Cardiogenomics meets Artificial Intelligence: a step forward in arrhythmogenic cardiomyopathy diagnosis and treatment

Arrhythmogenic cardiomyopathy (ACM) is a genetic disease characterized by progressive cardiomyocyte loss and fibrofatty replacement, which in turn lead to the occurrence of ventricular arrhythmias and sudden cardiac death (SCD), particularly in the young and athletes. At present, ACM is uncurable; with an incidence of 1:5000, it can be considered a major CVD disease.

The subform involving only the right ventricle is the most common; the majority of its causative mutations are identified in just three desmosomal genes: PKP2, DSP, and DSG2.

However, many of the identified variants in these disease genes are still of uncertain clinical significance (VUS) and thus of limited clinical utility.

The overall aim of the project is to combine large-scale data from genomics, proteomics and instrumental analysis obtained from patients with data from structural and functional analyses of in vitro (3D microtissue) and in vivo (murine) models, to establish the genotype/cardiac phenotype relationship, potentially leading to a better understanding of the role and impact of known genes and epigenetic factors (ie, miRNAs) on susceptibility, clinical progression, and treatment of ACM.The projects outcomes will pave the way towards novel therapies for ACM.