Uncovering the mechanisms of osteoarthritis in human knee applying spatial transcriptomics
Osteoarthritis (OA) is the most prevalent chronic musculoskeletal disorder causing pain, morbidity and disability, giving rise to enormous healthcare expenditures and loss of work. The exact triggers and pathogenesis of OA are still poorly understood. Currently, there are no measures to slow down the progression of OA. Bulk tissue-based multi-omics and small-scale single cell RNA-seq studies focussing on chondrocytes and synoviocytes have identified novel cell clusters, supporting the hypothesis that OA is a disease of the whole joint. However, one of the key relevant tissues (bone) have not yet been studied. In addition, approaches to date have employed lengthy live cell extraction approaches that affect the transcriptome pattern. Finally, the spatial dimension of molecular changes in the osteochondral unit has not been studied to date. This work will fill this fundamental gap in our understanding of the molecular aetiopathogenesis and progression of OA by employing a novel cutting-edge technique, spatial transcriptomics (ST). ST acts like a high-throughput molecular microscope to allow visualisation and quantitative analysis of the transcriptome with spatial resolution in individual tissue sections, affording near-single cell resolution. SpatialArth will generate new knowledge on the molecular profile of the osteochondral unit and will identify with spatial resolution which cells are involved in the pathogenesis of OA. I will combine ST sequencing and protein expression data from cartilage and bone tissues from OA patients (matched tissues from intact and degraded regions of tibial plateau) and tissues derived from non-OA knee joints. Additionally, I will develop my computational genomics skillset, aiming to help fill the need for a much-needed next generation of interdisciplinary researchers. SpatialArth addresses several mandatory European Union calls - finding strategies supporting healthy and active aging and decreasing the economic burden on healthcare.