scholarly journals A proteomic repertoire of autoantigens identified from the classic autoantibody clinical test substrate HEp-2 cells

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Julia Y. Wang ◽  
Wei Zhang ◽  
Jung-hyun Rho ◽  
Michael W. Roehrl ◽  
Michael H. Roehrl
Keyword(s):  
Autoimmune Diseases ◽  
Interaction Network ◽  
Molecular Complexes ◽  
Mitotic Cell ◽  
Clinical Test ◽  
Current Standard ◽  
Cytoplasmic Staining ◽  
Affinity Enrichment ◽  
Indirect Immunofluorescence Staining ◽  
Pathway Analyses

Abstract Background Autoantibodies are a hallmark of autoimmune diseases. Autoantibody screening by indirect immunofluorescence staining of HEp-2 cells with patient sera is a current standard in clinical practice. Differential diagnosis of autoimmune disorders is based on commonly recognizable nuclear and cytoplasmic staining patterns. In this study, we attempted to identify as many autoantigens as possible from HEp-2 cells using a unique proteomic DS-affinity enrichment strategy. Methods HEp-2 cells were cultured and lysed. Total proteins were extracted from cell lysate and fractionated with DS-Sepharose resins. Proteins were eluted with salt gradients, and fractions with low to high affinity were collected and sequenced by mass spectrometry. Literature text mining was conducted to verify the autoantigenicity of each protein. Protein interaction network and pathway analyses were performed on all identified proteins. Results This study identified 107 proteins from fractions with low to high DS-affinity. Of these, 78 are verified autoantigens with previous reports as targets of autoantibodies, whereas 29 might be potential autoantigens yet to be verified. Among the 107 proteins, 82 can be located to nucleus and 15 to the mitotic cell cycle, which may correspond to the dominance of nuclear and mitotic staining patterns in HEp-2 test. There are 55 vesicle-associated proteins and 12 ribonucleoprotein granule proteins, which may contribute to the diverse speckled patterns in HEp-2 stains. There are also 32 proteins related to the cytoskeleton. Protein network analysis indicates that these proteins have significantly more interactions among themselves than would be expected of a random set, with the top 3 networks being mRNA metabolic process regulation, apoptosis, and DNA conformation change. Conclusions This study provides a proteomic repertoire of confirmed and potential autoantigens for future studies, and the findings are consistent with a mechanism for autoantigenicity: how self-molecules may form molecular complexes with DS to elicit autoimmunity. Our data contribute to the molecular etiology of autoimmunity and may deepen our understanding of autoimmune diseases.

scholarly journals A Proteomic Repertoire of Autoantigens Identified from the Classic Autoantibody Clinical Test Substrate HEp-2 Cells

2020 ◽  
Author(s):  
Julia Y Wang ◽  
Wei Zhang ◽  
Jung-hyun Rho ◽  
Michael W Roehrl ◽  
Michael H. Roehrl
Keyword(s):  
Autoimmune Diseases ◽  
Interaction Network ◽  
Molecular Complexes ◽  
Mitotic Cell ◽  
Clinical Test ◽  
Current Standard ◽  
Cytoplasmic Staining ◽  
Affinity Enrichment ◽  
Indirect Immunofluorescence Staining ◽  
Pathway Analyses

Abstract Background: Autoantibodies are a hallmark of autoimmune diseases. Autoantibody screening by indirect immunofluorescence staining of HEp-2 cells with patient sera is a current standard in clinical practice. Differential diagnosis of autoimmune disorders is based on commonly recognizable nuclear and cytoplasmic staining patterns. In this study, we attempted to identify as many autoantigens as possible from HEp-2 cells using a unique proteomic DS-affinity enrichment strategy.Methods: HEp-2 cells were cultured and lysed. Total proteins were extracted from cell lysate and fractionated with DS-Sepharose resins. Proteins were eluted with salt gradients, and fractions with low to high affinity were collected and sequenced by mass spectrometry. Literature text mining was conducted to verify the autoantigenicity of each protein. Protein interaction network and pathway analyses were performed on all identified proteins.Results: This study identified 107 proteins from fractions with low to high DS-affinity. Of these, 78 are verified autoantigens with previous reports as targets of autoantibodies, whereas 29 might be potential autoantigens yet to be verified. Among the 107 proteins, 82 can be located to nucleus and 15 to the mitotic cell cycle, which may correspond to the dominance of nuclear and mitotic staining patterns in HEp-2 test. There are 55 vesicle-associated proteins and 12 ribonucleoprotein granule proteins, which may contribute to the diverse speckled patterns in HEp-2 stains. There are also 32 proteins related to the cytoskeleton. Protein network analysis indicates that these proteins have significantly more interactions among themselves than would be expected of a random set, with the top 3 networks being mRNA metabolic process regulation, apoptosis, and DNA conformation change.Conclusions: This study provides a proteomic repertoire of confirmed and potential autoantigens for future studies, and the findings are consistent with a mechanism for autoantigenicity: how self-molecules may form molecular complexes with DS to elicit autoimmunity. Our data contribute to the molecular etiology of autoimmunity and may deepen our understanding of autoimmune diseases.

