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May 26, 2026Frontiers in Immunology0 citationsOpen Access

Single-cell extracellular vesicle-program scoring maps immunometabolic rewiring and immune crosstalk of mesenchymal stromal cells in intervertebral disc degeneration, prioritizing AP2S1 and CSTB

FMFengyu MaKSKelv ShenZWZiqiang Wu

Key Points

  • The aim is to explore the role of mesenchymal stromal cells and their extracellular vesicles in immunometabolic changes during intervertebral disc degeneration.
  • Analyzed single-cell RNA sequencing data from GSE230809 (8 IDD and 3 control samples) with preprocessing and batch correction.
  • Derived MSC EV–associated program scores and stratified MSCs by EV scores.
  • Employed machine learning with LASSO/SVM-RFE to prioritize candidate regulators and used CellChat to infer ligand-receptor communication.
  • Identified seven major cell populations and observed higher EV-program scores in MSCs from IDD tissues.
  • EV-score-high MSCs exhibited increased immune interaction potential, correlating with immune–metabolic pathways like IL6/JAK–STAT3.
  • AP2S1 and CSTB were highlighted as key hub genes, with a model distinguishing IDD from control samples (AUC = 0.836).

Abstract

Background Intervertebral disc degeneration (IDD) is increasingly viewed as an immune-perturbed and metabolically stressed niche rather than a purely mechanical or aging-related disorder. Mesenchymal stromal cells (MSCs) and their extracellular vesicles (EVs) may shape local immune signaling, yet MSC EV–associated transcriptional programs and their immune-network context remain poorly defined at single-cell resolution. Methods We analyzed single-cell RNA sequencing (scRNA-seq) data from GSE230809 (8 IDD and 3 control nucleus pulposus samples) with standard preprocessing and batch correction. We derived a transcriptome-inferred MSC EV–associated program score by integrating complementary gene-set scoring strategies, stratified MSCs into EV-score–high versus –low states, and prioritized candidate regulators using a consensus LASSO/SVM-RFE workflow. CellChat was used to infer ligand–receptor communication, while pathway-level immunometabolic remodeling was assessed with GSVA/GSEA and immune-signature correlation analyses. Selected genes were examined by RT–qPCR in an in vitro inflammatory NP-cell model, and docking was performed to explore tractable compound–target hypotheses. Results We resolved seven major cell populations and observed a marked shift toward higher EV-program scores in MSCs from IDD tissues. EV-score–high MSCs showed increased incoming signaling and interaction potential in CellChat networks, consistent with an “immune cue–responsive” state. Machine-learning prioritization converged on five hub genes (AP2S1, CSTB, GSTP1, RPL28, and TSG101). The hub-gene program aligned with immune–metabolic axes including IL6/JAK–STAT3 and interferon-related signaling, together with oxidative phosphorylation and ROS stress signatures, and was systematically associated with immune mediators (notably chemokines and checkpoint-related genes). AP2S1 and CSTB displayed dynamic expression along MSC pseudotime trajectories and were supported by RT–qPCR under inflammatory stimulation. A hub-gene model distinguished IDD from control samples within the discovery cohort (AUC = 0.836). Docking suggested a plausible interaction between CSTB and ripasudil (−5.98 kcal/mol). Conclusions This study maps an MSC EV–associated program at single-cell resolution and places it within an immune–communication and immunometabolic framework in IDD. AP2S1 and CSTB are candidate nodes linking EV-program states to immune signaling and metabolic stress, providing candidate biomarkers and tractable intervention hypotheses.

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Cite This Study

Ma et al. (2026) studied this question.

synapsesocial.com/papers/6a153790b5d9c58d83e8bf89https://doi.org/10.3389/fimmu.2026.1820174
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