Hepatocyte growth factor and matrix metalloprotease 2 levels in synovial fluid of the knee joint are correlated with clinical outcome of meniscal repair

Systematic Review of Relevant Biomarkers for Human Connective Tissue Repair and Healing Outcome: Implications for Understanding Healing Processes and Design of Healing Interventions

Objective: The healing process following connective tissue (CT) injuries is complex, resulting in variable and often suboptimal outcomes. Patients undergoing CT repair frequently experience healing failures, compromised function, and chronic degenerative diseases. The identification of biomarkers to guide improved clinical outcomes after CT injuries remains an emerging but promising field. [Figure: see text] [Figure: see text] Design: Systematic review. Data sources: Databases, including PubMed, MEDLINE Ovid, Web of Science, and Google Scholar, were searched up to August 2024. Eligibility criteria: To achieve the research objective, randomized control trials, cohort studies, and case-control studies on biomarkers associated with CT repair and healing outcomes were selected. The present analysis was confined to clinical and preclinical models, excluding imaging studies. The entire process of this systematic review adhered strictly to the guidelines outlined in the Preferred Reporting Items for Systematic Review and Meta-Analyses protocol checklist. Results: A total of 1,815 studies on biomarkers of CT repair were initially identified, with 75 studies meeting eligibility criteria and 55 passing quality assessments. For biomarkers associated with CT healing outcomes, 281 studies were considered, with 30 studies meeting eligibility criteria and 24 passing quality assessments. Twenty-one overlapping studies investigated the effects of biomarkers on both CT repair and healing outcomes. Specific biomarkers identified, and ranked from highest to lowest quality, include complement factor D, eukaryotic elongation factor-2, procollagen type I N-terminal propetide, procollagen type III N-terminal propetide, lactate, pyruvate, platelet-derived growth factor-BB, tissue inhibitor of metalloproteinase-3 (TIMP-3), cysteine-rich protein-1, plastin-3, periostin, protein S100-A11, vimentin, matrix metalloproteinases (MMP-2, MMP-7, and MMP-9), hepatocyte growth factor, interferon-γ, interleukins (IL-6, IL-8, and IL-10), MMP-1, MMP-3, tumor necrosis factor-α, fibroblast growth factor-2, IL-1α, chondroitin-6-sulfate, inter-alpha-trypsin inhibitor heavy chain-4, transforming growth factor-beta 1, vascular endothelial growth factor, C-C chemokine receptor 7, C-C chemokine ligand 19, IL-1β, IL-1Ra, IL-12p40, granulocyte-macrophage colony-stimulating factor (GM-CSF), and TIMP-1. Conclusions: All of the 37 identified potential biomarkers demonstrated regulatory effects on CT repair and mediated healing outcomes. Notably, the identified biomarkers from human studies can potentially play an essential role in the development of targeted treatment protocols to counteract compromised healing and can also serve as predictors for detecting CT healing processes and long-term outcomes.

Growth factors that drive aggrecan synthesis in healthy articular cartilage. Role for transforming growth factor-β?

Introduction

Articular cartilage makes smooth movement possible and destruction of this tissue leads to loss of joint function. An important biomolecule that determines this function is the large aggregating proteoglycan of cartilage, aggrecan. Aggrecan has a relatively short half-life in cartilage and therefore continuous production of this molecule is essential.

Methods

In this narrative review we discuss what is the role of growth factors in driving the synthesis of aggrecan in articular cartilage. A literature search has been done using the search items; cartilage, aggrecan, explant, Transforming Growth factor-β (TGF-β), Insulin-like Growth Factor (IGF), Bone Morphogenetic Protein (BMP) and the generic term "growth factors". Focus has been on studies using healthy cartilage and models of cartilage regeneration have been excluded.

Results

In healthy adult articular cartilage IGF is the main factor that drives aggrecan synthesis and maintains adequate levels of production. BMP's and TGF-β have a very limited role but appear to be more important during chondrogenesis and cartilage development. The major role of TGF-β is not stimulation of aggrecan synthesis but maintenance of the differentiated articular cartilage chondrocyte phenotype.

Conclusion

TGF-β is a factor that is generally considered as an important factor in stimulating aggrecan synthesis in cartilage but its role in this might be very restrained in healthy, adult articular cartilage.

