Mikael Hartman

PRANA adapts polygenic risk scores to non-European populations, improving predictive accuracy by 5%-20% in South Asian, East Asian, and Ashkenazi Jewish populations.

This paper evaluates differences in a breast cancer polygenic risk score across genomic platforms and finds that calibration improves consistency in high-risk classification.

This study explores preferences of Asian women for breast cancer risk reports, finding a preference for comprehensive, simplified, and visually clear reports with follow-up recommendations.

The paper uses whole-exome sequencing data to identify novel breast cancer susceptibility genes and assess the contribution of coding variants to breast cancer risk.

The paper assesses breast cancer risks linked to rare missense variants in five susceptibility genes using logistic and mixture models, finding varying risk contributions across genes.

This study improves transcriptome-wide association studies by integrating pleiotropy-guided methods with GWAS data to identify new cancer susceptibility genes.