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

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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 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 ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.1038/s41588-024-02050-9

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.

Related Topics

Biology

Phenotype

Disease

Mendelian Inheritance

Concepts

Mendelian randomization Biology Phenotype Allele Disease Genetics Gene Quantitative trait locus Mendelian inheritance Expression quantitative trait loci Trait Genetic variants Single-nucleotide polymorphism Genotype Internal medicine Medicine Programming language Computer science

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Type: article
Language: en
Landing Page: https://doi.org/10.1038/s41588-024-02050-9
PDF: https://www.nature.com/articles/s41588-024-02050-9.pdf
OA Status: hybrid
Cited By: 14
References: 56
Related Works: 10
OpenAlex ID: https://openalex.org/W4406232070

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DOI: https://doi.org/10.1038/s41588-024-02050-9

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

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Type: article

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Language: en

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Publication year: 2025

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Publication date: 2025-01-10

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Authors: 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

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Landing page: https://doi.org/10.1038/s41588-024-02050-9

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PDF URL: https://www.nature.com/articles/s41588-024-02050-9.pdf

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Concepts: Mendelian randomization, Biology, Phenotype, Allele, Disease, Genetics, Gene, Quantitative trait locus, Mendelian inheritance, Expression quantitative trait loci, Trait, Genetic variants, Single-nucleotide polymorphism, Genotype, Internal medicine, Medicine, Programming language, Computer science

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Cited by: 14

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