Douglas F. Easton

This study analyzes breast cancer GWAS across multiple ancestries, finding similar heritability and genetic correlations, and identifies shared regulatory and cellular contexts.

The paper distinguishes germline and somatic TP53 variants using whole-exome data from UK Biobank participants, showing somatic variants dominate cancer risk in middle-aged adults.

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

The paper estimates the contribution of rare coding variants to cancer heritability using UK Biobank whole-exome sequencing data and finds ovarian cancer has the highest proportion of heritability from protein-truncating variants.

The paper updates breast cancer risk estimates for BRCA2 carriers aged 60 and older using data from two large studies.

The paper analyzes age-related changes in clonal haematopoiesis (CH) using whole exome data from 420,000 UK Biobank participants, finding a deceleration of clonal expansion with age.

This paper evaluates methods to incorporate alternative polygenic risk scores into the BOADICEA breast cancer risk prediction model, finding that retrospective likelihood approaches provide more accurate estimates.

This paper evaluates polygenic risk scores for breast cancer prediction in Korean women, finding that combining Asian and European PRS improves discrimination over lifestyle factors.

This study analyzes 17,425 breast cancer families to assess genetic factors contributing to familial risk, finding a recessive risk component and polygenic factors explain residual familial variance.

This paper updates the BOADICEA cancer risk prediction model to include new genetic variants and continuous risk factors, improving risk reclassification for specific gene carriers.

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.

This paper develops polygenic risk scores for breast cancer prediction in women of African ancestry by combining African and European ancestry datasets, improving prediction accuracy.

The paper develops a multifactorial risk model for epithelial tubo-ovarian cancer incorporating genetic and epidemiological factors to stratify risk and guide screening.

ClinGen and the PGS Catalog expand the GRIPS guideline into a 22-item Polygenic Risk Score Reporting Statement covering study populations, model construction, evaluation, and clinical interpretation.

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

CamCNV improves detection of rare CNVs from Illumina arrays by using z-score segmentation, achieving 85% sensitivity for deletions and 65% for duplications with reliable false discovery rate control.

This study assesses polygenicity and risk prediction using common variants across 14 cancers, finding varying numbers of susceptibility variants and risk score effectiveness.

This study combines genome-wide association data from four cancers to identify shared and novel genetic associations and pleiotropic effects.

This paper evaluates how sample size affects polygenic hazard score models for prostate cancer, finding that 20-30k samples are needed for discovery models, but 10k suffice if SNPs are pre-established.

The paper maps chromatin interactions at 139 breast cancer risk signals using Capture Hi-C and identifies candidate target genes and functional mechanisms.

The paper evaluates a polygenic hazard score for prostate cancer screening, showing it improves positive predictive value by adjusting screening age based on genetic risk.

This study identifies 15 common and 9 low-frequency protein-coding variants associated with body fat distribution, implicating novel genes related to lipid homeostasis and type 2 diabetes.

The paper identifies 14 genes, including NTN4, associated with breast cancer risk variants through allelic expression imbalance analysis.

The paper identifies genetic determinants of mosaic Y chromosome loss in blood and links it to genomic instability and non-haematological cancer risk.

This study identifies 78 genetic signals for male puberty timing using a large sample of men, revealing links to hair color and health outcomes.

This paper identifies novel pleiotropic risk loci for melanoma and nevus density, implicating multiple biological pathways and gene expression under MITF regulation.

This paper develops a genetic risk score to personalize prostate cancer screening age based on polygenic hazard scores and validates its predictive power in a separate dataset.