scholarly journals A Proteomic Repertoire of Autoantigens Identified from the Classic Autoantibody Clinical Test Substrate HEp-2 Cells

2020 ◽  
Author(s):  
Julia Y Wang ◽  
Wei Zhang ◽  
Jung-hyun Rho ◽  
Michael W Roehrl ◽  
Michael H. Roehrl
Keyword(s):  
Autoimmune Diseases ◽  
Strong Support ◽  
Interaction Network ◽  
Molecular Complexes ◽  
Mitotic Cell ◽  
Clinical Test ◽  
Current Standard ◽  
Cytoplasmic Staining ◽  
Affinity Enrichment ◽  
Pathway Analyses

Abstract Background: Autoantibodies are a hallmark of autoimmune diseases. Autoantibody screening by indirect immunofluorescence staining of HEp-2 cells with patient sera is a current standard in clinical practice. Differential diagnosis of autoimmune disorders is based on commonly recognizable nuclear and cytoplasmic staining patterns. In this study, we attempted identifying as many autoantigens as possible from HEp-2 cells using a unique DS-affinity enrichment strategy.Methods: HEp-2 cells were cultured and lysed. Total proteins were extracted from cell lysate and fractionated with DS-Sepharose resins. Proteins were eluted with salt gradients, and fractions with low to high affinity were collected and sequenced by mass spectrometry. Literature text mining was conducted to verify the autoantigenicity of each protein. Protein interaction network and pathway analyses were performed on all identified proteins. Results: This study identified 107 proteins from fractions with low to high DS-affinity. Of these, 78 are verified autoantigens with previous reports as targets of autoantibodies, whereas 29 might be potential autoantigens yet to be verified. Among the 107 proteins, 82 can be located to nucleus and 15 to the mitotic cell cycle, which may correspond to the dominance of nuclear and mitotic staining patterns in HEp-2 test. There are 55 vesicle-associated proteins and 12 ribonucleoprotein granule proteins, which may contribute to the diverse speckled patterns in HEp-2 stains. There are also 32 proteins related to the cytoskeleton. Protein network analysis indicates that these proteins have significantly more interactions among themselves than would be expected of a random set, with the top 3 networks being mRNA metabolic process regulation, apoptosis, and DNA conformation change.Conclusions: This study provides a proteomic repertoire of confirmed and potential autoantigens for future studies, and it provides strong support for a unifying mechanism of autoantigenicity on how self-molecules may form molecular complexes with DS to elicit autoimmunity, which may help unravel the molecular etiology of autoimmunity and deepen our understanding of autoimmune diseases.

scholarly journals An Autoantigen-ome from HS-Sultan B-Lymphoblasts Offers a Molecular Map for Investigating Autoimmune Sequelae of COVID-19

2021 ◽  
Author(s):  
Julia Y. Wang ◽  
Wei Zhang ◽  
Victor B. Roehrl ◽  
Michael W. Roehrl ◽  
Michael H. Roehrl
Keyword(s):  
Autoimmune Diseases ◽  
Dermatan Sulfate ◽  
Platelet Activating Factor ◽  
Mitotic Cell ◽  
Nucleocytoplasmic Transport ◽  
Insulin Degrading Enzyme ◽  
Altered Expression ◽  
Affinity Enrichment ◽  
Disulfide Isomerases ◽  
B1 Cells

