Daniel R. Weinberger

The paper identifies 253 autism-associated genes using rare variation from 62,429 individuals and finds pleiotropy across physiological systems and developmental disorders.

The paper uses a novel 'liquidity' metric to analyze gene expression trajectories across lifespan, revealing delayed maturation and perinatal GABA switch in schizophrenia risk without detectable neuropathology.

The paper examines how schizophrenia genetic risk and resilience variants, co-expressed in the human brain, are associated with cognitive performance across development in 16,520 individuals.

The paper identifies distinct DNA methylation mechanisms for common and rare noncoding genetic risk in brain disorders using deep learning and single-nucleus DNAm data.

The paper introduces co-expression-based models to improve eQTL predictions and identifies novel schizophrenia-associated genes using brain RNA-seq data.

This study investigates the genetic regulation of miRNA expression in human brain tissues and identifies miRNAs associated with psychiatric and neurodegenerative disorders.

The paper uses image-based profiling of hiPSC-derived trophoblasts to identify SCZ risk signatures linked to sex, placental genomic risk, and hypoxic stress.

The paper investigates how APOE genotype affects gene expression in the human entorhinal cortex, identifying an oligodendrocyte subtype as a potential mediator of Alzheimer's disease risk.

This study identifies ADARB1 overexpression in T21 fetal brain due to trisomy 21, leading to increased A-to-I RNA editing and altered GRIA gene recoding.

The paper performs transcriptomic analysis of the human habenula and identifies molecular changes associated with schizophrenia risk and illness state.

The paper analyzes the transcriptomic landscape of the human locus coeruleus in relation to Alzheimer's disease risk factors and neuromelanin content using spatially-resolved transcriptomics.

The paper compares gene expression in immature neurons across species to identify human-specific features and shared biological processes.

The paper identifies genes with disrupted connectivity in schizophrenia gene co-expression networks, revealing atypical neuronal-glial interactions and synaptic transmission disturbances.

The paper examines FKBP5 DNA methylation in schizophrenia and finds lower methylation in a proximal enhancer linked to higher gene expression and age.

The paper identifies a specific APOE transcript and functional SNP associated with Alzheimer's disease using integrated genomic data from human postmortem brains.

The paper analyzes transcriptomic and proteomic data from specific brain regions to identify molecular changes in schizophrenia, showing superior regional discrimination in transcriptomic and proteomic data.

The paper analyzes repeat expression across the human lifespan in the neurotypical brain, identifying age-dependent upregulation of HERV-K in older adults.

This paper introduces a transformer-based model to predict cell type-specific DNA methylation regulatory variants and improves fine mapping for brain disorders.

The paper re-analyzes RNA sequencing data comparing gene expression in living and postmortem human brain tissue, finding that living samples had lower quality, and questions the validity of previous conclusions about postmortem studies.

The paper identifies a striatal gene set linked to schizophrenia risk that predicts in vivo dopamine synthesis and striatal activation in neurotypical and patient cohorts.

The paper examines how genetic ancestry influences gene expression and DNA methylation in admixed African/Black Americans, showing environmental and genetic factors affect brain disease risk.

The paper identifies and validates copy number variants in single human neurons using a new method, revealing nonrandom CNV locations and complex karyotypes in a subset of neurons.

The paper constructs a cross-ancestry, cell-type-informed gene regulatory atlas of the developing human brain, identifying genetic regulation and linking it to neuropsychiatric disorders.

DeepMosaic detects mosaic single nucleotide variants without control samples using deep convolutional neural networks, achieving high accuracy and uncovering many variants missed by existing methods.

The paper identifies sex differences in schizophrenia across three brain regions using RNA-seq and genotypes, finding sex-specific genes, eQTLs, and transcriptional features.

This study characterizes TAF1 expression variation in XDP female carriers and human brain ontogeny, identifying age- and region-specific patterns that may explain neostriatum vulnerability in XDP.

The paper uses ventral forebrain organoids from schizophrenia patients and controls to show accelerated maturation of inhibitory neurons and shared gene expression patterns with postmortem brain tissue.

The paper evaluates brain somatic mosaicism in the adult human to identify rules governing cellular distribution during embryogenesis.

The paper identifies electrophysiological measures in hiPSC-derived neurons linked to schizophrenia diagnosis and cognitive performance.