#AI reads Urine#Identification of Biomarkers for Right Ventricular Dysfunction in Idiopathic Dilated Cardiomyopathy Via Urinary Proteomics and Machine Learning

This study aimed to identify reliable non-invasive biomarkers for right ventricular dysfunction in patients with idiopathic dilated cardiomyopathy. The research team enrolled 147 relevant patients, who were divided into two groups (with and without right ventricular dysfunction) using cardiac magnetic resonance imaging. Mass spectrometry was employed to analyze proteins in the patients' urine, leading to the identification of 46 differentially expressed proteins. Ultimately, a three-protein panel consisting of retinoic acid receptor responder protein 1, multivesicular body subunit 12B, and glycogen synthase kinase 3 alpha was determined. This panel exhibited significantly higher accuracy in diagnosing right ventricular dysfunction compared to traditional indicators and could effectively stratify patients based on risk scores. The incidence of adverse clinical outcomes in the high-risk group was significantly higher than that in the low-risk group, providing a non-invasive and effective tool for the diagnosis and prognostic evaluation of idiopathic dilated cardiomyopathy complicated with right ventricular dysfunction.

J Am Heart Assoc. 2025 Dec 17:e044254. doi: 10.1161/JAHA.125.044254.

Youhe Gao

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For earlier AI Reads Urine articles：

https://www.keaipublishing.com/en/journals/advances-in-biomarker-sciences-and-technology/ai-reads-urine/