To understand how COVID-19 may induce autoimmune diseases, we have been compiling an atlas of COVID-autoantigens (autoAgs). Using dermatan sulfate (DS) affinity enrichment of autoantigenic proteins extracted from HS-Sultan lymphoblasts, we identified 362 DS-affinity proteins, of which at least 201 (56%) are confirmed autoAgs. Comparison with available multi-omic COVID data shows that 315 (87%) of the 362 proteins are affected in SARS-CoV-2 infection via altered expression, interaction with viral components, or modification by phosphorylation or ubiquitination, at least 186 (59%) of which are known autoAgs. These proteins are associated with gene expression, mRNA processing, mRNA splicing, translation, protein folding, vesicles, and chromosome organization. Numerous nuclear autoAgs were identified, including both classical ANAs and ENAs of systemic autoimmune diseases and unique autoAgs involved in the DNA replication fork, mitotic cell cycle, or telomerase maintenance. We also identified many uncommon autoAgs involved in nucleic acid and peptide biosynthesis and nucleocytoplasmic transport, such as aminoacyl-tRNA synthetases. In addition, this study found autoAgs that potentially interact with multiple SARS-CoV-2 Nsp and Orf components, including CCT/TriC chaperonin, insulin degrading enzyme, platelet-activating factor acetylhydrolase, and the ezrin-moesin-radixin family. Furthermore, B-cell-specific IgM-associated ER complex (including MBZ1, BiP, heat shock proteins, and protein disulfide-isomerases) is enriched by DS-affinity and up-regulated in B-cells of COVID-19 patients, and a similar IgH-associated ER complex was also identified in autoreactive pre-B1 cells in our previous study, which suggests a role of autoreactive B1 cells in COVID-19 that merits further investigation. In summary, this study demonstrates that virally infected cells are characterized by alterations of proteins with propensity to become autoAgs, thereby providing a possible explanation for infection-induced autoimmunity. The COVID autoantigen-ome provides a valuable molecular resource and map for investigation of COVID-related autoimmune sequelae and considerations for vaccine design.

Study on the Antipyretic Mechanism of Baihu Decoction: Network Pharmacology Prediction and Experimental Verification

2021 ◽  
Vol 15 (3) ◽  
pp. 334-341
Author(s):  
Jiahang Zuo ◽  
Hongbo Ye ◽  
He Lin ◽  
Guangfu Lv ◽  
Yuchen Wang ◽  
...  
Keyword(s):  
Biological Function ◽  
Kegg Pathway ◽  
Function Analysis ◽  
Hypoxia Inducible Factor ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Antipyretic Effect ◽  
Hypoxia Inducible Factor 1 ◽  
Forkhead Box ◽  
Pathway Analyses

To better understand the antipyretic mechanism of Baihu decoction, the network pharmacology was used to predict its antipyretic components, targets, functions and pathways, and the prediction results were experimentally verified. BATMAN-TCM was used to obtain the components of Baihu decoction, GeneCards was used to screen fever related targets, STRING was used to analyze the protein interaction network of the selected targets. Bioconductor software was used to analyze the gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway, and one of the KEGG pathway analyses was performed by cell inflammation model, and was verified by experiments. In the results, total 263 compounds were screened out, 54 potential antipyretic targets were identified, 84 items were obtained by GO function analysis, and 29 pathways were obtained by KEGG analysis, including hypoxia inducible factor-1, Forkhead box O (FOXO) Ras related protein 1 (Rap1), nuclear factor-κ (NF-κB) and other signalling pathways. In the verification experiment of NF-κB signalling pathway, the expression of NF-κB, Inhibitory kappa B kinase beta (IκKβ) and IκBα protein were significantly difference between the Baihu decoction group (P < 0.01) and the model group (P < 0.05), suggesting that Baihu decoction plays the antipyretic effect by affecting IκKβ, Inhibitory kappa B alpha (IκBα) and NF-κB. In conclusion, the interaction of multiple targets in the antipyretic effect of Baihu Decoction and its biological function and pathways were preliminarily demonstrated.

scholarly journals Comprehensive Analysis of a Long Noncoding RNA-Associated Competing Endogenous RNA Network in Wilms Tumor

