into SAH cellular composition. The convolutional neural network model exhibited a sensitivity and specificity of 1 in both datasets. Additionally, CD14, GPNMB, SPP1 and PRDX5 were specifically expressed in SAH-associated macrophages, highlighting its potential as a therapeutic target. Network pharmacology analysis identified some targeting drugs for SAH treatment. Our study characterised SAH macrophage subpopulations and identified key associated genes. We developed a robust diagnostic model and recognised CD14, GPNMB, SPP1 and PRDX5 as potential therapeutic targets. Further experiments and clinical investigations are needed to validate these findings and explore the clinical implications of targets in SAH treatment.