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CD8 T-cells, CD86+ macrophages, and TNF-α signaling pathways are correlated with fetlock osteoarthritis in racehorses

ABSTRACT: Background: There is emerging evidence for the role of the immune system in osteoarthritis (OA) pathophysiology; however, little is known about how immune cells and the synovial transcriptome are altered in naturally occurring equine OA. Objectives: To evaluate synovial fluid (SF) and synovial membrane (SM) immune cell populations and the SM transcriptome in racehorses with fetlock osteoarthritis. Methods: Fetlock joints from racehorses euthanized on NY racetracks were considered for inclusion. SF and SM were analyzed by flow cytometry using T-cell (CD3, CD4, CD8) and macrophage (CD14, CD86, CD206) surface markers. OA severity was characterized by gross joint evaluation and SM histology. Bulk RNA-sequencing of SM was performed to identify differentially expressed genes. Flow cytometry data was analyzed with mixed linear modeling, including OA severity as a fixed effect and horse as a random effect. RNA-sequencing was evaluated with mixed linear and quadratic modeling using DREAMSeq method to capture differential gene expression over the range of OA severity. Results: Twenty-four fetlocks from 12 horses met inclusion criteria. CD8+ T-cells (R2 = 0.25 for SM, 0.35 for SF) and CD86+ macrophages (R2 = 0.14 for SM) were positively correlated with OA severity, while CD4+ T-cells (R2 = 0.17 for SM, 0.31 for SF) were negatively correlated. Macrophages co-expressing CD86 and CD206 correlated with OA severity in SM (R2 = 0.31). Pathways including those associated with TNF-α signaling, connective tissue development, and cell and neuron projection organization/development were differentially regulated in SM with greater OA scores. Main Limitations: Limited sample size, particularly of horses with severe OA. Conclusions: CD8+ T-cells, CD86+ macrophages, and macrophages co-expressing CD206 and CD86 are enriched in horses with more advanced OA. Gene set analysis suggests the importance of TNF-α signaling and disinhibition of neuron and cell projection development in OA pathogenesis.

ORGANISM(S): Equus caballus

PROVIDER: GSE312304 | GEO | 2026/04/21

REPOSITORIES: GEO

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Project description:Osteoarthritis (OA) is characterised by loss of articular cartilage, synovial membrane dysfunction and subchondral sclerosis. Few studies have used a global approach to stratify equine synovial fluid (SF) molecular profiles according to OA severity. SF was collected from 58 metacarpophalangeal (MCP) and metatarsophalangeal joints of racing Thoroughbred horses (Hong Kong Jockey Club; HKJC) and 83 MCP joints of mixed breed horses from an abattoir and equine hospital (biobank). Joints were histologically and macroscopically assessed for OA severity. For proteomic analysis, native SF and SF loaded onto ProteoMiner™ equalisation columns, to deplete high abundant proteins, were analysed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and label-free quantification. Validation of selected differentially expressed proteins was undertaken using clinical SF collected during diagnostic investigations. Native SF metabolites were analysed using 1D 1H Nuclear Magnetic Resonance (NMR). 1,834 proteins and 40 metabolites were identified in equine SF. Afamin levels decreased with synovitis severity and four uncharacterised proteins decreased with OA severity. Gelsolin and lipoprotein binding protein decreased with OA severity and apolipoprotein A1 levels increased for mild and moderate OA. Within the biobank, glutamate levels decreased with OA severity and for the HKJC, 2-aminobutyrate, alanine and creatine increased with severity. Proteomic and metabolomic integration was undertaken using linear regression via Lasso penalisation modelling, incorporating 29 variables (R2=0.82) with principal component 2 able to discriminate advanced OA from earlier stages, predominantly driven by H9GZQ9, F6ZR63 and alanine. Combining biobank and HKJC datasets, discriminant analysis of principal components modelling prediction was good for mild OA (90%). This study has stratified equine OA using both metabolomic and proteomic SF profiles and identified a panel of markers of interest which may be applicable to grading OA severity. This is also the first study to undertake computational integration of NMR metabolomic and LC-MS/MS proteomic datasets of any biological system.

Project description:Osteoarthritis (OA) is characterised by loss of articular cartilage, synovial membrane dysfunction and subchondral sclerosis. Few studies have used a global approach to stratify equine synovial fluid (SF) molecular profiles according to OA severity. SF was collected from 58 metacarpophalangeal (MCP) and metatarsophalangeal joints of racing Thoroughbred horses (Hong Kong Jockey Club; HKJC) and 83 MCP joints of mixed breed horses from an abattoir and equine hospital (biobank). Joints were histologically and macroscopically assessed for OA severity. For proteomic analysis, native SF and SF loaded onto ProteoMinerTM equalisation columns, to deplete high abundant proteins, were analysed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and label-free quantification. Validation of selected differentially expressed proteins was undertaken using clinical SF collected during diagnostic investigations. Native SF metabolites were analysed using 1D 1H Nuclear Magnetic Resonance (NMR). 1,834 proteins and 40 metabolites were identified in equine SF. Afamin levels decreased with synovitis severity and four uncharacterised proteins decreased with OA severity. Gelsolin and lipoprotein binding protein decreased with OA severity and apolipoprotein A1 levels increased for mild and moderate OA. Within the biobank, glutamate levels decreased with OA severity and for the HKJC, 2-aminobutyrate, alanine and creatine increased with severity. Proteomic and metabolomic integration was undertaken using linear regression via Lasso penalisation modelling, incorporating 29 variables (R2=0.82) with principal component 2 able to discriminate advanced OA from earlier stages, predominantly driven by H9GZQ9, F6ZR63 and alanine. Combining biobank and HKJC datasets, discriminant analysis of principal components modelling prediction was good for mild OA (90%). This study has stratified equine OA using both metabolomic and proteomic SF profiles and identified a panel of markers of interest which may be applicable to grading OA severity. This is also the first study to undertake computational integration of NMR metabolomic and LC-MS/MS proteomic datasets of any biological system. Proteomic dataset depositied in PRIDE - <a href='https://www.ebi.ac.uk/pride/archive/projects/PXD019842' rel='noopener noreferrer' target='_blank'>PXD019842</a>.

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CD8 T-cells, CD86+ macrophages, and TNF-α signaling pathways are correlated with fetlock osteoarthritis in racehorses

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