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Pelissier A, Laragione T, Gulko PS, Rodríguez Martínez M. Cell-Specific Gene Networks and Drivers in Rheumatoid Arthritis Synovial Tissues. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.28.573505. [PMID: 38234732 PMCID: PMC10793435 DOI: 10.1101/2023.12.28.573505] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Rheumatoid arthritis (RA) is a common autoimmune and inflammatory disease characterized by inflammation and hyperplasia of the synovial tissues. RA pathogenesis involves multiple cell types, genes, transcription factors (TFs) and networks. Yet, little is known about the TFs, and key drivers and networks regulating cell function and disease at the synovial tissue level, which is the site of disease. In the present study, we used available RNA-seq databases generated from synovial tissues and developed a novel approach to elucidate cell type-specific regulatory networks on synovial tissue genes in RA. We leverage established computational methodologies to infer sample-specific gene regulatory networks and applied statistical methods to compare network properties across phenotypic groups (RA versus osteoarthritis). We developed computational approaches to rank TFs based on their contribution to the observed phenotypic differences between RA and controls across different cell types. We identified 18,16,19,11 key regulators of fibroblast-like synoviocyte (FLS), T cells, B cells, and monocyte signatures and networks, respectively, in RA synovial tissues. Interestingly, FLS and B cells were driven by multiple independent co-regulatory TF clusters that included MITF, HLX, BACH1 (FLS) and KLF13, FOSB, FOSL1 (synovial B cells). However, monocytes were collectively governed by a single cluster of TF drivers, responsible for the main phenotypic differences between RA and controls, which included RFX5, IRF9, CREB5. Among several cell subset and pathway changes, we also detected reduced presence of NKT cell and eosinophils in RA synovial tissues. Overall, our novel approach identified new and previously unsuspected KDG, TF and networks and should help better understanding individual cell regulation and co-regulatory networks in RA pathogenesis, as well as potentially generate new targets for treatment.
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Affiliation(s)
- Aurelien Pelissier
- IBM Research Europe, 8803 Rüschlikon, Switzerland
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
- Currently at Institute of Computational Life Sciences, ZHAW, 8400 Winterthur, Switzerland
| | - Teresina Laragione
- Division of Rheumatology, Icahn School of Medicine at Mount Sinai, 10029 New York, United States
| | - Percio S. Gulko
- Division of Rheumatology, Icahn School of Medicine at Mount Sinai, 10029 New York, United States
| | - María Rodríguez Martínez
- IBM Research Europe, 8803 Rüschlikon, Switzerland
- Currently at Yale School of Medicine, 06510 New Haven, United States
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Xu D, Jiang C, Xiao Y, Ding H. Identification and validation of disulfidptosis-related gene signatures and their subtype in diabetic nephropathy. Front Genet 2023; 14:1287613. [PMID: 38028597 PMCID: PMC10658004 DOI: 10.3389/fgene.2023.1287613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Accepted: 10/24/2023] [Indexed: 12/01/2023] Open
Abstract
Background: Diabetic nephropathy (DN) is the most common complication of diabetes, and its pathogenesis is complex involving a variety of programmed cell death, inflammatory responses, and autophagy mechanisms. Disulfidptosis is a newly discovered mechanism of cell death. There are little studies about the role of disulfidptosis on DN. Methods: First, we obtained the data required for this study from the GeneCards database, the Nephroseq v5 database, and the GEO database. Through differential analysis, we obtained differential disulfidptosis-related genes. At the same time, through WGCNA analysis, we obtained key module genes in DN patients. The obtained intersecting genes were further screened by Lasso as well as SVM-RFE. By intersecting the results of the two, we ended up with a key gene for diabetic nephropathy. The diagnostic performance and expression of key genes were verified by the GSE30528, GSE30529, GSE96804, and Nephroseq v5 datasets. Using clinical information from the Nephroseq v5 database, we investigated the correlation between the expression of key genes and estimated glomerular filtration rate (eGFR) and serum creatinine content. Next, we constructed a nomogram and analyzed the immune microenvironment of patients with DN. The identification of subtypes facilitates individualized treatment of patients with DN. Results: We obtained 91 differential disulfidptosis-related genes. Through WGCNA analysis, we obtained 39 key module genes in DN patients. Taking the intersection of the two, we preliminarily screened 20 genes characteristic of DN. Through correlation analysis, we found that these 20 genes are positively correlated with each other. Further screening by Lasso and SVM-RFE algorithms and intersecting the results of the two, we identified CXCL6, CD48, C1QB, and COL6A3 as key genes in DN. Clinical correlation analysis found that the expression levels of key genes were closely related to eGFR. Immune cell infiltration is higher in samples from patients with DN than in normal samples. Conclusion: We identified and validated 4 DN key genes from disulfidptosis-related genes that CXCL6, CD48, C1QB, and COL6A3 may be key genes that promote the onset of DN and are closely related to the eGFR and immune cell infiltrated in the kidney tissue.
