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<p>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 <i>cis</i>-eQTLs and <i>trans</i>-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 <i>cis</i>-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.</p>

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A meta-analysis of single-nucleus expression quantitative trait loci linking genetic risk to brain disorders

  • 期刊论文

  • 发表日期：

    2026年3月19日

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  • Beomjin Jang,
  • Kailash BP,
  • Alex Tokolyi,
  • Winston H. Dredge,
  • Ashvin Ravi,
  • Sang-Hyuk Jung,
  • Tatsuhiko Naito,
  • Beomsu Kim,
  • Min Seo Kim,
  • Minyoung Cho,
  • Mi-So Park,
  • Mikaela Rosen,
  • Joel Blanchard,
  • Jack Humphrey,
  • David A. Knowles,
  • Hong-Hee Won,
  • Towfique Raj

摘要

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.