Paolo Di Domenico

This paper develops a label-free polygenic risk score framework to identify residual CAD risk in individuals with zero coronary artery calcium, finding higher risk in top PRS groups despite normal imaging.

The paper shows that polygenic risk scores significantly affect the penetrance of rare breast cancer mutations and highlights the importance of including polygenic background in genetic risk assessments.

The paper develops a SaaS tool for genomic risk prediction of complex diseases using PRS and demonstrates its superior predictive performance compared to existing methods and clinical markers.