Identification and validation of key biomarkers for the early diagnosis of diabetic kidney disease

Yu, Wei; Wang, Ting; Wu, Feng; Zhang, Yiding; Shang, Jin; Zhao, Zhanzheng

doi:10.3389/fphar.2022.931282

Cited by 4 publications

(4 citation statements)

References 49 publications

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“…Using the GSE96804 database, research determined that THBS2, COL1A2, COL6A3, and CD44 might be potential biomarkers and treatment prospects for DKD ( 45 ). Finally, about GSE104948, scientists used this database for bioinformatics analysis and experimental verification identified three novel DKD-specific genes ( 46 ).…”

Section: Discussionmentioning

confidence: 99%

Single-cell RNA and transcriptome sequencing profiles identify immune-associated key genes in the development of diabetic kidney disease

et al. 2023

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BackgroundThere is a growing public concern about diabetic kidney disease (DKD), which poses a severe threat to human health and life. It is important to discover noninvasive and sensitive immune-associated biomarkers that can be used to predict DKD development. ScRNA-seq and transcriptome sequencing were performed here to identify cell types and key genes associated with DKD.MethodsHere, this study conducted the analysis through five microarray datasets of DKD (GSE131882, GSE1009, GSE30528, GSE96804, and GSE104948) from gene expression omnibus (GEO). We performed single-cell RNA sequencing analysis (GSE131882) by using CellMarker and CellPhoneDB on public datasets to identify the specific cell types and cell-cell interaction networks related to DKD. DEGs were identified from four datasets (GSE1009, GSE30528, GSE96804, and GSE104948). The regulatory relationship between DKD-related characters and genes was evaluated by using WGCNA analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) datasets were applied to define the enrichment of each term. Subsequently, immune cell infiltration between DKD and the control group was identified by using the “pheatmap” package, and the connection Matrix between the core genes and immune cell or function was illuminated through the “corrplot” package. Furthermore, RcisTarget and GSEA were conducted on public datasets for the analysis of the regulation relationship of key genes and it revealed the correlation between 3 key genes and top the 20 genetic factors involved in DKD. Finally, the expression of key genes between patients with 35 DKD and 35 healthy controls were examined by ELISA, and the relationship between the development of DKD rate and hub gene plasma levels was assessed in a cohort of 35 DKD patients. In addition, we carried out immunohistochemistry and western blot to verify the expression of three key genes in the kidney tissue samples we obtained.ResultsThere were 8 cell types between DKD and the control group, and the number of connections between macrophages and other cells was higher than that of the other seven cell groups. We identified 356 different expression genes (DEGs) from the RNA-seq, which are enriched in urogenital system development, kidney development, platelet alpha granule, and glycosaminoglycan binding pathways. And WGCNA was conducted to construct 13 gene modules. The highest correlations module is related to the regulation of cell adhesion, positive regulation of locomotion, PI3K-Akt, gamma response, epithelial-mesenchymal transition, and E2F target signaling pathway. Then we overlapped the DEGs, WGCNA, and scRNA-seq, SLIT3, PDE1A and CFH were screened as the closely related genes to DKD. In addition, the findings of immunological infiltration revealed a remarkable positive link between T cells gamma delta, Macrophages M2, resting mast cells, and the three critical genes SLIT3, PDE1A, and CFH. Neutrophils were considerably negatively connected with the three key genes. Comparatively to healthy controls, DKD patients showed high levels of SLIT3, PDE1A, and CFH. Despite this, higher SLIT3, PDE1A, and CFH were associated with an end point rate based on a median follow-up of 2.6 years. And with the gradual deterioration of DKD, the expression of SLIT3, PDE1A, and CFH gradually increased.ConclusionsThe 3 immune-associated genes could be used as diagnostic markers and therapeutic targets of DKD. Additionally, we found new pathogenic mechanisms associated with immune cells in DKD, which might lead to therapeutic targets against these cells.

