Identification of Pathways and Key Genes in Venous Remodeling After Arteriovenous Fistula by Bioinformatics Analysis

The arteriovenous fistula (AVF) is the first choice for vascular access for hemodialysis of renal failure patients. Venous remodeling after exposure to high fistula flow is important for AVF to mature but the mechanism underlying remodeling is still unknown. The objective of this study is to identify the molecular mechanisms that contribute to venous remodeling after AVF. To screen and identify the differentially expressed genes (DEGs) that may involve venous remodeling after AVF, we used bioinformatics to download the public microarray data (GSE39488) from the Gene Expression Omnibus (GEO) and screen for DEGs. We then performed gene ontology (GO) function analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and gene set enrichment analysis (GSEA) for the functional annotation of DEGs. The protein-protein interaction (PPI) network was constructed and the hub genes were carried out. Finally, we harvested 12 normal vein samples and 12 AVF vein samples which were used to confirm the expressions of the hub genes by immunohistochemistry. A total of 45 DEGs were detected, including 32 upregulated and 13 downregulated DEGs. The biological process (BP) of the GO analysis were enriched in the extrinsic apoptotic signaling pathway, cGMP-mediated pathway signaling, and molting cycle. The KEGG pathway analysis showed that the upregulated DEGs were enriched in glycosaminoglycan biosynthesis and purine metabolism, while the downregulated DEGs were mainly enriched in pathways of glycosaminoglycan biosynthesis, antifolate resistance, and ABC transporters. The GSEA analysis result showed that the top three involved pathways were oxidative phosphorylation, TNFA signaling via NF-K B, and the inflammatory response. The PPI was constructed and the hub genes found through the method of DMNC showed that INHBA and NR4A2 might play an important role in venous remodeling after AVF. The integrated optical density (DOI) examined by immunohistochemistry staining showed that the expression of both INHBA and NR4A2 increased in AVF compared to the control group. Our research contributes to the understanding of the molecular mechanism of venous remodeling after exposure to high fistula flow, which may be useful in treating AVF failure.

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Screening and Functional Prediction of Key Candidate Genes in Hepatitis B Virus-Associated Hepatocellular Carcinoma

BioMed Research International ◽

10.1155/2020/7653506 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13

Author(s):

Xia Chen ◽

Ling Liao ◽

Yuwei Li ◽

Hengliu Huang ◽

Qing Huang ◽

...

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Hepatitis B Virus ◽

Hepatitis B ◽

Pathway Analysis ◽

Kegg Pathway ◽

Metabolic Process ◽

Hub Genes ◽

Kegg Pathway Analysis ◽

B Virus

Background. The molecular mechanism by which hepatitis B virus (HBV) induces hepatocellular carcinoma (HCC) is still unknown. The genomic expression profile and bioinformatics methods were used to investigate the potential pathogenesis and therapeutic targets for HBV-associated HCC (HBV-HCC). Methods. The microarray dataset GSE55092 was downloaded from the Gene Expression Omnibus (GEO) database. The data was analyzed by the bioinformatics software to find differentially expressed genes (DEGs). Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, ingenuity pathway analysis (IPA), and protein-protein interaction (PPI) network analysis were then performed on DEGs. The hub genes were identified using Centiscape2.2 and Molecular Complex Detection (MCODE) in the Cytoscape software (Cytoscape_v3.7.2). The survival data of these hub genes was downloaded from the Gene Expression Profiling Interactive Analysis (GEPIA). Results. A total of 2264 mRNA transcripts were differentially expressed, including 764 upregulated and 1500 downregulated in tumor tissues. GO analysis revealed that these DEGs were related to the small-molecule metabolic process, xenobiotic metabolic process, and cellular nitrogen compound metabolic process. KEGG pathway analysis revealed that metabolic pathways, complement and coagulation cascades, and chemical carcinogenesis were involved. Diseases and biofunctions showed that DEGs were mainly associated with the following diseases or biological function abnormalities: cancer, organismal injury and abnormalities, gastrointestinal disease, and hepatic system disease. The top 10 upstream regulators were predicted to be activated or inhibited by Z-score and identified 25 networks. The 10 genes with the highest degree of connectivity were defined as the hub genes. Cox regression revealed that all the 10 genes (CDC20, BUB1B, KIF11, TTK, EZH2, ZWINT, NDC80, TPX2, MELK, and KIF20A) were related to the overall survival. Conclusion. Our study provided a registry of genes that play important roles in regulating the development of HBV-HCC, assisting us in understanding the molecular mechanisms that underlie the carcinogenesis and progression of HCC.

