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Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis
Published on: June 18, 2020
An integrated co-expression network analysis reveals novel genetic biomarkers for immune cell infiltration in chronic
Jia Xia1, Yutong Hou2, Anxiang Cai1
1Department of Nephrology, Molecular Cell Lab for Kidney Disease, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Background:
Chronic kidney disease (CKD) is characterized by persistent damage to kidney function or structure. Progression to end-stage leads to adverse effects on multiple systems. However, owing to its complex etiology and long-term cause, the molecular basis of CKD is not completely known.
Methods:
To dissect the potential important molecules during the progression, based on CKD databases from Gene Expression Omnibus, we used weighted gene co-expression network analysis (WGCNA) to identify the key genes in kidney tissues and peripheral blood mononuclear cells (PBMC). Correlation analysis of these genes with clinical relevance was evaluated based on Nephroseq. Combined with a validation cohort and receiver operating characteristic curve (ROC), we found the candidate biomarkers. The immune cell infiltration of these biomarkers was evaluated. The expression of these biomarkers was further detected in folic acid-induced nephropathy (FAN) murine model and immunohistochemical staining.
Results:
In total, eight genes (CDCP1, CORO1C, DACH1, GSTA4, MAFB, TCF21, TGFBR3, and TGIF1) in kidney tissue and six genes (DDX17, KLF11, MAN1C1, POLR2K, ST14, and TRIM66) in PBMC were screened from co-expression network. Correlation analysis of these genes with serum creatinine levels and estimated glomerular filtration rate from Nephroseq showed a well clinical relevance. Validation cohort and ROC identified TCF21, DACH1 in kidney tissue and DDX17 in PBMC as biomarkers for the progression of CKD. Immune cell infiltration analysis revealed that DACH1 and TCF21 were correlated with eosinophil, activated CD8 T cell, activated CD4 T cell, while the DDX17 was correlated with neutrophil, type-2 T helper cell, type-1 T helper cell, mast cell, etc. FAN murine model and immunohistochemical staining confirmed that these three molecules can be used as genetic biomarkers to distinguish CKD patients from healthy people. Moreover, the increase of TCF21 in kidney tubules might play important role in the CKD progression.
Discussion:
We identified three promising genetic biomarkers which could play important roles in the progression of CKD.
Insights
Researchers identified three key genetic biomarkers, TCF21, DACH1, and DDX17, crucial for understanding chronic kidney disease (CKD) progression. These findings offer new insights into CKD molecular mechanisms and potential diagnostic tools.
Area of Science:
- Genomics
- Nephrology
- Biomarker Discovery
Background:
- Chronic kidney disease (CKD) is a progressive condition with complex etiology, and its underlying molecular mechanisms remain incompletely understood.
- End-stage renal disease significantly impacts multiple organ systems.
- Identifying key molecules is crucial for understanding CKD progression.
Purpose of the Study:
- To identify key genes and potential molecular biomarkers associated with CKD progression.
- To investigate the clinical relevance and diagnostic potential of identified genes.
- To explore the role of these biomarkers in immune cell infiltration and CKD pathogenesis.
Main Methods:
- Weighted Gene Co-expression Network Analysis (WGCNA) applied to CKD gene expression datasets (Gene Expression Omnibus).
- Correlation analysis with clinical parameters (serum creatinine, eGFR) using Nephroseq database.
- Validation cohort, Receiver Operating Characteristic (ROC) curve analysis, and immune cell infiltration assessment.
- Folic acid-induced nephropathy (FAN) murine model and immunohistochemical staining for validation.
Main Results:
- Eight genes in kidney tissue and six genes in peripheral blood mononuclear cells (PBMC) were initially screened.
- TCF21 and DACH1 (kidney tissue) and DDX17 (PBMC) were identified as significant biomarkers for CKD progression.
- These biomarkers showed correlations with specific immune cell types and were validated in a murine model, confirming their potential diagnostic utility.
Conclusions:
- TCF21, DACH1, and DDX17 are promising genetic biomarkers for distinguishing CKD patients from healthy individuals.
- TCF21, particularly its increased expression in kidney tubules, may play a significant role in CKD progression.
- These findings contribute to a better understanding of CKD's molecular basis and offer potential avenues for early diagnosis and therapeutic strategies.
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