Gonçalo R. Abecasis

This paper performs a local ancestry-aware GWAS on SCD cohorts to identify novel genetic loci associated with eGFR, uncovering regions linked to inflammation, ECM integrity, and other pathways relevant to SCD nephropathy.

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.

This study identifies 207 height-associated genes using rare protein-altering variants from over 1.4 million individuals, showing large effect sizes and overlap with Mendelian height syndromes.

This study quantifies cancer risk and penetrance in CHEK2 heterozygotes using genomic data from two large biobanks, finding increased risks for several cancers and younger age of onset.

The paper introduces REMETA, a tool for efficiently performing meta-analysis of gene-based tests using summary statistics, demonstrating its application on UK Biobank data.

The paper improves rare variant association studies by using proteomics-informed large language models, identifying more gene-trait associations than existing methods.

This study identifies 1,257 genetic variants associated with human personality traits using large-scale GWAS and finds widespread genetic correlations with behaviors and life outcomes.

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

The paper introduces SBAT, a method for joint testing of rare variant burden scores, showing it is well calibrated and outperforms existing tests in some scenarios.

The paper compares the effectiveness of whole genome sequencing, whole exome sequencing with imputation, and array genotyping in detecting genetic associations across 100 complex traits in the UK Biobank, finding that WES+IMP provides similar signal yield to WGS with greater efficiency.

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.

This paper presents the largest catalog of human protein-coding variation from 985,830 individuals, identifying rare variants and their functional implications for precision medicine.

The Michigan Genomics Initiative links genotypes with electronic clinical records in Michigan Medicine patients, showing higher disease prevalence and validating GWAS findings.

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 identifies rare coding variants in CHRNB2 associated with reduced smoking likelihood and links them to downstream smoking-related phenotypes.

The paper introduces a framework for detecting noncoding rare variant associations using whole-genome sequencing data, applying it to lipid traits in the TOPMed program.

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 genotypes and sequences 140,000 adults from the Mexico City Prospective Study, revealing ancestry diversity and developing imputation resources for genetic studies.

The paper examines genetic variation and natural selection at SARS-CoV-2 host genes in diverse populations and links selected variants to clinical phenotypes in COVID-19.

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 identifies a rare variant that lowers ACE2 expression and reduces COVID-19 risk, and develops a genetic risk score predicting severe disease.

The paper estimates heritability for height and BMI using whole-genome sequence data and finds that rare variants contribute significantly to the missing heritability.

The paper identifies 51 known and 23 novel gene-disease associations using exome sequencing data from 200,000 UK Biobank participants, highlighting high-impact rare variants for 26 diseases and traits.

This study uses exome sequencing of 628,388 individuals to identify genetic variants associated with clonal hematopoiesis and its health outcomes.

The paper conducts a genome-wide association study of liver fat, iron, and extracellular fluid fraction using UK Biobank MRI data, identifying novel genetic loci for these traits.

The paper reports whole-genome association analyses of sleep-disordered breathing traits in the NHLBI TOPMed program, identifying rare and common variant associations.

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.