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FKBP-related ncRNA-mRNA axis in breast cancer

10.21203/rs.3.rs-16732/v1 ◽

2020 ◽

Author(s):

Hanchu Xiong ◽

Zihan Chen ◽

Wenwen Zheng ◽

Jing Sun ◽

Qingshuang Fu ◽

...

Keyword(s):

Breast Cancer ◽

Transcription Factors ◽

Differential Expression ◽

Pathway Analysis ◽

Kegg Pathway ◽

Ppi Network ◽

Hub Genes ◽

Go Annotation ◽

Prognostic Analysis ◽

Kegg Pathway Analysis

Abstract Background Breast cancer (BC) is a disease with morbidity ranking the first of women worldwidely. FK506-binding protein (FKBP) family has been demonstrated to possess various functions by interacting with different molecular targets in BC. However, a comprehensive ncRNA-mRNA regulatory axis of FKBP has not yet been reported. Methods FKBP related miRNAs were obtained from miRWalk database. Then, potential lncRNAs, transcription factors as well as mRNAs of screened differentially expressed miRNAs (DE-miRNAs) were analysed by using LncBase v.2, miRGen v3 and miRWalk database. Additionally, differential expression and prognostic analysis of lncRNAs were evaluated using TANRIC database. Next, GO annotation and KEGG pathway analysis were processed using DAVID database. Protein-Protein Interaction (PPI) network was established and hub genes were identified using STRING database. Finally, differential expression and prognostic analysis of hub genes were further conducted using UALCAN and bc-GenExMiner v4.2 database, respectively. Results Eleven DE-miRNAs, consisting of four FKBP4 related DE-miRNAs and seven FKBP5 related DE-miRNAs, were screened. 482 predicted lncRNAs were found for DE-miRNAs. Then, expression and prognostic results of nine of top twenty lncRNAs of BC were significantly identified. LINC00662 and LINC00963 expression were significantly associated with patients’ overall survival (OS). Then, nine potential upstream transcription factors were identified in motifs of DE-miRNAs. 320 target genes were identified for GO annotation and KEGG pathway analysis, which were mainly enriched in cysteine-type endopeptidase activity involved in apoptotic process. Construction and analysis in PPI network showed that RAB7A was selected as a hub gene with the toppest connectivity scores. Differential expression analysis of nine in top ten hub genes of BC were significantly identified. RAB7A and ARRB1 expression were significantly related with BC patients’ OS. Conclusions In current study, we firstly established a predicted FKBP-related ncRNA-mRNA regulatory network, thus exploring a comprehensive interpretation of molecular mechanisms and providing potential clues in seeking novel therapeutics for BC. In the future, much more experiments should be conducted to verify our findings.

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Network analyses of circular RNAs expression profiles and their hub genes in pancreatic ductal adenocarcinoma

10.21203/rs.2.15313/v1 ◽

2019 ◽

Author(s):

Yanyan Tang ◽

Ping Zhang

Keyword(s):

Gene Expression ◽

Pancreatic Ductal Adenocarcinoma ◽

Signaling Pathway ◽

Pathway Analysis ◽

Kegg Pathway ◽

Expression Profiles ◽

Ductal Adenocarcinoma ◽

Ppi Network ◽

Hub Genes ◽

Kegg Pathway Analysis

Abstract Pancreatic ductal adenocarcinoma (PDAC) is one of the most common malignant tumor in digestive system. CircRNAs involve in lots of biological processes through interacting with miRNAs and their targeted mRNA. We obtained the circRNA gene expression profiles from Gene Expression Omnibus (GEO) and identified differentially expressed genes (DEGs) between PDAC samples and paracancerous tissues. Bioinformatics analyses, including GO analysis, KEGG pathway analysis and PPI network analysis, were conducted for further investigation. We also constructed circRNA‑microRNA-mRNA co-expression network. A total 291 differentially expressed circRNAs were screened out. The GO enrichment analysis revealed that up-regulated DEGs were mainly involved metabolic process, biological regulation, and gene expression, and down-regulated DEGs were involved in cell communication, single-organism process, and signal transduction. The KEGG pathway analysis, the upregulated circRNAs were enriched cGMP-PKG signaling pathway, and HTLV-I infection, while the downregulated circRNAs were enriched in protein processing in endoplasmic reticulum, insulin signaling pathway, regulation of actin cytoskeleton, etc. Four genes were identified from PPI network as both hub genes and module genes, and their circRNA‑miRNA-mRNA regulatory network also be constructed. Our study indicated possible involvement of dysregulated circRNAs in the development of PDAC and promoted our understanding of the underlying molecular mechanisms.

