Daniel R. Weinberger

This study identifies the KIBRA-PKCγ signaling pathway as crucial for modulating memory performance in both mice and humans.

The paper shows that incorporating cell size parameters improves deconvolution of brain RNA-seq data, but using external cell size estimates can introduce bias.

This paper introduces a graph convolutional network that links genetic risk pathways with neuroimaging phenotypes in schizophrenia, achieving better classification performance than existing methods.

This paper identifies potential nootropic drug targets by integrating large-scale cognitive GWAS and transcriptomic data to find credible druggable genes.

The paper manipulates genomic risk signatures for schizophrenia in brain co-expression networks to explore their impact on gene connectivity and variability.

This study identifies somatic SNVs in non-cancerous human brain tissues and establishes best practices for detecting low-frequency variants.

The paper identifies transcriptomic differences in human pluripotent stem cells that correlate with retinoic acid response and neural fate bias.

The paper examines the developmental expression of genes related to voltage-gated cation channels and their association with psychiatric disorders, finding that gene expression patterns vary with age and disorder type.

The paper investigates how psychiatric disease and aging affect FKBP5 expression in the human brain, identifying supragranular neurons as key targets.

The paper introduces a machine learning method to detect somatic L1 insertions in human brain tissue, revealing their widespread distribution in neurons and glia and potential role in neuropsychiatric diseases.

The paper identifies widespread genetic influences on DNA methylation in the human brain and links schizophrenia GWAS variants to epigenetic changes.

This paper shows that primed human pluripotent stem cells can differentiate to trophoblast stem cells without becoming naive, using specific signaling conditions and revealing a transcriptional network involving BMP5/7 and GATA3.

The paper characterizes dynamic DNA methylation patterns in the prenatal human cortex, identifying loci associated with gene expression, enhancer states, and psychiatric disorder genes.

The paper examines feedforward parietal-prefrontal connectivity in schizophrenia patients and healthy controls, linking it to delusions and polygenic risk for schizophrenia.

The paper models the progression of human neural stem cells in vitro, showing they transition through organizer states before committing to cortical excitatory or inhibitory neuronal fates.

The paper uses hiPSC transcriptomics to study neuronal differentiation and maturation across multiple conditions and develops a tool to estimate neuronal maturity.

The paper uses long-read sequencing to uncover the complex splicing profile of the CACNA1C gene in human brain, identifying numerous novel exons and transcripts with potential functional implications.

This study characterizes DNA methylation changes in human neurons across development, identifies distinct methylation patterns, and links them to heritable brain-related phenotypes.

The paper uses pleiotropic meta-analysis to identify genetic loci associated with cognition, education, and schizophrenia, revealing distinct biological mechanisms for concordant and discordant genetic correlations.

This study evaluates biases in small RNA sequencing methods, showing that UMIs improve accuracy and highlighting limitations in current miRNA and isomiR quantification.

The paper identifies regional differences in gene expression and regulation in hippocampus and dorsolateral prefrontal cortex across development and in schizophrenia using RNA-seq data from 900 samples.

The paper examines how childhood urbanization affects prefrontal cortical responses to trait anxiety and interacts with polygenic depression risk in a genetically homogeneous population.

The paper uses LCM-seq to profile gene expression in the human dentate gyrus granule cell layer, identifying cell type-specific genetic effects and novel schizophrenia-associated variants not detected in bulk RNA-seq.

The paper identifies a gene co-expression module enriched for schizophrenia risk genes and shows its association with treatment response in schizophrenia patients.

The paper characterizes nuclear and cytoplasmic transcriptomes in human cortex development and finds increased nuclear retention in mature brain, linked to psychiatric disease gene regulation.

The paper identifies differentially methylated DNA sites and associated genes in Alzheimer’s disease across multiple brain regions, linking them to gene expression and biological processes.

This study identifies and prioritizes gene sets linked to schizophrenia risk using co-expression network analysis in human brain data, highlighting modules associated with diagnosis and polygenic risk scores.

The paper replicates a postmortem association of LINC01268 with violent suicide and links it to in vivo aggression and prefrontal cortex function in living individuals.

The paper integrates brain DNA methylation data with GWAS to identify psychiatric risk genes, finding heritable CpG sites and methylation-trait associations linked to schizophrenia and bipolar disorder.

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