Joshua S. Weinstock

This study identifies centromeric structural variants linked to molecular traits and complex diseases in humans using long-read sequencing and haplotype-resolved analysis.

The paper analyzes 791K whole genomes to identify genetic, geographic, and phenotypic factors associated with somatic passenger mutations in blood, revealing shared pathways and population-specific determinants of clonal hematopoiesis.

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.

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

The paper identifies novel non-coding driver mutations in clonal hematopoiesis using whole genome sequences from the UK Biobank and links them to common diseases.

This paper introduces PRSFNN, a neural empirical Bayesian method for polygenic prediction that outperforms existing methods on 17 of 18 traits in the UK Biobank.

This paper introduces GLEANR, a method for sparse matrix factorization of GWAS summary statistics that accounts for sample sharing and identifies interpretable genetic factors.

This study uses CRISPR perturbations in CD4+ T cells to infer a gene regulatory network, revealing trans-regulatory mechanisms linking immune GWAS genes to signaling pathways.

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

This study benchmarks expression forecasting methods using 11 perturbation datasets, finding that simple baselines often outperform complex models using mean squared error.

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

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.

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

This study conducts a meta-analysis of EHR-based lab measurements across two biobanks, identifying novel genetic associations and validating EHR data as a source for GWAS.

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

Meta-MultiSKAT improves power for region-based genetic association tests by meta-analyzing multiple correlated phenotypes using summary statistics and variance component tests.