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PSXII-25 Isolation and identification of bovine preadipocytes and screening of miRNAs associated with adipogenesis

Journal of Animal Science ◽

10.1093/jas/skaa278.445 ◽

2020 ◽

Vol 98 (Supplement_4) ◽

pp. 244-245

Author(s):

Xiang Yu ◽

Xibi Fang ◽

Runjun Yang

Keyword(s):

Lipid Metabolism ◽

Pathway Analysis ◽

Kegg Pathway ◽

Expression Profiles ◽

Marker Gene ◽

Control Group ◽

Small Rna Sequencing ◽

Fatty Tissue ◽

Isolation And Identification ◽

Kegg Pathway Analysis

Abstract Introduction: In the breeding of beef cattle, the adipogenesis is a significant process to fat deposition. Thus isolating and identifying bovine preadipocytes in vitro is a basis for investigating mechanism of adipogenesis. As important transcriptional regulators, miRNAs play a pivotal role in adipogenesis. Materials and methods: Bovine preadipocytes were isolated from subcutaneous fatty tissue and induced to differentiate into adipocytes. The verification of preadipocytes and adipocytes was performed by qPCR, Oil Red O stain and triglycerides detection. Total RNAs were extracted from bovine preadipocytes and adipocytes and proceeded small-RNA sequencing. KEGG pathway analysis and GO analysis were used to screen differently expressed miRNAs associated with adipogenesis. Results: The result showed that more lipid drops in induced group were observed and stained red compared with control group. The expression levels of key genes (pparγ, c/ebpα, fabp4, fasn and leptin) associated with adipogenesis were increased. Dlk1, as a marker gene of preadipocytes, was scarcely expressed in adipocytes. The content of cellar triglycerides detected in adipocytes was significantly upgraded. 131 miRNAs were found to be highly expressed in bovine adipocytes, and 119 miRNAs were highly expressed in bovine preadipocytes. KEGG pathway analysis showed that 4.76% of the differentially expressed genes were enriched in lipid metabolism. Discussion and conclusion: Previous studies have found that some miRNAs could regulate lipid metabolism. But few studies have explored the relationship between miRNAs and adipogenesis. In our study, we characterized the miRNAs associated with adipogenesis in bovine preadipocytes. The expression profiles of 11 miRNAs verified by q-PCR, including miR-149-5p, miR-199a-3p, miR-199a-5p, miR-148a and miR-449a were the same to sequencing data. Based on the KEGG pathway analysis, the predicted target genes were mainly enriched in signal transduction, catabolism and lipid metabolism. This work contributes to existing knowledge by providing an understanding of bovine adipogenesis at the molecular level.

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Potential Genes Related to Levofloxacin Resistance in Mycobacterium tuberculosis Based on Transcriptome and Methylome Overlap Analysis

Journal of Molecular Evolution ◽

10.1007/s00239-019-09926-z ◽

2020 ◽

Vol 88 (2) ◽

pp. 202-209 ◽

Cited By ~ 1

Author(s):

Hai-cheng Li ◽

Hui-xin Guo ◽

Tao Chen ◽

Wei Wang ◽

Zhu-hua Wu ◽

...

Keyword(s):

