Identification of Hub Genes and Immune-Related Pathways for Membranous Nephropathy by Bioinformatics Analysis

Identification and validation of biomarkers in membranous nephropathy and pan-cancer analysis

Background

Membranous nephropathy (MN) is an autoimmune disease and represents the most prevalent type of renal pathology in adult patients afflicted with nephrotic syndrome. Despite substantial evidence suggesting a possible link between MN and cancer, the precise underlying mechanisms remain elusive.

Methods

In this study, we acquired and integrated two MN datasets (comprising a single-cell dataset and a bulk RNA-seq dataset) from the Gene Expression Omnibus database for differential expression gene (DEG) analysis, hub genes were obtained by LASSO and random forest algorithms, the diagnostic ability of hub genes was assessed using ROC curves, and the degree of immune cell infiltration was evaluated using the ssGSEA function. Concurrently, we gathered pan-cancer-related genes from the TCGA and GTEx databases, to analyze the expression, mutation status, drug sensitivity and prognosis of hub genes in pan-cancer.

Results

We conducted intersections between the set of 318 senescence-related genes and the 366 DEGs, resulting in the identification of 13 senescence-related DEGs. Afterwards, we meticulously analyzed these genes using the LASSO and random forest algorithms, which ultimately led to the discovery of six hub genes through intersection (PIK3R1, CCND1, TERF2IP, SLC25A4, CAPN2, and TXN). ROC curves suggest that these hub genes have good recognition of MN. After performing correlation analysis, examining immune infiltration, and conducting a comprehensive pan-cancer investigation, we validated these six hub genes through immunohistochemical analysis using human renal biopsy tissues. The pan-cancer analysis notably accentuates the robust association between these hub genes and the prognoses of individuals afflicted by diverse cancer types, further underscoring the importance of mutations within these hub genes across various cancers.

Conclusion

This evidence indicates that these genes could potentially play a pivotal role as a critical link connecting MN and cancer. As a result, they may hold promise as valuable targets for intervention in cases of both MN and cancer.

Identification of GMFG as a novel biomarker in IgA nephropathy based on comprehensive bioinformatics analysis

Background

IgA nephropathy (IgAN) stands as the most prevalent form of glomerulonephritis and ranks among the leading causes of end-stage renal disease worldwide. Regrettably, we continue to grapple with the absence of dependable diagnostic markers and specific therapeutic agents for IgAN. Therefore, this study endeavors to explore novel biomarkers and potential therapeutic targets in IgAN, while also considering their relevance in the context of tumors.

Methods

We gathered IgAN datasets from the Gene Expression Omnibus (GEO) database. Subsequently, leveraging these datasets, we conducted an array of analyses, encompassing differential gene expression, weighted gene co-expression network analysis (WGCNA), machine learning, receiver operator characteristic (ROC) curve analysis, gene expression validation, clinical correlations, and immune infiltration. Finally, we carried out pan-cancer analysis based on hub gene.

Results

We obtained 1391 differentially expressed genes (DEGs) in GSE93798 and 783 DGEs in GSE14795, respectively. identifying 69 common genes for further investigation. Subsequently, GMFG was identified the hub gene based on machine learning. In the verification set and the training set, the GMFG was higher in the IgAN group than in the healthy group and all of the GMFG area under the curve (AUC) was more 0.8. In addition, GMFG has a close relationship with the prognosis of malignancies and a range of immune cells.

Conclusions

Our study suggests that GMFG could serve as a promising novel biomarker and potential therapeutic target for both IgAN and certain types of tumors.

Single-Cell RNA Sequencing Reveals RAC1 Involvement in Macrophages Efferocytosis in Diabetic Kidney Disease

Macrophage-mediated inflammation plays a significant role in the development and progression of diabetic kidney disease (DKD). Studies have suggested that impaired macrophage efferocytosis aggravates the inflammatory response. However, its contribution to DKD progression remains unknown. Using single-cell RNA sequencing (scRNA-seq) data obtained from the GSE131882, GSE195460, GSE151302, GSE195460, and GSE131685 datasets, we successfully clustered 13 cell types. Through analysis of the ligand-receptor network, it was discovered that macrophages interact with other cells. Additionally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed that macrophages exhibit a heightened presence of phagocytosis signaling. We discovered that RAC1 was closely related to macrophage efferocytosis through a Venn diagram and protein-protein interaction (PPI) analysis, which predicted the correlation with the clinical features of DKD using the NephroseqV5 tool. Furthermore, we verified that RAC1 exhibited decreased expression in macrophages cultured with lipopolysaccharide (LPS) and high glucose. Nevertheless, the overexpression of RAC1 promoted macrophage efferocytosis and inhibited the inflammatory response. In summary, our study focused on examining the presence and importance of efferocytosis-related molecules in DKD macrophages. Through a comprehensive analysis using scRNA-seq, we discovered that RAC1 plays a crucial role as an efferocytosis molecule in DKD. These findings enhance our current knowledge of the molecular mechanisms involved in the development of DKD and aid the exploration of new treatments.

