Analysis of mRNA-lncRNA and mRNA-lncRNA-Pathway co-expression networks based on WGCNA in developing pediatric sepsis

Abstract Background: Pediatric sepsis is a great threat in death worldwide. However, the pathogenesis has not been clearly understood until now in sepsis.Methods: This study identified differentially expressed mRNA (DEMs) and lncRNAs (DELs) based on Gene Expression Omnibus (GEO) database. And the weighted gene co-expression network analysis (WGCNA) was performed to explore co-expression modules associated with pediatric sepsis. Then Gene Ontology (GO), KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway, DEMs‑DELs and DEMs‑DELs-Pathway co-expression network analysis was conducted in selected significant module. Results: A total of 1941 DEMs and 225 DELs were used to conduct WGCNA. And the turquoise module was selected as the significant module that was associated with particular traits. The DEMs functions associated with many vital processes were also shown by GO and KEGG pathway analysis in the turquoise module. Finally, 15 DEMs and 4 DELs (GSEC, NONHSAT160878.1, XR_926068.1 and RARA-AS1) were selected as candidate biomarkers in DEMs-DELs-Pathway co-expression network. Conclusions: Our study identified 15 DEMs and 4 DELs as diagnostic markers, which could also provide more directions to study molecular mechanism of pediatric sepsis.

Download Full-text

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.

Download Full-text

Integrated bioinformatics analysis for differentially expressed genes and signaling pathways identification in gastric cancer

10.21203/rs.2.17512/v1 ◽

2019 ◽

Author(s):

ChenChen Yang ◽

Aifeng Gong

Keyword(s):

Gene Expression ◽

Gastric Cancer ◽

Differentially Expressed Genes ◽

Kegg Pathway ◽

Gene Expression Omnibus ◽

Differentially Expressed ◽

Mrna Levels ◽

Pcr Assay ◽

Microarray Datasets ◽

Geo Database

Abstract Background Gastric cancer (GC) has a high mortality rate in cancer-related deaths worldwide. Here, we identified several vital candidate genes related to gastric cancer development and revealed the potential pathogenic mechanisms using integrated bioinformatics analysis.Methods Two microarray datasets from Gene Expression Omnibus (GEO) database integrated. Limma package was used to analyze differentially expressed genes (DEGs) between GC and matched normal specimens. DAVID was utilized to conduct Gene ontology (GO) and KEGG enrichment analysis. The relative expression of OLFM4, IGF2BP3, CLDN1and MMP1were analyzed based on TCGA database provided by UALCAN. Western blot and quantitative real time PCR assay were performed to determine the protein and mRNA levels of OLFM4, IGF2BP3, CLDN1and MMP1 in GC tissues and cell lines, respectively.Results We downloaded the expression profiles of GSE103236 and GSE118897 from the Gene Expression Omnibus (GEO) database. Two integrated microarray datasets were used to obtain differentially expressed genes (DEGs), and bioinformatics methods were used for in-depth analysis. After gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments analysis, we identified 61 DEGs in common, of which the expression of 34 genes were elevated and 27 genes were decreased. GO analysis displayed that the biological functions of DEGs mainly focused on negative regulation of growth, fatty acid binding, cellular response to zinc ion and calcium-independent cell-cell adhesion. KEGG pathway analysis demonstrated that these DEGs mainly related to the Wnt and tumor signaling pathway. Interestingly, we found 4 genes were most significantly upregulated in the DEGs, which were OLFM4, IGF2BP3, CLDN1 and MMP1.Then, we confirmed the upregulation of these genes in STAD based on sample types. In the final, western blot and qRT-PCR assay were performed to determine the protein and mRNA levels of OLFM4, IGF2BP3, CLDN1 and MMP1 in GC tissues and cell lines.Conclusion In our study, using integrated bioinformatics to screen DEGs in gastric cancer could benefit us for understanding the pathogenic mechanism underlying gastric cancer progression. Meanwhile, we also identified four significantly upregulated genes in DEGs from both two datasets, which might be used as the biomarkers for early diagnosis and prevention of gastric cancer.

Download Full-text

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.

Download Full-text

Analysis of Long Noncoding RNA and mRNA Expression Profiles in IL-9-Activated Astrocytes and EAE Mice

Cellular Physiology and Biochemistry ◽

10.1159/000487975 ◽

2018 ◽

Vol 45 (5) ◽

pp. 1986-1998 ◽

Cited By ~ 6

Author(s):

Xiaomei Liu ◽

Qing Zhang ◽

Weixiao Wang ◽

Dongjiao Zuo ◽

Jing Wang ◽

...

