David Edgar Neal

Germline polygenic score for prostate cancer aggressiveness

This paper develops a germline polygenic score (PRSagg) to predict prostate cancer aggressiveness and validates it across multiple datasets.

From a genomic risk model to clinical trial implementation in a learning health system: the ProGRESS Study

The paper develops a polygenic risk model for prostate cancer using VA data and validates it in external cohorts, showing its clinical utility in risk stratification.

Prostate cancer risk stratification improved across multiple ancestries with new polygenic hazard score

The paper improves prostate cancer risk stratification across multiple ancestries using a new polygenic hazard score with additional SNPs, showing higher hazard ratios and positive predictive value for clinically significant prostate cancer.

Additional SNPs improve the performance of a polygenic hazard score for prostate cancer

This study improves a polygenic hazard score for prostate cancer by adding 120 SNPs, enhancing hazard ratios but not positive predictive value of PSA testing.

The effect of sample size on polygenic hazard models for prostate cancer

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.

Disease mechanism, drug-target and biomarker prediction software: Application on prostate cancer and validation

The paper introduces an R software package for differential network analysis to predict disease mechanisms, drug targets, and biomarkers using gene expression data from two conditions, validated on prostate cancer datasets.

A genetic hazard score to personalize prostate cancer screening, applied to population data

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.

Large-scale transcriptome-wide association study identifies new prostate cancer risk regions

This study integrates a large prostate cancer GWAS with gene expression data to identify 235 genes associated with risk, prioritizing causal genes through Bayesian credible sets.

A genetic risk score to guide age-specific, personalized prostate cancer screening

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.