Inside the Joint of Inflammatory Arthritis Patients: Handling and Processing of Synovial Tissue Biopsies for High Throughput Analysis

Type I Interferons induce endothelial destabilization in Systemic Lupus Erythematosus in a Tie2-dependent manner

Endothelial cell (EC) dysfunction is a hallmark of Systemic Lupus Erythematosus (SLE) and Tie2 is a receptor essential for vascular stability. Inflammatory processes promote inhibition of Tie2 homeostatic activation, driving vascular dysfunction. In this work we determined whether type I Interferons (IFN) induce Tie2 signalling-mediated endothelial dysfunction in patients with SLE. Serum levels of Angiopoietin (Ang)-1, Ang-2 and soluble (s)Tie1 in patients with SLE and healthy controls were measured by ELISA. Monocytes from patients with SLE and Human Umbilical Vein EC (HUVEC) were stimulated with IFN-α, IFN-β (1000 I.U.) or SLE serum (20%). mRNA and protein expression, phosphorylation and translocation were determined by quantitative PCR, ELISA, Western Blot, flow cytometry and confocal microscopy. Viability and angiogenic capacity were determined by calcein and tube formation assays. We found that sTie1 and Ang-2 serum levels were increased and Ang-1 decreased in patients with SLE and were associated with clinical characteristics. Type I IFN significantly decreased Ang-1 and increased Ang-2 in monocytes from patients with SLE. Type I IFN increased sTie1 and Ang-2 secretion and reduced Tie2 activation in HUVEC. Functionally, type I IFN significantly reduced EC viability and impaired angiogenesis in a Tie2 signalling-dependent manner. Finally, SLE serum increased Ang-2 and sTie1 secretion and significantly decreased tube formation. Importantly, Tie1 and IFNAR1 knockdown reversed these effects in tube formation. Overall, type I IFN play an important role in the stability of EC by inhibiting Tie2 signalling, suggesting that these processes may be implicated in the cardiovascular events observed in patients with SLE.

Computational approaches in rheumatic diseases - Deciphering complex spatio-temporal cell interactions

Inflammatory arthritis, including rheumatoid (RA), and psoriatic (PsA) arthritis, are clinically and immunologically heterogeneous diseases with no identified cure. Chronic inflammation of the synovial tissue ushers loss of function of the joint that severely impacts the patient's quality of life, eventually leading to disability and life-threatening comorbidities. The pathogenesis of synovial inflammation is the consequence of compounded immune and stromal cell interactions influenced by genetic and environmental factors. Deciphering the complexity of the synovial cellular landscape has accelerated primarily due to the utilisation of bulk and single cell RNA sequencing. Particularly the capacity to generate cell-cell interaction networks could reveal evidence of previously unappreciated processes leading to disease. However, there is currently a lack of universal nomenclature as a result of varied experimental and technological approaches that discombobulates the study of synovial inflammation. While spatial transcriptomic analysis that combines anatomical information with transcriptomic data of synovial tissue biopsies promises to provide more insights into disease pathogenesis, in vitro functional assays with single-cell resolution will be required to validate current bioinformatic applications. In order to provide a comprehensive approach and translate experimental data to clinical practice, a combination of clinical and molecular data with machine learning has the potential to enhance patient stratification and identify individuals at risk of arthritis that would benefit from early therapeutic intervention. This review aims to provide a comprehensive understanding of the effect of computational approaches in deciphering synovial inflammation pathogenesis and discuss the impact that further experimental and novel computational tools may have on therapeutic target identification and drug development.