Ronald de Vlaming

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 genetic variants associated with income and shows they correlate with health outcomes and educational attainment.

This study performs a multivariate GWAS on psychiatric disorders and symptoms to identify two genetic liabilities distinguishing common mood disturbances from serious mental illnesses.

The paper uses multivariate analysis to estimate heritability and genetic correlations between brain morphology and behavioral traits, identifying four genetically distinct brain clusters.

This paper compares two methods to reduce measurement error in polygenic indices by simulating and validating their performance on educational attainment and height data.

This study identifies genetic loci associated with macronutrient intake and links them to health outcomes using GWAS in over 235,000 individuals.

GWAS in over one million individuals identify 611 loci across risk tolerance and risky behaviors, revealing shared genetic architecture and implicating glutamatergic and GABAergic neurotransmission.

This study uses genome-wide association data for educational attainment and schizophrenia to identify genetic heterogeneity and novel candidate genes for schizophrenia.

Structural equation modeling over GWAS summary statistics fits several traits jointly; across five psychiatric traits it surfaced 27 SNPs the univariate GWASs missed and sharpened polygenic scores.

The paper estimates the joint distribution of effect size and MAF for genetic variants in 28 complex traits and detects widespread negative selection signatures.

This paper shows that LDSC regression and individual-level data methods yield similar results under population stratification, but warns that LDSC intercepts can misattribute stratification to heritability estimates.

The paper identifies genetic variants associated with subjective well-being, depressive symptoms, and neuroticism using genome-wide association studies and proxy-phenotype analyses.