Mycobacterium Tuberculosis ◽

Pathway Analysis ◽

Molecular Mechanisms ◽

Kegg Pathway ◽

Control Group ◽

Tb Treatment ◽

Kegg Pathway Analysis ◽

Differentially Methylated Genes ◽

Resistant Group ◽

And Control

AbstractDrug-resistant Mycobacterium tuberculosis (M. tuberculosis) has become an increasingly serious public health problem and has complicated tuberculosis (TB) treatment. Levofloxacin (LOF) is an ideal anti-tuberculosis drug in clinical applications. However, the detailed molecular mechanisms of LOF-resistant M. tuberculosis in TB treatment have not been revealed. Our study performed transcriptome and methylome sequencing to investigate the potential biological characteristics of LOF resistance in M. tuberculosis H37Rv. In the transcriptome analysis, 953 differentially expressed genes (DEGs) were identified; 514 and 439 DEGs were significantly downregulated and upregulated in the LOF-resistant group and control group, respectively. The KEGG pathway analysis revealed that 97 pathways were enriched in this study. In the methylome analysis, 239 differentially methylated genes (DMGs) were identified; 150 and 89 DMGs were hypomethylated and hypermethylated in the LOF-resistant group and control group, respectively. The KEGG pathway analysis revealed that 74 pathways were enriched in this study. The overlap study suggested that 25 genes were obtained. It was notable that nine genes expressed downregulated mRNA and upregulated methylated levels, including pgi, fadE4, php, cyp132, pckA, rpmB1, pfkB, acg, and ctpF, especially cyp132, pckA, and pfkB, which were vital in LOF-resistant M. tuberculosis H37Rv. The overlapping genes between transcriptome and methylome could be essential for studying the molecular mechanisms of LOF-resistant M. tuberculosis H37Rv. These results may provide informative evidence for TB treatment with LOF.

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Gene-expression profile and postpartum transition of bovine endometrial side population cells†

Biology of Reproduction ◽

10.1093/biolre/ioab004 ◽

2021 ◽

Author(s):

Ryoki Tatebayashi ◽

Sho Nakamura ◽

Shiori Minabe ◽

Tadashi Furusawa ◽

Ryoya Abe ◽

...

Keyword(s):

Gene Expression ◽

Progenitor Cells ◽

Pathway Analysis ◽

Kegg Pathway ◽

Side Population ◽

Gene Set Enrichment Analysis ◽

Stem Cell Marker ◽

Endometrial Cells ◽

Kegg Pathway Analysis ◽

Upregulated Genes

Abstract The mechanism of bovine endometrial regeneration after parturition remains unclear. Here, we hypothesized that bovine endometrial stem/progenitor cells participate in the postpartum regeneration of the endometrium. Flow cytometry analysis identified the presence of side population (SP) cells among endometrial stromal cells. Endometrial SP cells were shown to differentiate into osteoblasts and adipocytes. RNA-seq data showed that the gene expression pattern was different between bovine endometrial SP cells and main population cells. Gene Set Enrichment Analysis identified the enrichment of stemness genes in SP cells. Significantly (false discovery rate < 0.01) upregulated genes in SP cells contained several stem cell marker genes. Gene ontology (GO) analysis of the upregulated genes in SP cells showed enrichment of terms related to RNA metabolic process and transcription. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of upregulated genes in SP cells revealed enrichment of signaling pathways associated with maintenance and differentiation of stem/progenitor cells. The terms involved in TCA cycles were enriched in GO and KEGG pathway analysis of downregulated genes in SP cells. These results support the assumption that bovine endometrial SP cells exhibit characteristics of somatic stem/progenitor cells. The ratio of SP cells to endometrial cells was lowest on days 9–11 after parturition, which gradually increased thereafter. SP cells were shown to differentiate into epithelial cells. Collectively, these results suggest that bovine endometrial SP cells were temporarily reduced immediately after calving possibly due to their differentiation to provide new endometrial cells.

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TP53 Targetome: A Database of Novel Breast Cancer Biomarkers

Current Drug Targets ◽

10.2174/1389450122666210129105016 ◽

2021 ◽

Vol 22 ◽

Author(s):

Yasir Hameed ◽

Samina Ejaz

Keyword(s):

