Patrick T. Ellinor

This study integrates common and rare variant mapping across diverse populations to identify novel therapeutic targets, finding NRG4 as a candidate for preserving kidney function.

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 shows that silencing Spp1 in TREM2+ cardiac macrophages reduces atrial fibrosis and suppresses AFib in mice, suggesting a new immunotherapy approach.

This study examines associations between leukocyte telomere length and genomic, phenomic, and geographic factors in diverse U.S. populations, identifying novel loci and genes.

This study identifies 12 enhancers in the 9p21.3 CAD risk locus that regulate MTAP, modulating vascular cell-state transitions and CAD risk through stress-responsive mechanisms.

HeartMap integrates single-nucleus RNA sequencing data from 2.4 million cells across 209 individuals to characterize cardiac cell types and identify disease-associated gene signatures in cardiomyopathies.

The paper analyzes over 800,000 human genomes to assess penetrance of clinically relevant variants, finding that 95% of pLoF variants in severe diseases have explanations for lack of disease manifestation.

This paper shows that obesity-related extracellular vesicles from visceral adipose tissue impair cardiac function and contribute to arrhythmia by affecting cardiomyocytes, fibroblasts, and macrophages.

The paper identifies pleiotropic loci across 1,167 traits using GWAS meta-analysis and shows they are enriched for functional annotations and improve polygenic score predictions.

This paper uses snRNA-seq to analyze human HFpEF myocardium, identifying differential gene expression and pathway enrichment in cardiomyocytes and fibroblasts compared to controls and DCM.

This study identifies 80 genetic loci and 61 effector genes associated with dilated cardiomyopathy through GWAS and integrates transcriptomic data to uncover biological pathways and cellular states involved in the disease.

The paper identifies a rare variant in VE-PTP associated with CSC, varicose veins, and glaucoma using genome-wide data from multiple cohorts.

Rare-variant depletion in 1kb windows of 76,156 gnomAD genomes, versus feature-adjusted mutation expectations, marks regulatory elements and outperforms seven alternative scores at flagging functional non-coding variants.

The paper develops a method to infer compound heterozygosity from exome sequencing data, achieving high accuracy in phasing rare variants for recessive disease diagnosis.

The paper analyzes genetic, ancestral, and geospatial data from a biobank to explore their relationships with health outcomes in a historically diverse population.

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.

CellBender removes systematic background noise from droplet-based single-cell data using a deep generative model, improving alignment with established gene expression patterns.

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

FusNet predicts protein-mediated chromatin loops using genome sequence, open chromatin, and ChIP-seq data, showing high consistency with Hi-C and associations with regulatory functions and disease risk variants.

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

The paper applies transfer learning to predict network biology features across different biological contexts.

The paper uses machine learning to analyze myocardial T1 time in UK Biobank data, identifying genetic loci and pathways associated with interstitial fibrosis and related cardiovascular diseases.

The paper shows adjusting for common variant polygenic scores improves rare variant association yield in 65 UK Biobank traits without increasing false positives.

This study constructs a 3D genome atlas of genetic variants and their pathological effects using a scoring algorithm and a web-based database.

The paper analyzes whole-genome sequences from 98,622 participants to identify common and rare variants associated with cardiometabolic traits, replicating known associations and finding new loci.

The paper imputes tissue-specific gene expression for 486,452 UK Biobank participants and demonstrates its use in prioritizing therapeutic targets and predicting phenotypic risk.

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.

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