Haglund Alexander, Zuber Verena, Abouzeid Maya, Yang Yifei, Ko Jeong Hun, Wiemann Liv, Otero-Jimenez Maria, Muhammed Louwai, Feleke Rahel, Nott Alexi, Mills James D, Laaniste Liisi, Gveric Djordje O, Clode Daniel, Babtie Ann C, Pagni Susanna, Bellampalli Ravishankara, Somani Alyma, McDade Karina, Anink Jasper J, Mesarosova Lucia, Fancy Nurun, Willumsen Nanet, Smith Amy, Jackson Johanna, Alegre-Abarrategui Javier, Aronica Eleonora, Matthews Paul M, Thom Maria, Sisodiya Sanjay M, Srivastava Prashant K, Malhotra Dheeraj, Bryois Julien, Bottolo Leonardo, Johnson Michael R
Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK.
Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
Nat Genet. 2025 Feb;57(2):358-368. doi: 10.1038/s41588-024-02050-9. Epub 2025 Jan 10.
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.
基因表达数量性状位点被广泛用于推断基因与中枢神经系统（CNS）表型之间的关系；然而，脑部疾病对这些推断的影响尚不清楚。利用来自391个疾病病例和对照大脑的2348438个单核图谱，我们报告了13939个基因，其表达与遗传变异相关，其中16.7%-40.8%（取决于细胞类型）表现出疾病依赖性等位基因效应。在30个中枢神经系统性状的501个共定位中，即使在调整疾病状态后，仍有23.6%存在疾病依赖性。为了估计基因对结果的无混杂效应，我们使用无疾病大脑（n = 183）重复了分析，并报告了在更大的疾病与对照混合数据集中不存在的另外91个共定位，这表明对疾病相关变异的解释得到了增强。在仅含对照的大脑中原则性地实施单细胞孟德尔随机化确定了140个可能的因果基因-性状关联，其中11个在英国生物银行中得到了重复，从而确定了预测中枢神经系统结果的候选外周生物标志物的优先级。
