Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity.
Chiara Fallerini, Nicola Picchiotti, Margherita Baldassarri, Kristina Zguro, Sergio Daga, Francesca Fava, Elisa Benetti, Sara Amitrano, Mirella Bruttini, Maria Palmieri, Susanna Croci, Mirjam Lista, Giada Beligni, Floriana Valentino, Ilaria Meloni, , Pier Giorgio Scotton
The paper develops a machine learning model to predict COVID-19 severity using exonic variants from whole exome sequencing data, finding that variants across all frequency categories contribute to severity.
Human Genetics · Dec 10, 2021Peer-reviewedGenetic & Genomic Medicine