Vahram H. Haroutunian

The paper introduces dreamlet, an R package for efficient differential expression analysis of large-scale single-cell transcriptomics data, showing improved speed and memory usage compared to existing methods.

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.

The paper constructs a single-nucleus atlas of genetic regulation in the human brain, identifying cell-type-specific regulatory effects and disease-associated genes.

The paper develops a multi-omics cohort of prefrontal cortex data from cognitively normal older adults to identify molecular signatures of cognitive resilience to Alzheimer's disease.

The paper profiles human myeloid cells across aging and Alzheimer's disease, identifies AD-associated changes, and links GPNMB to neuroprotection via TREM2.

The paper constructs a single-cell transcriptomic atlas of the human dorsolateral prefrontal cortex across neurodegenerative and neuropsychiatric diseases, revealing shared and distinct molecular mechanisms.

This study creates a single-nucleus transcriptomic atlas of Parkinson's disease progression, identifying cell-type-specific gene expression changes and linking them to genetic risk factors and disease stages.

The paper presents a long-read RNA-seq atlas of microglia isoforms, identifying novel isoforms and their associations with genetic risk loci in Alzheimer's and Parkinson's disease.

The paper maps transcriptomic and chromatin accessibility profiles across 25 human brain regions and identifies genes linked to neuropsychiatric disorder risk.

This study creates a single-nucleus transcriptomic atlas of the human DLPFC across the lifespan, revealing three transcriptomic phases and ten age-related trajectories linked to neurodevelopmental and neurodegenerative disease risk.

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 identifies cell-type specific chromatin accessibility QTLs and their functional impact on brain disease risk.

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.

The paper identifies an AD-like subtype in brain aging across multiple regions, showing overlap with AD gene signatures and regional differences in gene expression.

This study identifies somatic copy number variants (sCNVs) in schizophrenia cases, revealing their contribution to risk and specific NRXN1 disruptions.

This paper develops a deep learning pipeline to automate amyloid pathology quantification in Alzheimer's disease, achieving human-level accuracy and enabling high-throughput analysis.

This study maps chromatin accessibility in Alzheimer's disease using ATAC-seq, identifying regulatory changes and 3D genomic alterations linked to disease.

The paper identifies population-level variation in enhancer expression in the human brain and links enhancer eQTL to schizophrenia heritability.

The paper creates a comprehensive neuroanatomical atlas of glycoprotein hormone receptor expression in the brain using single-transcript detection technologies.

The paper identifies regulatory mechanisms for 21 Alzheimer's disease risk loci in human microglia using transcriptome and chromatin accessibility profiling.

The paper identifies acetylated chromatin domains associated with dysfunction in schizophrenia and bipolar disorder by analyzing histone modifications in prefrontal cortex samples.

The paper analyzes proteomic data from Alzheimer's disease brains, revealing disease-related changes not seen at the RNA level and identifying potential therapeutic targets.

This study identifies sex-dependent genetic risk loci shared and specific to mood and psychotic disorders using genome-wide interaction analysis.

The paper identifies transcriptomic changes in normal aging brains that resemble Alzheimer's disease in specific subgroups, suggesting early molecular links between aging and LOAD.

This study identifies JADE1 as a novel genetic factor in tauopathy through genome-wide association and functional validation in human and Drosophila models.

This study performs a meta-analysis of DNA methylation data from Alzheimer's disease patients to identify differentially methylated loci across brain regions and cortex.

The paper compares ten polygenic score methods for psychiatric disorders across multiple cohorts, finding that some methods significantly improve prediction statistics over the baseline PC+T method.

This paper performs a large-scale eQTL meta-analysis across cerebral cortical and cerebellar brain regions, identifying distinct eQTL patterns and demonstrating improved power over existing studies.

The paper identifies global down-regulation of proteasome subunits in a subgroup of schizophrenia patients through transcriptome sequencing and pathway analysis across multiple cohorts.

The paper functionally annotates rare structural variants in the human brain by integrating SV calling with RNA-seq data to assess their regulatory effects and prioritize pathogenic deletions.