骨关节炎
转录组
计算生物学
计算机科学
生物
医学
遗传学
基因
病理
基因表达
替代医学
作者
Peng Xie,Antonia RuJia Sun,Feng Gao,Li Lin,Ross Crawford,Indira Prasadam
标识
DOI:10.1016/j.joca.2025.07.007
摘要
Osteoarthritis (OA) is a multifactorial joint disease characterized by complex tissue interactions, spatially compartmentalized pathology, and diverse cellular phenotypes. Traditional transcriptomic approaches have provided valuable insights into OA pathogenesis but lack the spatial resolution required to understand how cellular behaviour is influenced by local tissue context. Spatial transcriptomics (ST) has emerged as a transformative tool that enables in situ gene expression profiling while preserving the anatomical architecture of tissues. In this review, we explore recent advances in ST technologies and highlight their application across key joint compartments in OA, including cartilage, synovium, subchondral bone, and periarticular tissues. We discuss how ST is uncovering zonal gene expression patterns, pathogenic cell states, immune cell interactions, and signalling gradients that drive disease progression. We also outline current technical limitations and propose future directions for integrating spatial data with other omics and imaging modalities. As ST platforms continue to evolve, they hold immense promise for redefining OA phenotypes, identifying novel therapeutic targets, and advancing precision medicine approaches for joint disease.
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