In collaboration with the Sorbonne University, Ksilink used both patient-derived and genome edited cellular models for desmin-related cardiomyopathy to analyze how the DESE439K mutation disrupts cellular function and contributes to disease phenotypes. Our findings highlighted key phenotypic defects such as cytoplasmic protein aggregation, mitochondrial and sarcomere defects, and contractile dysfunctions. We also developed a machine learning prediction model to classify cellular phenotypes, which can be used for drug candidate screening.
New publication on phenotypic and transcriptomic characterization, and machine learning-based classification of desmin-related cardiomyopathy disease features