2020 ◽  
Vol 27 (2) ◽  
pp. 107327482093699
Author(s):  
Feng Zhang ◽  
Liping Zeng ◽  
Qinming Cai ◽  
Zihao Xu ◽  
Ruida Liu ◽  
...  
Keyword(s):  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Wilms Tumor ◽  
Interaction Network ◽  
Tumor Stage ◽  
Messenger Rnas ◽  
Competing Endogenous Rna ◽  
Ontology Term ◽  
Normal Tissues ◽  
Pathway Analyses

Long noncoding RNA (lncRNA) plays crucial roles in various biological processes of different cancers, especially acting as a competing endogenous RNA (ceRNA). However, the role of lncRNA-mediated ceRNA in Wilms tumor (WT), which is the most common malignant kidney cancer in children, remains unknown. In present study, RNA sequence profiles and clinical data of 125 patients with WT consisting of 119 tumor and 6 normal tissues from Therapeutically Applicable Research To Generate Effective Treatments database were analyzed. A total of 1833 lncRNAs, 156 microRNAs (miRNAs), and 3443 messenger RNAs (mRNAs) were identified as differentially expressed (DE) using “DESeq2” package. The lncRNA-miRNA-mRNA ceRNA regulatory network involving 748 DElncRNAs, 33 DEmiRNAs, and 189 DEmRNAs was constructed based on miRcode, Targetscan, miRTarBase, and miRDB database. Gene Ontology term and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that DEmRNAs were mainly enriched in cell proliferation-related processes and tumor-related pathways, respectively, and 13 hub genes were identified by a protein–protein interaction network. Survival analysis detected 48 lncRNAs, 7 miRNAs, and 16 mRNAs to have significant impact on the overall survival of patients with WT. Additionally, we found that 6 DElncRNAs with potential prognostic value were correlated with tumor stage ( DENND5B-AS1) and histologic classification ( TMPO-AS1, RP3-523K23.2, RP11-598F7.3, LAMP5-AS1, and AC013275.2) of patients with WT. Our research provides a great insight into understanding the molecular mechanism underlying occurrence and progression of WT, as well as the potential to develop targeted therapies and prognostic biomarkers.

scholarly journals Exploring genes of rectal cancer for new treatments based on protein interaction network

2016 ◽  
Author(s):  
wenjing Teng ◽  
Yan Li ◽  
Chao Zhou
Keyword(s):  
Rectal Cancer ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Molecular Complexes ◽  
Cellular Protein ◽  
Cancer Genes ◽  
Protein Protein Interaction ◽  
New Treatments ◽  
Protein Protein Interaction Network

Objective: To develop a protein-protein interaction network of rectal cancer, which is based on genetic genes as well as to predict biological pathways underlying the molecular complexes in the network. In order to analyze and summarize genetic markers related to diagnosis and prognosis of rectal cancer. Methods: the genes expression profile was downloaded from OMIM (Online Mendelian Inheritance in Man) database; the protein-protein interaction network of rectal cancer was established by Cytoscape; the molecular complexes in the network were detected by Clusterviz plugin and the pathways enrichment of molecular complexes were performed by DAVID online and Bingo (The Biological Networks Gene Ontology tool). Results and Discussion: A total of 127 rectal cancer genes were identified to differentially express in OMIM Database. The protein-protein interaction network of rectal cancer was contained 966 nodes (proteins), 3377 edges (interactive relationships) and 7 molecular complexes (score>7.0). Regulatory effects of genes and proteins were focused on cell cycle, transcription regulation and cellular protein metabolic process. Genes of DDK1, sparcl1, wisp2, cux1, pabpc1, ptk2 and htra1 were significant nodes in PPI network. The discovery of featured genes which were probably related to rectal cancer, has a great significance on studying mechanism, distinguishing normal and cancer tissues, and exploring new treatments for rectal cancer.

scholarly journals Association Between Depression and Breast Cancer: TNF/TNFRSF1β and LEP/LEPR Axis

