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

Original title: Single-nucleus atlas of cell-type specific genetic regulation in the human brain.

Genetic risk variants for common diseases are predominantly located in non-coding regulatory regions and modulate gene expression.

By Zeng, Yang, Prashant N +14Nature geneticsSep 23, 2026

Score█████░░░░░4.7

VerdictWorth a reader's time today.

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Abstract

Genetic risk variants for common diseases are predominantly located in non-coding regulatory regions and modulate gene expression. Although bulk tissue studies have elucidated shared mechanisms of regulatory and disease-associated genetics, the cellular specificity of these mechanisms remains largely unexplored. Here we present a comprehensive, single-nucleus multi-ancestry atlas of genetic regulation of gene expression in the human prefrontal cortex, comprising 5.6 million nuclei from 1,384 donors of diverse ancestries. Through multi-resolution analyses spanning eight major cell classes and 27 subclasses, we identify genetic regulation for 14,258 genes, with 981 showing cell type-specific regulatory effects at the class level and 857 at the subclass level. Colocalization of genetic variants associated with gene regulation and disease traits uncovers novel cell type-specific genes implicated in Alzheimer's disease, schizophrenia and other disorders that were not detectable in bulk tissue analyses. Analysis of dynamic genetic regulation at the single-nucleus level identifies 2,073 genes with regulatory effects that vary across developmental trajectories, inferred from a broad age range of donors. We also uncover 1,655 genes with trans-regulatory effects, revealing distal regulation of gene expression. This high-resolution atlas provides insight into the cell type-specific regulatory architecture of the human brain, and offers novel mechanistic targets for understanding the genetic basis of neuropsychiatric and neurodegenerative diseases.

Biao Zeng, Hui Yang, Prashant N M, Sanan Venkatesh, Deepika Mathur, Pavan Auluck, David A Bennett, Stefano Marenco, Vahram Haroutunian, PsychAD Consortium, Georgios Voloudakis, Donghoon Lee, John F Fullard, Jaroslav Bendl, Kiran Girdhar, Gabriel E Hoffman, Panos Roussos

The editor's rubric

Heuristic review

Dimension	Level	Weight	What that level means
Leverage	███░░ 3	10%	A method or resource many groups across the field will adopt within a year.
Magnitude	██░░░ 2	20%	Solid incremental gain on a meaningful problem.
Evidence	███░░ 3	32%	Solid: multiple benchmarks or cohorts, ablations, fair baselines, released code or data.
Novelty	███░░ 3	8%	A genuinely new approach to an open problem.
Trajectory	██░░░ 2	5%	Some room to improve with obvious engineering.
Stakes	███░░ 3	25%	Meaningful benefit to many people within a few years.

Editor’s rationale

Heuristic triage from title and abstract text only, not a reading of the paper. Cues found: method (we propose); novelty (discovery); stakes (global scale, major disease, genetic disease).

How the score was computed

rank-2026-09-29

Score█████░░░░░4.7

Score = 10 × (80% × adjusted merit / 10 + 10% × attention + 10% × freshness)

Merit: 5.5 / 10; Weighted rubric, evidence-gated.
Adjusted merit: 4.6 / 10; Shrunk toward the desk prior by editor confidence (40%).
Attention: 43%; Citations, upvotes, points, mentions.
Freshness: 60%; Half-life decay since publication.

Citations2 (reference 20, via openalex, Sep 29, 2026, 23:37 UTC)
Field-weighted citation impact9.2 (reference 3, via openalex, Sep 29, 2026, 23:37 UTC)

The record

Reviewed by heuristic-v2 on Sep 29, 2026, 23:53 UTC. Paper type: method.
Categories: Journal Article
BRIEF, No.1 in the Biology edition of September 30, 2026.
TOP, No.6 in the Biology edition of September 29, 2026.