Ruth C. Travis

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.

Identifying therapeutic targets for cancer: 2,094 circulating proteins and risk of nine cancers

This study identifies 40 circulating proteins associated with cancer risk using MR and colocalization, highlighting potential therapeutic targets and adverse effects of protein-altering interventions.

A new pipeline for the normalization and pooling of metabolomics data

The paper introduces a pipeline to normalize and pool metabolomics data across studies, improving comparability and reducing inter-study variability.

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.

IL-18 and Lower Risk for Lung Cancer: Triangulated Evidence from Germline Predictions, Pre-Diagnostic Measurements, and Tumor Expression

This study identifies IL-18 as a biomarker for reduced lung cancer risk using genetic, pre-diagnostic, and tumor expression data, with potential therapeutic implications.

Polygenic hazard score is associated with prostate cancer in multi-ethnic populations

This study evaluates a polygenic hazard score in multi-ethnic populations and finds it is associated with age at prostate cancer diagnosis, aggressive diagnosis, and death across European, Asian, and African ancestries.

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.

Insulin-like growth factor-1 (IGF-1), insulin-like growth factor-binding protein-3 (IGFBP-3) and breast cancer risk: observational and Mendelian randomization analyses

This study examines the association between IGF-1 and breast cancer risk using observational and Mendelian randomization analyses, finding a positive association and suggesting a causal relationship.

Physical activity and risks of breast and colorectal cancer: A Mendelian randomization analysis

This study uses Mendelian randomization to show that higher physical activity levels are associated with lower risks of breast and colorectal cancer.

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.