Wendy S. Post

This study integrates CAD GWAS with transcriptomic data to identify genes and networks associated with CAD and subclinical atherosclerosis.

The paper evaluates polygenic risk scores for dementia prediction in diverse populations, finding that a model with fewer SNPs outperforms one with more SNPs in multiple ethnic groups.

The paper identifies plasma proteins associated with clonal hematopoiesis and links them to cardiovascular disease through proteomic and genetic analyses.

The paper develops a method to quantify somatic mutation burden in whole-genome sequencing data without paired-tissue samples and identifies genetic and phenotypic correlates of clonal hematopoiesis without known driver mutations.

The paper shows that variant effect sizes on quantitative endophenotypes support pathogenicity in monogenic disease genes.

This study investigates how rare and common genetic variations contribute to QT interval duration, finding that both monogenic and polygenic factors influence QTc prolongation, with polygenic risk modulating the effect of rare variants.

The paper uses bidirectional Mendelian randomization to show LTL lengthening increases CHIP risk, while CHIP accelerates LTL shortening, with modest mediation between CHIP and CAD via LTL.

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 investigates the association between mitochondrial DNA copy number and risk of atrial fibrillation in three cohorts, finding an inverse relationship after adjustment for traditional risk factors.

This study identifies one known and two novel genetic variants associated with heart failure through GWAS and multi-omic analyses, revealing potential causal mechanisms and shared heritability with musculoskeletal traits.

The paper introduces SMMAT, a variant-set mixed model association test for continuous and binary traits in large-scale WGS studies, showing it controls type I error rates and applies to population structured and related samples.

This study identifies rare genetic variants associated with type 2 diabetes using exome sequencing of 20,791 cases and 24,440 controls, and provides a Bayesian framework to improve variant prioritization.

The paper uses whole genome sequencing to identify genetic variants associated with plasma lipoprotein(a) levels and finds high heritability and inter-ethnic differences in Lp(a) risk.