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

Introduction

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.

Incidence and Characteristics

At present, ACM is uncurable; with an incidence of 1:5000, it can be considered a major cardiovascular disease (CVD). The subform involving only the right ventricle is the most common.

Genetic Factors

The majority of its causative mutations are identified in just three desmosomal genes:

• PKP2
• DSP
• DSG2

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

Project Aim

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.

Objectives

This approach aims to:

1. Establish the genotype/cardiac phenotype relationship.
2. Potentially lead to a better understanding of the role and impact of known genes and epigenetic factors (i.e., miRNAs) on susceptibility, clinical progression, and treatment of ACM.

Expected Outcomes

The project’s outcomes will pave the way towards novel therapies for ACM.