Robert C. Kaplan

The paper examines the relationship between self-reported race, genetic ancestry, and hypertension prevalence among Hispanics/Latinos using the HCHS/SOL dataset.

The paper introduces the expected polygenic risk score (ePRS) framework to address population stratification in polygenic risk score analysis by modeling ancestral makeup, showing it provides equitable risk quantification across diverse populations.

This paper improves polygenic prediction of height in an admixed Latino cohort by incorporating genetic ancestry, achieving a 0.1 increase in R² compared to using polygenic scores alone.

This study investigates the association between mosaic loss of Y chromosome (mLOY) and lung function, emphysema, and epigenetic aging in men across multiple cohorts.

The paper investigates unexplained admixture mapping signals in the Hispanic Community Health Study/Study of Latinos by examining rare variants and expanded common variant regions, finding that common variants explain most signals.

The paper introduces MultiSTAAR, a statistical framework for multi-trait rare variant analysis in WGS studies, identifying new lipid trait associations in diverse populations.

This study conducts a GWAS on fatty acids and oxylipins in HCHS/SOL participants, identifying 19 genetic loci and shared/distinct genetic architecture.

The paper introduces a CN caller for KIV-2 repeats using short reads, showing high accuracy and demonstrating its correlation with Lp(a) levels and population-specific CN distributions.

The paper introduces ClOneHORT, a method to generate synthetic genomes with high fidelity using deep generative models, achieving accurate results in downstream analyses.

The paper introduces a weighted variance components framework to integrate metagenomic and metabolomic data for pathway analysis, showing improved power while controlling type I error.

The paper identifies 83 rare lncRNA variant sets associated with blood lipid levels using WGS data from the TOPMed program and validates some in UK Biobank data.

The paper analyzes inflammation biomarkers using whole-genome sequencing from the TOPMed consortium, identifying both single-variant and rare variant associations with inflammatory traits.

This study shows that common splice-regulatory variants can reduce the pathogenicity of rare exonic variants by modulating mRNA splicing.

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

StocSum generates stochastic summary statistics for whole genome sequencing studies without external reference panels, enabling various genetic analyses and improving utility for underrepresented populations.

The paper identifies a gene-diet interaction modifying the association between macronutrient intake and glycemic traits, highlighting challenges in detecting such interactions due to measurement error and sample size.

The paper presents a comprehensive catalog of structural variants across 138,134 individuals, identifying novel variants and their associations with cardio-metabolic and hematologic traits.

The paper performs whole genome sequence analysis of plasma lipid levels in 66,329 individuals, identifying new lipid-associated alleles, including rare non-coding variants.

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

The paper integrates multi-omics data to analyze how sleep-disordered breathing traits affect gene expression, metabolites, and potential causal pathways across blood cell types.

This paper constructs a multi-ethnic polygenic risk score for hypertension and shows it is associated with hypertension prevalence, progression, and related clinical outcomes.

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 introduces a kernel-based method to identify host genetic variants associated with microbiome beta-diversity, finding immunity-related genes influence gut microbiota composition.

The paper estimates genetic and environmental correlations between complex phenotypes across different racial/ethnic groups and sexes using data from the TOPMed program.

The paper shows Amerind ancestry is linked to lower LC-PUFA levels and increased cardiometabolic risk in Hispanic populations due to FADS genetic variation.

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.

The paper identifies 31 host genetic loci influencing gut microbiome composition through GWAS and suggests causal effects in inflammatory diseases.

The paper catalogs structural variants across 19,652 genomes and identifies their associations with proteomic measurements and disease phenotypes.