From desk to bed: computational simulations provide indication for rheumatoid arthritis clinical trials

Identification of novel rheumatoid arthritis-associated MiRNA-204-5p from plasma exosomes

Rheumatoid arthritis (RA) is an autoimmune disease characterized by infiltration of immune cells in the synovium. However, the crosstalk of immune cells and synovial fibroblasts is still largely unknown. Here, global miRNA screening in plasma exosomes was carried out with a custom microarray (RA patients vs. healthy controls = 9:9). A total of 14 exosomal miRNAs were abnormally expressed in the RA patients. Then, downregulated expression of exosomal miR-204-5p was confirmed in both the replication (RA patients vs. healthy controls = 30:30) and validation groups (RA patients vs. healthy controls = 56:60). Similar to the findings obtained in humans, a decreased abundance of exosomal miR-204-5p was observed in mice with collagen-induced arthritis (CIA). Furthermore, Spearman correlation analysis indicated that plasma exosomal miR-204-5p expression was inversely correlated with disease parameters of RA patients, such as rheumatoid factor, erythrocyte sedimentation rate, and C-reactive protein. In vitro, our data showed that human T lymphocytes released exosomes containing large amounts of miR-204-5p, which can be transferred into synovial fibroblasts, inhibiting cell proliferation. Overexpression of miR-204-5p in synovial fibroblasts suppressed synovial fibroblast activation by targeting genes related to cell proliferation and invasion. In vivo assays found that administration of lentiviruses expressing miR-204-5p markedly alleviated the disease progression of the mice with CIA. Collectively, this study identified a novel RA-associated plasma exosomal miRNA-204-5p that mediates the communication between immune cells and synovial fibroblasts and can be used as a potential biomarker for RA diagnosis and treatment.

A microRNA that is significantly reduced in joint tissues in rheumatoid arthritis could provide a therapeutic target and act as a biomarker for disease progression. In rheumatoid arthritis, immune cells release exosomes, tiny vesicles containing microRNA and proteins that are transferred to cells in the synovium, the connective tissue lining the inside of the joint capsule. This transfer of molecules influences synovial cell activity. Shu-Feng Lei and Fei-Yan Deng at the Medical School of Soochow University, Suzhou, China, and co-workers identifed exosomal microRNAs present in rheumatoid arthritis, and examined their effect on synovial cells. Levels of one exosomal microRNA, miR-204-5p, were significantly lower in patient samples and mice models, inversely correlating with disease severity. The team believe that chronic inflammation may suppress levels of miR-204-5p. Treatment boosting microRNA levels in mice models slowed disease progression.

The greater inflammatory pathway-high clinical potential by innovative predictive, preventive, and personalized medical approach

BACKGROUND AND LIMITATIONS

Impaired wound healing (WH) and chronic inflammation are hallmarks of non-communicable diseases (NCDs). However, despite WH being a recognized player in NCDs, mainstream therapies focus on (un)targeted damping of the inflammatory response, leaving WH largely unaddressed, owing to three main factors. The first is the complexity of the pathway that links inflammation and wound healing; the second is the dual nature, local and systemic, of WH; and the third is the limited acknowledgement of genetic and contingent causes that disrupt physiologic progression of WH.

PROPOSED APPROACH

Here, in the frame of Predictive, Preventive, and Personalized Medicine (PPPM), we integrate and revisit current literature to offer a novel systemic view on the cues that can impact on the fate (acute or chronic inflammation) of WH, beyond the compartmentalization of medical disciplines and with the support of advanced computational biology.

CONCLUSIONS

This shall open to a broader understanding of the causes for WH going awry, offering new operational criteria for patients' stratification (prediction and personalization). While this may also offer improved options for targeted prevention, we will envisage new therapeutic strategies to reboot and/or boost WH, to enable its progression across its physiological phases, the first of which is a transient acute inflammatory response versus the chronic low-grade inflammation characteristic of NCDs.

Mechanotransduction map: simulation model, molecular pathway, gene set

MOTIVATION

Mechanotransduction--the ability to output a biochemical signal from a mechanical input--is related to the initiation and progression of a broad spectrum of molecular events. Yet, the characterization of mechanotransduction lacks some of the most basic tools as, for instance, it can hardly be recognized by enrichment analysis tools, nor could we find any pathway representation. This greatly limits computational testing and hypothesis generation on mechanotransduction biological relevance and involvement in disease or physiological mechanisms.

RESULTS

We here present a molecular map of mechanotransduction, built in CellDesigner to warrant that maximum information is embedded in a compact network format. To validate the map's necessity we tested its redundancy in comparison with existing pathways, and to estimate its sufficiency, we quantified its ability to reproduce biological events with dynamic simulations, using Signaling Petri Networks.

AVAILABILITY AND IMPLEMENTATION

SMBL language map is available in the Supplementary Data: core_map.xml, basic_map.xml.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Network medicine analysis of chondrocyte proteins towards new treatments of osteoarthritis

Osteoarthritis (OA) is a progressive disorder with high incidence in the ageing human population that still has no treatment currently. This disorder induces the breakdown of articular cartilage, leading to the exposure and damage of bone surfaces. For a global understanding of OA development, the systematic integration of known OA-related proteins with protein-protein interaction (PPI) networks is required. In this work, the OA-related interactome was reconstructed using multiple data sources to have the most up-to-date information on OA-related proteins and their interactions. We then combined emergent concepts in network medicine to detect new unclassified OA-related proteins. The mapping of known OA-related proteins with PPI networks showed that these proteins are locally connected to each other and agglomerated in a large component. To expand this module, we applied a diffusion-based algorithm that probabilistically induces more searches in the vicinity of the seed OA-related proteins. As a result, the 10 topmost ranked proteins were connected to the OA disease module, supporting the local hypothesis. We computed structural modules and selected those that had the highest enrichment of OA-related proteins. The identified molecules show a link between structural topology and disease dysfunctionality. Interestingly, the protein Q6EEV6 was highlighted for OA association by both methods, reinforcing the potential involvement of this protein. These results suggest that similar disease-connected modules may exist in different human disorders, which could lead to systematic identification of genes or proteins that have a joint role in specific disease phenotypes.