Chris Chatzinakos

This study performs a single-nucleus transcriptome-wide association study to identify gene-trait associations in brain disorders, revealing cell-type-specific genetic regulation and ancestry-specific patterns.

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.

The paper identifies rare and common genetic variants associated with acute myeloid leukemia using whole-genome sequencing data from the All of Us Research Program.

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 identifies genetic risk loci and factors underlying clinical subtypes of bipolar disorder using GWAS and meta-analysis.

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 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 paper engineers human-derived ARMMs for in vivo delivery of genome editing tools, showing efficient gene knockout and therapeutic potential in mouse models.

The paper identifies 46,802 enhancers and 164 psychiatric disorder variants with regulatory effects in the developing cortex and organoids using massively parallel reporter assays and deep learning.

The paper processes single-nuclei multi-omics data from 388 human brains to identify regulatory elements and build cell-type networks, revealing changes in aging and neuropsychiatric disorders.

The paper generates a molecular neuroanatomical map of the human prefrontal cortex using spatial transcriptomics and single nucleus RNA-sequencing, revealing novel spatial domains and cell-cell interactions linked to psychiatric disorders.

This study identifies 240 novel genetic loci associated with mosaic loss of chromosome Y through a multi-ancestry GWAS of the Million Veteran Program and UK Biobank.

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

The paper profiles lncRNA and protein coding gene expression in nucleus accumbens from alcohol-dependent and control subjects, identifying differentially expressed genes and their functional roles in alcohol dependence.

The paper introduces JEPEGMIX2-P, a TWAS pathway method that improves computational efficiency and performance for psychiatric disorder GWAS, showing increased power over existing methods like MAGMA.

This paper improves psychiatric GWAS by re-imputing summary statistics using a larger, more diverse reference panel, revealing new signals from rare variants.

This study shows that using unscreened or super-normal controls in GWA studies biases genetic correlation estimates between disorders upward, with stronger effects at higher prevalence and lower true genetic correlation.

The paper identifies SNRNP35 as a trauma type-specific PTSD gene through analysis of genetically regulated gene expression in PTSD cases and controls.

JEPEGMIX2 improves gene-level eQTL analysis by using updated cis-eQTL SNPs and adjusting for background enrichment, reducing false positives in cosmopolitan cohorts.