Urinary microRNAs for the non-invasive diagnosis of endometriosis identified by next-generation sequencing and machine learning

The authors investigate the potential of urinary microRNAs as non-invasive biomarkers for the diagnosis of endometriosis, aiming to reduce reliance on invasive diagnostic procedures. Through next-generation sequencing and machine learning, they identify a signature of 20 miRNAs, including the novel biomarker hsa-miR-10400-5p, which shows promise in distinguishing endometriosis patients from controls. The study suggests that urinary miRNA profiling could facilitate earlier diagnosis of endometriosis, pending validation in larger cohorts.