Volume 14, Issue 55 (6-2024)
NCMBJ 2024, 14(55): 73-82 |
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Gholipour A, Bagheri Moghaddam M, Malakootian M, Oveisee M. Bioinformatics analyzing of genes expression alterations in peripheral blood monocyte cells of osteoarthritis patients. NCMBJ 2024; 14 (55) :73-82
URL: http://ncmbjpiau.ir/article-1-1683-en.html
URL: http://ncmbjpiau.ir/article-1-1683-en.html
Orthopedic Department, Bam University of Medical Sciences, Bam, Iran , Maziar.oveisee@gmail.com
Abstract: (152 Views)
Aim and Background: Osteoarthritis (OA) is the most common chronic joint disease in the world and the main cause of movement disorders in the elderly. Identification the precise molecular pathogenesis pathways of osteoarthritis disease, early diagnosis and effective treatment for OA is challenging because OA pathogenesis is still unclear. Therefore, one of the key and important goals of OA disease is to identify sensitive biomarkers, which is very valuable and effective for clinical applications, considering the availability of peripheral blood samples. The present study aimed to find differential expression genes in peripheral blood mononuclear cells (PBMCs) of OA patients and introduced a reliable biomarker to distinguish OA via bioinformatics analysis.
Material and methods: The microarray dataset of PBMCs of OA patients and normal individuals (GSE48556) was obtained from the GEO database. Differential expression analysis between OA and normal groups was performed using GEO2R and genes with differential expression were isolated. Signaling pathways and GO analysis were determined using Enrichr databases. Next, genes with differential expression were introduced and ROC curve analysis was performed for analysis the probability of the selected gene as a biomarker.
Results: The bioinformatics results showed 1515 genes had significant differential expression which 657 genes upregulated and 858 gens downregulated. Analysis of signaling pathways showed that proteasome pathways, chemokine signaling pathway and FoxO signaling pathway are important in this disease. It was also found that the SRSF10 gene has the most downregulation in OA patients and the ROC curve analysis showed that this gene can differentiate OA patients from healthy individuals with high sensitivity and specificity.
Conclusion: Overall, our data demonstrated that the differential genes expressions have potentially to be considered as biological biomarkers with diagnostic and therapeutic target approaches. In this regard, the reduction of SRSF10 gene expression can probably be a biomarker to identify OA disease in PBMC cells, which should be confirmed in experimental analysis.
Material and methods: The microarray dataset of PBMCs of OA patients and normal individuals (GSE48556) was obtained from the GEO database. Differential expression analysis between OA and normal groups was performed using GEO2R and genes with differential expression were isolated. Signaling pathways and GO analysis were determined using Enrichr databases. Next, genes with differential expression were introduced and ROC curve analysis was performed for analysis the probability of the selected gene as a biomarker.
Results: The bioinformatics results showed 1515 genes had significant differential expression which 657 genes upregulated and 858 gens downregulated. Analysis of signaling pathways showed that proteasome pathways, chemokine signaling pathway and FoxO signaling pathway are important in this disease. It was also found that the SRSF10 gene has the most downregulation in OA patients and the ROC curve analysis showed that this gene can differentiate OA patients from healthy individuals with high sensitivity and specificity.
Conclusion: Overall, our data demonstrated that the differential genes expressions have potentially to be considered as biological biomarkers with diagnostic and therapeutic target approaches. In this regard, the reduction of SRSF10 gene expression can probably be a biomarker to identify OA disease in PBMC cells, which should be confirmed in experimental analysis.
Type of Study: Research Article |
Subject:
Physiology
Received: 2024/08/13 | Accepted: 2024/06/30 | Published: 2024/06/30
Received: 2024/08/13 | Accepted: 2024/06/30 | Published: 2024/06/30
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