Machine Learning Identifies Key Cells and Therapeutic Targets in Intervertebral Disc Degeneration: SASP-Driven Matrix Catabolism, Inflammation Amplification, and Metabolic Collapse.

ABSTRACT: Intervertebral disc degeneration (IVDD) is a major contributor to low back pain, yet its cellular and molecular mechanisms remain incompletely understood. In this study, we integrated single-cell and bulk transcriptomic data to uncover the role of senescence-associated secretory phenotype (SASP) signaling in IVDD progression. Single-cell RNA sequencing delineated the heterogeneity of nucleus pulposus cells (NPCs) subtypes and revealed significant differences in senescence levels and SASP activity. Bulk RNA-seq integration across multiple datasets further confirmed widespread SASP activation and defined a core regulatory network centered on Bone Morphogenetic Protein 2 (BMP2) and Matrix Metalloproteinase 3 (MMP3), identified via WGCNA and machine learning algorithms (LASSO, Random Forest, B

SUBMITTER: Kang Y 

PROVIDER: S-EPMC12835096 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature