Daniel A Levy

The paper analyzes expression and splicing quantitative trait loci (e/sQTL) across multiple tissues in the TOPMed dataset and finds that secondary e/sQTL signals are still discoverable, with many GWAS signals colocalizing with these e/sQTL.

eQTM Atlas, an R Shiny resource, curates over 11 million DNA methylation-gene expression associations from eight cohorts and 11 tissues to annotate EWAS CpGs beyond proximity.

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.

The paper identifies a genomic signature, G-tract-AG motifs, that regulates transcriptome integrity and diversity through repression of AG usage and SNV-induced splicing activation.

The paper identifies variance QTLs (vQTLs) and gene-environment interactions for body fat distribution using UK Biobank MRI and genetic data, with replication in external cohorts.

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 introduces a method to compute Bayes factors for linear mixed models in genetic association studies using Bayesian regression and demonstrates its equivalence to BLUP predictions.

cellSTAAR integrates single-cell ATAC-seq with whole-genome sequencing to enhance power and interpretation of rare variant association tests in non-coding regions.

The paper identifies genes associated with obesity risk loci by integrating genetic and transcriptomic data from blood and brain tissues.

This paper introduces reflection knockoffs for feature selection in highly correlated datasets, showing improved performance in proteomics and genetic fine mapping.

The paper identifies a variant in DSP associated with QRS interval and shows that DSP-AS1 regulates DSP expression through functional and Mendelian randomization analyses.

This study identifies 22 novel gene-sleep duration interaction loci for blood pressure traits across 811,405 individuals, highlighting distinct genetic influences of short and long sleep on cardiovascular health.

The paper identifies genetic and phenotypic correlates of mosaic loss of chromosome Y in blood using whole genome sequencing data from the TOPMed program.

This study identifies gene-environment interactions between excessive daytime sleepiness and genetic variants linked to obstructive sleep apnea severity, revealing novel therapeutic targets.

This study identifies genetic variants influencing miRNA expression and links them to disease associations using genome-wide association studies and Mendelian randomization.

This study identifies over 2,000 POE eQTL in whole blood gene expression from the Framingham Heart Study, showing their abundance and complexity, and highlights implications for GWAS and Mendelian randomization.

The paper estimates mCA fitness in the NHLBI TOPMed cohort and identifies genetic variants associated with clonal expansion rates.

This paper introduces Kindred, a method for estimating inbreeding and kinship coefficients by modeling latent identity-by-descent states, showing high accuracy and non-negativity in kinship estimates.

The paper identifies novel genetic loci associated with systolic blood pressure that interact with the DASH diet score through genome-wide interaction analysis.

This paper introduces IDUL and IDUL{dagger}, efficient and asymptotically exact methods for fitting linear mixed models in genetic association studies, particularly for multiomics data.

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 identifies IL1RAP and AIM2 as key modifiers of CHIP-associated cardiovascular risk using UK Biobank data and CRISPR experiments in mice.

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.

This paper uses gradient boosted trees to improve polygenic risk prediction by capturing non-linear genetic effects and SNP interactions, showing significant increases in variance explained for multiple complex traits.

The paper examines heteroplasmic mitochondrial genetic variants in human cardiac tissues and finds they differ from those in blood and skeletal muscle, with higher variant counts in cardiac tissue linked to age.

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 integrates DNA methylation with clinical risk factors to improve mortality prediction, identifying CpG biomarkers associated with all-cause, cardiovascular, and cancer mortality.

This study identifies 592 genetic loci associated with 184 plasma proteins in 26,494 individuals and finds causal relationships between protein levels and disease.

The paper examines the concordance and characteristics of mitochondrial heteroplasmic mutations in maternal pairs of European and African ancestry, finding higher concordance in close relatives and associations with age and nuclear genome regions.

The paper identifies three causal lipid genes using Mendelian randomization and confirms their effects through mouse knockout studies and RNA-seq analysis.