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Zhang Y, Zhang D, Jiao X, Yue X, Cai B, Lu S, Xu R. Uncovering the shared neuro-immune-related regulatory mechanisms between spinal cord injury and osteoarthritis. Heliyon 2024; 10:e30336. [PMID: 38707272 PMCID: PMC11068815 DOI: 10.1016/j.heliyon.2024.e30336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 04/21/2024] [Accepted: 04/24/2024] [Indexed: 05/07/2024] Open
Abstract
Adults with spinal cord injury (SCI), a destructive neurological injury, have a significantly higher incidence of osteoarthritis (OA), a highly prevalent chronic joint disorder. This study aimed to dissect the neuroimmune-related regulatory mechanisms of SCI and OA using bioinformatics analysis. Using microarray data from the Gene Expression Omnibus database, differentially expressed genes (DEGs) were screened between SCI and sham samples and between OA and control samples. Common DEGs were used to construct a protein-protein interaction (PPI) network. Weighted gene co-expression network analysis (WGCNA) was used to mine SCI- and OA-related modules. Shared miRNAs were identified, and target genes were predicted using the Human MicroRNA Disease Database (HMDD) database. A miRNA-gene-pathway regulatory network was constructed with overlapping genes, miRNAs, and significantly enriched pathways. Finally, the expression of the identified genes and miRNAs was verified using RT-qPCR. In both the SCI and OA groups, 185 common DEGs were identified, and three hub clusters were obtained from the PPI network. WGCNA revealed three SCI-related modules and two OA-related modules. There were 43 overlapping genes between the PPI network clusters and the WGCNA network modules. Seventeen miRNAs shared between patients with SCI and OA were identified. A regulatory network consisting of five genes, six miRNAs, and six signaling pathways was constructed. Upregulation of CD44, TGFBR1, CCR5, and IGF1, while lower levels of miR-125b-5p, miR-130a-3p, miR-16-5p, miR-204-5p, and miR-204-3p in both SCI and OA were successfully verified using RT-qPCR. Our study suggests that a miRNA-gene-pathway network is implicated in the neuroimmune-related regulatory mechanisms of SCI and OA. CD44, TGFBR1, CCR5, and IGF1, and their related miRNAs (miR-125b-5p, miR-130a-3p, miR-16-5p, miR-204-5p, and miR-204-3p) may serve as promising biomarkers and candidate therapeutic targets for SCI and OA.
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Affiliation(s)
- Yuxin Zhang
- Department of Rehabilitation Medicine, Fengcheng branch, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
- Department of Oral Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, College of Stomatology, Shanghai Jiao Tong University, National Center for Stomatology, National Clinical Research Center for Oral Diseases, Shanghai Key Laboratory of Stomatology, Shanghai, 200011, China
- Shanghai Key Laboratory of Orthopedic Implants, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Dahe Zhang
- Department of Oral Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, College of Stomatology, Shanghai Jiao Tong University, National Center for Stomatology, National Clinical Research Center for Oral Diseases, Shanghai Key Laboratory of Stomatology, Shanghai, 200011, China
| | - Xin Jiao
- Shanghai Key Laboratory of Orthopedic Implants, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Xiaokun Yue
- Shanghai Key Laboratory of Orthopedic Implants, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Bin Cai
- Department of Rehabilitation Medicine, Fengcheng branch, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Shenji Lu
- Department of Rehabilitation Medicine, Fengcheng branch, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Renjie Xu
- Department of Rehabilitation Medicine, Kunshan Rehabilitation Hospital, Suzhou 210000, Jiangsu, China
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Chen Y, You N, Yang C, Zhang J. Helicobacter pylori infection increases the risk of carotid plaque formation: Clinical samples combined with bioinformatics analysis. Heliyon 2023; 9:e20037. [PMID: 37809782 PMCID: PMC10559771 DOI: 10.1016/j.heliyon.2023.e20037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 07/19/2023] [Accepted: 09/08/2023] [Indexed: 10/10/2023] Open
Abstract
