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Akca MN, Kasavi C. Identifying new molecular signatures and potential therapeutics for idiopathic pulmonary fibrosis: a network medicine approach. Mamm Genome 2024:10.1007/s00335-024-10069-w. [PMID: 39254743 DOI: 10.1007/s00335-024-10069-w] [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: 06/22/2024] [Accepted: 08/31/2024] [Indexed: 09/11/2024]
Abstract
Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease characterized by excessive collagen deposition and fibrosis of the lung parenchyma, leading to respiratory failure. The molecular mechanisms underlying IPF pathogenesis remain incompletely understood, hindering the development of effective therapeutic strategies. We have used a network medicine approach to comprehensively analyze molecular interactions and identify novel molecular signatures and potential therapeutics associated with IPF progression. Our integrative analysis revealed dysregulated molecular networks that are central to IPF pathophysiology. We have highlighted key molecular players and signaling pathways that are implicated in aberrant fibrotic processes. This systems-level understanding enables the identification of new biomarkers and therapeutic targets for IPF, providing potential avenues for precision medicine. Drug repurposing analysis revealed several drug candidates with anti-fibrotic, anti-inflammatory, and anti-cancer activities that could potentially slow fibrotic progression and improve patient outcomes. This study offers new insights into the molecular underpinnings of IPF and highlights network medicine approaches in uncovering complex disease mechanisms. The molecular signatures and therapeutic targets identified hold promise for developing precision therapies tailored to individual patients, ultimately advancing the management of this debilitating lung disease.
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Affiliation(s)
- Mecbure Nur Akca
- Department of Bioengineering, Faculty of Engineering, Marmara University, İstanbul, Türkiye
| | - Ceyda Kasavi
- Department of Bioengineering, Faculty of Engineering, Marmara University, İstanbul, Türkiye.
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Alamin MH, Rahaman MM, Ferdousi F, Sarker A, Ali MA, Hossen MB, Sarker B, Kumar N, Mollah MNH. In-silico discovery of common molecular signatures for which SARS-CoV-2 infections and lung diseases stimulate each other, and drug repurposing. PLoS One 2024; 19:e0304425. [PMID: 39024368 PMCID: PMC11257407 DOI: 10.1371/journal.pone.0304425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 05/12/2024] [Indexed: 07/20/2024] Open
Abstract
COVID-19 caused by SARS-CoV-2 is a global health issue. It is yet a severe risk factor to the patients, who are also suffering from one or more chronic diseases including different lung diseases. In this study, we explored common molecular signatures for which SARS-CoV-2 infections and different lung diseases stimulate each other, and associated candidate drug molecules. We identified both SARS-CoV-2 infections and different lung diseases (Asthma, Tuberculosis, Cystic Fibrosis, Pneumonia, Emphysema, Bronchitis, IPF, ILD, and COPD) causing top-ranked 11 shared genes (STAT1, TLR4, CXCL10, CCL2, JUN, DDX58, IRF7, ICAM1, MX2, IRF9 and ISG15) as the hub of the shared differentially expressed genes (hub-sDEGs). The gene ontology (GO) and pathway enrichment analyses of hub-sDEGs revealed some crucial common pathogenetic processes of SARS-CoV-2 infections and different lung diseases. The regulatory network analysis of hub-sDEGs detected top-ranked 6 TFs proteins and 6 micro RNAs as the key transcriptional and post-transcriptional regulatory factors of hub-sDEGs, respectively. Then we proposed hub-sDEGs guided top-ranked three repurposable drug molecules (Entrectinib, Imatinib, and Nilotinib), for the treatment against COVID-19 with different lung diseases. This recommendation is based on the results obtained from molecular docking analysis using the AutoDock Vina and GLIDE module of Schrödinger. The selected drug molecules were optimized through density functional theory (DFT) and observing their good chemical stability. Finally, we explored the binding stability of the highest-ranked receptor protein RELA with top-ordered three drugs (Entrectinib, Imatinib, and Nilotinib) through 100 ns molecular dynamic (MD) simulations with YASARA and Desmond module of Schrödinger and observed their consistent performance. Therefore, the findings of this study might be useful resources for the diagnosis and therapies of COVID-19 patients who are also suffering from one or more lung diseases.
