Meta-analysis Integrated With Multi-omics Data Analysis to Elucidate Pathogenic Mechanisms of Age-Related Knee Osteoarthritis in Mice

Geroscience and pathology: a new frontier in understanding age-related diseases

Geroscience, a burgeoning discipline at the intersection of aging and disease, aims to unravel the intricate relationship between the aging process and pathogenesis of age-related diseases. This paper explores the pivotal role played by geroscience in reshaping our understanding of pathology, with a particular focus on age-related diseases. These diseases, spanning cardiovascular and cerebrovascular disorders, malignancies, and neurodegenerative conditions, significantly contribute to the morbidity and mortality of older individuals. We delve into the fundamental cellular and molecular mechanisms underpinning aging, including mitochondrial dysfunction and cellular senescence, and elucidate their profound implications for the pathogenesis of various age-related diseases. Emphasis is placed on the importance of assessing key biomarkers of aging and biological age within the realm of pathology. We also scrutinize the interplay between cellular senescence and cancer biology as a central area of focus, underscoring its paramount significance in contemporary pathological research. Moreover, we shed light on the integration of anti-aging interventions that target fundamental aging processes, such as senolytics, mitochondria-targeted treatments, and interventions that influence epigenetic regulation within the domain of pathology research. In conclusion, the integration of geroscience concepts into pathological research heralds a transformative paradigm shift in our understanding of disease pathogenesis and promises breakthroughs in disease prevention and treatment.

Network-based cytokine inference implicates Oncostatin M as a driver of an inflammation phenotype in knee osteoarthritis

Inflammatory cytokines released by synovium after trauma disturb the gene regulatory network and have been implicated in the pathophysiology of osteoarthritis. A mechanistic understanding of how aging perturbs this process can help identify novel interventions. Here, we introduced network paradigms to simulate cytokine-mediated pathological communication between the synovium and cartilage. Cartilage-specific network analysis of injured young and aged murine knees revealed aberrant matrix remodeling as a transcriptomic response unique to aged knees displaying accelerated cartilage degradation. Next, network-based cytokine inference with pharmacological manipulation uncovered IL6 family member, Oncostatin M (OSM), as a driver of the aberrant matrix remodeling. By implementing a phenotypic drug discovery approach, we identified that the activation of OSM recapitulated an "inflammatory" phenotype of knee osteoarthritis and highlighted high-value targets for drug development and repurposing. These findings offer translational opportunities targeting the inflammation-driven osteoarthritis phenotype.

How is Big Data reshaping preclinical aging research?

The exponential scientific and technological progress during the past 30 years has favored the comprehensive characterization of aging processes with their multivariate nature, leading to the advent of Big Data in preclinical aging research. Spanning from molecular omics to organism-level deep phenotyping, Big Data demands large computational resources for storage and analysis, as well as new analytical tools and conceptual frameworks to gain novel insights leading to discovery. Systems biology has emerged as a paradigm that utilizes Big Data to gain insightful information enabling a better understanding of living organisms, visualized as multilayered networks of interacting molecules, cells, tissues and organs at different spatiotemporal scales. In this framework, where aging, health and disease represent emergent states from an evolving dynamic complex system, context given by, for example, strain, sex and feeding times, becomes paramount for defining the biological trajectory of an organism. Using bioinformatics and artificial intelligence, the systems biology approach is leading to remarkable advances in our understanding of the underlying mechanism of aging biology and assisting in creative experimental study designs in animal models. Future in-depth knowledge acquisition will depend on the ability to fully integrate information from different spatiotemporal scales in organisms, which will probably require the adoption of theories and methods from the field of complex systems. Here we review state-of-the-art approaches in preclinical research, with a focus on rodent models, that are leading to conceptual and/or technical advances in leveraging Big Data to understand basic aging biology and its full translational potential.