Objective Infection with Helicobacter pylori (H. pylori) may increase atherosclerosis, which can lead to carotid plaque formation. Our study examined the relationship between H. pylori infection and carotid plaque formation, and its underlying mechanisms. Methods A total of 36,470 people who underwent physical examination in Taizhou Hospital Health Examination Center from June 2017 to June 2022 were included in this study. All people participated in the urease test, neck ultrasound, blood pressure detection, anthropometric measurement and biochemical laboratory examination. In addition, the GSE27411 and GSE28829 datasets in the Gene Expression Omnibus (GEO) database were used to analyze the mechanism of H. pylori infection and atherosclerosis progression. Results H. pylori infection, sex, age, blood lipids, blood pressure, fasting blood glucose, glycated hemoglobin and body mass index were risk factors for carotid plaque formation. An independent risk factor was still evident in the multivariate logistic regression analysis, indicating H. pylori infection. Furthermore, after weighted gene coexpression network analysis (WGCNA), we discovered 555 genes linked to both H. pylori infection and the advancement of atherosclerosis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed a strong correlation between these genes and immunity, infection, and immune disorders. SsGSEA analysis showed that H. pylori infection and atherosclerosis included changes in the immune microenvironment. Finally, three genes MS4A6A, ADAMDEC1 and AQP9 were identified to be involved in the formation of atherosclerosis after H. pylori infection. Conclusion: Our research affirms that H. pylori is a unique contributor to the formation of carotid plaque, examines the immune microenvironment associated with H. pylori infection and advanced carotid atherosclerosis, and offers fresh perspectives on how H. pylori infection leads to atherosclerosis.
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Affiliation(s)
- Yi Chen
- Departments of Gastroenterology, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, China
| | - Ningning You
- Departments of Gastroenterology, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, China
| | - Chaoyu Yang
- Departments of Gastroenterology, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, China
| | - Jinshun Zhang
- Health Management Center, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, China
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Gene-Based Network Analysis Reveals Prognostic Biomarkers Implicated in Diabetic Tubulointerstitial Injury. DISEASE MARKERS 2022; 2022:2700392. [PMID: 36092962 PMCID: PMC9452978 DOI: 10.1155/2022/2700392] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 08/16/2022] [Indexed: 12/25/2022]
Abstract
Background Diabetic nephropathy (DN), a significant cause of chronic kidney disease (CKD), is a devastating disease worldwide. Objective The aim of this study was to reveal crucial genes closely linked to the molecular mechanism of tubulointerstitial injury in DN. Methods The Gene Expression Omnibus (GEO) database was used to download the datasets. Based on this, a weighted gene coexpression network analysis (WGCNA) network was constructed to detect DN-related modules and hub genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichments were performed on the selected hub genes and modules. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed on the obtained gene signature. Results The WGCNA network was constructed based on 3019 genes, and nine gene coexpression modules were generated. A total of 57 genes, including 34 genes in the magenta module and 23 genes in the purple module, were adapted as hub genes. 61 significantly downregulated and 119 upregulated genes were screened as differentially expressed genes (DEGs). 25 overlapping genes between hub genes chosen from WGCNA and DEG were identified. Through LASSO analysis, a 9-gene signature may be a potential prognostic biomarker for DN. To further explore the potential mechanism of DN, the different immune cell infiltrations between tubulointerstitial samples of DN and healthy samples were estimated. Conclusions This bioinformatics study identified CX3CR1, HRG, LTF, TUBA1A, GADD45B, PDK4, CLIC5, NDNF, and SOCS2 as candidate biomarkers for the diagnosis of DN. Moreover, DN tends to own a higher proportion of memory B cell.