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Affiliation(s)
- Muhammad Habibulla Alamin
- Faculty of Science, Department of Statistics, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh
| | - Md. Matiur Rahaman
- Faculty of Science, Department of Statistics, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh
- Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Zhejiang University, Haining, P. R. China
| | - Farzana Ferdousi
- Faculty of Science, Department of Statistics, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh
| | - Arnob Sarker
- Faculty of Science, Department of Biochemistry and Molecular Biology, University of Rajshahi, Rajshahi, Bangladesh
- Faculty of Science, Department of Statistics, Bioinformatics Laboratory (Dry), University of Rajshahi, Rajshahi, Bangladesh
| | - Md. Ahad Ali
- Faculty of Science, Department of Statistics, Bioinformatics Laboratory (Dry), University of Rajshahi, Rajshahi, Bangladesh
- Faculty of Science, Department of Chemistry, University of Rajshahi, Rajshahi, Bangladesh
| | - Md. Bayazid Hossen
- Faculty of Science, Department of Statistics, Bioinformatics Laboratory (Dry), University of Rajshahi, Rajshahi, Bangladesh
- Department of Agricultural and Applied Statistics, Bangladesh Agricultural University, Mymensingh, Bangladesh
| | - Bandhan Sarker
- Faculty of Science, Department of Statistics, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh
| | - Nishith Kumar
- Faculty of Science, Department of Statistics, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh
| | - Md. Nurul Haque Mollah
- Faculty of Science, Department of Statistics, Bioinformatics Laboratory (Dry), University of Rajshahi, Rajshahi, Bangladesh
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Xu J, Abdulsalam Khaleel R, Zaidan HK, Faisal Mutee A, Fahmi Fawy K, Gehlot A, Abbas AH, Arias Gonzáles JL, Amin AH, Ruiz-Balvin MC, Imannezhad S, Bahrami A, Akhavan-Sigari R. Discovery of common molecular signatures and drug repurposing for COVID-19/Asthma comorbidity: ACE2 and multi-partite networks. Cell Cycle 2024; 23:405-434. [PMID: 38640424 DOI: 10.1080/15384101.2024.2340859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 04/04/2024] [Indexed: 04/21/2024] Open
Abstract
Angiotensin-converting enzyme 2 (ACE2) is identified as the functional receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the ongoing global coronavirus disease-2019 (COVID-19) pandemic. This study aimed to elucidate potential therapeutic avenues by scrutinizing approved drugs through the identification of the genetic signature associated with SARS-CoV-2 infection in individuals with asthma. This exploration was conducted through an integrated analysis, encompassing interaction networks between the ACE2 receptor and common host (co-host) factors implicated in COVID-19/asthma comorbidity. The comprehensive analysis involved the identification of common differentially expressed genes (cDEGs) and hub-cDEGs, functional annotations, interaction networks, gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), and module construction. Interaction networks were used to identify overlapping disease modules and potential drug targets. Computational biology and molecular docking analyzes were utilized to discern functional drug modules. Subsequently, the impact of the identified drugs on the expression of hub-cDEGs was experimentally validated using a mouse model. A total of 153 cDEGs or co-host factors associated with ACE2 were identified in the COVID-19 and asthma comorbidity. Among these, seven significant cDEGs and proteins - namely, HRAS, IFNG, JUN, CDH1, TLR4, ICAM1, and SCD-were recognized as pivotal host factors linked to ACE2. Regulatory network analysis of hub-cDEGs revealed eight top-ranked transcription factors (TFs) proteins and nine microRNAs as key regulatory factors operating at the transcriptional and post-transcriptional levels, respectively. Molecular docking simulations led to the proposal of 10 top-ranked repurposable drug molecules (Rapamycin, Ivermectin, Everolimus, Quercetin, Estradiol, Entrectinib, Nilotinib, Conivaptan, Radotinib, and Venetoclax) as potential treatment options for COVID-19 in individuals with comorbid asthma. Validation analysis demonstrated that Rapamycin effectively inhibited ICAM1 expression in the HDM-stimulated mice group (p < 0.01). This study unveils the common pathogenesis and genetic signature underlying asthma and SARS-CoV-2 infection, delineated by the interaction networks of ACE2-related host factors. These findings provide valuable insights for the design and discovery of drugs aimed at more effective therapeutics within the context of lung disease comorbidities.
