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Published on: June 9, 2020
Identification and analysis of diverse cell death patterns in diabetic kidney disease using microarray-based
Yuanyuan Luo1, Lerong Liu2, Cheng Zhang1
1Department of Endocrinology, Chongqing University Three Gorges Hospital, Chongqing, 404000, China; Chongqing Municipality Clinical Research Center for Endocrinology and Metabolic Diseases, Chongqing University Three Gorges Hospital, Chongqing, 404000, China.
Background:
Diabetic kidney disease (DKD) is the most lethal complication of diabetes. Diverse programmed cell death (PCD) has emerged as a crucial disease phenotype that has the potential to serve as an indicator of renal function decline and can be used as a target for researching drugs for DKD.
Methods:
Microarray-based transcriptome profiling and single-nucleus transcriptome sequencing (snRNA-seq) related to DKD were retrieved from the Gene Expression Omnibus (GEO) database. 13 PCD-related genes (including alkaliptosis, apoptosis, autophagy-dependent cell death, cuproptosis, disulfidptosis, entotic cell death, ferroptosis, lysosome-dependent cell death, necroptosis, netotic cell death, oxeiptosis, parthanatos, and pyroptosis) were obtained from various public databases and reviews. The gene set variation analysis (GSVA) analysis was used to explore the pathway activity of these 13 PCDs in DKD, and the pathway activity of these PCDs in different renal cells was studied based on DKD-related snRNA-seq data. To identify the core PCDs that play a significant role in DKD, we analyzed the relationships between different types of PCD and immune infiltration, fibrosis-related gene expression levels, glomerular filtration rate (GFR), and diagnostic efficiency in DKD. Using the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm, we screened for core death genes among the core PCDs and constructed a cell death-related signature (CDS) risk score based on the Least Absolute Shrinkage and Selection Operator (LASSO). Finally, we validated the predictive performance of the CDS risk score in an independent validation set.
Results:
We identified 4 core PCD pathways, namely entotic cell death, apoptosis, necroptosis, and pyroptosis in DKD, and further applied the WGCNA algorithm to screen 4 core death genes (CASP1, CYBB, PLA2G4A, and CTSS) and constructed a CDS risk score based on these genes. The CDS risk score demonstrated high diagnostic efficiency for DKD patients, and those with higher scores had higher levels of immune cell infiltration and poorer GFR.
Conclusion:
Our study sheds light on the fact that multiple PCDs contribute to the progression of DKD, highlighting potential therapeutic targets for treating this disease.
Insights
Diverse programmed cell death (PCD) pathways are implicated in diabetic kidney disease (DKD) progression. Identifying key PCDs and developing risk scores can improve diagnosis and guide therapeutic strategies for DKD.
Area of Science:
- Nephrology
- Molecular Biology
- Genetics
Background:
- Diabetic kidney disease (DKD) is a severe complication of diabetes, characterized by declining renal function.
- Programmed cell death (PCD) pathways are increasingly recognized as critical factors in DKD pathogenesis and potential therapeutic targets.
Purpose of the Study:
- To investigate the role of diverse PCD pathways in DKD.
- To identify core PCDs and develop a predictive risk score for DKD progression.
Main Methods:
- Transcriptome profiling (microarray and snRNA-seq) of DKD samples.
- Analysis of 13 PCD pathways using Gene Set Variation Analysis (GSVA).
- Weighted Gene Co-expression Network Analysis (WGCNA) to identify core genes and construct a Cell Death Signature (CDS) risk score.
Main Results:
- Four core PCD pathways (entotic cell death, apoptosis, necroptosis, pyroptosis) were identified in DKD.
- A CDS risk score based on four genes (CASP1, CYBB, PLA2G4A, CTSS) showed high diagnostic efficiency.
- Higher CDS risk scores correlated with increased immune cell infiltration and reduced glomerular filtration rate (GFR).
Conclusions:
- Multiple PCDs significantly contribute to DKD progression.
- The developed CDS risk score serves as a valuable diagnostic and prognostic tool for DKD.
- These findings highlight potential therapeutic targets for DKD treatment.
