Eric Otto Johnson

This paper develops a polygenic score for smoking persistence and finds it is associated with earlier or later cessation ages across diverse populations.

This study uses single-nucleus multi-omic analysis to show cannabis use in HIV patients alters gene expression and chromatin accessibility in immune cell types, with cell-type-specific effects on inflammation and transcription factor regulation.

This study identifies epigenetic variation linked to opioid overdose using H3K27ac profiling and machine learning, revealing splicing dysregulation and CELF5 as a key factor.

The paper identifies FDA-approved drugs targeting genes associated with opioid use disorder by integrating multi-omic data and drug databases.

This study evaluates 18 functional weighting methods to enhance GWAS discovery, finding some methods can nominate high PPV variants for multiple traits without increasing sample size.

This paper introduces a method to combine genotypes from genotyping arrays and whole genome sequencing to expand public controls for GWAS, improving power for non-European ancestries.

The paper identifies case-specific epigenetic alterations in opioid dependence using ChIP-seq and Hi-C, revealing convergent regulatory loci associated with genetic and environmental risk factors.

The paper uses Hi-C data to link genetic risk variants for smoking and alcohol use to specific genes and pathways in brain regions involved in addiction.

The paper identifies novel genetic loci associated with nicotine dependence and shows genetic correlations with other smoking traits and comorbidities using genome-wide association studies.

The paper identifies a DNA methylation biomarker in blood associated with lifetime cannabis use and develops a classifier to detect cannabis use.

This study identifies DNA methylation differences in the nucleus accumbens of smokers versus nonsmokers, revealing both shared and tissue-specific CpGs associated with smoking.

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

This study conducts the largest GWAS for PTSD, identifying 6 genome-wide significant loci in European and African ancestries and highlighting novel biological pathways.

This study identifies gene expression changes in the prenatal human cortex due to maternal smoking and links them to neuropsychiatric disorder risk genes.

The paper investigates the genetic link between schizophrenia and substance use disorder, finding shared polygenic liability across multiple datasets.