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Affiliation(s)
- Jiajun Xu
- College of Veterinary & Life Sciences, the University of Glasgow, Glasgow, UK
| | | | | | | | - Khaled Fahmi Fawy
- Department of Chemistry, Faculty of Science, King Khalid University, Abha, Saudi Arabia
| | - Anita Gehlot
- Uttaranchal Institute of Technology, Uttaranchal University, Dehradun, India
| | | | - José Luis Arias Gonzáles
- Department of Social Sciences, Faculty of Social Studies, University of British Columbia, Vancouver, Canada
| | - Ali H Amin
- Zoology Department, Faculty of Science, Mansoura University, Mansoura, Egypt
| | | | - Shima Imannezhad
- Department of Pediatrics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Abolfazl Bahrami
- Biomedical Center for Systems Biology Science Munich, Ludwig-Maximilians-University, Munich, Germany
- Department of Animal Science, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
| | - Reza Akhavan-Sigari
- Department of Neurosurgery, University Medical Center Tuebingen, Tuebingen, Germany
- Department of Health Care Management and Clinical Research, Collegium Humanum, Warsaw, Poland
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Huang T, He J, Zhou X, Pan H, He F, Du A, Yu B, Jiang N, Li X, Yuan K, Wang Z. Discovering common pathogenetic processes between COVID-19 and tuberculosis by bioinformatics and system biology approach. Front Cell Infect Microbiol 2023; 13:1280223. [PMID: 38162574 PMCID: PMC10757339 DOI: 10.3389/fcimb.2023.1280223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Accepted: 11/07/2023] [Indexed: 01/03/2024] Open
Abstract
Introduction The coronavirus disease 2019 (COVID-19) pandemic, stemming from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has persistently threatened the global health system. Meanwhile, tuberculosis (TB) caused by Mycobacterium tuberculosis (M. tuberculosis) still continues to be endemic in various regions of the world. There is a certain degree of similarity between the clinical features of COVID-19 and TB, but the underlying common pathogenetic processes between COVID-19 and TB are not well understood. Methods To elucidate the common pathogenetic processes between COVID-19 and TB, we implemented bioinformatics and systematic research to obtain shared pathways and molecular biomarkers. Here, the RNA-seq datasets (GSE196822 and GSE126614) are used to extract shared differentially expressed genes (DEGs) of COVID-19 and TB. The common DEGs were used to identify common pathways, hub genes, transcriptional regulatory networks, and potential drugs. Results A total of 96 common DEGs were selected for subsequent analyses. Functional enrichment analyses showed that viral genome replication and immune-related pathways collectively contributed to the development and progression of TB and COVID-19. Based on the protein-protein interaction (PPI) network analysis, we identified 10 hub genes, including IFI44L, ISG15, MX1, IFI44, OASL, RSAD2, GBP1, OAS1, IFI6, and HERC5. Subsequently, the transcription factor (TF)-gene interaction and microRNA (miRNA)-gene coregulatory network identified 61 TFs and 29 miRNAs. Notably, we identified 10 potential drugs to treat TB and COVID-19, namely suloctidil, prenylamine, acetohexamide, terfenadine, prochlorperazine, 3'-azido-3'-deoxythymidine, chlorophyllin, etoposide, clioquinol, and propofol. Conclusion This research provides novel strategies and valuable references for the treatment of tuberculosis and COVID-19.
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Affiliation(s)
- Tengda Huang
- Division of Liver Surgery, Department of General Surgery and Laboratory of Liver Surgery, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
| | - Jinyi He
- Division of Liver Surgery, Department of General Surgery and Laboratory of Liver Surgery, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
| | - Xinyi Zhou
- Division of Liver Surgery, Department of General Surgery and Laboratory of Liver Surgery, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
| | - Hongyuan Pan
- Division of Liver Surgery, Department of General Surgery and Laboratory of Liver Surgery, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
| | - Fang He
- Center of Infectious Diseases, West China Hospital, Sichuan University, Chengdu, China
| | - Ao Du
- Division of Liver Surgery, Department of General Surgery and Laboratory of Liver Surgery, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
| | - Bingxuan Yu
- Division of Liver Surgery, Department of General Surgery and Laboratory of Liver Surgery, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
| | - Nan Jiang
- Division of Liver Surgery, Department of General Surgery and Laboratory of Liver Surgery, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
| | - Xiaoquan Li
- Division of Liver Surgery, Department of General Surgery and Laboratory of Liver Surgery, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
| | - Kefei Yuan
- Division of Liver Surgery, Department of General Surgery and Laboratory of Liver Surgery, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
| | - Zhen Wang
- Division of Liver Surgery, Department of General Surgery and Laboratory of Liver Surgery, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
