Related Experiment Video
Updated: Jun 10, 2025
Comparative Proteomic Analysis of Whole Kidney, Medulla, and Cortical Tubules in Diabetic Pathogenesis of Kidney Injury in Mice
Published on: May 2, 2025
Exploring diagnostic biomarkers of type 2 cardio-renal syndrome based on secreted proteins and bioinformatics
Chuanjing Zhang1, Zhuonan Wu2, Yongfei Song1
1The Affiliated Lihuili Hospital of Ningbo University, Health Science Center, Ningbo University, No.57, Xingning Road, Ningbo, 315040, Zhejiang Province, China.
Insights
New biomarkers CD48, COL3A1, and LOXL1 show promise for early detection of chronic kidney disease (CKD) in patients with chronic heart failure (CHF). This research identifies key genes and pathways involved in cardio-renal syndrome type 2 (CRS2).
Area of Science:
- Cardiovascular Medicine
- Nephrology
- Genomics
- Biomarker Discovery
Background:
- Chronic heart failure (CHF) can lead to chronic kidney disease (CKD), a condition known as type 2 cardio-renal syndrome (CRS2).
- The precise mechanisms underlying CRS2 remain unclear, and there is a critical need for early diagnostic biomarkers for CKD in CHF patients.
- Existing research lacks comprehensive molecular insights into the pathogenesis of CRS2.
Purpose of the Study:
- To identify key pathogenic genes and potential therapeutic targets for CRS2.
- To discover and validate novel biomarkers for the early detection of CKD in the context of CHF.
- To elucidate the molecular mechanisms linking cardiac and peripheral secretomes to CKD progression in CHF.
Main Methods:
- Utilized GEO database for gene expression profiles (CKD, CHF-PBMC, CHF-cardiac tissue).
- Applied differential expression analysis, Weighted Gene Co-expression Network Analysis (WGCNA), and protein-protein interaction (PPI) analysis to identify key genes and pathways.
- Employed machine learning algorithms to screen biomarkers and construct a diagnostic nomogram, validated in external cohorts and clinical serum samples.
Main Results:
- Identified 225 CKD key genes and 316 CHF-related secreted proteins; pinpointed 204 CRS2-related pathogenic genes enriched in immune and inflammatory pathways.
- Discovered three hub genes (CD48, COL3A1, LOXL1) as potential CKD biomarkers, with a nomogram achieving an AUC > 0.80 in validation cohorts.
- Validated the diagnostic value of these biomarkers in clinical serum samples, with the nomogram achieving an AUC of 0.876 for CKD detection.
Conclusions:
- CHF can drive CKD progression through cardiac and PBMC secreted proteins, highlighting the role of CRS2.
- CD48, COL3A1, and LOXL1 represent promising novel biomarkers for early CKD detection in CHF patients.
- The identified biomarkers correlate with kidney function and immune cell infiltration, offering potential for monitoring disease progression.
Abstract:
Chronic heart failure (CHF) can induce chronic kidney disease (CKD), called type 2 cardio-renal syndrome (CRS2). The mechanism is not completely clear, and there is a lack of early warning biomarkers of CKD in the context of CHF. Two CKD, one CHF-PBMC and four CHF-cardiac tissue expression profile datasets were obtained from GEO database. Differential expression analysis and WGCNA were used to detect CKD key genes and CHF-related secreted proteins. Protein-protein interaction (PPI), functional enrichment, and cMAP analysis reveal potential mechanisms and drugs of CHF-related CKD. Five machine learning algorithms were used to screen candidate biomarkers, construct a diagnostic nomogram for CKD and validate it in two external cohorts. Clinical serum samples were collected in our hospital to evaluate the correlation and diagnostic value of biomarkers and CKD. 225 CKD key genes and 316 CHF-related secreted proteins were identified. Four key subgroups, including 204 genes, were identified as CRS2-related pathogenic genes by PPI analysis. Enrichment analysis revealed that the identified subgroups exhibited significant enrichment in cytokine action, immune responses, and inflammatory processes. The cMAP analysis highlighted metiradone as a drug with greater potential for therapeutic intervention for CRS2. Utilizing five machine learning algorithms, three hub genes (CD48, COL3A1, LOXL1) were pinpointed as potential biomarkers for CKD, and a nomogram model was constructed. Receiver operating characteristic analysis demonstrated that the nomogram's area under the curve (AUC) exceeded 0.80 in both the CKD combined dataset and two external cohorts. In addition, the three biomarkers were significantly correlated with the glomerular filtration rate, and the AUC of the model predicting disease progression was 0.944. Furthermore, analysis of immune cell infiltration indicated a correlation between the three biomarkers and the infiltration fraction of macrophages, neutrophils, and other immune cells in CKD. Our clinical cohort validated the expression patterns of three biomarkers in serum, and the diagnostic model achieved an AUC of 0.876. CHF has the potential to facilitate the progression of CKD via the release of cardiac and PBMC secreted proteins. Furthermore, CD48, COL3A1, and LOXL1 have been identified as potential biomarkers for the detection of CKD.
Related Concept Videos
01:26Nephrotic Syndrome II : Assessment and Medical Management
01:19Blood Studies for Cardiovascular System II: CRP, Hcy, and Cardiac Natriuretic Peptide Markers
These markers indicate stress or strain on the heart muscle:
Natriuretic Peptides (BNP)
Cardiac myocytes produce these hormones in response to ventricular stretching...
01:20Blood Studies for Cardiovascular System I: Cardiac Biomarkers
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
Troponins
Troponins, particularly cardiac troponins I and T, are the most precise and sensitive markers of myocardial injury. They are detectable within 4-6 hours of myocardial injury and remain...
01:24Serum Studies: Renal Function Tests
01:28Chronic Kidney Disease III: Interprofessional Care
01:30Acute Kidney Injury IV: Diagnostic Studies and Prevention