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Bai X, Zhang W, Yu T. Integrative bioinformatics analysis identifies APOB as a critical biomarker in coronary in-stent restenosis. Biomark Med 2023; 17:983-998. [PMID: 38223945 DOI: 10.2217/bmm-2023-0507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2024] Open
Abstract
Aim: Coronary artery disease (CAD) is a major contributor to the worldwide prevalence of cardiovascular disease. In-stent restenosis (ISR) is a common complication which can lead to stent implantation failure, necessitating repeated intervention and presenting a significant obstacle for CAD management. Methods: To accurately assess and determine the hub genes associated with ISR, CAD databases from the Gene Expression Omnibus were utilized and weighted gene coexpression network analysis was employed to identify key genes in blood samples. Results: APOB was identified as a risk gene for ISR occurrence. Subsequent correlation analysis of APOB demonstrated a positive association with ISR. Clinical validation further confirmed the predictive value of APOB in ISR detection. Conclusion: We have identified APOB as a critical predictive biomarker for ISR in CAD patients.
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Affiliation(s)
- Xinghua Bai
- Department of Cardiovascular Medicine, The First People's Hospital of Linping District, Hangzhou, 311100, PR China
| | - Weizong Zhang
- Department of Cardiovascular Medicine, The First People's Hospital of Linping District, Hangzhou, 311100, PR China
| | - Tao Yu
- Department of Cardiovascular Medicine, The First People's Hospital of Linping District, Hangzhou, 311100, PR China
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Qi B, Wang HY, Ma X, Chi YF, Gui C. Identification of the Key Genes of Immune Infiltration in Dilated Cardiomyopathy. Int Heart J 2023; 64:1054-1064. [PMID: 37967988 DOI: 10.1536/ihj.23-182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2023]
Abstract
Dilated cardiomyopathy (DCM) is a common cause of heart failure. In this study, we screened the immune infiltration-related genes associated with DCM to explore the potential molecular mechanisms and provide a basis for the early diagnosis and development of new immunotherapeutic targets. A dataset related to DCM was downloaded from the Gene Expression Omnibus (GEO) database. R software was applied to the genetic differential analysis of patients with DCM and healthy individuals, and the obtained differential expressed genes (DEGs) were screened for differentially expressed immune-related genes (DEIRGs) after comparison with the immune microsatellite database. Gene functional analysis established a protein interaction network (PPI). The immune infiltration in patients with DCM versus normal controls was assessed using the CIBERSORT algorithm, the hub genes were screened using the MOCDE app, and the hubs were validated in multiple datasets. A total of 246 DEGs were screened (adj. P < 0.05 and |logFC| > 0.3), and a total of 170 DEIRGs were compared. Gene Ontology analysis showed significant (adj. P < 0.05) Biological Process entries of 591, Cellular Component of 10, and Molecular Function of 39; Kyoto Encyclopedia of Genes and Genomes showed 20 significant entries, mainly focused on cytokines involved in immune-related response, etc. A protein interaction network comprising 28 hub DEGs was constructed in combination with the PPI network interactions. DEIRG was mainly distributed in the T-cell receptor pathway by immune infiltration detection analysis, and significant changes in central memory T-cells were found by analyzing T-cell-related subpathways, where INSR, HLA-B, IFITM1, and HBEGF were significantly differentially expressed. We selected 632 hospitalized patients for validation and found that INSR and HLA-B expression were associated with DCM development by Nomogram. The expression of HLA-B in peripheral blood T-cells was higher in DCM patients than in the normal group, as verified by qRT-PCR. However, the detailed mechanism needs to be further explored.
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Affiliation(s)
- Bin Qi
- Department of Cardiology, First Affiliated Hospital, Guangxi Medical University
| | - Hai-Yan Wang
- Department of Cardiology, First Affiliated Hospital, Guangxi Medical University
| | - Xiao Ma
- Department of Cardiology, First Affiliated Hospital, Guangxi Medical University
| | - Yu-Feng Chi
- Department of Cardiology, First Affiliated Hospital, Guangxi Medical University
| | - Chun Gui
- Department of Cardiology, First Affiliated Hospital, Guangxi Medical University
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Cao DM, Liang QF, Zhang ZT, He WJ, Tang D. Combination of UHPLC-Q Exactive-Orbitrap MS, Bioinformatics and Molecular Docking to Reveal the Mechanism of Huan-Lian-Jie-Du Decoction in the Treatment of Diabetic Encephalopathy. Chem Biodivers 2023; 20:e202300434. [PMID: 37486314 DOI: 10.1002/cbdv.202300434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 07/18/2023] [Accepted: 07/21/2023] [Indexed: 07/25/2023]
Abstract
Diabetic encephalopathy (DE) is a serious complication of diabetes, which affects patients' quality of life. We aimed to explore HLJDD in the treatment of DE by LC/MS and bioinformatics. UPLC-Q Exactive-Orbitrap MS was employed to clarify the compounds. The modules and hub targets of DE were gained from WGCNA. Subsequently, an Herb-Compound-Target network was constructed and enrichment analysis was used. In addition, a protein-protein interaction (PPI) network was constructed and molecular docking was used to verify the above analysis. As result, 138 compounds and 10 prototypes in brain were identified. In network pharmacology, 8 modules and 5692 hub targets were obtained from WGCNA. An Herb-Compound-Target network was constructed by 4 herbs, 10 compounds and 56 targets. The enrichment analysis showed that the treatment of DE with HLJDD involve oxidative stress and neuroprotection. Beside, SRC, JUN, STAT3, MAPK1 and PIK3R1 were identified and as hub targets of HLJDD in treating DE. Moreover, Molecular docking showed that five hub targets had strong affinity with the corresponding alkaloids. Therefore, we explored the underlying mechanisms of HLJDD in the treatment of DE and to provide the theoretical and scientific basis for subsequent experimental studies and clinical applications.
