Peter B. Barr

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 relationships between substance use disorders and externalizing/internalizing psychopathology, finding that internalizing contributes uniquely to SUD risk.

This study examines how genetic risk scores for alcohol use behaviors change over time across multiple cohorts, finding varying associations with drinking patterns and trajectories.

This study identifies a genetic link between externalizing traits and suicide risk using genomic data and electronic health records from over 500,000 veterans.

This study identifies ten genetic loci associated with dry eye disease and finds significant genetic correlations with several comorbidities.

This study conducts trans-ancestry GWAS on UK Biobank data to identify novel MDD risk loci, finding 61 loci with increased sample size and ancestry inclusivity.

This study examines how polygenic risk scores for Alcohol Use Disorder affect microglial responses to ethanol exposure in human iPSC-derived microglia.

This study identifies correlates of risk for disinhibited behaviors in veterans using polygenic scores and electronic health records, finding strong associations with substance use disorders and related health outcomes.

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.

This study uses machine learning to predict alcohol-related memory problems in older adults by integrating multi-domain features including brain connectivity, polygenic risk, and lifestyle factors.

The paper validates polygenic risk scores for schizophrenia, bipolar disorder, and depression using VA EHR data and shows their association with disease risk and hospitalization.

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 uses polygenic risk scores to predict substance use disorders in two samples, finding increased risk with higher scores but limited clinical utility.

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