2022 ◽  
Author(s):  
Jiaying Lin ◽  
Guangman Cui ◽  
Wenwei Jiang ◽  
Zhousheng Lin ◽  
Xinyue Lan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Interaction Network ◽  
Epidemiological Studies ◽  
Gene Expression Omnibus ◽  
Inflammatory Factors ◽  
Biological Mechanism ◽  
Breast Cancer Patients ◽  
Protein Protein Interaction ◽  
Genes Encoding ◽  
Pathway Analyses

Abstract Depression contributes to enhanced initiation, development and metastasis of breast cancer. Despite epidemiological studies and experimental data suggest that depression and breast cancer may share a common biological mechanism, the results from these studies remain inconsistent. Here, we fully focus on the underlying biological mechanism behind the adverse effects of depression against breast cancer patients, and highlight the practical therapeutic intervention and improving quality of life. Publicly available datasets deposited in the Gene Expression Omnibus (GEO) were downloaded. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses of the differentially expressed genes (DEGs), which were extracted by using R tools, were performed. The protein-protein interaction network of the target DEGs was constructed using Cytoscape software and the hub genes were identified. In our study, we found that genes encoding proinflammatory cytokine, such as IL-1β and TNF, had significantly increased expression in depression. Following chronically stimulated by TNFα and IL-1β (usually for 14-18 days), inflammatory cancer-associated fibroblasts (CAFs) had elevated expression of inflammatory genes. Furthermore, the TNF/TNFRSF1β and LEP/LEPR regulatory axes were proven to be hub pathways of the crosstalk between depression and breast cancer. Our findings demonstrate that inflammatory factors are messengers linking depression and breast cancer, and provided further guidance in clinical medication.

scholarly journals Transcriptomic and proteomic analyses of a new cytoplasmic male sterile line with a wild Gossypium bickii genetic background

BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Haiyan Zhao ◽  
Jianshe Wang ◽  
Yunfang Qu ◽  
Renhai Peng ◽  
Richard Odongo Magwanga ◽  
...  
Keyword(s):  
Genetic Background ◽  
Developmental Stages ◽  
Interaction Network ◽  
Differentially Expressed ◽  
Future Research ◽  
Glutathione S Transferase ◽  
Male Sterile ◽  
Genomic Databases ◽  
Wild Cotton ◽  
Pathway Analyses

Abstract Background Cotton is an important fiber crop but has serious heterosis effects, and cytoplasmic male sterility (CMS) is the major cause of heterosis in plants. However, to the best of our knowledge, no studies have investigated CMS Yamian A in cotton with the genetic background of Australian wild Gossypium bickii. Conjoint transcriptomic and proteomic analysis was first performed between Yamian A and its maintainer Yamian B. Results We detected 550 differentially expressed transcript-derived fragments (TDFs) and at least 1013 proteins in anthers at various developmental stages. Forty-two TDFs and 11 differentially expressed proteins (DEPs) were annotated by analysis in the genomic databases of G. austral, G. arboreum and G. hirsutum. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed to better understand the functions of these TDFs and DEPs. Transcriptomic and proteomic results showed that UDP-glucuronosyl/UDP-glucosyltransferase, 60S ribosomal protein L13a-4-like, and glutathione S-transferase were upregulated; while heat shock protein Hsp20, ATPase, F0 complex, and subunit D were downregulated at the microspore abortion stage of Yamian A. In addition, several TDFs from the transcriptome and several DEPs from the proteome were detected and confirmed by quantitative real-time PCR as being expressed in the buds of seven different periods of development. We established the databases of differentially expressed genes and proteins between Yamian A and its maintainer Yamian B in the anthers at various developmental stages and constructed an interaction network based on the databases for a comprehensive understanding of the mechanism underlying CMS with a wild cotton genetic background. Conclusion We first analyzed the molecular mechanism of CMS Yamian A from the perspective of omics, thereby providing an experimental basis and theoretical foundation for future research attempting to analyze the abortion mechanism of new CMS with a wild Gossypium bickii background and to realize three-line matching.

scholarly journals Predicting the Mechanism of the Analgesic Property of Yanhusuo Based on Network Pharmacology

