Pulse Brain · Growing Health Evidence Index
Peer-reviewed

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

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 Gverić, Daniel Clode, Ann C. Babtie, Susanna Pagni, Ravishankara Bellampalli, Alyma Somani, Karina McDade, Jasper J. Anink, Lucia Mesarosova, Nurun Fancy, Nanet Willumsen, Amy M. 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

Nature Genetics · 2025

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Summary

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, demons

Subject
Other / interdisciplinary
Source type
Peer-reviewed study
System type
Other
DOI
10.1038/s41588-024-02050-9
Catalogue ID
SNmoj1ynsa-79se2c
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