Analysis of complement system and its related factors in Alzheimer's disease

Alzheimer's disease (AD) is a primary cause of dementia. The complement system is closely related to AD pathology and may be a potential target for the prevention and treatment of AD. In our study, we conducted a bioinformatics analysis to analyze the role of the complement system and its related factors in AD using Gene Expression Omnibus (GEO) data. We also conducted a functional analysis. Our study verified that 23 genes were closely related to differentially expressed complement system genes in diseases after intersecting the disease-related complement system module genes and differentially expressed genes. The STRING database was used to predict the interactions between the modular gene proteins of the differential complement system. A total of 21 gene proteins and 44 interaction pairs showed close interactions. We screened key genes and created a diagnostic model. The predictive effect of the model was constructed using GSE5281 and our study indicated that the predictive effect of the model was good. Our study also showed enriched negative regulation of Notch signaling, cytokine secretion involved in the immune response pathway, and cytokine secretion involved in immune response hormone-mediated apoptotic signaling pathway. We hope that our study provides a promising target to prevent and delay the onset, diagnosis, and treatment of AD.

APOC1 exacerbates renal fibrosis through the activation of the NF-κB signaling pathway in IgAN

Introduction: IgA nephropathy (IgAN) is the most common disease leading to end-stage renal disease, and tubular fibrosis represents an important risk factor for disease progression. However, research on early molecular diagnostic indicators of tubular fibrosis and the mechanisms underlying disease progression is still lacking. Methods: The GSE93798 dataset was downloaded from the GEO database. DEGs were screened and analyzed for GO and KEGG enrichment in IgAN. The least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) algorithms were applied to screen for hub secretory genes. The expression and diagnostic efficacy of hub genes were confirmed by the GSE35487 dataset. ELISA was applied to detect the expression of APOC1 in serum. The expression and localization of hub genes in IgAN were verified by the expression of IHC and IF in human kidney tissues, and the correlation of expression with clinical data was verified in the Nephroseq database. Finally, cellular experiments clarified the role of hub genes in the signaling pathway. Results: A total of 339 DEGs were identified in IgAN, of which 237 were upregulated and 102 downregulated. The KEGG signaling pathway is enriched in the ECM-receptor interaction and AGE-RAGE signaling pathway. APOC1, ALB, CCL8, CXCL2, SRPX2, and TGFBI identified six hub secretory genes using the LASSO and SVM-RFE algorithms. In vivo and in vitro experiments demonstrated that APOC1 expression was elevated in IgAN. The serum concentration of APOC1 was 1.232 ± 0.1812 μg/ml in IgAN patients, whereas it was 0.3956 ± 0.1233 μg/ml in healthy individuals. APOC1 exhibited high diagnostic efficacy for IgAN (AUC of 99.091%, specificity of 95.455%, and sensitivity of 99.141%) in the GSE93798 dataset. APOC1 expression negatively correlated with eGFR (R ² = 0.2285, p = 0.0385) and positively correlated with serum creatinine (R ² = 0.41, p = 0.000567) in IgAN. APOC1 exacerbated renal fibrosis, possibly in part by activating the NF-κB pathway in IgAN. Conclusion: APOC1 was identified as the core secretory gene of IgAN, which was closely associated with blood creatinine and eGFR and had significant efficacy in the diagnosis of IgAN. Mechanistic studies revealed that the knockdown of APOC1 could improve IgAN renal fibrosis by inhibiting the NF pathway, which may be a potential therapeutic target for improving renal fibrosis in IgAN.

The role of the complement system in primary membranous nephropathy: A narrative review in the era of new therapeutic targets

Primary membranous nephropathy (MN) is an important cause of nephrotic syndrome and chronic kidney disease (CKD) in the adult population. Although the discovery of different autoantibodies against glomerular/podocytic antigens have highlighted the role of B cells in the pathogenesis of MN, suboptimal response or even resistance to B cell-directed therapies occurs, suggesting that other pathophysiological mechanisms are involved in mediating podocyte injury. The complement system plays an important role in the innate immune response to infection, and dysregulation of the complement system has been observed in various kidney diseases. There is compelling evidence of complement cascade activation in primary MN, with the mannose-binding lectin (MBL) and alternative pathways particularly implicated. With appropriate validation, assays of complements and associated activation products could hold promise as adjunctive tools for non-invasive disease monitoring and prognostication. While there is growing interest to target the complement system in MN, there is concern regarding the risk of infection due to encapsulated organisms and high treatment costs, highlighting the need for clinical trials to identify patients most likely to benefit from complement-directed therapies.