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Nat. Genet., Published: 19 March 2026 | https://doi.org/10.1038/s41588-026-02541-x A meta-analysis of single-nucleus expression quantitative trait loci linking genetic risk to brain disorders

Beomjin Jang^1,2,3,4,5,6, Kailash BP^1,2,3,4,5, Alex Tokolyi^7,8, Winston H. Dredge^1,2,3,4,5, Ashvin Ravi^1,2,3,4,5,9, Sang-Hyuk Jung¹⁰, Tatsuhiko Naito^1,2,3,4,5, Beomsu Kim^6,11,12, Min Seo Kim^13,14, Minyoung Cho⁶, Mi-So Park⁶, Mikaela Rosen^1,2,3,4,5, Joel Blanchard^2,3, Jack Humphrey^1,2,3,4,5, David A. Knowles^7,8, Hong-Hee Won^6,15& Towfique Raj^1,2,3,4,5

¹Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York City, NY, USA.
²Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA.
³Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York City, NY, USA.
⁴Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York City, NY, USA.
⁵Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York City, NY, USA.
⁶Department of Digital Health, SAIHST, Sungkyunkwan University, Samsung Medical Center, Seoul, Republic of Korea.
⁷Departments of Computer Science and Systems Biology, Columbia University, New York City, NY, USA.
⁸New York Genome Center, New York City, NY, USA.
⁹Biological and Medical Informatics PhD Program, University of California, San Francisco, San Francisco, CA, USA.
¹⁰Department of Medical Informatics, Kangwon National University College of Medicine, Chuncheon, Republic of Korea.
¹¹Division of Nephrology, Boston Children’s Hospital, Boston, MA, USA.
¹²Kidney Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
¹³Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
¹⁴Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
¹⁵Department of Precision Medicine, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.

Corresponding authors
Correspondence to Hong-Hee Won or Towfique Raj.

Abstract

Most genetic risk variants for neurological diseases are located in noncoding regulatory regions, where they often act as expression quantitative trait loci (eQTLs), modulating gene expression and influencing disease susceptibility. However, eQTL studies in bulk brain tissue or cell lines fail to capture the brain’s cellular diversity. Single-nucleus RNA sequencing (snRNA-seq) allows high-resolution mapping of eQTLs across diverse brain cell types. Here we performed a meta-analysis by integrating snRNA-seq and genotype data from four cohorts, totaling 5.8 million nuclei from 983 individuals of European ancestry. We mapped cis-eQTLs and trans-eQTLs across major brain cell types and subtypes, including disease-specific and sex-specific eQTLs, and applied colocalization and Mendelian randomization to identify genes that mediate neurological disease risk. We observed up to tenfold more cis-eQTLs and uncovered cell-type-specific genes linked to neurological disease. SingleBrain is a comprehensive single-cell eQTL resource that provides insights into the genetic mechanism of brain disorders.

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