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Affiliation(s)
- Danping Xu
- School of Medicine, University of Electronic Science and Technology of China, Sichuan Provincial People’s Hospital, Chengdu, China
| | - Chonghao Jiang
- Affiliated Hospital of North China University of Science and Technology, Tangshan, China
| | - Yonggui Xiao
- North China University of Science and Technology, Tangshan, China
| | - Hanlu Ding
- Renal Division and Institute of Nephrology, Sichuan Academy of Medical Science and Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
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Wang Y, Jin M, Cheng CK, Li Q. Tubular injury in diabetic kidney disease: molecular mechanisms and potential therapeutic perspectives. Front Endocrinol (Lausanne) 2023; 14:1238927. [PMID: 37600689 PMCID: PMC10433744 DOI: 10.3389/fendo.2023.1238927] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 07/17/2023] [Indexed: 08/22/2023] Open
Abstract
Diabetic kidney disease (DKD) is a chronic complication of diabetes and the leading cause of end-stage renal disease (ESRD) worldwide. Currently, there are limited therapeutic drugs available for DKD. While previous research has primarily focused on glomerular injury, recent studies have increasingly emphasized the role of renal tubular injury in the pathogenesis of DKD. Various factors, including hyperglycemia, lipid accumulation, oxidative stress, hypoxia, RAAS, ER stress, inflammation, EMT and programmed cell death, have been shown to induce renal tubular injury and contribute to the progression of DKD. Additionally, traditional hypoglycemic drugs, anti-inflammation therapies, anti-senescence therapies, mineralocorticoid receptor antagonists, and stem cell therapies have demonstrated their potential to alleviate renal tubular injury in DKD. This review will provide insights into the latest research on the mechanisms and treatments of renal tubular injury in DKD.