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Rabby MG, Rahman MH, Islam MN, Kamal MM, Biswas M, Bonny M, Hasan MM. In silico identification and functional prediction of differentially expressed genes in South Asian populations associated with type 2 diabetes. PLoS One 2023; 18:e0294399. [PMID: 38096208 PMCID: PMC10721103 DOI: 10.1371/journal.pone.0294399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Accepted: 11/01/2023] [Indexed: 12/17/2023] Open
Abstract
Type 2 diabetes (T2D) is one of the major metabolic disorders in humans caused by hyperglycemia and insulin resistance syndrome. Although significant genetic effects on T2D pathogenesis are experimentally proved, the molecular mechanism of T2D in South Asian Populations (SAPs) is still limited. Hence, the current research analyzed two Gene Expression Omnibus (GEO) and 17 Genome-Wide Association Studies (GWAS) datasets associated with T2D in SAP to identify DEGs (differentially expressed genes). The identified DEGs were further analyzed to explore the molecular mechanism of T2D pathogenesis following a series of bioinformatics approaches. Following PPI (Protein-Protein Interaction), 867 potential DEGs and nine hub genes were identified that might play significant roles in T2D pathogenesis. Interestingly, CTNNB1 and RUNX2 hub genes were found to be unique for T2D pathogenesis in SAPs. Then, the GO (Gene Ontology) showed the potential biological, molecular, and cellular functions of the DEGs. The target genes also interacted with different pathways of T2D pathogenesis. In fact, 118 genes (including HNF1A and TCF7L2 hub genes) were directly associated with T2D pathogenesis. Indeed, eight key miRNAs among 2582 significantly interacted with the target genes. Even 64 genes were downregulated by 367 FDA-approved drugs. Interestingly, 11 genes showed a wide range (9-43) of drug specificity. Hence, the identified DEGs may guide to elucidate the molecular mechanism of T2D pathogenesis in SAPs. Therefore, integrating the research findings of the potential roles of DEGs and candidate drug-mediated downregulation of marker genes, future drugs or treatments could be developed to treat T2D in SAPs.
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Affiliation(s)
- Md. Golam Rabby
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Md. Hafizur Rahman
- Department of Agro Product Processing Technology, Jashore University of Science and Technology, Khulna, Bangladesh
- Faculty of Food Sciences and Safety, Department of Quality Control and Safety Management, Khulna Agricultural University, Khulna, Bangladesh
| | - Md. Numan Islam
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Md. Mostafa Kamal
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Mrityunjoy Biswas
- Department of Agro Product Processing Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Mantasa Bonny
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Md. Mahmudul Hasan
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
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Upadhyay A, Pal D, Kumar A. Deciphering Target Protein Cascade in Salmonella typhi Biofilm using Genomic Data Mining, and Protein-protein Interaction. Curr Genomics 2023; 24:100-109. [PMID: 37994324 PMCID: PMC10662377 DOI: 10.2174/1389202924666230815144126] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 05/17/2023] [Accepted: 07/05/2023] [Indexed: 11/24/2023] Open
Abstract
Background Salmonella typhi biofilm confers a serious public health issue for lengthy periods and the rise in antibiotic resistance and death rate. Biofilm generation has rendered even the most potent antibiotics ineffective in controlling the illness, and the S. typhi outbreak has turned into a fatal disease typhoid. S. typhi infection has also been connected to other deadly illnesses, such as a gall bladder cancer. The virulence of this disease is due to the interaction of numerous genes and proteins of S. typhi. Objective The study aimed to identify a cascade of target proteins in S. typhi biofilm condition with the help of genomic data mining and protein-protein interaction analysis. Methods The goal of this study was to notice some important pharmacological targets in S. typhi. using genomic data mining, and protein-protein interaction approaches were used so that new drugs could be developed to combat the disease. Results In this study, we identified 15 potential target proteins that are critical for S. typhi biofilm growth and maturation. Three proteins, CsgD, AdrA, and BcsA, were deciphered with their significant role in the synthesis of cellulose, a critical component of biofilm's extracellular matrix. The CsgD protein was also shown to have high interconnectedness and strong interactions with other important target proteins of S. typhi. As a result, it has been concluded that CsgD is involved in a range of activities, including cellulose synthesis, bacterial pathogenicity, quorum sensing, and bacterial virulence. Conclusion All identified targets in this study possess hydrophobic properties, and their cellular localization offered proof of a potent therapeutic target. Overall results of this study, drug target shortage in S. typhi is also spotlighted, and we believe that obtained result could be useful for the design and development of some potent anti-salmonella agents for typhoid fever in the future.
