The future of deep phenotyping in osteoarthritis: How can high throughput omics technologies advance our understanding of the cellular and molecular taxonomy of the disease?

Inhibition of TLR4 signalling to dampen joint inflammation in osteoarthritis

Local and systemic low-grade inflammation, mainly involving the innate immune system, plays an important role in the development of OA. A receptor playing a key role in initiation of this inflammation is the pattern-recognition receptor Toll-like receptor 4 (TLR4). In the joint, various ligands for TLR4, many of which are damage-associated molecular patterns (DAMPs), are present that can activate TLR4 signalling. This leads to the production of pro-inflammatory and catabolic mediators that cause joint damage. In this narrative review, we will first discuss the involvement of TLR4 ligands and signalling in OA. Furthermore, we will provide an overview of methods for inhibit, TLR4 signalling by RNA interference, neutralizing anti-TLR4 antibodies, small molecules and inhibitors targeting the TLR4 co-receptor MD2. Finally, we will focus on possible applications and challenges of these strategies in the dampening of inflammation in OA.

Pain-phenotyping in osteoarthritis: Current concepts, evidence, and considerations towards a comprehensive framework for assessment and treatment

Objectives

Pain as central symptom of osteoarthritis (OA) needs to be addressed as part of successful treatment. The assessment of pain as feature of disease or outcome in clinical practice and drug development remains a challenge due to its multidimensionality and the plethora of confounders. This article aims at providing insights into our understanding of OA pain-phenotypes and suggests a framework for systematic and comprehensive assessments.

Methods

This narrative review is based on a search of current literature for various combinations of the search terms "pain-phenotype" and "knee OA" and summarizes current knowledge on OA pain-phenotypes, putting OA pain and its assessment into perspective of current research efforts.

Results

Pain is a complex phenomenon, not necessarily associated with tissue damage. Various pain-phenotypes have been described in knee OA. Among those, a phenotype with high pain levels not necessarily matching structural changes and a phenotype with low pain levels and impact are relatively consistent. Further subgroups can be differentiated based on patient reported outcome measures, assessments of comorbidities, anxiety and depression, sleep, activity and objective measures such as quantitative sensory testing.

Conclusions

The complexity of both OA as disease and pain in OA prompt the definition of a set of variables that facilitate assessments comparable across studies to maximize our understanding of pain, as central concern for the patient.

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.

From biochemical markers to molecular endotypes of osteoarthritis: a review on validated biomarkers

INTRODUCTION

Osteoarthritis (OA) affects over 500 million people worldwide. OA patients are symptomatically treated, and current therapies exhibit marginal efficacy and frequently carry safety-risks associated with chronic use. No disease-modifying therapies have been approved to date leaving surgical joint replacement as a last resort. To enable effective patient care and successful drug development there is an urgent need to uncover the pathobiological drivers of OA and how these translate into disease endotypes. Endotypes provide a more precise and mechanistic definition of disease subgroups than observable phenotypes, and a panel of tissue- and pathology-specific biochemical markers may uncover treatable endotypes of OA.

AREAS COVERED

We have searched PubMed for full-text articles written in English to provide an in-depth narrative review of a panel of validated biochemical markers utilized for endotyping of OA and their association to key OA pathologies.

EXPERT OPINION

As utilized in IMI-APPROACH and validated in OAI-FNIH, a panel of biochemical markers may uncover disease subgroups and facilitate the enrichment of treatable molecular endotypes for recruitment in therapeutic clinical trials. Understanding the link between biochemical markers and patient-reported outcomes and treatable endotypes that may respond to given therapies will pave the way for new drug development in OA.

Endoscopic and morphological features of chronic gastritis in patients with lumbar spine osteochondrosis

OBJECTIVE

Aim: of the study is to determine the endoscopic and morphological features of chronic gastritis (CG) in patients with lumbar spinal OC.

PATIENTS AND METHODS

Materials and Methods: 102 patients with lumbar spine OC and CG were examined. The patients were diagnosed with Helicobacter pylori (HP) infection, according to which the patients were divided into two groups: the first group included 92 HP-positive patients, the second group consisted of 10 HP-negative patients.

RESULTS

Results: Among HP infected patients with lumbar spine OC, erosive gastropathy was most often diagnosed (in 40 (43.5%) of the examined), as well as erosive-papular and erosive-hemorrhagic gastropathy (in 14 (15.2%) and in 16 (17, 4 %) of patients, respectively), while erythematous gastropathy was more often diagnosed among HP-negative patients (in 7 (70.0 %) cases, respectively).

CONCLUSION

Conclusions: 1. 90.2% of patients with lumbar spine OC and CG have been diagnosed with HP infection. 2. Endoscopically, the lesion of the stomach MM in patients with lumbar spine OC corresponds mainly to erosive and erosive-hemorrhagic forms of gastropathy. 3. During histological examination of stomach MM, mainly 2nd and 3rd degrees of inflammation were established, especially in patients with erosive, erosive-papular and erosive-hemorrhagic forms of gastropathy.

