Rho-GTPase pathways may differentiate treatment response to TNF-alpha and IL-17A inhibitors in psoriatic arthritis

Proteome and phospholipidome interrelationship of synovial fluid-derived extracellular vesicles in equine osteoarthritis: An exploratory 'multi-omics' study to identify composite biomarkers

Osteoarthritis causes progressive joint deterioration, severe morbidity, and reduced mobility in both humans and horses. Currently, osteoarthritis is diagnosed at late stages through clinical examination and radiographic imaging, hence it is challenging to address and provide timely therapeutic interventions to slow disease progression or ameliorate symptoms. Extracellular vesicles are cell-derived vesicles that play a key role in cell-to-cell communication and are potential sources for specific composite biomarker panel discovery. We here used a multi-omics strategy combining proteomics and phospholipidomics in an integral approach to identify composite biomarkers associated to purified extracellular vesicles from synovial fluid of healthy, mildly and severely osteoarthritic equine joints. Although the number of extracellular vesicles was unaffected by osteoarthritis, proteome profiling of extracellular vesicles by mass spectrometry identified 40 differentially expressed proteins (non-adjusted p < 0.05) in osteoarthritic joints associated with 7 significant canonical pathways in osteoarthritis. Moreover, pathway analysis unveiled changes in disease and molecular functions during osteoarthritis development. Phospholipidome profiling by mass spectrometry showed a relative increase in sphingomyelin and a decrease in phosphatidylcholine, phosphatidylinositol, and phosphatidylserine in extracellular vesicles derived from osteoarthritic joints compared to healthy joints. Unsupervised data integration revealed positive correlations between the proteome and the phospholipidome. Comprehensive analysis showed that some phospholipids and their related proteins increased as the severity of osteoarthritis progressed, while others decreased or remained stable. Altogether our data show interrelationships between synovial fluid extracellular vesicle-associated phospholipids and proteins responding to osteoarthritis pathology and which could be explored as potential composite diagnostic biomarkers of disease.

Do genetics contribute to TNF inhibitor response prediction in Psoriatic Arthritis?

Psoriatic arthritis (PsA) is a heterogeneous chronic musculoskeletal disease, affecting up to 30% of people with psoriasis. Research into PsA pathogenesis has led to the development of targeted therapies, including Tumor Necrosis Factor inhibitors (TNF-i). Good response is only achieved by ~60% of patients leading to 'trial and error' drug management approaches, adverse reactions and increasing healthcare costs. Robust and well-validated biomarker identification, and subsequent development of sensitive and specific assays, would facilitate the implementation of a stratified approach into clinical care. This review will summarise potential genetic biomarkers for TNF-i (adalimumab, etanercept and infliximab) response that have been reported to date. It will also comment upon the importance of managing clinical confounders when understanding drug response prediction. Variants in multiple gene regions including TNF-A, FCGR2A, TNFAIP3, TNFR1/TNFR1A/TNFRSF1A, TRAIL-R1/TNFRSF10A, FCGR3A have been reported to correlate with TNF-i response at various levels of statistical significance in patients with PsA. However, results were often from heterogenous and underpowered cohorts and none are currently implemented into clinical practice. External validation of genetic biomarkers in large, well-documented cohorts is required, and assessment of the predictive value of combining multiple genetic biomarkers with clinical measures is essential to clinically embed pharmacogenomics into PsA drug management.

Defining imaging sub-phenotypes of psoriatic arthritis: integrative analysis of imaging data and gene expression in a PsA patient cohort

OBJECTIVES

To define imaging sub-phenotypes in patients with PsA; determine their association with whole blood gene expression and identify biological pathways characterizing the sub-phenotypes.

METHODS

Fifty-five patients with PsA ready to initiate treatment for active disease were prospectively recruited. We performed musculoskeletal ultrasound assessment of the extent of inflammation in the following domains: synovitis, peritenonitis, tenosynovitis and enthesitis. Peripheral whole blood was profiled with RNAseq, and gene expression data were obtained. First, unsupervised cluster analysis was performed to define imaging sub-phenotypes that reflected the predominant tissue involved. Subsequently, principal component analysis was used to determine the association between imaging-defined sub-phenotypes and peripheral blood gene expression profile. Pathway enrichment analysis was performed to identify underlying mechanisms that characterize individual sub-phenotypes.

RESULTS

Cluster analysis revealed three imaging sub-phenotypes: (i) synovitis predominant [n = 31 (56%)]; (ii) enthesitis predominant [n = 13 (24%)]; (iii) peritenonitis predominant [n = 11 (20%)]. The peritenonitis-predominant sub-phenotype had the most severe clinical joint involvement, whereas the enthesitis-predominant sub-phenotype had the highest tender entheseal count. Unsupervised clustering of gene expression data identified three sub-phenotypes that partially overlapped with the imaging sub-phenotypes suggesting biological and clinical relevance of these sub-phenotypes. We therefore characterized enriched differential pathways, which included: immune system (innate system, B cells and neutrophil degranulation), complement system, platelet activation and coagulation function.

CONCLUSIONS

We identified three sub-phenotypes based on the predominant tissue involved in patients with active PsA. Distinct biological pathways may underlie these imaging sub-phenotypes seen in PsA, suggesting their biological and clinical importance.

Clinical and molecular significance of genetic loci associated with psoriatic arthritis

Psoriatic arthritis (PsA) is caused by a combination of environmental and multiple genetic factors, with clear evidence for a strong genetic basis. The remarkable accumulation of knowledge gained from genetic, pharmacogenetic, and therapeutic response of biologic agents in PsA has fundamentally changed and advanced our understanding of disease pathogenesis and has identified key signalling pathways. However, only one-quarter of the genetic contribution of PsA has been accounted for; and dissecting the genetic contributors of the cutaneous disease from those that would identify joint disease has been challenging. More importantly, the clinical utility of multiple proposed loci is unclear. In this review, we summarize the potential clinical relevance from established genetic associations and provide insight on the proposed molecular pathways that arise from these associations.