Massive single-nucleus atlas reveals how genetic risk for brain disease acts cell by cell

In the largest effort of its kind, researchers have mapped how genetic variants tune gene expression across the human brain one cell at a time. The study, published in Nature Genetics, draws on single-nucleus RNA sequencing of 5.6 million nuclei from the dorsolateral prefrontal cortex of 1,384 postmortem donors, more than a third of whom are of non-European ancestry. By profiling eight major cell classes and 27 finer subclasses, the team built a multi-resolution atlas of expression quantitative trait loci, or eQTLs, the genetic variants that influence how strongly a gene is transcribed. The result is a resource that begins to explain, with unprecedented cellular precision, why genetic risk variants for schizophrenia, Alzheimer’s disease and other brain disorders so often act in one cell type and not another.

The scale of the dataset matters because statistical power in single-cell genetics is notoriously hard to come by. Most variants identified by genome-wide association studies sit in non-coding regions of the genome, where they are thought to act as regulatory elements that dial gene expression up or down. Bulk tissue studies, which average signals across millions of mixed cells, have linked many of these variants to specific genes, but they cannot resolve which of the brain’s dozens of cell types actually carry out the regulation. By aggregating nuclei from each donor into cell-type-specific pseudobulk profiles and fitting linear mixed models that account for population structure, the researchers detected significant eQTLs for 14,258 genes, with 981 genes showing regulatory effects specific to a cell class and 857 specific to a subclass.

The number of detectable eGenes varied enormously across cell types, and the authors are candid about why. Excitatory neurons yielded 10,913 eGenes at the class level, while endothelial cells yielded only 414. At the subclass level, layer 2/3 intratelencephalic excitatory neurons produced 8,812 eGenes compared with just 1,683 in layer 6b excitatory neurons. Much of this variation tracks cell type abundance and average sequencing depth per cell, a reminder that rare but biologically important populations remain underpowered even in a study of this magnitude. Concordance between cell-type-level and bulk-level effect sizes also rose with cell abundance, with neurons showing markedly higher agreement than non-neuronal cells.

To validate the biology behind the statistics, the team examined whether cell-type-specific open chromatin regions, identified from single-cell ATAC-seq data, were enriched around the lead eQTL variants of the matching cell types. They were, with particularly strong enrichment for glial cells, consistent with the idea that regulatory variants act through cell-type-specific chromatin landscapes. Fine-mapping with a probabilistic model narrowed candidate causal variants to credible sets of roughly ten to thirty variants per locus. An independent check against a massively parallel reporter assay in stem-cell-derived excitatory neurons showed that fine-mapped regulatory variants in that cell type had the strongest association with measured allelic effects, lending functional weight to the catalog.

The most striking findings emerge when the regulatory atlas is crossed with disease genetics. Using stratified linkage disequilibrium score regression, the researchers showed that regulatory variants from neurons are enriched for the heritability of neuropsychiatric traits, with schizophrenia showing the broadest signal, followed by bipolar disorder and major depressive disorder. But astrocytes and oligodendrocytes were also enriched for these psychiatric traits, and oligodendrocyte precursor cells carried signals for schizophrenia and depression. Neurodegenerative traits told a different story: Alzheimer’s and Parkinson’s disease heritability was enriched in microglia but not in neuronal subclasses, echoing the established role of the brain’s resident immune cells in neurodegeneration.

Colocalization analysis, which tests whether the same variant drives both gene regulation and disease risk, pinpointed specific genes and cell types. The analysis identified 46 genes colocalizing with Alzheimer’s disease risk, 22 with major depressive disorder and 46 with schizophrenia. Up to 18 of these genes were detected exclusively in the single-nucleus data and had been invisible to previous bulk RNA-seq studies. For schizophrenia, many colocalized genes appeared only in excitatory or inhibitory neurons, including FUT9, ACE and FURIN, while DRD2 and FAM171A1 were specific to excitatory neurons and ERBB4 and SP4 to inhibitory neurons. For Alzheimer’s, beyond 16 genes in immune cells driven largely by microglia, the team found nine genes in oligodendrocytes, 12 in astrocytes and six in neurons, with microglial genes enriched for amyloid-beta formation and oligodendrocyte genes for complement activation, hinting at an immune-regulatory role for these myelin-producing cells.