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Affiliation(s)
- Aditya Upadhyay
- Department of Biotechnology, National Institute of Technology Raipur, Raipur, 492010 (CG), India
| | - Dharm Pal
- Department of Chemical Engineering, National Institute of Technology Raipur, Raipur, 492010 (CG), India
| | - Awanish Kumar
- Department of Biotechnology, National Institute of Technology Raipur, Raipur, 492010 (CG), India
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Xi YJ, Guo Q, Zhang R, Duan GS, Zhang SX. Identifying cellular senescence associated genes involved in the progression of end-stage renal disease as new biomarkers. BMC Nephrol 2023; 24:231. [PMID: 37553608 PMCID: PMC10408218 DOI: 10.1186/s12882-023-03285-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 07/28/2023] [Indexed: 08/10/2023] Open
Abstract
BACKGROUND Cellular senescence plays an essential role in the development and progression of end-stage renal disease (ESRD). However, the detailed mechanisms phenomenon remains unclear. METHODS The mRNA expression profiling dataset GSE37171 was taken from the Gene Expression Omnibus (GEO) database. The cell senescence-associated hub genes were selected by applying protein-protein interaction (PPI), followed by correlation analysis, gene interaction analysis, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. We next explored the relationships of hub genes with miRNAs, TFs, and diseases. The absolute abundance of eight immune cells and two stromal cells were calculated by MCPcount and the correlation of hub genes with these ten cells was analyzed. Lasso was used to selecting for trait genes. ROC curves and DCA decision curves were used to assess the accuracy and predictive power of the trait genes. RESULTS A total of 65 cellular senescence signature genes were identified among patients and controls. The PPI network screened out ten hub genes. GO and KEGG indicated that ten hub genes were associated with ESRD progression. Transcription factor gene interactions and common regulatory networks of miRNAs were also identified in the datasets. The hub genes were significantly correlated with immune cells and stromal cells. Then the lasso model was constructed to screen out the five most relevant signature genes (FOS, FOXO3, SIRT1, TP53, SMARCA4). The area under the ROC curve (AUC) showed that these five characteristic genes have good resolving power for the diagnostic model. CONCLUSIONS Our findings suggested that cellular senescence-associated genes played an important role in the development of ESRD and immune regulation.
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Affiliation(s)
- Yu-Jia Xi
- Department of Urology, Second Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China
- Key Laboratory of Cellular Physiology at Shanxi Medical University, Ministry of Education, Taiyuan, Shanxi Province, China
| | - Qiang Guo
- Department of Urology, Second Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Ran Zhang
- School of Public Health, Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Guo-Sheng Duan
- Fifth School of Clinical Medicine, Shanxi Provincial People's Hospital, Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Sheng-Xiao Zhang
- Key Laboratory of Cellular Physiology at Shanxi Medical University, Ministry of Education, Taiyuan, Shanxi Province, China.
- Department of Rheumatology, Second Hospital of Shanxi Medical University, 382 Wuyi Road, Taiyuan, 030001, Shanxi Province, China.
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Zhou H, Xu M, Hu P, Li Y, Ren C, Li M, Pan Y, Wang S, Liu X. Identifying hub genes and common biological pathways between COVID-19 and benign prostatic hyperplasia by machine learning algorithms. Front Immunol 2023; 14:1172724. [PMID: 37426635 PMCID: PMC10328422 DOI: 10.3389/fimmu.2023.1172724] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 06/07/2023] [Indexed: 07/11/2023] Open
Abstract
Background COVID-19, a serious respiratory disease that has the potential to affect numerous organs, is a serious threat to the health of people around the world. The objective of this article is to investigate the potential biological targets and mechanisms by which SARS-CoV-2 affects benign prostatic hyperplasia (BPH) and related symptoms. Methods We downloaded the COVID-19 datasets (GSE157103 and GSE166253) and the BPH datasets (GSE7307 and GSE132714) from the Gene Expression Omnibus (GEO) database. In GSE157103 and GSE7307, differentially expressed genes (DEGs) were found using the "Limma" package, and the intersection was utilized to obtain common DEGs. Further analyses followed, including those using Protein-Protein Interaction (PPI), Gene Ontology (GO) function enrichment analysis, and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Potential hub genes were screened using three machine learning methods, and they were later verified using GSE132714 and GSE166253. The CIBERSORT analysis and the identification of transcription factors, miRNAs, and drugs as candidates were among the subsequent analyses. Results We identified 97 common DEGs from GSE157103 and GSE7307. According to the GO and KEGG analyses, the primary gene enrichment pathways were immune-related pathways. Machine learning methods were used to identify five hub genes (BIRC5, DNAJC4, DTL, LILRB2, and NDC80). They had good diagnostic properties in the training sets and were validated in the validation sets. According to CIBERSORT analysis, hub genes were closely related to CD4 memory activated of T cells, T cells regulatory and NK cells activated. The top 10 drug candidates (lucanthone, phytoestrogens, etoposide, dasatinib, piroxicam, pyrvinium, rapamycin, niclosamide, genistein, and testosterone) will also be evaluated by the P value, which is expected to be helpful for the treatment of COVID-19-infected patients with BPH. Conclusion Our findings reveal common signaling pathways, possible biological targets, and promising small molecule drugs for BPH and COVID-19. This is crucial to understand the potential common pathogenic and susceptibility pathways between them.
