INTRODUCTION:
Intervertebral disc (IVD) degeneration is a significant factor contributing to low back pain (LBP), a health problem with substantial socio-economic consequences. IVD degeneration is a complex condition with multiple underlying causes and plays a major role in the development of LBP. This degeneration process is initiated by a combination of changes in mechanobiology, inflammation, and nutrient supply, resulting in the loss of structural integrity and increased risk of protrusion and extrusion, causing disc-related pain. This patient population is quite heterogenous in nature, with a broad age range of multiple risk factors and variable responses to treatment strategies. This study aimed to categorize and characterize different subtypes of degenerated IVD based on proteomic markers. Additionally, we sought to establish connections among distinct tissue phenotypes, patient demographics, and radiological findings.
METHODS:
93 healthy and degenerated human intervertebral disc samples were collected from local hospitals with ethical approval and informed consent. Preoperative magnetic resonance imaging (MRI) findings and patient demographics were also recorded. Sagittal and parasagittal T2-weighted MRI slices were used to characterise the Pfirrmann grade, multilevel disease and other features. For proteomic analysis, the tissue was homogenized in radioimmunoprecipitation assay buffer using a Qiagen TissueLyser LT™. Protein concentration was confirmed using the bicinchoninic acid (BCA) assay. Isolated protein samples were trypsinised and cleaned. The samples were run on a QExactive™ Hybrid Quadrupole-Orbitrap™ Mass Spectrometer connected to a Dionex Ultimate 3000 (RSLCnano) chromatography system. A high-resolution (70,000) MS scan (300-1600 m/z) was performed to select the12 most intense ions and fragments using high-energy C-trap dissociation for MS/MS analysis. To identify peptides and proteins, MS/MS spectra were matched against the Uniprot UP000005640 database. All searches were performed using the default settings in MaxQuant. Label-free quantitative proteomic analysis was performed using Perseus (v2.0.3.1) to characterise differentially regulated signalling pathways across samples. Pathway analysis, including Gene Ontology (GO) and KEGG enrichment, was performed using Omics Playground (BigOmics Analytics, Switzerland).
RESULTS:
Proteomic analysis revealed that ECM proteins such as aggrecan and collagens were highly expressed in the IVD. Key signalling pathways such as acute-phase signalling, N-glycan synthesis, and extracellular matrix turnover were activated in degenerated tissues. Healthy annulus fibrosus (AF) and nucleus pulposus (NP) tissues demonstrate consistent proteomic expression, with a distinction between these two tissues. Two phenotypes of degeneration have been identified: a pro-inflammatory catabolic cohort and a senescent apoptotic cohort, each with unique demographic and radiological characteristics. Significantly altered expression was observed across patient demographics (sex, age, clinical symptoms, and reported outcomes), MRI findings, and other molecular markers.
DISCUSSION:
Several key signalling pathways are activated in human IVD degeneration. Preliminary analysis performed using principal component analysis (PCA) indicates that there is significant heterogeneity in the signalling pathways activated in IVD degeneration. Differential proteomic expression in patients with similar presentations may be a useful prognostic tool for predicting successful discectomy outcomes.