Difference Between Rheumatoid Arthritis And Osteoarthritis Pdf
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- Difference Between Osteoarthritis and Rheumatoid Arthritis
- Osteoarthritis vs. Rheumatoid Arthritis
- What's the difference between rheumatoid arthritis and osteoarthritis?
- Explain the pain – Is it osteoarthritis or rheumatoid arthritis?
Difference Between Osteoarthritis and Rheumatoid Arthritis
This is an open access article distributed under the terms of Creative Commons Attribution License. Rheumatoid arthritis RA and osteoarthritis OA are the two most frequent types of degenerative joint diseases and exhibit similar etiology 1 , 2.
RA is a complex, chronic inflammatory and autoimmune arthritis that typically causes pain, swelling, stiffness and loss of function in the joints 1. It has been estimated that RA affects 0. RA has become one of the most common causes of reduced productivity and disability in affected patients and may additionally pose a substantial financial burden on the family of the patient as well as society 5.
RA manifests as osteoporosis around the joint and joint space narrowing in the knees of patients 6. The bone anatomy degeneration and cystic degeneration of the bone joint surface may additionally occur with bone defects 7. During RA, the intercondylar fossa is enlarged and the tibial plateau sinks 8 , 9. Patients with late-stage RA may suffer from articular surface sclerosis, joint subluxation or joint stiffness Furthermore, OA, the most prevalent form of arthritis worldwide, is a multi-gene and multi-factorial disease, and is characterized by cartilage degeneration and subchondral bone alterations, involving synovial tissue and articular cartilage 10 — OA may reduce the quality of life for patients and eventually lead to disability due to pain.
The joint most commonly affected by OA is the knee 8. Similar to RA, OA additionally has an increased occurrence rate in older adults, particularly in women.
RA and OA exhibit overlapping symptoms, making differential diagnosis particularly challenging. In addition, differentiation between RA and OA is difficult in late-stage cases, primarily because disease progression frequently begins prior to the onset of symptoms. Therefore, accurate diagnosis of RA and OA may significantly improve the clinical outcomes and prognosis for affected patients.
However, the mechanisms underlying the initiation and progression of RA and OA remain unclear. Previously, important genes and diagnostic markers that interact with each other and with environmental and stochastic factors have been identified in the two diseases However, these markers may not entirely elucidate the complex pathogenesis of RA and OA.
Therefore, the present study aimed to investigate the developmental differences between RA and OA. An updated comprehensive analysis was performed to identify the potential novel biomarkers associated with synovial tissues obtained from patients with RA and OA.
In the present study, three multicenter genome-wide transcriptomic datasets, including 33 patients with RA and 26 patients with OA were retrieved and analyzed. The present study aimed to investigate the different mechanisms underlying the differential pathogenesis of RA and OA, and thus improve the diagnosis and treatment strategies available for patients suffering from the two diseases in clinical practice.
Datasets were included if they met the following inclusion criteria: i were based on gene expression profiling of synovial membrane samples from the same platform. When the microarray datasets are obtained from the same platform, their homogeneity is usually good. Subsequent to screening OA-associated microarray datasets, the GPL96 platform was used at the highest frequency. Patients with RA were diagnosed and classified based on the American College of Rheumatology criteria 14 and patients with OA were classified according to X-ray evidence of osteoarthritis The probes with no gene annotation were excluded from the analysis.
The expression values of all probes for a given gene were calculated from the average expression value. To reduce the false positive rate, DEGs of the three datasets were identified, and subsequently Venn diagrams Venn 2. Furthermore, pathway network analysis may reveal the possible interactions and crosstalk among these pathways.
A network was constructed consisting of nodes and lines in which each node represents a protein and the lines represent direct interactions between proteins. The PPI network was constructed based on human data alone. The number of nodes that may interact with a given node was expressed as the degree of the node.
The greater the degree values of the included genes, the greater the degree in the whole network. Identification of genes that may affect the development of RA and OA within the genome may provide a comprehensive understanding of the differences between the pathogenesis of RA and OA. Following this, the whole PPI network was filtered using a degree-filtering approach to include the most critical biomarkers in the occurrence of the two diseases using Cytoscape 3.
The means of two continuous, normally distributed variables were compared by independent sample Student's t-tests. Mann-Whitney U tests were used to compare the means of two groups of variables not normally distributed.
Receiver Operating Characteristic ROC analysis was performed to identify a more accurate cut-off point in the gene expression level, which may aid the classification of RA and OA. ROC curves were generated by plotting the range of sensitivity true positive fractions and specificity false positive fractions pairs for each subject's error rate, with case status RA vs.