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Affiliation(s)
- Hang Zhou
- Department of Urology, Tianjin Medical University General Hospital, Tianjin, China
| | - Mingming Xu
- Department of Urology, Tianjin Medical University General Hospital, Tianjin, China
| | - Ping Hu
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, China
| | - Yuezheng Li
- Department of Urology, Tianjin Medical University General Hospital, Tianjin, China
| | - Congzhe Ren
- Department of Urology, Tianjin Medical University General Hospital, Tianjin, China
| | - Muwei Li
- Department of Urology, Tianjin Medical University General Hospital, Tianjin, China
| | - Yang Pan
- Department of Urology, Tianjin Medical University General Hospital, Tianjin, China
| | - Shangren Wang
- Department of Urology, Tianjin Medical University General Hospital, Tianjin, China
| | - Xiaoqiang Liu
- Department of Urology, Tianjin Medical University General Hospital, Tianjin, China
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Dasgupta S, Das SS, Patidar S, Kajaria V, Chowdhury SR, Chaudhury K. Identification of Common Dysregulated Genes in COVID-19 and Hypersensitivity Pneumonitis: A Systems Biology and Machine Learning Approach. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2023; 27:205-214. [PMID: 37062762 DOI: 10.1089/omi.2022.0171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
A comprehensive knowledge on systems biology of severe acute respiratory syndrome coronavirus 2 is crucial for differential diagnosis of COVID-19. Interestingly, the radiological and pathological features of COVID-19 mimic that of hypersensitivity pneumonitis (HP), another pulmonary fibrotic phenotype. This motivated us to explore the overlapping pathophysiology of COVID-19 and HP, if any, and using a systems biology approach. Two datasets were obtained from the Gene Expression Omnibus database (GSE147507 and GSE150910) and common differentially expressed genes (DEGs) for both diseases identified. Fourteen common DEGs, significantly altered in both diseases, were found to be implicated in complement activation and growth factor activity. A total of five microRNAs (hsa-miR-1-3p, hsa-miR-20a-5p, hsa-miR-107, hsa-miR-16-5p, and hsa-miR-34b-5p) and five transcription factors (KLF6, ZBTB7A, ELF1, NFIL3, and ZBT33) exhibited highest interaction with these common genes. Next, C3, CFB, MMP-9, and IL1A were identified as common hub genes for both COVID-19 and HP. Finally, these top-ranked genes (hub genes) were evaluated using random forest classifier to discriminate between the disease and control group (coronavirus disease 2019 [COVID-19] vs. controls, and HP vs. controls). This supervised machine learning approach demonstrated 100% and 87.6% accuracy in differentiating COVID-19 from controls, and HP from controls, respectively. These findings provide new molecular leads that inform COVID-19 and HP diagnostics and therapeutics research and innovation.
