Bai Fan, Wang Lingting, Liu He, He Yufei, Wang Hong
Spinal Surgery Division, Yijishan Hospital, Wannan Medical College, 2 Zheshan West Road, Jinghu District, Wuhu, 241000, Anhui, China.
Clin Rheumatol. 2025 Jul 31. doi: 10.1007/s10067-025-07606-6.
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.
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.
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.
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.
椎间盘退变（IVDD）是慢性下腰痛的主要原因，对全球的生活质量和医疗保健系统产生重大影响。尽管其发病率很高，但IVDD的分子机制仍不清楚，且缺乏有效的生物标志物。本研究旨在鉴定与IVDD有因果关系的循环蛋白生物标志物，并探索其作为生物标志物的潜力。
利用芬兰基因队列的数据，对4907种循环蛋白进行全蛋白质组孟德尔随机化（MR）分析，以评估它们与IVDD的因果关系。进行单细胞RNA测序（scRNA-seq）以评估已鉴定蛋白在健康和退变椎间盘组织中的表达模式。此外，采用机器学习模型根据这些蛋白的治疗潜力对其进行排名。
鉴定出八种循环蛋白（CD96、CDH3、COPS2、DDX23、FAM210A、PNPO、STOML2和UBE2D2）与IVDD存在统计学关联。scRNA-seq分析显示健康组织和退变组织之间存在差异表达模式，其中COPS2和UBE2D2在区分组织状态方面具有最高的分类准确性（AUC = 0.85）。功能和通路分析突出了它们在炎症、细胞外基质调节和细胞应激反应中的作用。
本研究整合多组学方法以发现IVDD的新型蛋白生物标志物，COPS2和UBE2D2作为生物标志物或机制靶点显示出有前景的潜力。需要进一步的体内验证研究来证实它们的临床相关性和治疗适用性。要点 • 本研究利用孟德尔随机化和单细胞RNA测序鉴定出八种与IVDD有因果关系的循环蛋白。 • 机器学习模型的应用显示COPS2和UBE2D2是区分健康和退变椎间盘组织时分类准确性高的主要贡献者。 • 全面的多组学和通路分析突出COPS2和UBE2D2作为IVDD有前景的治疗靶点，需要进一步的体内验证。 • 富集分析确定了显著的免疫相关通路，强调炎症在IVDD进展中的关键作用，并为靶向干预提供了途径。