MRI overestimates articular cartilage thickness and volume compared to synchrotron radiation phase-contrast imaging

Accurate evaluation of morphological changes in articular cartilage are necessary for early detection of osteoarthritis (OA). 3T magnetic resonance imaging (MRI) has highly sensitive contrast resolution and is widely used clinically to detect OA. However, synchrotron radiation phase-contrast imaging computed tomography (SR-PCI) can also provide contrast to tissue interfaces that do not have sufficient absorption differences, with the added benefit of very high spatial resolution. Here, MRI was compared with SR-PCI for quantitative evaluation of human articular cartilage. Medial tibial condyles were harvested from non-OA donors and from OA patients receiving knee replacement surgery. Both imaging methods revealed that average cartilage thickness and cartilage volume were significantly reduced in the OA group, compared to the non-OA group. When comparing modalities, the superior resolution of SR-PCI enabled more precise mapping of the cartilage surface relative to MRI. As a result, MRI showed significantly higher average cartilage thickness and cartilage volume, compared to SR-PCI. These data highlight the potential for high-resolution imaging of articular cartilage using SR-PCI as a solution for early OA diagnosis. Recognizing current limitations of using a synchrotron for clinical imaging, we discuss its nascent utility for preclinical models, particularly longitudinal studies of live animal models of OA.

Biomarkers for osteoarthritis: Current status and future prospects

Osteoarthritis (OA) is the most common form of arthritis globally and a major cause of pain, physical disability, and loss of economic productivity, with currently no causal treatment available. This review article focuses on current research on OA biomarkers and the potential for using biomarkers in future clinical practice and clinical trials of investigational drugs. We discuss how biomarkers, specifically soluble ones, have a long path to go before reaching clinical standards of care. We also discuss how biomarkers can help in phenotyping and subtyping to achieve enhanced stratification and move toward better-designed clinical trials. We also describe how biomarkers can be used for molecular endotyping and for determining the clinical outcomes of investigational cell-based therapies. Biomarkers have the potential to be developed as surrogate end points in clinical trials and help private-public consortia and the biotechnology and pharmaceutical industries develop more effective and targeted personalized treatments and enhance clinical care for patients with OA.

Use of machine learning in osteoarthritis research: a systematic literature review

Objective

The aim of this systematic literature review was to provide a comprehensive and exhaustive overview of the use of machine learning (ML) in the clinical care of osteoarthritis (OA).

Methods

A systematic literature review was performed in July 2021 using MEDLINE PubMed with key words and MeSH terms. For each selected article, the number of patients, ML algorithms used, type of data analysed, validation methods and data availability were collected.

Results

From 1148 screened articles, 46 were selected and analysed; most were published after 2017. Twelve articles were related to diagnosis, 7 to prediction, 4 to phenotyping, 12 to severity and 11 to progression. The number of patients included ranged from 18 to 5749. Overall, 35% of the articles described the use of deep learning And 74% imaging analyses. A total of 85% of the articles involved knee OA and 15% hip OA. No study investigated hand OA. Most of the studies involved the same cohort, with data from the OA initiative described in 46% of the articles and the MOST and Cohort Hip and Cohort Knee cohorts in 11% and 7%. Data and source codes were described as publicly available respectively in 54% and 22% of the articles. External validation was provided in only 7% of the articles.

Conclusion

This review proposes an up-to-date overview of ML approaches used in clinical OA research and will help to enhance its application in this field.

Unraveling the Signaling Secretome of Platelet-Rich Plasma: Towards a Better Understanding of Its Therapeutic Potential in Knee Osteoarthritis

Platelets and their secretory products play an important role in determining the balance between tissue repair and tissue damage. To obtain novel insights into the molecular composition of platelet-rich plasma (PRP) and contextualize them in knee osteoarthritis (OA), two different plasma formulations, namely PRP and platelet-poor plasma (PPP), were prepared from six healthy donors following a biobank-automated protocol. Inter-donor differences were analyzed, and pools were created before performing multiplexing protein arrays. In addition, PRP and PPP were prepared from six patients following our in-house protocols. Supernatants from PRP and PPP were harvested one hour after calcium chloride activation. Multiplexing protein arrays were performed in parallel for all plasma formulations. Results were normalized to fold change in relation to PPP and examined using Ingenuity Pathway Analysis Software. Bioinformatic predictions showed that PRPs constitute a signaling system with interrelated networks of inflammatory and angiogenic proteins, including but not limited to interleukin-6 and -8 (IL-6, IL-8), insulin like growth factor 1 (IGF-1), transforming growth factor beta, (TGF-b), and vascular endothelial growth factor (VEGF) signaling, underlying biological actions. Predictions of canonical systems activated with PRP molecules include various inflammatory pathways, including high-mobility group box protein (HMGB1) and interleukin 17 (IL-17) signaling, neuroinflammation, and nuclear factor-kappa b (NF-κB) pathways. Eventually, according to these predictions and OA evolving knowledge, selected PRP formulations should be tailored to modulate different inflammatory phenotypes, i.e., meta-inflammation, inflame-aging or posttraumatic inflammatory osteoarthritis. However, further research to discriminate the peculiarities of autologous versus allogeneic formulations and their effects on the various OA inflammatory phenotypes is needed to foster PRPs.