Identification of novel therapeutic targets in hepatitis-B virus-associated membranous nephropathy using scRNA-seq and machine learning.

Abstract

Hepatitis B Virus-associated membranous nephropathy (HBV-MN) significantly impacts renal health, particularly in areas with high HBV prevalence. Understanding the molecular mechanisms underlying HBV-MN is crucial for developing effective therapeutic strategies. This study aims to elucidate the roles of miR-223-3p and CRIM1 in HBV-MN using single-cell RNA sequencing (scRNA-seq) and machine learning. scRNA-seq analysis identified a distinct subcluster of podocytes linked to HBV-MN progression. miR-223-3p emerged as a critical regulatory molecule, with overexpression resulting in decreased CRIM1 expression. Dual-luciferase reporter assays confirmed miR-223-3p targeting CRIM1 at a conserved binding site. These findings were corroborated by machine learning models, which highlighted the significance of miR-223-3p and CRIM1 in disease pathology. miR-223-3p plays a pivotal role in modulating CRIM1 expression in HBV-MN, providing a potential therapeutic target. Integrating scRNA-seq with machine learning offers valuable insights into the molecular landscape of HBV-MN, paving the way for novel interventions.