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Affiliation(s)
- Dong-Min Cao
- Key Laboratory of Digital Quality Evaluation of Chinese Materia Medica of State Administration of TCM and Engineering and Technology Research Center for Chinese Materia Medica Quality of Guangdong Province, Guangdong Pharmaceutical University, Guangdong, 510006, China
- Translational Medicine Research Institute, First People's Hospital of, Foshan, Guangdong, 528000, China
| | - Qing-Feng Liang
- Key Laboratory of Digital Quality Evaluation of Chinese Materia Medica of State Administration of TCM and Engineering and Technology Research Center for Chinese Materia Medica Quality of Guangdong Province, Guangdong Pharmaceutical University, Guangdong, 510006, China
| | - Zhi-Tong Zhang
- Key Laboratory of Digital Quality Evaluation of Chinese Materia Medica of State Administration of TCM and Engineering and Technology Research Center for Chinese Materia Medica Quality of Guangdong Province, Guangdong Pharmaceutical University, Guangdong, 510006, China
| | - Wen-Jiao He
- Key Laboratory of Digital Quality Evaluation of Chinese Materia Medica of State Administration of TCM and Engineering and Technology Research Center for Chinese Materia Medica Quality of Guangdong Province, Guangdong Pharmaceutical University, Guangdong, 510006, China
| | - Dan Tang
- Key Laboratory of Digital Quality Evaluation of Chinese Materia Medica of State Administration of TCM and Engineering and Technology Research Center for Chinese Materia Medica Quality of Guangdong Province, Guangdong Pharmaceutical University, Guangdong, 510006, China
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Yoon E, Zhang W, Cai Y, Peng C, Zhou D. Identification and Validation of Key Gene Modules and Pathways in Coronary Artery Disease Development and Progression. Crit Rev Eukaryot Gene Expr 2023; 33:81-90. [PMID: 37602455 DOI: 10.1615/critreveukaryotgeneexpr.2023039631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/22/2023]
Abstract
The development and progression of atherosclerosis represent a chronic process involving complex molecular interactions. Therefore, identifying the potential hub genes and pathways contributing to coronary artery disease (CAD) development is essential for understanding its underlying molecular mechanisms. To this end, we performed transcriptome analysis of peripheral venous blood collected from 100 patients who were divided into four groups according to disease severity, including 27 patients in the atherosclerosis group, 22 patients in the stable angina group, 35 patients in the acute myocardial infarction group, and 16 controls. Weighted gene co-expression network analysis was performed using R programming. Significant module-trait correlations were identified according to module membership and genetic significance. Metascape was used for the functional enrichment of differentially expressed genes between groups, and the hub genes were identified via protein-protein interaction network analysis. The hub genes were further validated by analyzing Gene Expression Omnibus (GSE48060 and GSE141512) datasets. A total of 9,633 messenger ribonucleic acids were detected in three modules, among which the blue module was highly correlated with the Gensini score. The hub genes were significantly enriched in the myeloid leukocyte activation pathway, suggesting its important role in the progression of atherosclerosis. Among these genes, the Mediterranean fever gene (MEFV) may play a key role in the progression of atherosclerosis and CAD severity.
