Michael G. Levin

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 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.

This study links a polygenic risk score for coronary artery disease to coronary atherosclerotic burden measured by clinical CT angiograms.

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 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.

The paper identifies 57 druggable targets for MASLD using genetic data and evaluates their therapeutic potential through Mendelian randomization and structural modeling.

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 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.

This paper introduces Multi-response Mendelian randomization (MR2) to identify shared and distinct exposures for multiple disease outcomes, showing improved power and accuracy by accounting for residual correlations between outcomes.

The paper identifies a FOG2 variant associated with coronary microvascular disease and shows it alters hypoxia-mediated gene transcription and angiogenesis.

This paper evaluates adding polygenic risk scores to the RECODe model for predicting cardiovascular outcomes in type 2 diabetes patients, finding no significant improvement in predictive performance.

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.

ColocQuiaL performs colocalization analysis between GWAS and eQTL/sQTL data to identify candidate causal genes for GWAS signals.

This study identifies 144 genetic loci associated with abdominal aortic aneurysm and highlights PCSK9 as a therapeutic target through Mendelian Randomization and pre-clinical validation.

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

The paper evaluates gene burden tests for rare variants in MYBPC3 and MYH7 using exome data and EHRs, finding differing associations between pLOF and pDM variants and HCM.

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