Christopher J. O’Donnell

This study identifies shared genetic loci and genes between PTSD and cardiovascular conditions using GWAS across multiple data sources and finds overlapping biological pathways and drug targets.

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.

This study compares the genetic architecture of heart failure with preserved ejection fraction (HFpEF) and reduced ejection fraction (HFrEF), finding distinct genetic associations and highlighting HFpEF's heterogeneity.

This study identifies 135 genomic loci associated with venous thromboembolism risk through cross-ancestry GWAS and provides insights into biological pathways and potential therapeutic targets.

This study investigates the genetic and longitudinal relationship between posttraumatic stress disorder and coronary artery disease using genome-wide data and electronic health records.

This study conducts a trans-ancestry GWAS using chronic ALT elevation as a proxy for NAFLD, identifies 77 significant loci, and validates 17 SNPs with histology and imaging data, revealing genetic links to metabolic and inflammatory traits.

This study integrates rare large-effect expression variants into polygenic risk scores, showing improved prediction of complex traits by including these variants in risk assessment.

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.

This study shows that FH genetic variants increase CAD risk even after adjusting for multiple LDL-C measurements from EHRs, indicating LDL-C data alone cannot fully explain the risk.

This study performs multi-trait GWAS on atherosclerosis-related traits to identify novel pleiotropic loci and their potential biological mechanisms.

This study identifies 424 new loci associated with kidney function using GWAS data from over 1.2 million individuals and prioritizes 34 genes for further functional investigation.

The paper evaluates penetrance and variable expressivity of monogenic metabolic conditions using exome data from 77,184 individuals, finding that monogenic variants have larger effect sizes than polygenic scores but low penetrance.

This study identifies new genetic loci associated with myocardial infarction and coronary heart disease using genome-wide association analyses across multiple cohorts.

This study shows smoking increases type 2 diabetes risk through BMI, but not coronary artery disease risk, using Mendelian randomization.

Multi-ethnic type 2 diabetes (T2D) meta-analysis of 228,499 cases and 1,178,783 controls finds 318 previously unreported loci, 804 expression-colocalized genes, and 13 SNP-by-T2D vascular-outcome interactions.

The paper describes the design and performance of the MVP 1.0 custom Axiom array for genotyping a diverse cohort, achieving high-quality genetic data with substantial ancestral diversity.

This study identifies 14 genome-wide significant loci and a polygenic signature for myeloproliferative neoplasms, implicating hematopoietic stem cell function and self-renewal in disease risk.

This paper evaluates the causal effect of fibrinogen on coronary heart disease using Mendelian randomization, finding a small effect with multi-variant methods but not with single variant approaches.

This paper develops an automated high-throughput phenotyping method (MAP) that improves phenotype accuracy and scalability for PheWAS studies.

The paper uses GWIS to analyze genetic correlations between HOMA-B/-IR and inflammatory markers, identifying novel loci and strong genetic links with PAI-1 and C-reactive protein.

This study evaluates the genetic architecture of sudden cardiac arrest through GWAS and Mendelian randomization, finding genetic correlations with CAD, height, BMI, and electrical instability traits.

The paper uses machine learning to identify SNPs predictive of advanced coronary artery calcium in two cohorts, finding that SNPs from extreme cases outperform those from prior GWAS.