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Bian W, Wang Z, Li X, Jiang X, Zhang H, Liu Z, Zhang D. Identification of vital modules and genes associated with heart failure based on weighted gene coexpression network analysis. ESC Heart Fail 2022; 9:1370-1379. [PMID: 35128826 PMCID: PMC8934958 DOI: 10.1002/ehf2.13827] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 01/11/2022] [Accepted: 01/14/2022] [Indexed: 12/04/2022] Open
Abstract
Aims Heart failure (HF) is a chronic heart disease with a high incidence and mortality. Due to the regulatory complexity of gene coexpression networks, the underlying hub genes regulation in HF remain incompletely appreciated. We aimed to explore potential key modules and genes for HF using weighted gene coexpression network analysis (WGCNA). Methods and results The expression profiles by high throughput sequencing of heart tissues samples from HF and non‐HF samples were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between HF and non‐HF samples were firstly identified. Then, a coexpression network was constructed to identify key modules and potential hub genes. The biological functions of potential hub genes were analysed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Finally, a protein–protein interaction (PPI) network was constructed using the STRING online tool. A total of 135 DEGs (133 up‐regulated and 2 down‐regulated DEGs) between HF and non‐HF samples were identified in the GSE135055 and GSE123976 datasets. Moreover, a total of 38 modules were screened based on WGCNA in the GSE135055 dataset, and six potential hub genes (UCK2, ASB1, CCNI, CUX1, IRX6, and STX16) were screened from the key module by setting the gene significance over 0.2 and the module membership over 0.8. Furthermore, 78 potential hub genes were obtained by taking the intersection of the 135 DEGs and all genes in the key module, and enrichment analysis revealed that they were mainly involved in the MAPK and PI3K‐AKT signalling pathways. Finally, in a PPI network constructed with the 78 potential hub genes, CUX1 and ASB1 were identified as hub genes in HF because they were also identified as potential hub genes in the WGCNA. Conclusions To the best of our knowledge, our study is the first to employ WGCNA to identify the key module and hub genes for HF. Our study identified a module and two genes that might play important roles in HF, which may provide potential biomarkers for the diagnosis of HF and improve our knowledge of the molecular mechanisms underlying HF.
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Affiliation(s)
- Weikang Bian
- Department of Cardiology Nanjing First Hospital, Nanjing Medical University 68 Changle Road Nanjing 210006 China
| | - Zhicheng Wang
- Department of Cardiology Nanjing First Hospital, Nanjing Medical University 68 Changle Road Nanjing 210006 China
| | - Xiaobo Li
- Department of Cardiology Nanjing First Hospital, Nanjing Medical University 68 Changle Road Nanjing 210006 China
| | - Xiao‐Xin Jiang
- Department of Cardiology Nanjing First Hospital, Nanjing Medical University 68 Changle Road Nanjing 210006 China
| | - Hongsong Zhang
- Department of Cardiology Nanjing First Hospital, Nanjing Medical University 68 Changle Road Nanjing 210006 China
| | - Zhizhong Liu
- Department of Cardiology Nanjing First Hospital, Nanjing Medical University 68 Changle Road Nanjing 210006 China
| | - Dai‐Min Zhang
- Department of Cardiology Nanjing First Hospital, Nanjing Medical University 68 Changle Road Nanjing 210006 China
- Department of Cardiology Sir Run Run Hospital, Nanjing Medical University Nanjing China
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Napoli C, Benincasa G, Ellahham S. Precision Medicine in Patients with Differential Diabetic Phenotypes: Novel Opportunities from Network Medicine. Curr Diabetes Rev 2022; 18:e221221199301. [PMID: 34951369 DOI: 10.2174/1573399818666211222164400] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Revised: 10/05/2021] [Accepted: 10/28/2021] [Indexed: 11/22/2022]
Abstract
INTRODUCTION Diabetes mellitus (DM) comprises differential clinical phenotypes ranging from rare monogenic to common polygenic forms, such as type 1 (T1DM), type 2 (T2DM), and gestational diabetes, which are associated with cardiovascular complications. Also, the high- -risk prediabetic state is rising worldwide, suggesting the urgent need for early personalized strategies to prevent and treat a hyperglycemic state. OBJECTIVE We aim to discuss the advantages and challenges of Network Medicine approaches in clarifying disease-specific molecular pathways, which may open novel ways for repurposing approved drugs to reach diabetes precision medicine and personalized therapy. CONCLUSION The interactome or protein-protein interactions (PPIs) is a useful tool to identify subtle molecular differences between precise diabetic phenotypes and predict putative novel drugs. Despite being previously unappreciated as T2DM determinants, the growth factor receptor-bound protein 14 (GRB14), calmodulin 2 (CALM2), and protein kinase C-alpha (PRKCA) might have a relevant role in disease pathogenesis. Besides, in silico platforms have suggested that diflunisal, nabumetone, niflumic acid, and valdecoxib may be suitable for the treatment of T1DM; phenoxybenzamine and idazoxan for the treatment of T2DM by improving insulin secretion; and hydroxychloroquine reduce the risk of coronary heart disease (CHD) by counteracting inflammation. Network medicine has the potential to improve precision medicine in diabetes care and enhance personalized therapy. However, only randomized clinical trials will confirm the clinical utility of network- oriented biomarkers and drugs in the management of DM.