Keyword(s):

Gene Ontology ◽

Pathway Analysis ◽

Kegg Pathway ◽

Expression Profiles ◽

Astrocyte Activation ◽

Kegg Pathway Analysis ◽

The Brain ◽

Brain Tissues

Background/Aims: Multiple sclerosis (MS) is an autoimmune disease in the central nervous system associated with demyelination and axonal injury. Astrocyte activation is involved in the pathogenesis of MS and experimental autoimmune encephalomyelitis (EAE), an animal model of MS. This study was designed to find potential lncRNAs in EAE mice and activated astrocytes. Methods: we performed microarray analysis of lncRNAs from the brain tissues of EAE mice and primary mouse astrocytes treated with IL-9(50 ng/ml). 12 lncRNAs were validated through real-time PCR. Gene ontology and KEGG pathway analysis were applied to explore the potential functions of lncRNAs. Results: Differentially expressed 3300 lncRNAs and 3250 mRNAs were in the brain tissues of EAE mice, and 3748 lncRNAs and 3332 mRNAs were in activated astrocytes. Notably, there were 2 co-up-regulated lncRNAs and 3 co-down-regulated lncRNAs both in the brain tissues of EAE mice and in activated astrocytes, including Gm14005, Gm12478, mouselincRNA1117, AK080435, and mouselincRNA0681, which regulate the ER calcium flux kinetics, zinc finger protein and cell apoptosis. Similarly, there were 7 mRNAs co-up-regulated and 2 mRNAs co-down-regulated both in vivo and in vitro. Gene ontology and KEGG pathway analysis showed that the biological functions of differentially expressed mRNAs were associated with metabolism, development and inflammation. The results of realtime PCR validation were consistent with the data from the microarrays. Conclusions: Our data uncovered the expression profiles of lncRNAs and mRNAs in vivo and in vitro, which may help delineate the mechanisms of astrocyte activation during MS/EAE process.

Download Full-text

Global Gene Expression Profiling and Alternative Splicing Events during the Chondrogenic Differentiation of Human Cartilage Endplate-Derived Stem Cells

BioMed Research International ◽

10.1155/2015/604972 ◽

2015 ◽

Vol 2015 ◽

pp. 1-11 ◽

Cited By ~ 3

Author(s):

Jin Shang ◽

Xin Fan ◽

Lei Shangguan ◽

Huan Liu ◽

Yue Zhou

Keyword(s):

Gene Expression ◽

Stem Cells ◽

Alternative Splicing ◽

Pathway Analysis ◽

Expression Profiling ◽

Chondrogenic Differentiation ◽

Kegg Pathway ◽

Cartilage Endplate ◽

Kegg Pathway Analysis ◽

Alternatively Spliced

Low back pain (LBP) is a very prevalent disease and degenerative disc diseases (DDDs) usually account for the LBP. However, the pathogenesis of DDDs is complicated and difficult to elucidate. Alternative splicing is a sophisticated regulatory process which greatly increases cellular complexity and phenotypic diversity of eukaryotic organisms. In addition, the cartilage endplate-derived stem cells have been discovered and identified by our research group. In this paper, we continue to investigate gene expression profiling and alternative splicing events during chondrogenic differentiation of cartilage endplate-derived stem cells. We adopted Affymetrix Human Transcriptome Array 2.0 (HTA 2.0) to compare the transcriptional and splicing changes between the control and differentiated samples. RT-PCR and quantitative PCR are used to validate the microarray results. The GO and KEGG pathway analysis was also performed. After bioinformatics analysis of the data, we detected 1953 differentially expressed genes. In terms of alternative splicing, the Splicing Index algorithm was used to select alternatively spliced genes. We detected 4411 alternatively spliced genes. GO and KEGG pathway analysis also revealed several functionally involved biological processes and signaling pathways. To our knowledge, this is the first study to investigate the alternative splicing mechanisms in chondrogenic differentiation of stem cells on a genome-wide scale.

Download Full-text

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.

Download Full-text

Array2KEGG: Web-based tool of KEGG pathway analysis for gene expression profile

BioChip Journal ◽

10.1007/s13206-010-4208-7 ◽

2010 ◽

Vol 4 (2) ◽

pp. 134-140 ◽

Cited By ~ 3

Author(s):

Jun-Sub Kim ◽

Seung-Jun Kim ◽

Hye-Won Park ◽

Jong-Pil Youn ◽

Yu Ri An ◽

...

