Marijn Schipper

This study identifies shared genetic factors across eight cardiovascular diseases using large-scale genetic data, revealing clusters and pathways related to vascular biology and systemic risk factors.

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

This study identifies 1,294 genomic regions and 961 effector genes associated with externalizing disorders, revealing neural mechanisms and polygenic predictors of variance in these conditions.

This study identifies shared genetic factors between insomnia, depression, and anxiety, highlighting synaptic processes as potential drug targets.

This study identifies 118 new genetic loci associated with Alzheimer's disease across diverse ancestries and discovers 48 novel risk loci, including those enriched in neuronal cell types.

This study benchmarks GWAS causal gene prioritization methods for drug discovery using 445 diseases, finding the nearest gene method performs as well as more complex approaches.

This paper prioritizes Parkinson's disease risk genes in GWAS loci using a polygenic priority score, identifying 46 genes with potential for therapeutic development.

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.

This paper introduces CALDERA, a gene prioritization tool for GWAS loci that outperforms existing methods in identifying causal genes.

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.

The paper constructs a single-cell chromatin accessibility atlas of the human first trimester brain, identifies regulatory elements linked to gene expression, and links disease SNPs to potential pathogenic mechanisms.

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.

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.