Breast Cancer ◽

Pathway Analysis ◽

Expression Profile ◽

Kegg Pathway ◽

Methylation Status ◽

Cancer Biomarkers ◽

Copy Number Variations ◽

Hub Genes ◽

Kegg Pathway Analysis ◽

Breast Cancer Biomarkers

Background and objectives : Due to the increasing demand for biomarkers in breast cancer we screened the TP53 targetome to discover some novel biomarkers, if any. Methods: For this purpose, a TP53 targetome dataset was downloaded and a protein-protein interaction network (PPI) was constructed and analyzed to identify the hub genes. In total 33 hub genes were identified and subjected to the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The information related to the expression and promoters’ methylation profiles of the hub genes was retrieved through UALCAN. Genetic alteration and copy number variations (CNVs) related information was obtained from the cBioPortal. While KM plotter tool helped to evaluate the prognostic potential of the identified hub genes. Results: The KEGG pathway analysis revealed the enrichment of hub genes in various diverse pathways. The expression analysis showed that the expression profile of majority hub genes was similar to the one as reported in the published literature. While, a few hub genes (CDKN1A, BRCA1, CHEK2, PMAIP1, TNFRSF10B, CHEK1, GADD45A, IGFBP3, CASP3, and FOXO3) exhibited differential expression profile and examined to have prognostic values, hence, suggested as novel potential biomarkers of BRIC. Moreover, the correlational analysis revealed some unusual correlations among expression levels and promoters methylation status of many hub genes. Conclusion: Our study has extended the database of breast cancer biomarkers by providing insights into some novel diagnostic and prognostic biomarkers having potential of clinical implementation.

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Exploration of the involvement of LncRNA in HIV-associated encephalitis using bioinformatics

PeerJ ◽

10.7717/peerj.5721 ◽

2018 ◽

Vol 6 ◽

pp. e5721 ◽

Cited By ~ 4

Author(s):

Diangeng Li ◽

Pengtao Bao ◽

Zhiwei Yin ◽

Lei Sun ◽

Jin Feng ◽

...

Keyword(s):

White Matter ◽

Pathway Analysis ◽

Target Genes ◽

Kegg Pathway ◽

Function Analysis ◽

Signal Pathways ◽

Public Database ◽

Kegg Pathway Analysis ◽

Nervous System Function ◽

Brain Tissues

Background HIV-associated encephalitis (HIVE) is one of the common complications of HIV infection, and the pathogenesis of HIVE remains unclear, while lncRNA might be involved it. In this study, we made re-annotation on the expression profiling from the HIVE study in the public database, identified the lncRNA that might be involved in HIVE, and explored the possible mechanism. Methods In the GEO public database, the microarray expression profile (GSE35864) of three regions of brain tissues (white matter, frontal cortex and basal ganglia brain tissues) was chosen, updated annotation was performed to construct the non-cording-RNA (ncRNA) microarray data. Morpheus was used to identify the differential expressed ncRNA, and Genbank of NCBI was used to identify lncRNAs. The StarBase, PITA and miRDB databases were used to predict the target miRNAs of lncRNA. The TargetScan, PicTar and MiRanda databases were used to predict the target genes of miRNAs. The GO and KEGG pathway analysis were used to make function analysis on the targets genes. Results Seventeen differentially expressed lncRNAs were observed in the white matter of brain tissues, for which 352 target miRNAs and 6,659 target genes were predicted. The GO function analysis indicated that the lncRNAs were mainly involved in the nuclear transcription and translation processes. The KEGG pathway analysis showed that the target genes were significantly enriched in 33 signal pathways, of which 11 were clearly related to the nervous system function. Discussion The brand-new and different microarray results can be obtained through the updated annotation of the chips, and it is feasible to identify lncRNAs from ordinary chips. The results suggest that lncRNA may be involved in the occurrence and development of HIVE, which provides a new direction for further research on the diagnosis and treatment of HIVE.

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Identification of differentially expressed genes, biological pathways and prognostic signature in bladder cancer

10.21203/rs.3.rs-362542/v1 ◽

2021 ◽

Author(s):

Fucai Tang ◽

Xiayan Qian ◽

Zeguang Lu ◽

Yongchang Lai ◽

Zhibiao Li ◽

...

Keyword(s):

