Roseann Elizabeth Peterson

This study investigates rare copy number variants in PTSD using whole-genome sequencing and biobank data, finding significant associations in specific ancestry groups and gene-sets.

This paper identifies 58 genome-wide significant loci for major anxiety disorders using a large meta-analysis and highlights GABAergic signaling as a potential mechanism.

This study identifies 52 genetic variants associated with adolescent-onset depression through a large GWAS, revealing age-specific mechanisms and potential drug targets.

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 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 identifies prevalence and disease risks for male and female sex chromosome trisomies using registry data from 1.5 million participants, finding shared phenotypic associations across trisomy subtypes.

This study uses twin-based Mendelian randomisation to find bidirectional causation between smoking and blood DNA methylation at multiple genomic sites.

This study evaluates imputation performance of reference panels in a Pakistani population, finding that ex1KG outperforms TOPMed despite its smaller size.

This paper combines transdiagnostic and disorder-level GWAS to enhance genetic risk profiles for psychiatric disorders in multi-ancestry samples, identifying novel SNPs and shared genetic variance.

This paper introduces MR-GSE, a multi-omics Mendelian randomization method for gene set enrichment in psychiatric disorders, showing increased detection of significant gene sets compared to non-MR methods.

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 study uses machine learning and functional weights to identify rare variants associated with AUDIT-P, finding significant associations in ADH1C and THRA genes.

This paper identifies risk genes and pathways for neuropsychiatric and substance use disorders using XWAS analyses in blood and brain tissues, finding shared signals in the MHC region and other genomic areas.

The paper analyzes rare functional variation in genes related to ethanol metabolism in severe alcohol dependence cases using a case-only design and WES data from the island of Ireland.

The paper examines genetic correlations between PTSD and alcohol-related phenotypes, finding distinct genetic factors for AUD versus alcohol consumption.

This study uses BMI GWAS and genomic structural equation modeling to show that genetic influences on BMI remain stable from age 40 to 73 in men and women.

This paper conducts a multi-ancestry GWAS of major depression, identifying 190 loci and 354 genes, with findings showing increased fine-mapping power and bidirectional BMI relationship in European ancestry samples.

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.

This study conducts a genome-wide association meta-analysis of childhood aggression across multiple raters, instruments, and ages, identifying genetic correlations with various traits but no genome-wide significant SNPs.

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

The paper develops MAGIC-LASSO to predict missing data in biobanks with non-random missingness, achieving high phenotypic and genetic correlations in UK Biobank AUDIT score predictions.

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.

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

The paper analyzes polygenic score usage and performance across diverse human populations, finding significant disparities in effect sizes and highlighting the need for more inclusive GWAS.

This study uses Mendelian randomization to find a causal link between major depression and alcohol dependence using large genetic datasets.

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

The paper constructs a polygenic risk atlas for 33 traits in emerging adults and finds genetic risks for schizophrenia, neuroticism, and depression predict various phenotypes.

The paper uses GWAS data to identify polygenic risk scores for drug metabolism pathways, finding that the GO:17144 pathway is significantly predictive of recurrent depressive disorder.

The paper confirms a polygenic effect on negative symptoms in schizophrenia using GWAS, identifies novel loci, and highlights the need for larger samples.