Characterization and miRNA Profiling of Extracellular Vesicles from Human Osteoarthritic Subchondral Bone Multipotential Stromal Cells (MSCs)

Therapeutics of the future: Navigating the pitfalls of extracellular vesicles research from an osteoarthritis perspective

Extracellular vesicles have gained wide momentum as potential therapeutics for osteoarthritis, a highly prevalent chronic disease that still lacks an approved treatment. The membrane-bound vesicles are secreted by all cells carrying different cargos that can serve as both disease biomarkers and disease modifiers. Nonetheless, despite a significant peak in research regarding EVs as OA therapeutics, clinical implementation seems distant. In addition to scalability and standardization challenges, researchers often omit to focus on and consider the proper tropism of the vesicles, the practicality and relevance of their source, their low native therapeutic efficacy, and whether they address the disease as a whole. These considerations are necessary to better understand EVs in a clinical light and have been comprehensively discussed and ultimately summarized in this review into a conceptualized framework termed the nanodiamond concept. Future perspectives are also discussed, and alternatives are presented to address some of the challenges and concerns.

A call for standardization for secretome and extracellular vesicles in osteoarthritis: results show disease-modifying potential, but protocols are too heterogeneous-a systematic review

The currently available osteoarthritis (OA) treatments offer symptoms' relief without disease-modifying effects. Increasing evidence supports the role of human mesenchymal stem cells (MSCs) to drive beneficial effects provided by their secretome and extracellular vesicles (EVs), which includes trophic and biologically active factors. Aim of this study was to evaluate the in vitro literature to understand the potential of human secretome and EVs for OA treatment and identify trends, gaps, and potential translational challenges. A systematic review was performed on PubMed, Embase, and Web-of-Science, identifying 58 studies. The effects of secretome and EVs were analysed on osteoarthritic cells regarding anabolic, anti-apoptotic/anti-inflammatory and catabolic/pro-inflammatory/degenerative activity, chondroinduction, and immunomodulation. The results showed that MSC-derived EVs elicit an increase in proliferation and migration, reduction of cell death and inflammation, downregulation of catabolic pathways, regulation of immunomodulation, and promotion of anabolic processes in arthritic cells. However, a high heterogeneity in several technical or more applicative aspects emerged. In conclusion, the use of human secretome and EVs as strategy to address OA processes has overall positive effects and disease-modifying potential. However, it is crucial to reduce protocol variability and strive toward a higher standardization, which will be essential for the translation of this promising OA treatment from the in vitro research setting to the clinical practice.

Extracellular vesicles are key players in mesenchymal stem cells' dual potential to regenerate and modulate the immune system

MSCs are used for treatment of inflammatory conditions or for regenerative purposes. MSCs are complete cells and allogenic transplantation is in principle possible, but mostly autologous use is preferred. In recent years, it was discovered that cells secrete extracellular vesicles. These are active budded off vesicles that carry a cargo. The cargo can be miRNA, protein, lipids etc. The extracellular vesicles can be transported through the body and fuse with target cells. Thereby, they influence the phenotype and modulate the disease. The extracellular vesicles have, like the MSCs, immunomodulatory or regenerative capacities. This review will focus on those features of extracellular vesicles and discuss their dual role. Besides the immunomodulation, the regeneration will concentrate on bone, cartilage, tendon, vessels and nerves. Current clinical trials with extracellular vesicles for immunomodulation and regeneration that started in the last five years are highlighted as well. In summary, extracellular vesicles have a great potential as disease modulating entity and treatment. Their dual characteristics need to be taken into account and often are both important for having the best effect.

Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications

Osteoarthritis (OA) is a debilitating degenerative disease affecting multiple joint tissues, including cartilage, bone, synovium, and adipose tissues. OA presents diverse clinical phenotypes and distinct molecular endotypes, including inflammatory, metabolic, mechanical, genetic, and synovial variants. Consequently, innovative technologies are needed to support the development of effective diagnostic and precision therapeutic approaches. Traditional analysis of bulk OA tissue extracts has limitations due to technical constraints, causing challenges in the differentiation between various physiological and pathological phenotypes in joint tissues. This issue has led to standardization difficulties and hindered the success of clinical trials. Gaining insights into the spatial variations of the cellular and molecular structures in OA tissues, encompassing DNA, RNA, metabolites, and proteins, as well as their chemical properties, elemental composition, and mechanical attributes, can contribute to a more comprehensive understanding of the disease subtypes. Spatially resolved biology enables biologists to investigate cells within the context of their tissue microenvironment, providing a more holistic view of cellular function. Recent advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various -omics lenses, such as genomics, transcriptomics, proteomics, and metabolomics, with spatial data. This fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial coordinates. Furthermore, advanced imaging techniques, including high-resolution microscopy, hyperspectral imaging, and mass spectrometry imaging, enable the visualization and analysis of the spatial distribution of biomolecules, cells, and tissues. Linking these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease phenotypes. This review summarizes the recent advancements in the molecular imaging modalities and methodologies for in-depth spatial analysis. It explores their applications, challenges, and potential opportunities in the field of OA. Additionally, this review provides a perspective on the potential research directions for these contemporary approaches that can meet the requirements of clinical diagnoses and the establishment of therapeutic targets for OA.

