Identifying the key microbiome associated with lumbar discherniation in Chinese patients

Inflammation and subsequent fibrotic remodeling-characterized by extracellular matrix deposition and myofibroblast activation-are hallmark processes in various degenerative disorders. Lumbar disc herniation (LDH) involves local inflammation and disruption of extracellular matrix organization; however, the role of systemic modulators such as gut microbiota and their metabolites remains poorly understood, particularly in the Han Chinese population.

A total of 69 LDH patients and 69 healthy controls were enrolled in this study. Fecal samples were subjected to 16 S rRNA sequencing, and untargeted metabolomics was performed to compare microbial diversity, taxonomic composition, and metabolic profiles between the two groups. A random forest model was constructed to evaluate the diagnostic predictive value of identified microbial and metabolic features.

LDH patients exhibited significant gut microbial dysbiosis, characterized by reduced alpha and beta diversity and markedly decreased abundances of Faecalibacterium and Bacteroides. These microbial alterations were associated with chronic inflammation driven by elevated proinflammatory factors, suppression of glutamatergic and GABAergic neuronal signaling, and dysregulation of pathways involved in mannan degradation and cytoskeleton assembly-processes closely linked to cell-matrix interactions and fibrotic tissue remodeling. Metabolites including phenylalanine and beta-alanine were identified as potential regulatory molecules. The random forest model incorporating microbial pathways and metabolites demonstrated good diagnostic accuracy for distinguishing LDH patients from healthy controls.

These findings suggest that gut microbiota may contribute to intervertebral disc degeneration by promoting chronic inflammatory responses and fibrotic structural remodeling. This study provides new insights into the inflammation-fibrosis continuum underlying spinal degeneration and identifies candidate biomarkers with potential for future translational applications.