Yuval Itan, PhD

Yuval Itan, PhD, is a computational biologist studying human disease genomics. He develops cutting-edge methods to predict the functional consequences of human genetic variants and has created the first approach that can computationally differentiate gain-of-function (GOF) from loss-of-function (LOF) pathogenic variants genome-wide. Additionally, Dr. Itan conducts extensive genome-wide and phenome-wide association studies (PheWAS) in large biobanks across multiple human populations, as demonstrated in his recent study identifying shared genetic factors between Parkinson’s disease (PD) and inflammatory bowel disease (IBD). His ongoing research includes developing the first genome-wide machine learning classifier to predict the specific disease consequences of any human genetic variant, as well as conducting extensive population-specific PheWAS analyses for all known human pathogenic GOF and LOF variants.