Keyword(s):

Gene Expression ◽

Gene Expression Profile ◽

Pathway Analysis ◽

Expression Profile ◽

Kegg Pathway ◽

Web Based ◽

Kegg Pathway Analysis

Download Full-text

Global Phosphoproteome Analysis Reveals Significant Differences Between Sporulated Oocysts of Virulent and Avirulent Strains of Toxoplasma Gondii

10.21203/rs.3.rs-84449/v1 ◽

2020 ◽

Author(s):

Ze-Xiang Wang ◽

Rui-Si Hu ◽

Xing-Quan Zhu ◽

Xiao-Lin Sun ◽

Hany M. Elsheikha

Keyword(s):

Network Analysis ◽

Toxoplasma Gondii ◽

Pathway Analysis ◽

Kegg Pathway ◽

Distinct Difference ◽

Biological Processes ◽

Motif Analysis ◽

Kegg Pathway Analysis ◽

Go Enrichment ◽

Phosphorylated Peptides

Abstract Background: The apicomplexan protozoan parasite Toxoplasma gondii is one of the most successful intracellular parasites capable of infecting warm-blooded animals. Several strains of T. gondii have been described and typed as virulent or avirulent based on their pathogenicity in mice, as well as sporulated oocysts of strains belonging to distinct T. gondii genotypes. Phosphorylation is a reversable form of protein post-translational modification (PTM) that influences many biological processes and is used by some apicomplexan parasites to facilitate manipulation of the host cells. Phosphoproteomic analysis of oocysts of T. gondii strains belonging to distinct genotypes may reveal mechanisms contributing to the differences in the virulence of this parasite at the posttranslational level.Methods: In this study, the differences in the phosphoproteomic landscape of sporulated oocysts between virulent and avirulent strains of Toxoplasma gondii were examined using a global phosphoproteomics approach. Phosphopeptides from sporulated oocysts of the virulent PYS strain (Chinese ToxoDB#9) and the avirulent PRU strain (type II) were enriched by titanium dioxide (TiO2) affinity chromatography and quantified using isobaric tag (iBT) approach. Motif analysis, GO enrichment, KEGG pathway analysis, STRING analysis and kinase related network analysis of phosphopeptides were conducted to discover distinct difference in sporulated oocysts between virulent and avirulent T. gondii strains. Results: A total of 10,645 unique phosphopeptides, 8,181 nonredundant phosphorylation sites and 2,792 phosphoproteins were identified. We also detected 4,129 differentially expressed phosphopeptides (DEPs) between sporulated oocysts of PYS strain and PRU strain (|log1.5 fold change| > 1 and p < 0.05), including 2,485 upregulated and 1,644 downregulated phosphopeptides. Motif analysis identified 24 motifs from the upregulated phosphorylated peptides including 22 serine motifs and two threonine motifs (TPE and TP), and 15 motifs from the downregulated phosphorylated peptides including 12 serine motifs and three threonine motifs (TP, RxxT and KxxT) in PYS strain when comparing PYS strain to PRU strain. Several kinases were consistent with motifs of overrepresented phosphopeptides, such as PKA, PKG, CKII, IKK, MAPK, EGFR, INSR, Jak, Syk, Src, Ab1. GO enrichment, KEGG pathway analysis and STRING analysis revealed DEPs significantly enriched in many biological processes and pathways. Kinase related network analysis showed that AGC kinase had the greatest connected peptides.Conclusions: The present study revealed the global phosphoproteomic differences in sporulated oocysts between virulent and avirulent T. gondii strains of different genotypes. Abundant phosphopeptides in sporulated oocysts between virulent and avirulent T. gondii strains exhibited distinct difference in the conserved motifs, GO terms, enriched pathways and PPI networks. The kinase associated network analysis indicated the role of phosphorylation in the transformation of T. gondii kinases. AGC kinase was the most connected kinases peptides. These data provide new insight into the phenotypic differences in sporulated oocysts of virulent and avirulent T. gondii strains.

Download Full-text

Microarray Profiling of Bone Marrow Long Non-Coding RNA Expression in Multiple Myeloma

Blood ◽

10.1182/blood.v128.22.5617.5617 ◽

2016 ◽

Vol 128 (22) ◽

pp. 5617-5617

Author(s):

Ying Shen ◽

Jing Liu ◽

Yun Yang ◽

Ju Bai ◽

Yue Peng ◽

...

