Jacquelyn Leigh Meyers

The paper derives lifespan trajectories of resting state bipolar EEG power from a large sample, finding age-related decreases followed by divergent patterns and sex-specific inter-frequency correlations.

The paper analyzes resting state EEG power trajectories across age and sex in a large sample, finding age-related decreases and sex-specific reversals in certain frequency bands.

This study estimates brain age in individuals with alcohol use disorder (AUD) and finds accelerated brain aging associated with impaired neurocognition and impulsivity.

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

The paper examines neural activity in the reward network during win and loss outcomes in a gambling task and links these activations to behavioral and cognitive traits.

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

The paper analyzes EEG coherence development in adolescents and young adults using tensorial analysis of covariance matrices, revealing non-linear patterns and sex differences in neural connectivity.

The paper predicts brain age in individuals with and at risk for alcohol use disorder using morphological brain features and finds accelerated brain aging in both groups.

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.

The paper examines how genetic variants in the cholinergic system affect theta band event-related oscillations, finding age and sex-dependent variations in these associations.

The paper uses polygenic risk scores from GWAS to assess their association with suicidal thoughts and behaviors in a sample with alcohol use disorders, finding significant contributions from multiple PRS.

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.

This paper uses PheWAS to investigate the phenotypic effects of GABRA2 variant rs279858, finding associations with anxiety-related and behavioral traits linked to alcohol use disorders.

The paper integrates GWAS data with multi-omics datasets to identify novel genes for alcohol use disorder and link them to neurodegenerative diseases.

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 conducts a multivariate GWAS of AUDIT items to correct biases and identify novel genetic associations between alcohol consumption, misuse, and health outcomes.

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

The paper identifies 129 differentially expressed genes in the PFC of alcoholics and links them to pathways and modules associated with alcohol dependence and consumption.

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