Intervertebral disc (IVD) disease (IDD) is a complex, multifactorial disease. While various aspects of IDD progression have been reported, the underlying molecular pathways and transcriptional networks that govern the maintenance of healthy nucleus pulposus (NP) and annulus fibrosus (AF) have not been fully elucidated. We defined the transcriptome map of healthy human IVD by performing single-cell RNA-sequencing (scRNA-seq) in primary AF and NP cells isolated from non-degenerated lumbar disc. Our systematic and comprehensive analyses revealed distinct genetic architecture of human NP and AF compartments and identified 2,196 differentially expressed genes. Gene enrichment analysis showed that SFRP1, BIRC5, CYTL1, ESM1 and CCNB2 genes were highly expressed in the AF cells; whereas, COL2A1, DSC3, COL9A3, COL11A1, and ANGPTL7 were mostly expressed in the NP cells. Further, functional annotation clustering analysis revealed the enrichment of receptor signaling pathways genes in AF cells, while NP cells showed high expression of genes related to the protein synthesis machinery. Subsequent interaction network analysis revealed a structured network of extracellular matrix genes in NP compartments. Our regulatory network analysis identified FOXM1 and KDM4E as signature transcription factor of AF and NP respectively, which might be involved in the regulation of core genes of AF and NP transcriptome.
Background: Rats are a widely accepted preclinical model for evaluating intervertebral disc (IVD) degeneration and regeneration. IVD morphology is commonly assessed using histology, which forms the foundation for quantifying the state of IVD degeneration. IVD degeneration severity is evaluated using different grading systems that focus on distinct degenerative features. A standard grading system would facilitate more accurate comparison across laboratories and more robust comparisons of different models and interventions.Aims: This study aimed to develop a histology grading system to quantify IVD degeneration for different rat models.
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