2019 ◽  
Vol 14 (10) ◽  
pp. 1934578X1988307
Author(s):  
Wen-Ping Xiao ◽  
Yan-Fang Yang ◽  
He-Zhen Wu ◽  
Yi-yi Xiong
Keyword(s):  
Molecular Docking ◽  
Metabolic Pathways ◽  
Interaction Network ◽  
Binding Activity ◽  
Network Pharmacology ◽  
Active Components ◽  
Network Diagram ◽  
Pathway Interaction ◽  
Pathway Interaction Network ◽  
Pathway Analyses

Yanhusuo (Corydalis Rhizoma) extracts are widely used for the treatment of pain and inflammation. The effects of Yanhusuo in pain assays were assessed in a few studies. However, there are few studies on its analgesic mechanism. In this paper, network pharmacology was used to explore the analgesic components of Yanhusuo and its analgesic mechanism. The active components of Yanhusuo were screened by TCMSP database, combined with literature data. PharmMapper and GeneCards databases were used for screening the analgesic targets of the components. The protein interaction network diagram was drawn by String database and Cytoscape software, the gene ontology and KEGG pathway analyses of the target were performed by DAVID database, and the component–target–pathway interaction network diagram was further drawn by Cytoscape3.6.1 software. System Dock Web Site verified the molecular docking among components and targets. Finally, an interaction network of the component–target–pathway of Yanhusuo was constructed, and the functions and pathways were analyzed for preliminarily investigating the mechanism of Yanhusuo in analgesia. The results showed that the active components of analgesic in Yanhusuo were Corynoline, 13-methylpalmatrubine, dehydrocorydaline, saulatine, 2,3,9,10-tetramethoxy-13-methyl-5,6-dihydroisoquinolino[2,1-b]isoquinolin-8-on-e, and Capaurine. The mechanisms were involved in metabolic pathways, PI3k-Akt signaling pathway, pathways in cancer, and so on. The top 3 targets were NOS3, glucose-6-phosphate dehydrogenase, and glucose-6-phosphate isomerase in components-target-pathways network, and they were all enriched in metabolic pathways. Meanwhile the molecular docking showed that there was a high binding activity between the 6 components and the important target proteins, as a further certification for the subsequent network analysis. This study reveals the relationship of the components, targets, and pathways of active components in Yanhusuo, and provides new ideas and methods for further research on the analgesic mechanism of Yanhusuo.

scholarly journals Integrated Analysis of Hub Genes and miRNAs in Dilated Cardiomyopathy

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Kai Huang ◽  
Shuyan Wen ◽  
Jiechun Huang ◽  
Fangrui Wang ◽  
Liewen Pang ◽  
...  
Keyword(s):  
Dilated Cardiomyopathy ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Regulatory Subunit ◽  
Integrated Analysis ◽  
Hub Genes ◽  
Using Data ◽  
Phosphoinositide 3 Kinase ◽  
Pathway Analyses ◽  
Inhibitor Of Dna Binding

Purpose. The aim of this study is to identify hub genes and miRNAs by the miRNA-mRNA interaction network in dilated cardiomyopathy (DCM) disease. Methods. The differentially expressed miRNAs (DEMis) and mRNAs (DEMs) were selected using data of DCM patients downloaded from the GEO database (GSE112556 and GSE3585). Gene Ontology (GO) pathway analysis and transcription factor enrichment analysis were used for selecting DEMis, and the target mRNAs of DEMis were filtered by using miRDB, miRTarBase, and TargetScan. Cytoscape software was used to visualize the network between miRNAs and mRNAs and calculate the hub genes. GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to analyze the mRNAs in the regulatory network. Results. A total of 9 DEMis and 281 DEMs were selected, from which we reconstructed the miRNA-mRNA network consisting of 7 miRNAs and 51 mRNAs. The top 10 nodes, miR-144-3p, miR-363-3p, miR-9-3p, miR-21-3p, miR-144-5p, miR-338-3p, ID4 (inhibitor of DNA binding/differentiation 4), miR-770-5p, PIK3R1 (p85α regulatory subunit of phosphoinositide 3-kinase (PI3K)), and FN1 (fibronectin 1), were identified as important regulators. Conclusions. The study uncovered several important hub genes and miRNAs involved in the pathogenesis of DCM, among which, the miR-144-3p/FN1 and miR-9-3p/FN1 pathways may play an important role in myocardial fibrosis, which can help identify the etiology of DCM, and provide potential therapeutic targets.

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