OA representing the classifier variable. Youden's index was used for capturing the performance of a dichotomous diagnostic test. The area under the ROC curve AUC , which provides an estimate of the accuracy of the diagnostic test for the discrimination between patients with RA and patients with OA, was used to assess the performance of the test.
Binary logistic regression using backward stepwise selection mode was performed to screen out potential biomarkers that were positively correlated with RA diagnosis when identified biomarkers were detected together. Following this, ROC analysis was performed to determine the performance of the established logistic regression models. DEGs were identified by the t-test statistical algorithm. Notably, 50 upregulated Fig. One DEG without a symbol was excluded from the upregulated DEGs, therefore 80 DEGs in total, containing 49 upregulated and 31 downregulated, were included in the final analysis.
The list of 80 DEG symbols is available upon request. Cytoscape 3. The results demonstrated that 80 overlapped DEGs were significantly enriched in immune, inflammation, apoptosis and antioxidant stress-associated functions and pathways. Top five biological functions and top ten KEGG pathways of the overlapped differentially expressed genes. A PPI network was constructed based on the biological interactions of the 80 identified DEGs to further elucidate their associations at the protein level.
As presented in Fig. PPI network analysis, Core network and Gene-pathway network. A PPI network of differentially expressed genes light red, upregulated; green, downregulated. B Core of the specific network affecting RA development. C Gene-pathway network associated with the development of RA.
Larger circles represent genes in the core network. In Cytoscape 3. RA, rheumatoid arthritis; PPI, protein-protein interaction. This approach included maximal members of candidate genes with the minimal interaction associations. To identify the most important core network, networks were filtered according to their degree using the degree-filtering approach. Receiver operating characteristic curves of the six genes in the core network to distinguish rheumatoid arthritis from osteoarthritis using data from the GSE, GSE and GSE datasets.
Optimal cut-off points and associated diagnostic values of six genes in the core network as determined by receiver operator characteristic analysis. Binary logistic regression results of the core network for rheumatoid arthritis diagnosis.
To investigate the reliability of the results of the ROC analyses obtained from all the three datasets and to identify if there was any possible overlapping between them, the same ROC analysis, including data from the GSE dataset was performed, and the results are presented in Fig. Notably, it was demonstrated that the six genes in the core network exhibited good performance in distinguishing RA from OA. In addition, the AUCs of genes identified in the GSE dataset were increased compared with the results obtained from the aforementioned three datasets.
In conclusion, the results suggested that the results obtained from the GSE dataset were closely associated with those obtained from the GSE, GSE and GSE datasets, which further confirmed the reliability of the aforementioned results. Receiver operating characteristic curves of the six genes in the core network to investigate the differentiation between rheumatoid arthritis and osteoarthritis using data from the GSE dataset.
RA and OA are the most common forms of degenerative joint diseases. They are the leading cause of chronic disability and may exhibit common clinical etiology 23 , However, there remains a paucity of studies investigating the sensitivity and specificity of detection indicators for identification of the two diseases, particularly for patients with advanced-stage RA or OA.
Recently, epigenetic dysregulation of cartilage genes has been demonstrated to have an important role in RA and OA development Despite advances in the field, biomarkers associated with the pathogenesis and progression of RA and OA are not well characterized. Therefore, investigation of the gene signatures associated with disease development in RA and OA may elucidate the molecular mechanisms underlying pathogenesis and identify potential therapeutic strategies for the development of a biomarker of differential diagnosis.
In previous years, bioinformatics has had an increasingly important role in examining the pathogenesis of multifactorial disorders In the present study, a comprehensive and systematic bioinformatics analysis of three gene expression profile datasets identified 80 significant DEGs, including 49 upregulated and 31 downregulated genes that may be associated with the development of RA and OA.
These results suggested that alterations in gene expression profiles in synovial tissue may affect the development of RA and OA. Therefore, detailed analysis of the biological functions of the DEGs may be utilized to further understand the pathogenesis of the two diseases and may additionally reveal biomarkers for more accurate identification of RA and OA. A previous study demonstrated that RA development may depend on a common alteration in the expression pattern of specific key genes 26 , which was consistent with the results of the present study.
Numerous previous studies have identified specific genes associated with RA development. Microarray analysis has additionally identified disease spectrum features in rheumatology and identified additional genes that may be associated with RA 28 , Biswas et al 30 identified a number of different biomarkers, genes and pathways, the majority of which have not been revealed in other studies.
Differential diagnoses of RA and OA remain clinically challenging due to substantial etiological similarities Microarray experiments performed by Wang et al 31 identified an overview of differences in OA gene expression compared with healthy patients and identified 85 DEGs.
