| Abstrakt: |
Background: Osteoarthritis (OA) is a common degenerative joint disease that poses a significant global healthcare challenge due to its complexity and limited treatment options. Advances in metabolomics have provided insights into OA by identifying dysregulated metabolites and their connection to altered signaling pathways. However, a comprehensive understanding of these biomarkers in OA is still required. Objectives: This systematic review aims to identify metabolomics biomarkers associated with dysregulated signaling pathways in OA, using data from various biological samples, including in vitro models, animal studies, and human research. Design: A systematic review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Data sources and methods: Data were gathered from literature published between August 2017 and May 2024, using databases such as "PubMed," "Scopus," "Web of Science," and "Google Scholar." Studies were selected based on keywords like "metabolomics," "osteoarthritis," "amino acids," "molecular markers," "biomarkers," "diagnostic markers," "inflammatory cytokines," "molecular signaling," and "signal transduction." The review focused on identifying key metabolites and their roles in OA-related pathways. Limitations include the potential exclusion of studies due to keyword selection and strict inclusion criteria. Results: The meta-analysis identified dysregulated metabolites and associated pathways, highlighting a distinct set of related metabolites consistently altered across the studies analyzed. The dysregulated metabolites, including amino acids, lipids, and carbohydrates, were found to play critical roles in inflammation, oxidative stress, and energy metabolism in OA. Metabolites such as alanine, lysine, and proline were frequently linked to pathways involved in inflammation, cartilage degradation, and apoptosis. Key pathways, including nuclear factor kappa B, mitogen-activated protein kinase, Wnt/β-catenin, and mammalian target of rapamycin, were associated with changes in metabolite levels, particularly in proinflammatory lipids and energy-related compounds. Conclusion: This review reveals a complex interplay between dysregulated metabolites and signaling pathways in OA, offering potential biomarkers and therapeutic targets. Further research is needed to explore the molecular mechanisms driving these changes and their implications for OA treatment. Plain language summary: Understanding how altered metabolites and signaling pathways contribute to osteoarthritis: a comprehensive review Aims and purpose of the research Research question: The main question we are exploring is how certain chemicals in the body, called metabolites, are linked to signaling pathways in osteoarthritis (OA). Hypotheses/Expectations: Before starting this review, we expected that specific metabolites would be connected to the processes that cause OA, like inflammation and cartilage tissue breakdown. Objective: Our goal is to identify these metabolites and understand how they interact with signaling pathways in OA. We aim to gather data from various sources, including laboratory experiments, animal studies, and human clinical studies. Background of the research Why this question matters: Osteoarthritis is a common and painful condition that affects the joints, making it hard for people to move and perform everyday tasks. There are not many effective treatments available, which is why it's important to study this disease in depth. By understanding the metabolic changes that occur in OA, we might find new ways to treat it. Scale of issue: Osteoarthritis affects millions of people around the world. It is a leading cause of disability and significantly impacts the quality of life of those who suffer from it. The high prevalence and limited treatment options make it a major public health issue. Methods and research design Research design: We conducted a systematic review of scientific literature published between August 2017 and May 2024. This means we carefully collected and analyzed all relevant studies available in major databases like PubMed, Scopus, Web of Science, and Google Scholar. We followed strict guidelines (PRISMA) to ensure our review was thorough and unbiased. Key variables: The key variables in our study were different types of metabolites, such as amino acids, lipids, and carbohydrates, and their association with signaling pathways known to be involved in OA, like NFκB, MAPK, Wnt/β-catenin, and mTOR. Participants: Our data came from a var. [ABSTRACT FROM AUTHOR] |