Resolution proved decisive. The gene CNTN4, involved in cell adhesion, colocalized with schizophrenia risk only in layer 6 corticothalamic excitatory neurons, a signal that vanished when neuronal subclasses were collapsed into broad classes. Similarly, SORL1, a well-known Alzheimer’s gene, colocalized with disease risk in microglia but not in perivascular macrophages, distinguishing two cell populations that bulk analyses would have merged. The team also tackled the thorny statistical problem of proving that a regulatory effect is genuinely cell-type-specific rather than merely undetected elsewhere. Using a multivariate Bayesian meta-analysis with a novel composite hypothesis test, they directly estimated the posterior probability that an effect is non-zero in one cell type and zero in all others. A standout example is EGFR, which carries at least two independent regulatory programs, one in astrocytes and one in oligodendrocytes; only the astrocytic signal, led by variant rs74504435 with a specificity posterior of 0.946, colocalizes with Alzheimer’s risk.

Because the donor cohort spans the entire postnatal lifespan, from birth to over a century old, the study could also ask whether genetic regulation itself changes over development. Using a supervised pseudotime trajectory anchored to donor age, the researchers tested whether variant effects on expression shift along the trajectory, fitting negative binomial mixed models at the single-nucleus level. They identified 2,073 genes with dynamic eQTLs, ranging from 1,364 in excitatory neurons to just nine in oligodendrocyte precursor cells, and these dynamic genes were enriched for developmental processes such as neuron generation and cell junction organization. Crucially, dynamic eGenes in excitatory neurons, inhibitory neurons and oligodendrocytes were enriched for genes with disease colocalization signals, and a handful, including CLU and BIN1 for Alzheimer’s and FAM171A1 for schizophrenia, showed dynamic regulation and disease colocalization in the same cell class.

Finally, the atlas reaches beyond local regulation. Trans-eQTL analysis, testing variants more than five megabases from their target genes, uncovered 1,655 genes under distal regulation, with limited overlap across cell classes and replication rates of 66 to 95 percent in an independent cohort. The team identified four trans-regulatory hubs centered on the transcriptional regulators SUPT3H, RUNX2 and ZNF160, the largest of which controls nine downstream targets in oligodendrocytes. In astrocytes, mediation analysis supported a mechanistic chain in which a variant regulates the developmental gene RERE locally and the neurodevelopmental gene AUTS2 in trans, with both signals weakly colocalizing with schizophrenia risk. Together, these layers of cis, trans and time-varying regulation sketch a dynamic, cell-by-cell picture of how the genome builds and maintains the human brain, and they offer a growing list of mechanistic targets for disorders that have long resisted explanation. The authors emphasize that expanding sample sizes and capturing rarer cell types will be the next frontier, alongside integrating multi-omic data and diverse ancestries to move brain genetics toward precision medicine.

Subject of Research: Cell-type-specific genetic regulation of gene expression in the human prefrontal cortex and its role in neuropsychiatric and neurodegenerative disease risk

Article Title: Single-nucleus atlas of cell-type specific genetic regulation in the human brain

Article References: Zeng, B., Yang, H., N. M, P., Venkatesh, S., Mathur, D., Auluck, P., Bennett, D. A., Marenco, S., Haroutunian, V., PsychAD Consortium, Hong, A., Li, A. Z., He, C., Gupta, C., Dillard, C., Porras, C., Casey, C., McClung, C. A., Spencer, C., … Roussos, P. (2026). Single-nucleus atlas of cell-type specific genetic regulation in the human brain. Nature Genetics, 58(10), 2525-2534. https://doi.org/10.1038/s41588-026-02733-5

Image Credits: AI Generated

DOI: 10.1038/s41588-026-02733-5

Keywords: single-nucleus RNA-seq, eQTL, human brain, Alzheimer's disease, schizophrenia, microglia, astrocytes, oligodendrocytes, gene regulation, GWAS, colocalization, neurodevelopment