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Updated: Jul 23, 2026
A Proinflammatory, Degenerative Organ Culture Model to Simulate Early-Stage Intervertebral Disc Disease.
Published on: February 14, 2021
Multi-omics identification of circulating protein biomarkers for intervertebral disc degeneration using Mendelian
Fan Bai1, Lingting Wang1, He Liu1
1Spinal Surgery Division, Yijishan Hospital, Wannan Medical College, 2 Zheshan West Road, Jinghu District, Wuhu, 241000, Anhui, China.
Background:
Intervertebral disc degeneration (IVDD) is a primary cause of chronic low back pain, significantly impacting quality of life and healthcare systems globally. Despite its prevalence, the molecular mechanisms underlying IVDD remain unclear, and effective biomarkers are lacking. This study aims to identify circulating protein biomarkers causally linked to IVDD and explore their potential as biomarkers.
Methods:
A proteome-wide Mendelian randomization (MR) analysis was conducted using data from 4907 circulating proteins to assess their causal relationships with IVDD, utilizing the FinnGen cohort. Single-cell RNA sequencing (scRNA-seq) was performed to evaluate the expression patterns of identified proteins in healthy and degenerated disc tissues. Additionally, machine learning models were employed to rank these proteins based on their therapeutic potential.
Results:
Eight circulating proteins (CD96, CDH3, COPS2, DDX23, FAM210A, PNPO, STOML2, and UBE2D2) were identified as statistically associated with IVDD. scRNA-seq analysis demonstrated differential expression patterns between healthy and degenerated tissues, with COPS2 and UBE2D2 achieving the highest classification accuracy for distinguishing tissue states (AUC = 0.85). Functional and pathway analyses highlighted their roles in inflammation, extracellular matrix regulation, and cellular stress responses.
Conclusions:
This study integrates multi-omics approaches to uncover novel protein biomarkers for IVDD, with COPS2 and UBE2D2 showing promising potential as biomarkers or mechanistic targets. Further in vivo validation studies are warranted to confirm their clinical relevance and therapeutic applicability. Key Points • This study utilized Mendelian randomization and single-cell RNA sequencing to identify eight circulating proteins causally associated with IVDD. • The application of machine learning models revealed COPS2 and UBE2D2 as top contributors with high classification accuracy in distinguishing healthy and degenerated disc tissues. • Comprehensive multi-omics and pathway analysis highlighted COPS2 and UBE2D2 as promising therapeutic targets for IVDD, warranting further in vivo validation. • Enrichment analyses identified significant immune-related pathways, underscoring inflammation's critical role in IVDD progression and providing avenues for targeted interventions.
