Peritoneal effluent MicroRNA profile for detection of encapsulating peritoneal sclerosis

Kun Lin Wu, Che Yi Chou, Hui Yin Chang, Chih Hsun Wu, An Lun Li, Chien Lung Chen, Jen Chieh Tsai, Yi Fan Chen, Chiung Tong Chen, Chin Chung Tseng, Jin Bor Chen, I. Kuan Wang, Yu Juei Hsu, Shih Hua Lin, Chiu Ching Huang, Nianhan Ma

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Background: Encapsulating peritoneal sclerosis (EPS) is a catastrophic complication of peritoneal dialysis (PD) with high mortality. Our aim is to develop a novel noninvasive microRNA (miRNA) test for EPS. Methods: We collected 142 PD effluents (EPS: 62 and non-EPS:80). MiRNA profiles of PD effluents were examined by a high-throughput real-time polymerase chain reaction (PCR) array to first screen. Candidate miRNAs were verified by single real-time PCR. The model for EPS prediction was evaluated by multiple logistic regression and machine learning. Results: Seven candidate miRNAs were identified from the screening of PCR-array of 377 miRNAs. The top five area under the curve (AUC) values with 5 miRNA-ratios were selected using 127 samples (EPS: 56 vs non-EPS: 71) to produce a receiver operating characteristic curve. After considering clinical characteristics and 5 miRNA-ratios, the accuracies of the machine learning model of Random Forest and multiple logistic regression were boosted to AUC 0.97 and 0.99, respectively. Furthermore, the pathway analysis of miRNA associated targeting genes and miRNA-compound interaction network revealed that these five miRNAs played the roles in TGF-β signaling pathway. Conclusion: The model-based miRNA expressions in PD effluents may help determine the probability of EPS and provide further therapeutic opinion for EPS.

Original languageEnglish
Pages (from-to)45-55
Number of pages11
JournalClinica Chimica Acta
StatePublished - 1 Nov 2022


  • Biomarker
  • Encapsulating peritoneal sclerosis
  • Peritoneal dialysis
  • microRNA


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