Mesenchymal stem cell-derived exosomes and skin photoaging: From basic research to practical application

BACKGROUND

Skin photoaging is a condition caused by long-term exposure to ultraviolet irradiation, resulting in a variety of changes in the skin, such as capillary dilation, increased or absent pigmentation, dryness, sagging, and wrinkles. Stem cells possess a remarkable antioxidant capacity and the ability to proliferate, differentiate, and migrate, and their main mode of action is through paracrine secretion, with exosomes being the primary form of secretion. Stem cell-derived exosomes contain a variety of growth factors and cytokines and may have great potential to promote skin repair and delay skin ageing.

METHODS

This review focuses on the mechanisms of UV-induced skin photoaging, the research progress of stem cell exosomes against skin photoaging, emerging application approaches and limitations in the application of exosome therapy.

RESULT

Exosomes derived from various stem cells have the potential to prevent skin photoaging.

CONCLUSION

The combination with novel materials may be a key step for their practical application, which could be an important direction for future basic research and practical applications.

Advances of Mesenchymal Stem Cells Released Extracellular Vesicles in Periodontal Bone Remodeling

Extracellular vesicles (EVs) are nanoparticles that include exosomes, microvesicles, and apoptotic bodies; they interact with target cell surface receptors and transport contents, including mRNA, proteins, and enzymes into the cytoplasm of target cells to function. The biological fingerprints of EVs practically mirror those of the parental cells they originated from. In the bone remodeling microenvironment, EVs could act on osteoblasts to regulate the bone formation, promote osteoclast differentiation, and regulate bone resorption. Therefore, there have been many attempts wherein EVs were used to achieve targeted therapy in bone-related diseases. Periodontitis, a common bacterial infectious disease, could cause severe alveolar bone resorption, resulting in tooth loss, whereas research on periodontal bone regeneration is also an urgent question. Therefore, EVs-related studies are important for periodontal bone remodeling. In this review, we summarize the current knowledge of mesenchymal stem cell-EVs involved in periodontal bone remodeling and explore the functional gene expression through a comparative analysis of transcriptomic content.

Synovitis mediates the association between bone marrow lesions and knee pain in osteoarthritis: data from the Foundation for the National Institute of Health (FNIH) Osteoarthritis Biomarkers Consortium

OBJECTIVES

Although subchondral bone marrow lesions (BMLs) and synovitis have been well acknowledged as important sources of pain in knee osteoarthritis (KOA), it is unclear if synovitis plays the mediating role in the relationship between BMLs and knee pain.

METHODS

We analyzed 600 subjects with magnetic resonance imaging (MRI) in the Foundation for National Institutes of Health Osteoarthritis Biomarkers Consortium (FNIH) cohort at baseline and 24-month. BMLs and synovitis were measured according to the MRI Osteoarthritis Knee Score (MOAKS) scoring system. BMLs were scored in five subregions. A summary synovitis score of effusion and Hoffa-synovitis was calculated. Knee pain was evaluated using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Linear regression models were applied to analyze the natural direct effect (NDE) of BMLs and synovitis with knee pain, respectively, and natural indirect effect (NIE) mediated by synovitis.

RESULTS

590 participants (58.8% females, with a mean age of 61.5) were included in the present analyses. For NDE, knee pain was cross-sectionally associated with medial femorotibial BMLs (β = 0.23, 95% CI: 0.09, 0.38) and synovitis (β = 0.40, 95% CI: 0.20, 0.60). Longitudinal associations retained significant [medial femorotibial BMLs (β = 0.37, 95% CI: 0.21, 0.53); synovitis (β = 0.72, 95% CI: 0.45, 0.99)]. In the NIE analyses, synovitis mediated the association between medial femorotibial BML and knee pain at baseline (β = 0.051, 95% CI: 0.01, 0.09) and over 24 months (β = 0.079, 95% CI: 0.023, 0.15), with the mediating proportion of 17.8% and 22.4%, respectively.

CONCLUSION

Synovitis partially mediates the association between medial femorotibial BMLs and knee pain.

Cross-Tissue Analysis Using Machine Learning to Identify Novel Biomarkers for Knee Osteoarthritis

Background

Knee osteoarthritis (KOA) is a common degenerative joint disease. In this study, we aimed to identify new biomarkers of KOA to improve the accuracy of diagnosis and treatment.

Methods

GSE98918 and GSE51588 were downloaded from the Gene Expression Omnibus database as training sets, with a total of 74 samples. Gene differences were analyzed by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway, and Disease Ontology enrichment analyses for the differentially expressed genes (DEGs), and GSEA enrichment analysis was carried out for the training gene set. Through least absolute shrinkage and selection operator regression analysis, the support vector machine recursive feature elimination algorithm, and gene expression screening, the range of DEGs was further reduced. Immune infiltration analysis was carried out, and the prediction results of the combined biomarker logistic regression model were verified with GSE55457.

Results

In total, 84 DEGs were identified through differential gene expression analysis. The five biomarkers that were screened further showed significant differences in cartilage, subchondral bone, and synovial tissue. The diagnostic accuracy of the model synthesized using five biomarkers through logistic regression was better than that of a single biomarker and significantly better than that of a single clinical trait.

Conclusions

CX3CR1, SLC7A5, ARL4C, TLR7, and MTHFD2 might be used as novel biomarkers to improve the accuracy of KOA disease diagnosis, monitor disease progression, and improve the efficacy of clinical treatment.