Abstract: FR-OR004
Gene Signatures Predicting Kidney Function Trajectories After Percutaneous Coronary Intervention in Patients with Acute Coronary Syndrome
Session Information
- AKI Everywhere All at Once: Risks, Trajectories, and Practice Patterns
November 07, 2025 | Location: Room 320A, Convention Center
Abstract Time: 05:00 PM - 05:10 PM
Category: Acute Kidney Injury
- 101 AKI: Epidemiology, Risk Factors, and Prevention
Authors
- Li, Diangeng, Capital Medical University Beijing Ditan Hospital, Beijing, China
- Jin, Meiling, Beijing Chaoyang Hospital Affiliated to Capital Medical University, Beijing, China
Background
Heterogeneous renal function trajectories post-percutaneous coronary intervention (PCI) significantly impact clinical outcomes in acute coronary syndrome (ACS) patients, while early predictive biomarkers remain lacking. This study aims to identify critical gene markers of post-PCI renal trajectories through preoperative peripheral blood mononuclear cell (PBMC) transcriptomics and establish early prediction models.
Methods
We prospectively enrolled ACS patients undergoing PCI from August 2023 to February 2024, stratifying them into control, abnormal renal function (ARF), and acute kidney injury (AKI) groups based on postoperative serum creatinine (SCr) and estimated glomerular filtration rate (eGFR) changes. Preoperative PBMC ribonucleic acid (RNA) sequencing identified differentially expressed genes (DEGs) using DESeq2. Six machine learning models (Linear Regression, Support Vector Machine [SVM], Partial Least Squares [PLS], Random Forest, k-Nearest Neighbors [KNN], Decision Tree) integrating clinical data were evaluated via receiver operating characteristic (ROC) analysis.
Results
Eighty-one ACS patients were categorized into control (n=40), AKI (n=22), and ARF groups (n=19). Compared with controls, the AKI group showed 409 significantly upregulated and 732 downregulated genes, while the abnormal renal function group exhibited 652 upregulated and 662 downregulated genes. Thirty-four genes were consistently upregulated and 45 downregulated in both pathological groups. DEGs were predominantly enriched in immune-related pathways. The random forest model achieved an AUC of 0.92 for AKI prediction, while the SVM model reached an AUC of 0.98 for ARF prediction. Correlation analysis revealed 23 genes significantly positively associated with postoperative creatinine elevation (R>0.5, p<0.05).
Conclusion
Preoperative abnormal expression of immune-related pathway genes in peripheral blood effectively predicts renal function trajectories after PCI, providing molecular markers for early risk stratification.