Lauren Costa

The paper uses Mendelian Randomization to predict adverse drug reactions by linking genetic variants to gene expression and protein abundance across large datasets.

This study conducts a multi-ancestry GWAS of rheumatoid arthritis using the VA Million Veteran Program, identifying 152 genome-wide significant loci and improving fine-mapping resolution.

This study uses large biobanks to identify gene-trait pairs with causal evidence, rediscover approved drug targets, and develop a predictive model for drug development.

Population-stratified GWAS of 2,068 traits in 635,969 Million Veteran Program participants, 29% genetically non-European, yields 98,485 associations and 57,601 fine-mapped signals with largely shared cross-population architecture.

The paper examines differential associations of the IL6R variant across genetic ancestries and identifies trait differences that may inform targeted therapies.

This study identifies genetic variants associated with severe COVID-19 and finds shared genetic architecture with complex diseases using EHR data from the Million Veteran Program.