Bladder Cancer ◽

Differentially Expressed Genes ◽

Pathway Analysis ◽

Kegg Pathway ◽

Biological Pathways ◽

Differentially Expressed ◽

Hub Genes ◽

Go Analysis ◽

Ppi Networks ◽

Kegg Pathway Analysis

Abstract Background Bladder cancer (BC) is one of the most common malignant cancer of urinary system in the worldwide. The purpose of the present study was to analysis differentially expressed genes (DEGs), biological pathways and prognostic significance BC by bioinformatics analysis. Methods The gene expression dataset GSE7476 and the mRNA Seq sequencing data were downloaded respectively from GEO and TCGA. A total of 220 DEGs were obtained in BC. GO analysis and KEGG pathway analysis were performed for up- and down-regulated DEGs. Then, a protein-protein interaction (PPI) networks and module were constructed by Cytoscape software. Survival analysis of hub genes was performed. Results The result of GO analysis revealed that the up-regulated DEGs were enriched mainly in sister chromatid segregation, while the down-regulated DEGs were enriched mainly in muscle contraction. The result of KEGG pathway analysis showed that up-regulated DEGs were enriched mainly in cell cycle, while down-regulated DEGs enriched in IL-17 signaling pathway. 41 hub gene and 3 crucial modules were identified in the PPI network. 15 genes significantly associated with patient prognosis in BC were obtained by Kaplan-Meier analysis. Conclusions In summary, the present study identified hub genes, crucial pathways and provide possible the molecular targets and prognostic biomarkers for targeted therapy and prognostic assessment of BC.

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POS0399 TMT-BASED QUANTITATIVE PROTEOMICS ANALYSIS OF SYNOVIAL FLUID-DERIVED EXOSOMES IN RHEUMATOID ARTHRITIS, AXIAL SPONDYLOARTHRITIS, GOUT AND OSTEOARTHRITIS

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2021-eular.3607 ◽

2021 ◽

Vol 80 (Suppl 1) ◽

pp. 428.3-429

Author(s):

Y. Liu ◽

Y. Huang ◽

Q. Huang ◽

Z. Huang ◽

Z. Li ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Cluster Analysis ◽

Synovial Fluid ◽

Pathway Analysis ◽

Quantitative Proteomics ◽

Axial Spondyloarthritis ◽

Kegg Pathway ◽

Hierarchical Cluster ◽

Kegg Pathway Analysis ◽

Differential Proteins

Background:The pathogeneses of the joint diseases rheumatoid arthritis (RA), axial spondyloarthritis (axSpA), gout, and osteoarthritis (OA) are still not fully elucidated. Exosomes in synovial fluid (SF) has a critical role in the pathogenesis of arthritis. None of study has compared the proteomics of SF-derived exosomes in RA, axSpA, gout and OA.Objectives:To compare the proteomics of SF-derived exosomes in RA, axSpA, gout and OA based on tandem mass tags (TMT) labeled quantitative proteomics technique.Methods:SF-derived exosomes was isolated from RA, axSpA, gout and OA patients by the Exoquick kit combined ultracentrifugation method. TMT labeled quantitative proteomics technique was used to compare the proteomics of SF-derived exosomes. Volcano plot, hierarchical cluster, Gene Ontologies (GO), Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted.Results:A total of 1678 credible proteins were detected. With the cut off criteria of |log2 (fold-change)| ≥1.2 and p-value <0.05, 267 (140 up-regulated and 127 down-regulated)differential proteins were found in OA vs gout, 291 (179 and 112) in axSpA vs OA, 515 (109 and 406) in RA vs axSpA, 298 (191 and 107) in axSpA vs gout, 462 (160 and 302) in RA vs gout, 536 (170 and 366) in RA vs OA. GO analysis showed that the biological progress of differential proteins were mainly enriched in the “immune response”. Regarding the molecular function, the differential proteins mainly mediated “antigen binding”. GO analysis of the cellular components indicated that most proteins were annotated as “extracellular exosomes”. KEGG pathway analysis demonstrated differential proteins were significantly enriched in “complement and coagulation cascades”. The hierarchical cluster analysis of the differential proteins in the four groups showed that Lysozyme C and Keratin were more abundant in gout, Hemoglobin and Actin-related protein 2/3 complex subunit 3 in OA, Sodium/potassium-transporting ATPase subunit alpha-1 and Immunoglobulin heavy constant delta in axSpA, Pregnancy zone protein and Stromelysin-1 in RA.Conclusion:The protein profiles of SF-derived exosomes in RA, axSpA, gout and OA patients were different. The differential proteins were the potential biomarkers of RA, axSpA, gout and OA.References:[1]Cretu D, Diamandis E P, Chandran V. Delineating the synovial fluid proteome: recent advancements and ongoing challenges in biomarker research.[J]. Critical reviews in clinical laboratory sciences, 2013,50(2):51-63.[2]McArdle A J, Menikou S. What is proteomics?[J]. Archives of disease in childhood. Education and practice edition, 2020.Figure 1.The hierarchical cluster analysis of differential proteins in axSpA, OA, Gout and RA.Disclosure of Interests:None declared

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