Scott M. Damrauer

The paper identifies shared and distinct genetic architectures for cardiac structure and function using UK Biobank data, revealing common variants influencing multiple chambers and phenotypic variability.

This study performs a multi-population GWAS meta-analysis of acute and chronic pancreatitis, identifying genetic loci and potential therapeutic targets.

This paper develops a two-step genetic risk model for brain arteriovenous malformations (bAVM) using rare Mendelian variants and a polygenic risk score, identifying high-risk individuals with improved screening efficiency.

This study evaluates polygenic risk scores for hernia susceptibility and finds they are associated with incisional hernia but do not improve clinical risk prediction beyond traditional factors.

The paper identifies 800 exome-wide significant rare coding variants associated with blood lipids in over a million diverse individuals, including 130 driven by non-European-like populations.

This study identifies 243 genome-wide significant loci for hernia subtypes, reveals shared and distinct genetic factors, and identifies potential therapeutic targets.

The paper shows that statistical uncertainty explains disagreement in type 2 diabetes polygenic scores and proposes using uncertainty measures to improve risk prediction.

This study uses genomic structural equation modeling to identify genetic overlaps between psychiatric and physical illnesses, finding shared risk factors across multiple domains.

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.

This study uses Mendelian randomization to show that higher glycemic traits are inversely associated with thoracic aortic diameters and reduced risk of aneurysm and dissection.

This study identifies platelet traits as key risk factors for stroke using Mendelian Randomization and subclustering, revealing mechanisms involving platelet reactivity and endothelial cell adhesion.

The paper evaluates proteomic and polygenic risk scores for disease prediction, finding proteomic scores outperform polygenic scores in most traits and show temporal responsiveness.

The paper identifies pleiotropic loci across 1,167 traits using GWAS meta-analysis and shows they are enriched for functional annotations and improve polygenic score predictions.

This study shows that angiographic CAD burden independently contributes to adverse cardiovascular outcomes, even when traditional risk factors are accounted for.

This study identifies 257 novel genetic loci associated with diverticular disease through a large GWAS, linking them to connective tissue and colonic motility mechanisms.

This study identifies 91 risk loci for gallstone disease through a trans-ancestry GWAS, including 37 novel loci, and links them to metabolic and liver-related traits.

The paper identifies CXCL12 as a genetic driver of coronary artery anatomy variation through GWAS and mouse models, showing its role in fetal coronary development.

This study creates a gene regulation map of the human fetal heart to interpret genetic variants associated with congenital heart disease and cardiac traits, identifying valvular interstitial cells as key regulators.

This study evaluates the reliability of coronary artery disease polygenic risk scores across diverse populations, finding poor individual agreement despite equivalent population-level performance.

This study shows that platelet inhibition increases rupture risk in early abdominal aortic aneurysm models in mice.

This study uses multi-omics data to connect MRI-derived cardiac measures with gene and protein changes in heart failure, identifying shared pathways and novel insights into disease mechanisms.

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 uses Mendelian randomization to assess the causal effect of height on cardiovascular diseases, finding that established risk factors largely explain the association, with minimal residual effect.

This study develops multi-ancestry polygenic risk scores for venous thromboembolism using diverse GWAS data and shows improved predictive performance across European- and African-ancestry populations.

This paper optimizes the SAIGE algorithm using GPUs to accelerate GWAS on large datasets, achieving 20x speedup on the Million Veteran Program data.

This paper conducts a multi-ancestry time-to-event GWAS to identify genetic variants associated with incident cardiovascular disease in people with type 2 diabetes, finding three novel loci and confirming known CAD variants.

The paper uses reduced order modeling of aortic hemodynamics from CT scans to identify clinically relevant associations with vascular diseases in a biobank.

This paper evaluates plasma biomarkers for causal association with peripheral artery disease using Mendelian randomization, identifying 19 biomarkers with significant genetic evidence for causality.

This study examines the association between CYP2C19 polymorphisms and major adverse cardiac events after PCI in patients with ACS or SIHD, finding no significant overall association but a numerical increase in risk for ACS patients.

The paper identifies a novel risk locus for PAD on 2q35 in Dominicans using admixture mapping and health systems data.