Lori C. Sakoda

This study performs a cell-type-aware transcriptome-wide association study (TWAS) of mammographic density phenotypes, identifying novel genes and prioritizing known GWAS loci through cell-type-specific gene expression analysis.

This study improves polygenic risk scores for colorectal cancer by combining Asian and European ancestry data, enhancing risk prediction across diverse racial and ethnic groups.

MiXcan performs cell-type-specific transcriptome-wide association studies, identifying more breast cancer susceptibility genes than conventional methods by considering cell-type heterogeneity.

This study identifies 22 genetic variant-phenotype associations linked to multiple primary cancers using whole-exome sequencing in two large multi-ancestry cohorts.

This study identifies eight novel genetic signals associated with asthma-COPD overlap through a genome-wide association analysis involving multiple cohorts.

This study identifies 13 new genetic loci specific to proximal or distal colorectal cancer subtypes, revealing partly distinct genetic architectures for these tumor locations.

This study evaluates polygenic risk scores across 17 cancer types in two large cohorts, identifying cross-cancer associations and non-cancer phenotype links.

This study identifies six novel genetic loci, including two rare variants, and shows that a polygenic risk score strongly predicts prostate cancer risk.

The paper conducts pan-cancer GWAS in two cohorts, identifying novel risk variants and shared genetic basis across 18 cancer types.