In conclusion, these studies suggested that RA and OA have complex pathogenic mechanisms, and future studies should perform comprehensive and systematic analyses to further elucidate these mechanisms. A constructed PPI network additionally demonstrated that RA progression was associated with immunodeficiency. RA has been well established to represent a progressive, chronic, inflammatory and destructive joint disease 2. These results were based on three high throughput microarray datasets with multi-center design and containing large sample numbers of synovial tissue, which may provide further evidence for future research.
To confirm this inference, a more complete and specific biological network based on GeneMANIA was determined, from which a core network of candidate genes that may affect RA and OA development was obtained.
Furthermore, the fact that the core network was closely aligned with the constructed PPI network further suggested that the six genes in the core network are involved in the occurrence and development of RA and OA. To further investigate how these genes exhibit their biological function and affect the occurrence of RA, a gene-pathway interaction network was constructed. Primary immunodeficiencies are a heterogeneous group of disorders that cause increased susceptibility to infection, autoimmune disease and malignancy Investigation of the diagnostic capacity to distinguish RA from OA suggested that the genes in the core network may be detected alone to predict and diagnose RA occurrence with high sensitivity and specificity; however, the combined detection of important indicators may improve the effectiveness of this diagnostic strategy.
A previous study identified that STAT1 is important in RA occurrence and is upregulated in patients with RA 34 , which corroborates the results of the present study. STAT1 has been widely regarded to represent an important transcription factor involved in joint inflammation and destruction 33 ,
Osteoarthritis vs. Rheumatoid Arthritis
Rheumatoid arthritis and osteoarthritis are different types of arthritis. They share some similar characteristics, but each has different symptoms and requires different treatment. So an accurate diagnosis is important. Osteoarthritis is the most common form of arthritis. Rheumatoid arthritis affects about one-tenth as many people as osteoarthritis. The main difference between osteoarthritis and rheumatoid arthritis is the cause behind the joint symptoms.
This is an open access article distributed under the terms of Creative Commons Attribution License. Rheumatoid arthritis RA and osteoarthritis OA are the two most frequent types of degenerative joint diseases and exhibit similar etiology 1 , 2. RA is a complex, chronic inflammatory and autoimmune arthritis that typically causes pain, swelling, stiffness and loss of function in the joints 1. It has been estimated that RA affects 0. RA has become one of the most common causes of reduced productivity and disability in affected patients and may additionally pose a substantial financial burden on the family of the patient as well as society 5. RA manifests as osteoporosis around the joint and joint space narrowing in the knees of patients 6.
Erosive OA EOA shows increased synovial thickening, rarely associated with PD features never found in patients with non-inflammatory joint pain. We compared the joint score of the hand including wrist, MCP and PIP joints with smaller, predefined joint scores, including 20, 18, 16, 14 and 10 and two sets of 4-joint for RA and scoring systems comprising 20, 12, 10 and 4 joints for OA. Results: In the joint system, OA patients [mean age When comparing OA joint scores, the joint score was the most comprehensive in assessing changes compared with the scores from 12, 10 or 4 joints. Interestingly, some OA joints were also characterized by inflammatory changes. The effectiveness of using smaller joint scores in RA may benefit time-constrained clinical settings.
What's the difference between rheumatoid arthritis and osteoarthritis?
Arthritis is a broad term for joint inflammation, but there are many kinds, starting with the two most common: osteoarthritis OA and rheumatoid arthritis RA. Learn more about how to tell these two chronic conditions apart. OA is the breakdown of a joint, says Bill Robinson, M.
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Arthritis is an umbrella term used to describe inflammation of the joints. However, there are different kinds of arthritis, including rheumatoid arthritis RA and osteoarthritis OA.
Explain the pain – Is it osteoarthritis or rheumatoid arthritis?
Rheumatoid arthritis and osteoarthritis both cause joint pain and stiffness. They are both forms of arthritis but have different causes and treatments. There are over types of arthritis and related diseases. Two of the most common types are rheumatoid arthritis RA and osteoarthritis OA.
If opening jars becomes more difficult because of painful hands, or if climbing stairs produces pain in your knees, "arthritis" is often the first thing that comes to mind. The two most common forms of arthritis—osteoarthritis and rheumatoid arthritis—can cause similar aches and pains, but there are a few key differences between them. For example:. Osteoarthritis occurs when cartilage tissue in your joints that cushions your bones wears away. Pain occurs when bone rubs against bone. This type of arthritis pain tends to develop gradually and intermittently over several months or years. Osteoarthritis is the most common type of arthritis affecting 27 million Americans.