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Affiliation(s)
- Ewnji Yoon
- Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, Guangdong, 518057, PR China; Research Center for Biomedical Information Technology, Shenzhen Institutes of Advanced Technologies, Chinese Academy of Sciences, Shenzhen, Guangdong, 518055, PR China
| | - Wenjing Zhang
- Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, Guangdong, 518057, PR China
| | - Yunpeng Cai
- Research Center for Biomedical Information Technology, Shenzhen Institutes of Advanced Technologies, Chinese Academy of Sciences, Shenzhen, Guangdong, 518055, PR China
| | - Changnong Peng
- Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, Guangdong, 518057, PR China
| | - Daxin Zhou
- Department of Cardiology, Shanghai Institute of Cardiovascular Disease, Zhongshan Hospital, Fudan University, Shanghai, China
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Shen M, Gong R, Li H, Yang Z, Wang Y, Li D. Identification of key molecular markers of acute coronary syndrome using peripheral blood transcriptome sequencing analysis and mRNA-lncRNA co-expression network construction. Bioengineered 2021; 12:12087-12106. [PMID: 34753383 PMCID: PMC8809957 DOI: 10.1080/21655979.2021.2003932] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
Acute coronary syndrome (ACS) is a term used to describe major cardiovascular diseases, and treatment of in-stent restenosis in patients with ACS remains a major clinical challenge. Further investigation into molecular markers of ACS may aid early diagnosis, and the treatment of ACS and post-treatment recurrence. In the present study, total RNA was extracted from the peripheral blood samples of 3 patients with ACS, 3 patients with percutaneous coronary intervention (PCI)_non-restenosis, 3 patients with PCI_restenosis and 3 healthy controls. Subsequently, RNA library construction and high-throughput sequencing were performed. DESeq2 package in R was used to screen genes that were differentially expressed between the different samples. Moreover, the intersection of the differentially expressed mRNAs (DEmRNAs) and differentially expressed long noncoding RNAs (DElncRNAs) obtained. GeneCodis4.0 was used to perform function enrichment for DEmRNAs, and lncRNA-mRNA co-expression network was constructed. The GSE60993 dataset was utilized for diagnostic analysis, and the aforementioned investigations were verified using in vitro studies. Results of the present study revealed a large number of DEmRNAs and DElncRNAs in the different groups. We selected genes in the top 10 of differential expression and also involved in the co-expression of lncRNA-mRNA for diagnostic analysis in the GSE60993 dataset. The area under curve (AUC) of PDZK1IP1 (0.747), PROK2 (0.769) and LAMP3 (0.725) were all >0.7. These results indicated that the identified mRNAs and lncRNAs may act as potential clinical biomarkers, and more specifically, PDZK1IP1, PROK2 and LAMP3 may act as potential biomarkers for the diagnosis of ACS.
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Affiliation(s)
- Ming Shen
- Department of Cardiology, The First Hospital of Hebei Medical University
| | - Rui Gong
- Department of internal medicine-Endocrinology, Children's Hospital of Hebei
| | - Haibin Li
- Department of General Medicine, the Third Hospital of Hebei Medical University
| | - Zhihui Yang
- Department of General Medicine, the Third Hospital of Hebei Medical University
| | - Yunpeng Wang
- Department of General Medicine, the Third Hospital of Hebei Medical University
| | - Dandan Li
- Department of General Medicine, the Third Hospital of Hebei Medical University
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Zheng K, Cai Y, Lei Y, Liu Y, Sun Z, Wang Y, Xu X, Zhang Z. Proteomic characteristics of beryllium sulfate-induced differentially expressed proteins in rats. Toxicol Res (Camb) 2021; 10:962-974. [PMID: 34733481 DOI: 10.1093/toxres/tfab051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 04/06/2021] [Accepted: 05/10/2021] [Indexed: 11/12/2022] Open
Abstract
Sprague Dawley rats were exposed to beryllium sulfate (BeSO4), and proteomic and bioinformatic techniques were applied to screen for differentially expressed proteins in their lung tissue and serum. A total of 12 coexpression modules were constructed for 18 samples with 2333 proteins. Four modules were found to have significant differences in the regulation of protein coexpression modules in the serum following exposure to BeSO4. A further three modules had significant differences in the regulation of protein coexpression modules in the lung tissues. Five modules with good correlation were obtained by calculating the gene significance and module membership values, whereas these module Hub proteins included: Hspbp1, Rps15a, Srsf2, Hadhb, Elmo3, Armt1, Rpl18, Afap1L1, Eif3d, Eif3c, and Rps3. The five proteins correlating highest with the Hub proteins in the lung tissue and serum samples were obtained using string analysis. KEGG and GO enrichment analyses showed that these proteins are mainly involved in ribosome formation, apoptosis, cell cycle regulation, and tumor necrosis factor regulation. By analyzing the biological functions of these proteins, proteins that can be used as biomarkers, such as Akt1, Prpf19, Cct2, and Rpl18, are finally obtained.
