Kelly Cho

This study evaluates cancer-specific polygenic risk scores (PRS) across diverse ancestries and finds they predict corresponding cancers with varying effectiveness and limited pleiotropy.

This study expands the human plasma proteome analysis using an enhanced SomaScan platform, identifying new genetic associations and disease mechanisms beyond the classical secretome.

The paper uses Mendelian Randomization to predict adverse drug reactions by linking genetic variants to gene expression and protein abundance across large datasets.

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 conducts an X-chromosome-wide association study to identify genetic signals for heart failure and its subtypes, finding novel loci and replicating some in UK Biobank.

This study conducts a multi-ancestry GWAS of rheumatoid arthritis using the VA Million Veteran Program, identifying 152 genome-wide significant loci and improving fine-mapping resolution.

This study identifies two independent BMI-associated variants at the GLP1R locus with distinct associations with T2D risk, suggesting heterogeneous genetic mechanisms.

The paper introduces a transformer-based language model to identify computable phenotype definitions in biomedical literature and integrates it into a platform for literature curation.

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.

The paper identifies causal protein drivers and drug targets for heterogeneous kidney diseases using proteome-wide Mendelian randomization and EHR data.

This study identifies novel genetic signals associated with severe obesity through GWAS and shows strong genetic overlap with BMI, highlighting shared comorbidities and lifestyle interactions.

This paper develops a semi-empirical Bayesian framework to calibrate weak instrumental bias in sex-specific Mendelian randomization studies, revealing significant sex differences in causal effects of sleep phenotypes on cardiovascular diseases.

This study performs a genome-wide association study for Long COVID, identifying a significant association with the FOXP4 locus and highlighting the role of pulmonary dysfunction and COVID-19 severity.

The paper performs GWAS on cardiovascular outcomes in CKD patients, identifying stroke-associated SNVs but not replicating CHD findings, and finding genetic correlations with published GWAS.

This paper presents a computational drug repurposing framework that identifies FDA-approved drugs for COVID-19 by integrating genetic expression data and EMR data, finding four compounds with protective effects in validation.

This study uses whole genome sequencing to identify 18 novel genetic loci associated with plasma fibrinogen levels, including variants more common in African populations and linked to liver-related traits and disease.

This study identifies 17 genetic loci associated with sleep duration and lipid levels, offering potential druggable targets for dyslipidemia in individuals with sleep disturbances.

This study uses Mendelian randomization to identify two proteins, CCL27 and TNFRSF14, that influence subsequent cardiovascular events after a stroke, suggesting inflammation as a contributing factor.

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 identifies six novel genetic loci associated with BMI change over adulthood using UK Biobank health records, finding lower heritability for BMI change compared to baseline BMI.

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

This study identifies novel genetic risk variants and potential drug targets for heart failure using GWAS and Mendelian randomization proteomics.

This study conducts a GWAS of obstructive sleep apnea in the Million Veteran Program, identifying sex-specific genetic loci and highlighting genetic heterogeneity by sex.

This study performs a GWAS of dementia in African-ancestry individuals, identifying risk loci and highlighting differences in gene expression.

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.

The paper examines differential associations of the IL6R variant across genetic ancestries and identifies trait differences that may inform targeted therapies.

The paper identifies IL10RB as a key regulator of COVID-19 host susceptibility and severity through integrative analysis of genetic and transcriptomic data, and validates potential drug repositioning candidates.

This study analyzes clonal hematopoiesis in over a million diverse individuals, identifying 72 genome-wide significant loci and linking CHIP to various phenotypes.

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 identifies genetic variants associated with severe COVID-19 and finds shared genetic architecture with complex diseases using EHR data from the Million Veteran Program.