Uncovering the "riddle of femininity" in osteoarthritis: a systematic review and meta-analysis of menopausal animal models and mathematical modeling of estrogen treatment

OBJECTIVE

Post-menopausal women are disproportionately affected by osteoarthritis (OA). As such, the purpose of this study was to (1) summarize the state-of-the-science aimed at understanding the effects of menopause on OA in animal models and (2) investigate how dosage and timing of initiation of estrogen treatment affect cartilage degeneration.

DESIGN

A systematic review identified articles studying menopausal effects on cartilage in preclinical models. A meta-analysis was performed using overlapping cartilage outcomes in conjunction with a rigor and reproducibility analysis. Ordinary differential equation models were used to determine if a relationship exists between cartilage degeneration and the timing of initiation or dosage of estrogen treatment.

RESULTS

Thirty-eight manuscripts were eligible for inclusion. The most common menopause model used was ovariectomy (92%), and most animals were young at the time of menopause induction (86%). Most studies did not report inclusion criteria, animal monitoring, protocol registration, or data accessibility. Cartilage outcomes were worse in post-menopausal animals compared to age-matched, non-menopausal animals, as evidenced by cartilage histological scoring [0.75, 1.72], cartilage thickness [-4.96, -0.96], type II collagen [-4.87, -0.56], and c-terminal cross-linked telopeptide of type II collagen (CTX-II) [2.43, 5.79] (95% CI of Effect Size (+greater in menopause, -greater in non-menopause)). Moreover, modeling suggests that cartilage health may be improved with early initiation and higher doses of estrogen treatment.

CONCLUSIONS

To improve translatability, animal models that consider aging and natural menopause should be utilized, and more attention to rigor and reproducibility is needed. Timing of initiation and dosage may be important factors modulating therapeutic effects of estrogen on cartilage.

Age-related matrix stiffening epigenetically regulates α-Klotho expression and compromises chondrocyte integrity

Extracellular matrix stiffening is a quintessential feature of cartilage aging, a leading cause of knee osteoarthritis. Yet, the downstream molecular and cellular consequences of age-related biophysical alterations are poorly understood. Here, we show that epigenetic regulation of α-Klotho represents a novel mechanosensitive mechanism by which the aged extracellular matrix influences chondrocyte physiology. Using mass spectrometry proteomics followed by a series of genetic and pharmacological manipulations, we discovered that increased matrix stiffness drove Klotho promoter methylation, downregulated Klotho gene expression, and accelerated chondrocyte senescence in vitro. In contrast, exposing aged chondrocytes to a soft matrix restored a more youthful phenotype in vitro and enhanced cartilage integrity in vivo. Our findings demonstrate that age-related alterations in extracellular matrix biophysical properties initiate pathogenic mechanotransductive signaling that promotes Klotho promoter methylation and compromises cellular health. These findings are likely to have broad implications even beyond cartilage for the field of aging research.

Osteoarthritis gene therapy in 2022

PURPOSE OF REVIEW

To assess the present status of gene therapy for osteoarthritis (OA).

RECENT FINDINGS

An expanding list of cDNAs show therapeutic activity when introduced into the joints of animals with experimental models of OA. In vivo delivery with adenovirus or adeno-associated virus is most commonly used for this purpose. The list of encoded products includes cytokines, cytokine antagonists, enzymes, enzyme inhibitors, growth factors and noncoding RNA. Elements of CRISPR-Cas have also been delivered to mouse knees to ablate key genes. Several human trials have been initiated, using transgenes encoding transforming growth factor-β1, interleukin-1 receptor antagonist, interferon-β, the NKX3.2 transcription factor or variant interleukin-10. The first of these, using ex vivo delivery with allogeneic chondrocytes, gained approval in Korea which was subsequently retracted. However, it is undergoing Phase III clinical trials in the United States. The other trials are in Phase I or II. No gene therapy for OA has current marketing approval in any jurisdiction.

SUMMARY

Extensive preclinical data support the use of intra-articular gene therapy for treating OA. Translation is beginning to accelerate and six gene therapeutics are in clinical trials. Importantly, venture capital has begun to flow and at least seven companies are developing products. Significant progress in the future can be expected.