Irwin D. Waldman

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 evaluates transdiagnostic polygenic risk scores for psychiatric disorders using the All of Us Research Program data, finding that a common psychiatric genetic factor PRS better predicts comorbidity burden than single-disorder scores.

The paper identifies five genomic factors explaining most genetic variance across 14 psychiatric disorders and finds shared and disorder-specific genetic signals with distinct biological functions.

This paper evaluates how down-sampling affects GWAS summary statistics and recommends reporting specific analyses to support their use.

This study uses Genomic Structural Equation Modeling to identify a common genetic factor underlying externalizing phenotypes and substance use disorders, finding that a single dimension of genetic risk best explains their relationships.

The paper uses multivariate genomic analysis of 1.5 million people to identify genetic loci related to addiction, antisocial behavior, and health, finding over 500 loci enriched for brain-expressed genes.

This study tests structural models of psychopathology using genetic correlations from GWAS, finding a four-factor model better fits the data than a bifactor model.

This study identifies risk variants and characterizes the polygenic architecture of ADHD comorbid with disruptive behavior disorders through a large GWAS meta-analysis.

Genome-wide association meta-analysis of 20,183 ADHD cases and 35,191 controls finds 12 significant loci; signal concentrates in conserved regions, constrained genes, and CNS regulatory elements.