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<p>Gene expression quantitative trait loci are widely used to infer relationships between genes and central nervous system (CNS) phenotypes; however, the effect of brain disease on these inferences is unclear. Using 2,348,438 single-nuclei profiles from 391 disease-case and control brains, we report 13,939 genes whose expression correlated with genetic variation, of which 16.7–40.8% (depending on cell type) showed disease-dependent allelic effects. Across 501 colocalizations for 30 CNS traits, 23.6% had a disease dependency, even after adjusting for disease status. To estimate the unconfounded effect of genes on outcomes, we repeated the analysis using nondiseased brains (<i>n</i> = 183) and reported an additional 91 colocalizations not present in the larger mixed disease and control dataset, demonstrating enhanced interpretation of disease-associated variants. Principled implementation of single-cell Mendelian randomization in control-only brains identified 140 putatively causal gene–trait associations, of which 11 were replicated in the UK Biobank, prioritizing candidate peripheral biomarkers predictive of CNS outcomes.</p>

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Cell state-dependent allelic effects and contextual Mendelian randomization analysis for human brain phenotypes

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年1月10日

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  • Alexander Haglund,
  • Verena Zuber,
  • Maya Abouzeid,
  • Yifei Yang,
  • Jeong Hun Ko,
  • Liv Wiemann,
  • Maria Otero-Jimenez,
  • Louwai Muhammed,
  • Rahel Feleke,
  • Alexi Nott,
  • James D. Mills,
  • Liisi Laaniste,
  • Djordje O. Gveric,
  • Daniel Clode,
  • Ann C. Babtie,
  • Susanna Pagni,
  • Ravishankara Bellampalli,
  • Alyma Somani,
  • Karina McDade,
  • Jasper J. Anink,
  • Lucia Mesarosova,
  • Nurun Fancy,
  • Nanet Willumsen,
  • Amy Smith,
  • Johanna Jackson,
  • Javier Alegre-Abarrategui,
  • Eleonora Aronica,
  • Paul M. Matthews,
  • Maria Thom,
  • Sanjay M. Sisodiya,
  • Prashant K. Srivastava,
  • Dheeraj Malhotra,
  • Julien Bryois,
  • Leonardo Bottolo,
  • Michael R. Johnson

摘要

Gene expression quantitative trait loci are widely used to infer relationships between genes and central nervous system (CNS) phenotypes; however, the effect of brain disease on these inferences is unclear. Using 2,348,438 single-nuclei profiles from 391 disease-case and control brains, we report 13,939 genes whose expression correlated with genetic variation, of which 16.7–40.8% (depending on cell type) showed disease-dependent allelic effects. Across 501 colocalizations for 30 CNS traits, 23.6% had a disease dependency, even after adjusting for disease status. To estimate the unconfounded effect of genes on outcomes, we repeated the analysis using nondiseased brains (n = 183) and reported an additional 91 colocalizations not present in the larger mixed disease and control dataset, demonstrating enhanced interpretation of disease-associated variants. Principled implementation of single-cell Mendelian randomization in control-only brains identified 140 putatively causal gene–trait associations, of which 11 were replicated in the UK Biobank, prioritizing candidate peripheral biomarkers predictive of CNS outcomes.