Guillaume Butler‐Laporte

This study maps MHC-pQTL across ancestries, identifying genetic associations with plasma proteins and linking HLA genes to immune-related traits.

The paper uses Mendelian randomization to show that current disease-mortality GWAS may lack sufficient power to detect shared genetic effects, despite strong associations in case-control studies.

The paper maps adipokine-associated variants to effector genes across 1,669 traits, identifying TGFB2 and VEGFA as linked to insulin resistance and distinct disease risks.

This paper identifies risk proteins for intracranial aneurysms using multi-ancestry proteogenomic analysis and finds ADH4 and PLEKHA1 as non-blood pressure-mediated candidates.

This study identifies OA-specific genetic effects and novel therapeutic targets by separating OA genetics from those shared with obesity using GWAS and proteomics data.

The paper introduces a customizable pipeline for exome-wide rare variant gene-trait associations, demonstrating its utility by replicating three studies and providing a standardized framework for similar analyses.

The paper tests using protein network partners to identify drug targets, finding that while sensitivity improves, precision is low, limiting practical application.

This paper introduces HLA-colocalization, a method for genetic colocalization at the HLA locus using HLA alleles, showing it identifies novel causal associations between viruses and autoimmune diseases.

This study uses proteome-phenome-wide Mendelian randomization across three ancestries to identify protein-phenotype associations and potential therapeutic targets.

This study evaluates AlphaMissense's impact on gene-based testing for disease causation using UK Biobank exome data, finding no significant improvement in identifying disease-causing genes.

The paper identifies HLA variants associated with HBV vaccine response in Bangladeshi infants and links them to vaccine escape mechanisms.

The paper identifies nephronectin as a mediator of obesity's effect on COVID-19 severity using proteome-wide Mendelian randomization and validates its expression in lung cells.

This study uses whole-exome sequencing to directly call HLA alleles in the UK Biobank, identifying 129 novel associations between HLA alleles and 11 autoimmune diseases.

The paper identifies an alternative splicing variant of OAS1 that provides protection against severe COVID-19 in people of African ancestry, independent of Neanderthal haplotypes.

The paper develops a machine learning model to predict COVID-19 severity using exonic variants from whole exome sequencing data, finding that variants across all frequency categories contribute to severity.

This study examines how a major genetic risk factor for COVID-19 affects mortality and severity, finding stronger effects in younger adults.

The paper investigates the association of rare loss-of-function variants in type I IFN immunity genes with severe COVID-19 and finds no significant association.

This study identifies OAS1 as a protective factor against COVID-19 severity and susceptibility using Mendelian randomization and case-control analyses.

This study identifies 13 genome-wide significant loci associated with SARS-CoV-2 infection or severe COVID-19 through a global meta-analysis of 49,562 patients.