Yann Le Guen

This study uses a CRISPR screen to identify genes critical for erythroblast enucleation, finding CLIC3 and VAMP8 as key factors with distinct roles in the process.

This paper conducts a genome-wide association study of Alzheimer's disease and dementia in a multi-ancestry military cohort, identifying 72 new dementia-associated loci through meta-analysis.

This study identifies CD44 as a host factor promoting Plasmodium falciparum invasion through cross-linking, which alters RBC membrane structure and enhances ligand-receptor interactions.

The paper investigates age-related changes in cerebellar microglia using single-nuclei RNA sequencing and MERFISH, finding enhanced neuroprotective immune activation and proximity to granule cells in aged mice.

The paper uses long-read genome sequencing and multi-omics data to identify structural variants associated with aging and neurodegenerative diseases, finding that SVs are more likely to be causal than SNVs.

The paper identifies neuronal proteins that degrade slower with aging and accumulate in microglia, linking impaired synaptic protein turnover to age-related cognitive decline.

This study finds that Alzheimer's disease patients have more clonal hematopoiesis mutations than controls, especially those with APOE ε3/ε3 genotype, suggesting a risk factor independent of APOE ε4.

CSF YWHAG:NPTX2 synapse protein ratio, from proteomics of 3,416 individuals across six cohorts, explains cognitive impairment beyond amyloid and tau and predicts decline (hazard ratio 15.4).

This study identifies genetic variants associated with human longevity, finding enrichment for oncogenic genes and pathways linked to cancer and clonal hematopoiesis.

The paper uses plasma proteomics from the UK Biobank to estimate organ age and links it to disease risk and longevity.

The paper identifies rare FN1 variants that protect APOEε4 carriers from Alzheimer's disease by modulating extracellular matrix deposition and gliosis.

This study shows that TREM1 deficiency prevents age-related myeloid metabolic changes and cognitive decline in Alzheimer's disease models.

This paper introduces a method to identify causal variants from genome-wide summary statistics, outperforming existing methods and discovering additional loci for complex traits.

This study identifies four novel genetic loci associated with soluble TREM2 levels in CSF through GWAS and provides functional validation of their roles in Alzheimer's disease.

The paper identifies high-priority missense variants in SORL1 associated with increased Alzheimer's Disease risk and earlier onset, suggesting clinical counseling considerations for carriers.

The paper identifies genetic variations in human gained enhancers that explain heritability of specific brain sulcal morphologies in the UK Biobank.

The paper identifies rare damaging variants in ATP8B4 and ABCA1 as novel risk factors for Alzheimer's Disease using exome sequencing data from 32,558 individuals.

This paper introduces GhostKnockoff, a method to improve causal variant identification in GWAS by increasing statistical power and reducing proxy variants.

This paper introduces a statistical method using knockoff statistics to identify causal loci in whole-genome sequencing data, showing increased discovery potential in Alzheimer's and COPD studies.

This study performs a genome-wide haplotype association analysis of brain sulcal openings in 16,304 UK Biobank subjects, finding haplotype analysis more sensitive than single-SNP approaches.

The paper identifies an enhancer locus in 14q23.1 associated with brain asymmetry in regions involved in language processing, using UK Biobank and IMAGEN data.

The paper identifies genetic variants influencing brain sulcal widening using UK Biobank data, finding an eQTL for KCNK2 associated with cortical atrophy and cognitive decline.

The paper identifies shared genetic influences between cognitive performance and brain activation in language and math tasks using the HCP dataset.

The paper presents a multiscale simulator for peripheral nerve signaling that integrates biophysical axon models with extracellular space models to predict signal shapes and stimulation thresholds.