Novel Classification of Peroneal Tendon Disease Reveals Cellular and Molecular Phenotypes of the Tenosvnovium
Authors: Matthias Julia , David Michael A. , Buckley Sara E. , Ross Daniel J. , Zona Nathaniel , Hewitt Michael A. , Metzl Joshua , Moon Daniel K. , Grimsrud Courtney , Adams Douglas J. , Zuscik Michael , Hunt Kenneth 
Published: December 2024

Category: Ankle; Basic Sciences/Biologics Introduction/Purpose: Peroneal tendon disease (PTD) represents a spectrum of pathologies often misdiagnosed as an ankle sprain. PTD encompasses a spectrum of peroneal tendon pathologies (e.g., tendinosis, tenosynovitis, tears, and instability), resulting in inflammation and/or degeneration of the peroneal tendon and surrounding tenosynovium. While the microenvironment of inflamed joints and tendons has been described for other parts of the human body, this has not been well investigated for patients with PTD. Furthermore, limited consensus exists on the classification of PTD, challenging accurate diagnosis and targeted therapeutic strategies. We aimed to develop a clinically meaningful classification system for PTD incorporating detailed analysis of molecular, cellular, and tissue changes of the tenosynovium surrounding the peroneal tendon. Methods: Patients undergoing surgery for PTD (IRB-approved) were classified using our 5-type classification system (Fig 1A). After classifying PTD, tenosynovium was processed for bulk RNA sequencing (RNA-seq; PTD0 vs PTD1-4; n = 7 for PTD0 and n = 3-7 for PTD1-4), and digital histopathology (DH; n = 1-7/PTD). For RNA-seq, standard Gene Ontology (GO) analysis was used to identify enriched gene pathways. For DH, tenosynovium was paraffin-embedded, sectioned, stained with hematoxylin/eosin, imaged using a slide scanner, and imported into QuPath software for quantification (n = 3 sections/tenosynovium). Briefly, tenosynovium was manually traced, and cellular density (cell numbers/tissue area) was quantified and averaged for each patient’s tenosynovium. A qualitative assessment evaluated the cell spatial distribution relative to tissue structures (e.g., fat, fibrous tissue, and vascularity). Kruskal Wallis with Dunn’s post-hoc was used to detect differences in cellular density between PTD1-4 vs PTD0. Results: We observed distinct transcriptomic signatures between the tenosynovium graded by our classification system (Fig 1D). GO term analysis highlighted increased gene expression associated with biological and molecular pathways related to inflammatory leukocyte and neutrophil activation/migration in PTD1 (Fig 1E). PTD2 was associated with decreased pathways related to glucose and fatty acid metabolism. PTD3 showed increased hemoglobin expression, gas transport, and detoxification (Fig 1E). PTD4 was associated with increased leukocyte activation and chemotaxis (Fig 1E). DH revealed increased cellular density (i.e., hypercellularity) with PTD4 (Figure 1B, C). Qualitatively, cells appeared spatially around vascular/nerve structures and non-fatty-like tissue (Fig 1B). Conclusion: Our novel classification system created to define PTD better demonstrates unique cellular and molecular signatures in each PTD type. Tissue level analysis showed increased cell density around vascular structures with increased PTD type. RNA-seq revealed an increase in inflammation-related gene pathways at PTD types 1 and 2, while pathways related to energy metabolism and detoxification were significantly altered at PTD types 2 and 3. Improved clarity in biological pathways and cellular characterization of the tenosynovium in each classification of PTD will help optimize surgical strategies and allow for personalized therapeutic intervention for PTD.