Michael J. Gandal

This study identifies three functional programs impacted by autism genes, contextualized across neuronal subclasses, developmental timing, and cortical regions.

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 models the genetic architecture of cortical expansion using GWAS data and links it to neuropsychiatric disorders.

This study uses single-nucleus multi-omics to analyze the developing Down syndrome neocortex, identifying dysregulated molecular and gene-regulatory mechanisms affecting neurogenesis and cell specification.

This study identifies 1,294 genomic regions and 961 effector genes associated with externalizing disorders, revealing neural mechanisms and polygenic predictors of variance in these conditions.

This study develops a method to generate neocortical organoids with distinct anterior-posterior molecular signatures and uses them to model Fragile X Syndrome pathology.

This study identifies shared genetic loci between psychiatric disorders and cortical brain structure using genome-wide association data from over 700,000 individuals.

The paper identifies five genomic factors explaining most genetic variance across 14 psychiatric disorders and finds shared and disorder-specific genetic signals with distinct biological functions.

The paper identifies cell-type-specific genetic regulation of RNA-editing and alternative polyadenylation in human neural progenitors and neurons, linking these to brain-related traits.

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 extensive isoform diversity in the developing human neocortex and links it to neuropsychiatric disorder risk mechanisms.

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 copy number variants (CNVs) associated with child psychopathology and cognitive function using data from the ABCD study.

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.

This study identifies 928 genes associated with brain weight variation across three datasets and links them to neurodevelopmental processes and brain function.

This study shows KAT6A mutations cause transcriptional dysregulation of cell cycle and autism risk genes in cerebral organoids, leading to delayed neural differentiation and altered gene expression patterns.

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.

The paper identifies neuron-specific transcriptomic changes in ASD temporal cortex, showing neuroinflammation and altered neuronal activity.

GeneticsMakie.jl provides a fast, scalable, and customizable visualization tool for locus-level genetic and genomic data, enabling integration of multiple annotations and association results.

The paper introduces a new statistical method for multivariate variance components models to analyze brain isoform expression and identifies novel psychiatric disease mechanisms.

The paper examines sex differences in white matter microstructure in children using DTI and RSI metrics, finding significant and replicable differences across brain regions.

GWAS of 2,347 neuroimaging phenotypes identifies genetic loci and structures related to cortical development, cellular processes, and neurodevelopmental disorders.

This paper introduces scDRS, a method to identify disease-associated cells in scRNA-seq data using polygenic risk scores, finding novel subpopulations linked to diseases like IBD and schizophrenia.

This paper introduces isoTWAS, a method that improves discovery of genetic risk mechanisms for neuropsychiatric disorders by analyzing isoform-level transcriptome-wide associations.

This paper conducts a multi-ancestry GWAS meta-analysis of suicide attempt, identifying 12 genome-wide significant loci and finding shared genetic risks with ADHD, smoking, and risk tolerance.

This study identifies genes linked to brain activity that show disrupted associations in autism spectrum disorder, highlighting excitation-inhibition imbalance and regional effects.

The paper identifies non-coding RNAs that mediate gene expression regulation in breast and prostate tissue and overlap with genetic signals for cancer susceptibility.