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Affiliation(s)
- Claudio Napoli
- Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania "Luigi Vanvitelli", 80138- Naples, Italy
- Clinical Department of Internal and Specialty Medicine (DAI), University Hospital (AOU), University of Campania "Luigi Vanvitelli", 80138 Naples, Italy
| | - Giuditta Benincasa
- Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania "Luigi Vanvitelli", 80138- Naples, Italy
| | - Samer Ellahham
- Department of Cardiology, Cleveland Clinic Abu Dhabi, Abu Dhabi, United Arab Emirates
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Benedetti R, Benincasa G, Glass K, Chianese U, Vietri MT, Congi R, Altucci L, Napoli C. Effects of novel SGLT2 inhibitors on cancer incidence in hyperglycemic patients: a meta-analysis of randomized clinical trials. Pharmacol Res 2021; 175:106039. [PMID: 34929299 DOI: 10.1016/j.phrs.2021.106039] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 12/10/2021] [Accepted: 12/15/2021] [Indexed: 02/06/2023]
Abstract
Epidemiological evidence shows that diabetic patients have an increased cancer risk and a higher mortality rate. Glucose could play a central role in metabolism and growth of many tumor types, and this possible mechanism is supported by the high rate of glucose demand and uptake in cancer. Thus, growing evidence suggests that hyperglycemia contributes to cancer progression but also to its onset. Many mechanisms underlying this association have been hypothesized, such as insulin resistance, hyperinsulinemia, and increased inflammatory processes. Inflammation is a common pathophysiological feature in both diabetic and oncological patients, and inflammation linked to high glucose levels sensitizes microenvironment to tumorigenesis, promoting the development of malignant lesions by altering and sustaining a pathological condition in tissues. Glycemic control is the first goal of antidiabetic therapy, and glucose level reduction has also been associated with favorable outcomes in cancer. Here, we describe key events in carcinogenesis focusing on hyperglycemia as supporter in tumor progression and in particular, related to the role of a specific hypoglycemic drug class, sodium-glucose linked transporters (SGLTs). We also discuss the use of SGLT2 inhibitors as a novel potential cancer therapy. Our meta-analysis showed that SGLT-2 inhibitors were significantly associated with an overall reduced risk of cancer as compared to placebo (RR = 0.35, CI 0.33-0.37, P = 0. 00) with a particular effectiveness for dapaglifozin and ertuglifozin (RR = 0. 06, CI 0. 06-0. 07 and RR = 0. 22, CI 0. 18-0. 26, respectively). Network Medicine approaches may advance the possible repurposing of these drugs in patients with concomitant diabetes and cancer.
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Affiliation(s)
- Rosaria Benedetti
- Department of Precision Medicine, University of Campania "Luigi Vanvitelli", Via L. De Crecchio 7, 80138 Naples, Italy
| | - Giuditta Benincasa
- Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania "Luigi Vanvitelli", Pz. Miraglia 2, 80138 Naples, Italy.
| | - Kimberly Glass
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Ugo Chianese
- Department of Precision Medicine, University of Campania "Luigi Vanvitelli", Via L. De Crecchio 7, 80138 Naples, Italy
| | - Maria Teresa Vietri
- Department of Precision Medicine, University of Campania "Luigi Vanvitelli", Via L. De Crecchio 7, 80138 Naples, Italy
| | - Raffaella Congi
- Department of Precision Medicine, University of Campania "Luigi Vanvitelli", Via L. De Crecchio 7, 80138 Naples, Italy
| | - Lucia Altucci
- Department of Precision Medicine, University of Campania "Luigi Vanvitelli", Via L. De Crecchio 7, 80138 Naples, Italy; Biogem Institute of Molecular and Genetic Biology, 83031 Ariano Irpino, Italy.
| | - Claudio Napoli
- Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania "Luigi Vanvitelli", Pz. Miraglia 2, 80138 Naples, Italy; Clinical Department of Internal Medicine and Specialistics, Division of Clinical Immunology, Transfusion Medicine and Transplant Immunology, AOU University of Campania "Luigi Vanvitelli", Via L. De Crecchio 7, 80138 Naples, Italy.
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