Preoperative Synovial Tissue and Synovial Fluid Biomarkers as Predictors for Outcomes After Knee Arthroscopy and ACL Reconstruction: A Narrative Review

BACKGROUND

Biomarkers collected in synovial tissue and fluid have been identified as potential predictors of outcomes after arthroscopy.

PURPOSE

To provide a narrative review of the current literature that assesses the associations between preoperative biomarkers in the synovial fluid or synovial tissue and patient outcomes after knee arthroscopy.

STUDY DESIGN

Narrative review.

METHODS

We searched the PubMed database with keywords, "biomarkers AND arthroscopy," "biomarkers AND anterior cruciate ligament reconstruction," and "biomarkers AND meniscectomy." To be included, studies must have collected synovial fluid or synovial tissue from patients before or during arthroscopic knee surgery and analyzed the relationship of biomarkers to postoperative patient outcomes. Biomarkers were classified into 4 main categories: metabolism of aggrecan in cartilage, metabolism of collagen in cartilage (type II collagen), noncollagenous proteins in the knee, and other. When biomarker levels and outcomes were expressed with continuous variables, we abstracted the Pearson or Spearman correlation coefficients as the effect measure. If the biomarker values were continuous and the outcomes binary, we abstracted the mean or median biomarker values in those with favorable versus unfavorable outcomes. We calculated effect sizes as the difference between means of both groups divided by the standard deviation from the mean in the group with better outcomes.

RESULTS

Eight studies were included in the review. Each study reported different patient outcomes. Biomarkers associated with metabolism of aggrecan, type II collagen metabolism, and noncollagenous proteins as well as inflammatory biomarkers had statistically significant associations with a range of patient outcomes after knee arthroscopy. Difference across studies in sample size and outcome measures precluded choosing a single biomarker that best predicted patient outcomes.

CONCLUSION

The findings suggest that biomarkers associated with metabolism of aggrecan, type II collagen metabolism, noncollagenous proteins, as well as inflammatory biomarkers may help surgeons and their patients anticipate surgical outcomes.

Molecular Biology of Meniscal Healing: A Narrative Review

This review provides insights at the molecular level into the current and old methods for treating meniscal injuries. Meniscal injuries have been found to have a substantial impact on the progression of osteoarthritis. In line with the "save the meniscus" approach, meniscectomy is considered a last-resort treatment. Nevertheless, it is important to note that mechanical repair alone may not achieve the complete restoration of the meniscus. A deep understanding of the healing pathways could lead to future improvements in meniscal healing. The inclusion of cytokines and chemokines has the potential to facilitate the process of tear repair or impede the inflammatory catabolic cascade. MicroRNA (miRNA) could serve as a potential biomarker for meniscal degeneration, and RNA injections might promote collagen and growth factor production. The critical aspect of the healing process is angiogenesis within the inner zone of the meniscus. The use of collagen scaffolds and the implantation of autologous meniscus fragments have been successfully integrated into clinical settings. These findings are encouraging and underscore the need for well-designed clinical trials to explore the most effective factors that can enhance the process of meniscal repair.

The Interplay of Biomechanical and Biological Changes Following Meniscus Injury

PURPOSE OF REVIEW

Meniscus injury often leads to joint degeneration and post-traumatic osteoarthritis (PTOA) development. Therefore, the purpose of this review is to outline the current understanding of biomechanical and biological repercussions following meniscus injury and how these changes impact meniscus repair and PTOA development. Moreover, we identify key gaps in knowledge that must be further investigated to improve meniscus healing and prevent PTOA.

RECENT FINDINGS

Following meniscus injury, both biomechanical and biological alterations frequently occur in multiple tissues in the joint. Biomechanically, meniscus tears compromise the ability of the meniscus to transfer load in the joint, making the cartilage more vulnerable to increased strain. Biologically, the post-injury environment is often characterized by an increase in pro-inflammatory cytokines, catabolic enzymes, and immune cells. These multi-faceted changes have a significant interplay and result in an environment that opposes tissue repair and contributes to PTOA development. Additionally, degenerative changes associated with OA may cause a feedback cycle, negatively impacting the healing capacity of the meniscus. Strides have been made towards understanding post-injury biological and biomechanical changes in the joint, their interplay, and how they affect healing and PTOA development. However, in order to improve clinical treatments to promote meniscus healing and prevent PTOA development, there is an urgent need to understand the physiologic changes in the joint following injury. In particular, work is needed on the in vivo characterization of the temporal biomechanical and biological changes that occur in patients following meniscus injury and how these changes contribute to PTOA development.