Christiaan de Leeuw

The paper identifies genetic variants associated with functional brain connectivity in a large cohort, linking them to neurodevelopment and health-related traits.

The paper uses GWAS to identify genetic variants associated with corpus callosum morphometry and links them to cortical structure and neuropsychiatric disorders.

This study benchmarks the impact of non-additive genetic effects on polygenic prediction and machine learning approaches using simulated and real data.

This study identifies 142 genes associated with both schizophrenia and height, finding enrichment in immune response genes and partial genetic overlap with white blood cell count.

The paper uses GWEIS and in silico methods to study gene-environment interactions in alcohol misuse, identifying SES-modulated genes and highlighting challenges in detecting molecular GxE effects.

This paper introduces FLAMES, a framework that improves gene prioritization in GWAS loci by integrating SNP-based and convergence-based evidence, outperforming single-modality approaches.

This study shows that interpreting TWAS results as evidence of genetic relationships between gene expression and phenotypes leads to inflated type 1 errors and unreliable conclusions.

The paper identifies local genetic sex differences in quantitative traits using UK Biobank data, showing that sex-dimorphic effects are common and that the scale of genetic effects impacts heritability interpretations.

This study uses local genetic correlation analysis to link depression with molecular and brain imaging endophenotypes, identifying potential genes and mechanisms involved in major depressive disorder.

The paper identifies the temporal emergence of genetic variants linked to human brain and cognitive traits over the past five million years.

DRUGSETS identifies therapeutic mechanisms by analyzing GWAS associations with drug and mechanism-of-action gene sets, revealing both established and novel targets across CNS and non-CNS phenotypes.

This study identifies 29 genome-wide significant loci and 85 genes associated with cerebellar volume using UK Biobank data, revealing shared genetic links with neurodevelopmental and neurodegenerative disorders.

This study identifies genes associated with structural and functional connectivity in resting-state networks and finds genetic overlap within functional domains.

This study investigates genetic overlaps between 12 psychiatric disorders, identifying pleiotropic SNPs and biological pathways, but finds challenges in interpreting shared mechanisms due to varying genetic architectures.

This study identifies 856 genetic loci associated with sulcal depth through a genome-wide association study using UK Biobank data, showing higher heritability and locus yield compared to cortical thickness and surface area.

The paper examines how genetic pathways regulating sensitive periods and socioeconomic disadvantage interact to influence depression risk using genome-wide data and developmental gene expression patterns.

The paper uses a proxy Alzheimer's disease/dementia phenotype from UK Biobank exomes to identify rare variant-associated genes, finding three replicated genes linked to clinical Alzheimer's.

LAVA analyzes local genetic correlations between multiple traits and demonstrates heterogeneous patterns across the genome that are masked by global analyses.

The paper updates H-MAGMA to address statistical issues, showing reduced false positives and consistent results in psychiatric disorder GWAS.

The paper examines common genetic variants' contribution to bipolar disorder risk in multiplex families and finds higher polygenic risk scores in affected individuals compared to controls and unaffected family members.

This study identifies 73 genome-wide significant loci for mood disorders, revealing shared and distinct genetic factors between major depressive disorder and bipolar disorder.

This study analyzes 4,155 GWASs to explore pleiotropy and genetic architecture across 558 traits, finding that most loci are associated with multiple traits and causal variants are enriched in coding and regulatory regions.

This study identifies 30 genome-wide significant loci associated with bipolar disorder, including novel genes involved in ion channels, neurotransmitters, and synaptic components.

This study evaluates multivariate association tests for genome-wide analysis, comparing their power and Type I error rates under various conditions.

This study identifies 202 genome-wide significant loci for insomnia using a large sample, linking them to specific brain cell types and pathways.

The paper analyzes rare coding variants in smoking and drinking behavior using exome chip data, finding that they contribute to phenotypic variation but require larger samples for individual variant associations.

This study identifies 206 new genomic loci and 1,041 genes associated with intelligence using a large GWAS meta-analysis of 279,930 individuals.

This study conducts a large GWAS meta-analysis of neuroticism, identifying 136 novel genetic loci and 599 genes, with functional insights into brain regions and pathways.

This study identifies 9 novel genetic loci and 215 potential causative genes associated with Alzheimer's disease risk through a large genome-wide association analysis.