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Affiliation(s)
- Yu Wang
- Department of Endocrinology and Metabolism, Shenzhen University General Hospital, Shenzhen, Guangdong, China
- Department of Biomedical Sciences, City University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Mingyue Jin
- Department of Endocrinology and Metabolism, Shenzhen University General Hospital, Shenzhen, Guangdong, China
| | - Chak Kwong Cheng
- School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Qiang Li
- Department of Endocrinology and Metabolism, Shenzhen University General Hospital, Shenzhen, Guangdong, China
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Yan M, Li W, Wei R, Li S, Liu Y, Huang Y, Zhang Y, Lu Z, Lu Q. Identification of pyroptosis-related genes and potential drugs in diabetic nephropathy. J Transl Med 2023; 21:490. [PMID: 37480090 PMCID: PMC10360355 DOI: 10.1186/s12967-023-04350-w] [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: 04/28/2023] [Accepted: 07/11/2023] [Indexed: 07/23/2023] Open
Abstract
BACKGROUND Diabetic nephropathy (DN) is one of the serious microvascular complications of diabetes mellitus (DM). A growing body of research has demonstrated that the inflammatory state plays a critical role in the incidence and development of DN. Pyroptosis is a new way of programmed cell death, which has the particularity of natural immune inflammation. The inhibition of inflammatory cytokine expression and regulation of pathways related to pyroptosis may be a novel strategy for DN treatment. The aim of this study is to identify pyroptosis-related genes and potential drugs for DN. METHODS DN differentially expressed pyroptosis-related genes were identified via bioinformatic analysis Gene Expression Omnibus (GEO) dataset GSE96804. Dataset GSE30528 and GSE142025 were downloaded to verify pyroptosis-related differentially expressed genes (DEGs). Least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct a pyroptosis-related gene predictive model. A consensus clustering analysis was performed to identify pyroptosis-related DN subtypes. Subsequently, Gene Set Variation Analysis (GSVA), Gene Ontology (GO) function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to explore the differences between DN clusters. A protein-protein interaction (PPI) network was used to select hub genes and DGIdb database was utilized to screen potential therapeutic drugs/compounds targeting hub genes. RESULTS A total of 24 differentially expressed pyroptosis-related genes were identified in DN. A 16 gene predictive model was conducted via LASSO regression analysis. According to the expression level of these 16 genes, DN cases were divided into two subtypes, and the subtypes are mainly associated with inflammation, activation of immune response and cell metabolism. In addition, we identified 10 hub genes among these subtypes, and predicted 65 potential DN therapeutics that target key genes. CONCLUSION We identified two pyroptosis-related DN clusters and 65 potential therapeutical agents/compounds for DN, which might shed a light on the treatment of DN.
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Affiliation(s)
- Meng Yan
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China.
- Department of Clinical Pharmacology, School of Pharmacy, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, 221004, Jiangsu, China.
| | - Wenwen Li
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Rui Wei
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Shuwen Li
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Yan Liu
- Jiangsu Key Laboratory of Brain Disease and Bioinformation, Research Center for Biochemistry and Molecular Biology, Xuzhou Medical University, Xuzhou, China
- Key Laboratory of Genetic Foundation and Clinical Application, Department of Genetics, Xuzhou Engineering Research Center of Medical Genetics and Transformation, Xuzhou Medical University, Xuzhou, China
| | - Yuqian Huang
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Yunye Zhang
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Zihao Lu
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Qian Lu
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China.
- Department of Clinical Pharmacology, School of Pharmacy, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, 221004, Jiangsu, China.
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Iizuka K, Yabe D, Abu-Farha M, Abubaker J, Al-Mulla F. Editorial: Advances in the research of diabetic nephropathy, volume II. Front Endocrinol (Lausanne) 2023; 14:1135265. [PMID: 36742377 PMCID: PMC9890146 DOI: 10.3389/fendo.2023.1135265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Accepted: 01/09/2023] [Indexed: 01/19/2023] Open
Affiliation(s)
- Katsumi Iizuka
- Department of Clinical Nutrition, Fujita Health University, Toyoake, Japan
- *Correspondence: Katsumi Iizuka,
| | - Daisuke Yabe
- Department of Diabetes, Endocrinology and Metabolism, Gifu University Graduate School of Medicine, Gifu, Japan
- Department of Rheumatology and Clinical Immunology, Gifu University Graduate School of Medicine, Gifu, Japan
- Center for One Medicine Innovative Research, Gifu University Institute for Advanced Study, Gifu, Japan
- Center for Healthcare Information Technology, Tokai National Higher Education and Research System, Nagoya, Japan
| | - Mohamed Abu-Farha
- Biochemistry and Molecular Biology Department, Dasman Diabetes Institute, Dasman, Kuwait
| | - Jehad Abubaker
- Biochemistry and Molecular Biology Department, Dasman Diabetes Institute, Dasman, Kuwait
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