Keyword(s):

Cell Cycle ◽

Bone Marrow ◽

Gene Ontology ◽

Iron Deficiency ◽

Iron Deficiency Anemia ◽

Pathway Analysis ◽

Biological Process ◽

Kegg Pathway ◽

Go Analysis ◽

Kegg Pathway Analysis

Abstract Introduction: Multiple myeloma (MM), the second most frequent hematologic malignancy, is characterized with clonal proliferation of malignant plasma cells in the bone marrow, and usually monoclonal protein in the blood and/or urine. Its clinical manifestations are associated with end-organ damage consisting of anaemia, renal insufficiency, bone lesions and hypercalcaemia. Long non-coding RNAs (lncRNAs) represent more than half of the mammalian noncoding transcriptome and are involved in many biological processes, including transcription regulation, competition with other linear RNAs and involvement in tumorigenesis or oncogenic pathways. Accumulating studies have revealed the important role of lncRNAs in the hematological tumors, especially MM. In order to investigate the further relationship between MM and lncRNAs, we performed global lncRNA profiling in both incipient MM patients and iron deficiency anemia (IDA) patients. We assumed that the bunch of deregulated lncRNAs in MM patients would broaden current understanding of progression of MM, and present a new approach to novel therapeutic targets. Methods: Bone marrow mononuclear cells were obtained from five MM patients with normal karyotype at the Department of Hematology, Second Affiliated Hospital, Xi'an Jiaotong University, in 2016. Additionally, bone marrow samples from five patients with IDA were used as controls. One sample in five MM patients was rejected because of its disqualification in clustering analysis. Arraystar Human LncRNA Array V4.0 was used to profile expression of lncRNAs, which was performed by KangChen Bio-tech (Shanghai, China). The array detects a total of 40,173 lncRNAs probes and an entire collection of 20,730 protein coding mRNAs. Gene Ontology (GO) analysis (http://david.abcc.ncifcrf.gov/summary.jsp) was used to analyze differentially expressed transcripts. Pathway analysis of differentially expressed transcripts were accomplished using Kyoto Encyclopedia of Genes and Genomes (KEGG) database (http://www.genome.jp/kegg). Results: Bioinformatic analysis of the lncRNA expression identified a total of 2445 lncRNAs were upregulated and 1519 lncRNAs were downregulated in four MM samples, among them, 199 lncRNAs were significantly upregulated and 27 lncRNAs were notably downregulated more than 10-fold in MM samples compared with IDA (Figure 1). GO analysis by Database for Annotation, Visualization and Integrated Discovery (DAVID ) showed that the top ten enriched biological process (BP) by upregulated transcripts were involved in multicellular organismal development and cell-cell adhesion, while downregulated transcripts were dragged in mitotic cell cycle and cell cycle. KEGG pathway analysis of the top ten enriched pathways included ECM-receptor interaction and protein processing in endoplasmic reticulum in upregulated transcript, while cell cycle and DNA replication were the top two enriched pathways in downregulated transcript (Figure 2). Among them, mitotic cell cycle was the most enriched pathway with p-value 3.86E-35. These results suggested that the dysregulated lncRNAs were related to MM cells adhesion and proliferation or differentiation closely. Conclusions: We have identified a group of dysregulated lncRNAs and mRNAs in bone marrow samples obtained from MM patients versus IDA controls. These lncRNAs participate in MM cell growth, migration and invasion by regulating cell adhesion and cell cycle, playing an important role in the development and progression of MM. Further investigation is still required to detect the underlying functions of these lncRNAs in MM pathogenesis and whether these lncRNAs may serve as new diagnostic biomarkers and therapeutic targets for MM. Figure 1 Clustering analysis of four mulitiple myeloma (MM) samples and five iron deficiency anemia (IDA) controls. Figure 1. Clustering analysis of four mulitiple myeloma (MM) samples and five iron deficiency anemia (IDA) controls. Figure 2 Gene Ontology(GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of dysregulated transcripts. (A) The top ten enriched biological process (BP) by upregulated transcripts. (B) The top ten enriched BP by downregulated transcripts. (C) The top ten enriched pathways in upregulated transcripts. (D) The top ten enriched pathways in downregulated transcripts. Figure 2. Gene Ontology(GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of dysregulated transcripts. (A) The top ten enriched biological process (BP) by upregulated transcripts. (B) The top ten enriched BP by downregulated transcripts. (C) The top ten enriched pathways in upregulated transcripts. (D) The top ten enriched pathways in downregulated transcripts. Disclosures No relevant conflicts of interest to declare.

Download Full-text

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

Download Full-text