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Section: Discussionmentioning

confidence: 99%

Single-cell RNA and transcriptome sequencing profiles identify immune-associated key genes in the development of diabetic kidney disease

et al. 2023

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“…Oligoadenylate synthetase 1 (OAS1) has been found to mediate apoptosis of thymic pre-T-cells and to be associated with auto-in ammatory immunode ciency [42]. Moreover, multiple reports have con rmed that OAS1 is a key biomarker for the diagnosis of diabetic nephropathy and a hub gene for lupus nephritis and chronic kidney disease [43][44][45]. Radical S-adenosyl methionine domain-containing protein 2 (RASD2) expression is closely related to the degree of differentiation of podocytes, and its regulatory expression gradually decreases with the development of the kidney [46].…”

Section: Discussionmentioning

confidence: 99%

Identification of key biomarkers and immune infiltration in Minimal Change Disease: Novel Insights from bioinformatics analysis

Tang

Yang

et al. 2022

Preprint

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Background Minimal change disease (MCD) is not a simple immune disease, and its pathogenesis has not been elucidated because of its complexity in terms of the glomerular microenvironment and genetic susceptibility. Hence the therapeutic approach is equally imprecise. Methods We downloaded GSE108109 from the Gene Expression Omnibus (GEO) database for bioinformatic analyses. Genome-wide expression analysis (GSEA) and functional enrichment analysis of differentially expressed genes (DEGs) were performed. Single sample gene set enrichment analysis (ssGSEA) was applied to assess the level of immune infiltration patterns of diseases. Protein-Protein Interaction (PPI) network was constructed to identify hub genes. Hub genes were intersected with immune-related genes downloaded from the Immunology Database and Analysis Portal (ImmPort) to obtain key genes. In addition, the expression levels of key genes were validated in the Kidney Interactive Transcriptomics webpage and Nephroseq database. Receiver operating characteristic (ROC) analysis and principal component analysis (PCA) was performed to explore the value of key genes for MCD diagnosis. Results 1029 DEGs were screened, of which 493 were up-regulated, and 536 were down-regulated. GSEA analysis revealed that DEGs were significantly enriched in three pathways, including T-cell receptor signaling pathway, natural killer cell-mediated cytotoxicity, and B-cell receptor signaling pathway. In addition, 17 of the 21 immune cell types were significantly different in MCD compared to the normal group. A total of five key genes (ISG15, IRF1, OAS1, RSAD2, BST2) were shown to play essential roles in the immune response. Among them, IRF1, OAS1, RSAD2, and BST2 were highly expressed in podocytes. Conclusions In this study, bioinformatics analysis revealed new insights into MCD: (1) Immune cell infiltration analysis provided new evidence and clues to the molecular mechanisms of MCD. (2) Key genes such as ISG15, IRF1, OAS1, RSAD2 and BST2 may contribute to the immunopathological process of MCD development.

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“…Furthermore, to explore the regulatory mechanisms of differentially signi cant genes and their regulatory mechanisms, we conducted small RNA sequencing on corresponding samples [51][52][53], including the affected child, their sibling, and their parents. We quanti ed the expression levels of microRNAs (miRNAs) and performed Weighted Gene Co-expression Network Analysis (WGCNA) [37,54] (Figures S5A-S5D and Table S5). Our results revealed that miRNAs were divided into 14 modules (de ned as densely interconnected clusters of genes) (Fig.…”

Section: Mir378c-mediated Regulation Of Ptpn14 Promotes the Activatio...mentioning

confidence: 99%

De novo mutations promote inflammation in children with STAT3 gain-of-function syndrome by affecting IL-1β expression

Chen,

Li,

Jiang

et al. 2024

Preprint

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Background STAT3 Gain-of-Function (GOF) syndrome characterized by early onset autoimmunity and primary immune regulatory disorder, the immunological mechanisms remain poorly understood. Employing whole-genome sequencing within familial trios, our study elucidated the pivotal role of de novo mutations in genetic diseases. Results We identified 37 high-risk pathogenic loci affecting 23 genes, notably including the novel STAT3c.508G>A mutation. Furthermore, significant downregulation of pathogenic genes in affected individuals, potentially associated with inflammatory responses regulated by PTPN14 via miR378c, was observed. Conclusion These findings not only contribute to our understanding of the pathogenesis but also highlight potential therapeutic strategies. Our study suggests that combined JAK inhibitors and IL-6R antagonists could offer promising avenues for mitigating the severity of these genetic disorders.

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Identification and validation of key biomarkers for the early diagnosis of diabetic kidney disease

Cited by 4 publications

References 49 publications

Single-cell RNA and transcriptome sequencing profiles identify immune-associated key genes in the development of diabetic kidney disease

Single-cell RNA and transcriptome sequencing profiles identify immune-associated key genes in the development of diabetic kidney disease

Identification of key biomarkers and immune infiltration in Minimal Change Disease: Novel Insights from bioinformatics analysis

De novo mutations promote inflammation in children with STAT3 gain-of-function syndrome by affecting IL-1β expression

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