Susan R. Heckbert

This study uses whole-genome sequence data from diverse participants to identify novel genetic loci associated with brain structural volumes, highlighting the importance of diverse cohorts in uncovering genetic architecture.

This study addresses dementia classification bias across ethnic groups using few-shot learning and domain alignment, reducing performance gaps between White American and Hispanic cohorts.

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 validates novel telomere length regulation genes POP5 and KBTBD6 identified through trans-ancestry GWAS using functional experiments in blood cells.

The paper develops PACER to infer clonal expansion rates from single timepoint data and identifies TCL1A activation as a mediator of clonal hematopoiesis fitness.

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.

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

The paper performs whole genome sequence association analysis of fasting glucose and insulin levels in diverse cohorts, identifying 22 significant variants across 16 gene regions, including rare variants.

The paper identifies 617 novel genomic loci and pathways associated with structural covariance patterns in the human brain using a stochastic multivariate factorization method.

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 describes a system for harmonizing phenotype data across multiple studies in the TOPMed program, enabling reproducible and shared phenotype data for over 80 studies.

Over 400 million variants, 97% below 1% frequency, emerge from deep whole-genome sequencing of 53,831 diverse TOPMed participants; TOPMed haplotypes enable imputation down to ~0.01% frequency.

This study identifies 59 sentinel variants and two novel genes associated with telomere length using whole genome sequences from 109,122 trans-ethnic individuals.

The paper identifies rare non-coding variants from whole genome sequencing in the TOPMed program, showing they contribute significantly to type 2 diabetes heritability.

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 uses TOPMed whole genome sequences to improve imputation quality and detect rare variant associations in admixed African and Hispanic/Latino populations, identifying two novel associations with hematological traits.

The paper identifies germline genetic variants associated with clonal hematopoiesis of indeterminate potential (CHIP) using whole genome sequences from the TOPMed program.

This study conducts a GWAS on QRS duration in Hispanic/Latino populations, identifying two new loci and confirming most previously known SNPs.

This study identifies over 50 new genetic loci associated with pulmonary function through a multiethnic meta-analysis of 90,715 individuals.

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.

This paper introduces SAPPHO methods to detect pleiotropy in GWAS by modeling shared patterns of genetic associations, finding 16 additional and 124 novel loci in meta-analysis.