Peritoneal Effluent MicroRNA Profile in Encapsulating Peritoneal Sclerosis

Abstract

Encapsulating peritoneal sclerosis (EPS) is a catastrophic complication of chronic peritoneal dialysis (PD). Late diagnosis is associated with high mortality. With the advancement of new diagnostic technologies, such as microRNA (miRNA), we attempted to develop a noninvasive test to assist in the diagnosis of EPS. The eight-hour PD effluents were collected from 71 non-EPS and 56 EPS patients. The screening set included 28 samples (20 of non-EPS vs. 8 of EPS). After analyzing the ratio values of two miRNA expression levels from the high-throughput real-time PCR-array of 377 miRNAs, eight candidate miRNAs were selected. The prediction model was conducted using 127 samples (71 of non-EPS vs 56 of EPS) to produce an area under the curve (AUC) value of the miRNA classifier. Candidate miRNAs were also verified by single real-time PCR. The ratios of the five miRNAs with the top five ROC values were selected to calculate the combined AUC by multiple logistic regression. The AUC value to detect EPS with the five miRNA ratios was 0.8929 with an accuracy of 78.7%. The accuracy of the EPS diagnosis was further optimized to 94.1% after considering clinical characteristics (AUC value 0.9931). A signature-based model of clinical characteristics and miRNA expression in PD effluents can efficiently assist in the diagnosis of EPS, thus preventing the catastrophic prognosis.