Raymond Kenney Walters

This paper constructs phenome-derived polygenic scores and evaluates how they, along with social determinants of health, influence disease risk across different populations and diseases.

This study performs a multi-ancestral GWAS of DSM-defined nicotine dependence, finding genetic correlations with other substance use disorders and health traits, and identifying a strong general addiction liability factor.

This paper introduces GISMO and GISMO-mis metrics to quantify gene loss and missense variation across mammals, identifying essential genes and improving gene-disease associations.

Meta-analyzing per-ancestry GWAS of 7,266 UK Biobank traits across six genetic ancestry groups adds 14,676 loci missed by European-only analysis, including ancestry-enriched CAMK2D and G6PD signals.

This study identifies genetic overlaps between psychiatric disorders, language ability, and creativity through a GWAS of school grades.

The paper investigates the female protective effect against autism spectrum disorder by analyzing genetic risk in siblings and parents of ASD cases, finding evidence of sex differences in inherited genetic risk.

The paper identifies genetic loci associated with survey nonresponse behaviors and shows their genetic correlation with education and health.

This study identifies genetic variants shared between schizophrenia and alcohol use disorder, finding both convergent and divergent effects and evidence of brain tissue expression.

This paper introduces MAMA, a method for multi-ancestry GWAS meta-analysis, which identifies novel genetic associations and improves power across populations.

The paper identifies sex-differential participation bias in genetic studies by performing GWAS on sex in 3.3 million individuals, finding 158 loci associated with sex and highlighting traits like BMI that may influence participation.

The paper examines sex-differentiated genetic effects across neuropsychiatric and behavioral traits using GWAS summary statistics and finds small, polygenic sex differences with enriched neuron-related genes.

From 125,748 exomes and 15,708 genomes, 443,769 high-confidence predicted loss-of-function variants yield LOEUF, a continuous gene intolerance score tracking mouse lethality, cell essentiality, and disease associations.

The paper compares genome-wide data from opioid use and dependence cases to identify genetic associations and differences between exposure and dependence.

The paper estimates genetic correlations between eating disorder and substance-use-related phenotypes using GWAS data, finding both positive and negative associations.

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

RICOPILI is a Perl-based pipeline for efficient GWAS analysis, including quality control, imputation, and meta-analysis, with automated parallelization for rapid data processing.

The paper identifies genetic correlations between ADHD and brain volumes, finding negative associations with intracranial volume and specific brain regions.

This study identifies five genome-wide significant loci and seven shared with other traits in a large ASD GWAS, highlighting polygenic heterogeneity and the value of large-scale GWAS in ASD.

Cross-disorder meta-analysis of eight psychiatric GWAS (232,964 cases, 494,162 controls) reports 109 loci shared by two or more disorders and three groups of correlated disorders.

The paper investigates polygenic associations between ADHD and literacy/language abilities, finding that genetic confounding with educational attainment masks ADHD-specific reading impairments.

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.

This study conducts a trans-ancestral GWAS of alcohol dependence, identifying genetic variants and correlations with psychiatric disorders.

Genetic correlations across 25 brain disorders (215,683 cases) reveal broad psychiatric common-variant sharing, largely distinct neurological disorders, and migraine as the only significant cross-category link.

The paper investigates the genetic burden of rare protein-truncating variants in ASD and ADHD, finding similar patterns of enrichment.

MTAG improves GWAS results by combining summary statistics across traits, increasing significant loci and enhancing polygenic score variance.

This study investigates genetic mechanisms underlying sex bias in ADHD prevalence using genome-wide data and finds no mean polygenic burden difference across sexes but increased risk in female siblings and comorbid conditions.

The paper uses polygenic transmission disequilibrium to show common and rare variants act additively in autism risk, with polygenic risk over-transmitted to ASD cases but not unaffected siblings.

This study shows that genetic risk scores from European GWAS are biased when applied to other populations due to demographic history, highlighting the need for more diverse data.