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Affiliation(s)
- Kai Zheng
- School of public health, University of South China, Hengyang, Hunan 421001, China
| | - Ying Cai
- School of public health, University of South China, Hengyang, Hunan 421001, China
| | - Yuandi Lei
- School of public health, University of South China, Hengyang, Hunan 421001, China
| | - Yanping Liu
- School of public health, University of South China, Hengyang, Hunan 421001, China
| | - Zhanbing Sun
- School of public health, University of South China, Hengyang, Hunan 421001, China
| | - Ye Wang
- School of public health, University of South China, Hengyang, Hunan 421001, China
| | - Xinyun Xu
- Institute of Environment and Health, Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong 518055, China
| | - Zhaohui Zhang
- School of public health, University of South China, Hengyang, Hunan 421001, China
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Hasankhani A, Bahrami A, Sheybani N, Fatehi F, Abadeh R, Ghaem Maghami Farahani H, Bahreini Behzadi MR, Javanmard G, Isapour S, Khadem H, Barkema HW. Integrated Network Analysis to Identify Key Modules and Potential Hub Genes Involved in Bovine Respiratory Disease: A Systems Biology Approach. Front Genet 2021; 12:753839. [PMID: 34733317 PMCID: PMC8559434 DOI: 10.3389/fgene.2021.753839] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 09/28/2021] [Indexed: 12/11/2022] Open
Abstract
Background: Bovine respiratory disease (BRD) is the most common disease in the beef and dairy cattle industry. BRD is a multifactorial disease resulting from the interaction between environmental stressors and infectious agents. However, the molecular mechanisms underlying BRD are not fully understood yet. Therefore, this study aimed to use a systems biology approach to systematically evaluate this disorder to better understand the molecular mechanisms responsible for BRD. Methods: Previously published RNA-seq data from whole blood of 18 healthy and 25 BRD samples were downloaded from the Gene Expression Omnibus (GEO) and then analyzed. Next, two distinct methods of weighted gene coexpression network analysis (WGCNA), i.e., module-trait relationships (MTRs) and module preservation (MP) analysis were used to identify significant highly correlated modules with clinical traits of BRD and non-preserved modules between healthy and BRD samples, respectively. After identifying respective modules by the two mentioned methods of WGCNA, functional enrichment analysis was performed to extract the modules that are biologically related to BRD. Gene coexpression networks based on the hub genes from the candidate modules were then integrated with protein-protein interaction (PPI) networks to identify hub-hub genes and potential transcription factors (TFs). Results: Four significant highly correlated modules with clinical traits of BRD as well as 29 non-preserved modules were identified by MTRs and MP methods, respectively. Among them, two significant highly correlated modules (identified by MTRs) and six nonpreserved modules (identified by MP) were biologically associated with immune response, pulmonary inflammation, and pathogenesis of BRD. After aggregation of gene coexpression networks based on the hub genes with PPI networks, a total of 307 hub-hub genes were identified in the eight candidate modules. Interestingly, most of these hub-hub genes were reported to play an important role in the immune response and BRD pathogenesis. Among the eight candidate modules, the turquoise (identified by MTRs) and purple (identified by MP) modules were highly biologically enriched in BRD. Moreover, STAT1, STAT2, STAT3, IRF7, and IRF9 TFs were suggested to play an important role in the immune system during BRD by regulating the coexpressed genes of these modules. Additionally, a gene set containing several hub-hub genes was identified in the eight candidate modules, such as TLR2, TLR4, IL10, SOCS3, GZMB, ANXA1, ANXA5, PTEN, SGK1, IFI6, ISG15, MX1, MX2, OAS2, IFIH1, DDX58, DHX58, RSAD2, IFI44, IFI44L, EIF2AK2, ISG20, IFIT5, IFITM3, OAS1Y, HERC5, and PRF1, which are potentially critical during infection with agents of bovine respiratory disease complex (BRDC). Conclusion: This study not only helps us to better understand the molecular mechanisms responsible for BRD but also suggested eight candidate modules along with several promising hub-hub genes as diagnosis biomarkers and therapeutic targets for BRD.
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Affiliation(s)
- Aliakbar Hasankhani
- Department of Animal Science, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
| | - Abolfazl Bahrami
- Department of Animal Science, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
- Biomedical Center for Systems Biology Science Munich, Ludwig-Maximilians-University, Munich, Germany
| | - Negin Sheybani
- Department of Animal and Poultry Science, College of Aburaihan, University of Tehran, Tehran, Iran
| | - Farhang Fatehi
- Department of Animal Science, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
| | - Roxana Abadeh
- Department of Animal Science, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | | | | | - Ghazaleh Javanmard
- Department of Animal Science, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
| | - Sadegh Isapour
- Department of Animal Science, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
| | - Hosein Khadem
- Department of Agronomy and Plant Breeding, University of Tehran, Karaj, Iran
| | - Herman W. Barkema
- Department of Production Animal Health, Faculty of Veterinary Medicine, University of Calgary, Calgary, AB, Canada
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