Jonathan Marchini

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.

The paper performs metabolomics exome and genome-wide association studies in Amish adults, identifying genetic variants linked to metabolites and cardiometabolic traits.

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.

This paper builds a haplotype reference panel from Genomics England data and imputes UK Biobank data, revealing more rare variants and suggesting limitations in detecting rare variant associations with current sample sizes.

The paper identifies a NOTCH3 variant, p.Arg1231Cys, enriched in South Asians and strongly associated with stroke risk, highlighting the importance of genetic diversity in stroke research.

The paper shows genetic effect sizes are similar across African and European populations for most traits, suggesting shared causal mutations and improving GWAS portability.

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

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.

This paper introduces a statistical framework for GWAS that controls false discovery rate while accounting for population structure and relatedness, validated through simulations and UK Biobank data.

The paper introduces REGENIE, a fast whole genome regression method for quantitative and binary traits, showing computational efficiency and accuracy on UK Biobank data.

The paper develops a non-linear randomized Haseman-Elston regression method to estimate gene-environment heritability using UK Biobank data and shows it is computationally efficient and correlated with existing methods.

The paper introduces a 4D tensor decomposition method for gene expression data, showing improved structure estimation compared to 3D methods on simulated data.

IMPUTE5 improves genotype imputation by scaling sub-linearly with reference panel size and using the Positional Burrows Wheeler Transform for efficient haplotype selection.

This paper introduces a Bayesian whole genome regression model to analyze gene-environment interactions in the UK Biobank, finding that GxE effects explain a notable proportion of phenotypic variance in several traits.

This study identifies traits associated with polygenic risk for depression using UK Biobank data and finds causal links between depression risk and brain structure, as well as environmental interactions.

SHAPEIT4 improves haplotype estimation with sub-linear scaling, high accuracy, and integration of external phasing information using UK Biobank and Genome In A Bottle datasets.

This study identifies genetic loci specific to periventricular and deep white matter hyperintensities, revealing distinct genetic architectures and potential biological mechanisms.

The paper develops a framework to analyze single-cell transcriptomes from mouse testes, identifying gene regulatory programs and pathological processes in mutant strains.

The paper uses MRI data to show that white matter microstructure predicts functional connectivity between brain regions, with genetic variants linked to this relationship.

Exomes of 49,960 UK Biobank participants reveal 231,631 predicted loss-of-function variants (>10-fold more than imputed data); burden tests implicate PIEZO1, MEPE, and COL6A1 in disease traits.

This study identifies genome-wide significant genetic loci for handedness and links them to microtubule-related genes associated with brain lateralization and neurodevelopmental disorders.