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Affiliation(s)
- Sanjukta Dasgupta
- School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, India
| | - Sankha Subhra Das
- Department of Human Genetics, University of California Los Angeles (UCLA), Los Angeles, California, USA
| | - Sankalp Patidar
- Department of Biotechnology, Indian Institute of Technology Kharagpur, Kharagpur, India
| | - Vaibhav Kajaria
- Department of Pulmonology, Fortis Hospital Anandapur, Kolkata, India
| | | | - Koel Chaudhury
- School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, India
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Pergolizzi JV, LeQuang JA, Varrassi M, Breve F, Magnusson P, Varrassi G. What Do We Need to Know About Rising Rates of Idiopathic Pulmonary Fibrosis? A Narrative Review and Update. Adv Ther 2023; 40:1334-1346. [PMID: 36692679 PMCID: PMC9872080 DOI: 10.1007/s12325-022-02395-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 11/30/2022] [Indexed: 01/25/2023]
Abstract
The most common type of idiopathic interstitial pneumonia is idiopathic pulmonary fibrosis (IPF), an irreversible, progressive disorder that has lately come into question for possible associations with COVID-19. With few geographical exceptions, IPF is a rare disease but its prevalence has been increasing markedly since before the pandemic. Environmental exposures are frequently implicated in IPF although genetic factors play a role as well. In IPF, healthy lung tissue is progressively replaced with an abnormal extracellular matrix that impedes normal alveolar function while, at the same time, natural repair mechanisms become dysregulated. While chronic viral infections are known risk factors for IPF, acute infections are not and the link to COVID-19 has not been established. Macrophagy may be a frontline defense against any number of inflammatory pulmonary diseases, and the inflammatory cascade that may occur in patients with COVID-19 may disrupt the activity of monocytes and macrophages in clearing up fibrosis and remodeling lung tissue. It is unclear if COVID-19 infection is a risk factor for IPF, but the two can occur in the same patient with complicating effects. In light of its increasing prevalence, further study of IPF and its diagnosis and treatment is warranted.
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Affiliation(s)
| | | | - Marco Varrassi
- Department of Radiology, University of L'Aquila, L'Aquila, Italy
| | | | - Peter Magnusson
- Institution of Medical Sciences, Orebro University, Orebro, Sweden
- Institute of Medicine, Karolinska Institutet, Stockholm, Sweden
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Islam MA, Kibria MK, Hossen MB, Reza MS, Tasmia SA, Tuly KF, Mosharof MP, Kabir SR, Kabir MH, Mollah MNH. Bioinformatics-based investigation on the genetic influence between SARS-CoV-2 infections and idiopathic pulmonary fibrosis (IPF) diseases, and drug repurposing. Sci Rep 2023; 13:4685. [PMID: 36949176 PMCID: PMC10031699 DOI: 10.1038/s41598-023-31276-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Accepted: 03/09/2023] [Indexed: 03/24/2023] Open
Abstract
Some recent studies showed that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and idiopathic pulmonary fibrosis (IPF) disease might stimulate each other through the shared genes. Therefore, in this study, an attempt was made to explore common genomic biomarkers for SARS-CoV-2 infections and IPF disease highlighting their functions, pathways, regulators and associated drug molecules. At first, we identified 32 statistically significant common differentially expressed genes (cDEGs) between disease (SARS-CoV-2 and IPF) and control samples of RNA-Seq profiles by using a statistical r-package (edgeR). Then we detected 10 cDEGs (CXCR4, TNFAIP3, VCAM1, NLRP3, TNFAIP6, SELE, MX2, IRF4, UBD and CH25H) out of 32 as the common hub genes (cHubGs) by the protein-protein interaction (PPI) network analysis. The cHubGs regulatory network analysis detected few key TFs-proteins and miRNAs as the transcriptional and post-transcriptional regulators of cHubGs. The cDEGs-set enrichment analysis identified some crucial SARS-CoV-2 and IPF causing common molecular mechanisms including biological processes, molecular functions, cellular components and signaling pathways. Then, we suggested the cHubGs-guided top-ranked 10 candidate drug molecules (Tegobuvir, Nilotinib, Digoxin, Proscillaridin, Simeprevir, Sorafenib, Torin 2, Rapamycin, Vancomycin and Hesperidin) for the treatment against SARS-CoV-2 infections with IFP diseases as comorbidity. Finally, we investigated the resistance performance of our proposed drug molecules compare to the already published molecules, against the state-of-the-art alternatives publicly available top-ranked independent receptors by molecular docking analysis. Molecular docking results suggested that our proposed drug molecules would be more effective compare to the already published drug molecules. Thus, the findings of this study might be played a vital role for diagnosis and therapies of SARS-CoV-2 infections with IPF disease as comorbidity risk.
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Affiliation(s)
- Md Ariful Islam
- Bioinformatics Lab(Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Md Kaderi Kibria
- Bioinformatics Lab(Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Md Bayazid Hossen
- Bioinformatics Lab(Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Md Selim Reza
- Bioinformatics Lab(Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Samme Amena Tasmia
- Bioinformatics Lab(Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Khanis Farhana Tuly
- Bioinformatics Lab(Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Md Parvez Mosharof
- Bioinformatics Lab(Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh
- School of Business, University of Southern Queensland, Toowoomba, QLD, 4350, Australia
| | - Syed Rashel Kabir
- Department of Biochemistry and Molecular Biology, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Md Hadiul Kabir
- Bioinformatics Lab(Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Md Nurul Haque Mollah
- Bioinformatics Lab(Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh.
