Zijie Zhao

This paper introduces a statistical framework for regularized ensemble polygenic risk prediction using GWAS summary statistics, showing improved performance across traits and populations.

This study introduces PENGUIN, a framework to control genetic confounding in epidemiologic studies, showing it effectively removes confounding in educational attainment associations.

This paper introduces a statistical framework to optimize and benchmark polygenic risk scores using GWAS summary statistics, showing improved performance over existing methods.

This study identifies correlates of risk for disinhibited behaviors in veterans using polygenic scores and electronic health records, finding strong associations with substance use disorders and related health outcomes.

The paper uses polygenic scores from sibling pairs in the UK Biobank to show compensatory processes in educational attainment, reducing genetic associations by 20% for higher-ranked siblings.

This paper introduces X-Wing, a framework that improves genetic prediction across populations using GWAS summary statistics by identifying portable genetic effects.

This paper estimates direct and indirect genetic effects using summary statistics from multi-generational GWAS, showing distinct patterns for traits like educational attainment and autism spectrum disorder.

ORIGAMI simulates offspring genomes from parental data to improve polygenic transmission disequilibrium analysis, revealing significant within-family risk variation for complex traits.

This paper introduces PUMAS, a method to fine-tune polygenic risk scores using GWAS summary statistics, improving predictive performance and statistical power in downstream analyses.