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Cao J, Li L, Xiong L, Wang C, Chen Y, Zhang X. Research on the mechanism of berberine in the treatment of COVID-19 pneumonia pulmonary fibrosis using network pharmacology and molecular docking. PHYTOMEDICINE PLUS : INTERNATIONAL JOURNAL OF PHYTOTHERAPY AND PHYTOPHARMACOLOGY 2022; 2:100252. [PMID: 35403089 PMCID: PMC8895682 DOI: 10.1016/j.phyplu.2022.100252] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 02/24/2022] [Accepted: 03/02/2022] [Indexed: 05/14/2023]
Abstract
Purpose Pulmonary fibrosis caused by COVID-19 pneumonia is a serious complication of COVID-19 infection, there is a lack of effective treatment methods clinically. This article explored the mechanism of action of berberine in the treatment of COVID-19 (Corona Virus Disease 2019, COVID-19) pneumonia pulmonary fibrosis with the help of the network pharmacology and molecular docking. Methods We predicted the role of berberine protein targets with the Pharmmapper database and the 3D structure of berberine in the Pubchem database. And GeneCards database was used in order to search disease target genes and screen common target genes. Then we used STRING web to construct PPI interaction network of common target protein. The common target genes were analyzed by GO and KEGG by DAVID database. The disease-core target gene-drug network was established and molecular docking was used for prediction. We also analyzed the binding free energy and simulates molecular dynamics of complexes. Results Berberine had 250 gene targets, COVID-19 pneumonia pulmonary fibrosis had 191 gene targets, the intersection of which was 23 in common gene targets. Molecular docking showed that berberine was associated with CCl2, IL-6, STAT3 and TNF-α. GO and KEGG analysis reveals that berberine mainly plays a vital role by the signaling pathways of influenza, inflammation and immune response. Conclusion Berberine acts on TNF-α, STAT3, IL-6, CCL2 and other targets to inhibit inflammation and the activation of fibrocytes to achieve the purpose of treating COVID-19 pneumonia pulmonary fibrosis.
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Key Words
- ARDS, acute respiratory distress syndrome
- BP, biological process
- Berberine
- CC, cellular component
- CCL2, chemokine ligand2
- COVID-19
- COVID-19 pneumonia
- COVID-19, corona virus disease 2019
- ECM, extracellular matrix
- EMT, epithelial-mesenchymal cell transformation
- FOXM1, forkhead box M1
- Fsp1, fibroblast-specific protein 1
- GO, gene ontology
- HIF-1, hypoxia inducible factor
- IBD, inflammatory bowel disease
- IL-12, interleukin 12
- IL-6, interleukin 6
- JAK, Janus kinase
- KEGG, Kyoto encyclopedia of genes and genomes
- LR-MSCs, mesenchymal stem cells
- MF, molecular function
- MMP14, matrix metalloproteinase 14
- MMP7, matrix metalloproteinase 7
- Molecular docking
- NF-κB, nuclear transcription factor
- NOS, nitric oxide synthase
- Network pharmacology
- OTUB1, deubiquitinase
- PAI-1, plasminogen activator inhibitor 1
- PPI, protein-protein interaction
- Pulmonary fibrosis
- STAT3, transcription activator
- TGF-β, transforming growth factor-β
- TNF-α, tumor necrosis factor-α
- sIL-6R, interleukin 6 receptor
- α-SMA, α-smooth muscle actin
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Affiliation(s)
- Junfeng Cao
- Clinical Laboratory Medicine, Chengdu Medical College, Chengdu, China
| | - Lianglei Li
- Center for Experimental Technology of Preclinical Medicine, Chengdu Medical College, No.783 Xindu Road, Xindu District, Chengdu, Sichuan 610500, China
| | - Li Xiong
- Clinical Laboratory Medicine, Chengdu Medical College, Chengdu, China
| | - Chaochao Wang
- Clinical Laboratory Medicine, Chengdu Medical College, Chengdu, China
| | - Yijun Chen
- Clinical Laboratory Medicine, Chengdu Medical College, Chengdu, China
| | - Xiao Zhang
- Center for Experimental Technology of Preclinical Medicine, Chengdu Medical College, No.783 Xindu Road, Xindu District, Chengdu, Sichuan 610500, China
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