Cell State-dependent Allelic Effects and Contextual Mendelian Randomization Analysis for Human Brain Phenotypes

Overview

Journal Nat Genet

Date 2025 Jan 10

PMID 39794547

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 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

Affiliations

Soon will be listed here.

Abstract

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.

References

Bowden J, Del Greco M F, Minelli C, Davey Smith G, Sheehan N, Thompson J . A framework for the investigation of pleiotropy in two-sample summary data Mendelian randomization. Stat Med. 2017; 36(11):1783-1802. PMC: 5434863. DOI: 10.1002/sim.7221. View

Soskic B, Cano-Gamez E, Smyth D, Ambridge K, Ke Z, Matte J . Immune disease risk variants regulate gene expression dynamics during CD4 T cell activation. Nat Genet. 2022; 54(6):817-826. PMC: 9197762. DOI: 10.1038/s41588-022-01066-3. View

de Klein N, Tsai E, Vochteloo M, Baird D, Huang Y, Chen C . Brain expression quantitative trait locus and network analyses reveal downstream effects and putative drivers for brain-related diseases. Nat Genet. 2023; 55(3):377-388. PMC: 10011140. DOI: 10.1038/s41588-023-01300-6. View

McCarthy S, Das S, Kretzschmar W, Delaneau O, Wood A, Teumer A . A reference panel of 64,976 haplotypes for genotype imputation. Nat Genet. 2016; 48(10):1279-83. PMC: 5388176. DOI: 10.1038/ng.3643. View

Fujita M, Gao Z, Zeng L, McCabe C, White C, Ng B . Cell subtype-specific effects of genetic variation in the Alzheimer's disease brain. Nat Genet. 2024; 56(4):605-614. DOI: 10.1038/s41588-024-01685-y. View

Murphy A, Schilder B, Skene N . MungeSumstats: a Bioconductor package for the standardization and quality control of many GWAS summary statistics. Bioinformatics. 2021; 37(23):4593-4596. PMC: 8652100. DOI: 10.1093/bioinformatics/btab665. View

Hao Y, Hao S, Andersen-Nissen E, Mauck 3rd W, Zheng S, Butler A . Integrated analysis of multimodal single-cell data. Cell. 2021; 184(13):3573-3587.e29. PMC: 8238499. DOI: 10.1016/j.cell.2021.04.048. View

Lun A, Riesenfeld S, Andrews T, Dao T, Gomes T, Marioni J . EmptyDrops: distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data. Genome Biol. 2019; 20(1):63. PMC: 6431044. DOI: 10.1186/s13059-019-1662-y. View

Burgess S, Thompson S . Avoiding bias from weak instruments in Mendelian randomization studies. Int J Epidemiol. 2011; 40(3):755-64. DOI: 10.1093/ije/dyr036. View

10.

Bryois J, Calini D, Macnair W, Foo L, Urich E, Ortmann W . Cell-type-specific cis-eQTLs in eight human brain cell types identify novel risk genes for psychiatric and neurological disorders. Nat Neurosci. 2022; 25(8):1104-1112. DOI: 10.1038/s41593-022-01128-z. View

11.

Maurano M, Humbert R, Rynes E, Thurman R, Haugen E, Wang H . Systematic localization of common disease-associated variation in regulatory DNA. Science. 2012; 337(6099):1190-5. PMC: 3771521. DOI: 10.1126/science.1222794. View

12.

Meyer D, Aguiar V, Bitarello B, Brandt D, Nunes K . A genomic perspective on HLA evolution. Immunogenetics. 2017; 70(1):5-27. PMC: 5748415. DOI: 10.1007/s00251-017-1017-3. View

13.

Bowles K, Pugh D, Liu Y, Patel T, Renton A, Bandres-Ciga S . 17q21.31 sub-haplotypes underlying H1-associated risk for Parkinson's disease are associated with LRRC37A/2 expression in astrocytes. Mol Neurodegener. 2022; 17(1):48. PMC: 9284779. DOI: 10.1186/s13024-022-00551-x. View

14.

Zheng J, Haberland V, Baird D, Walker V, Haycock P, Hurle M . Phenome-wide Mendelian randomization mapping the influence of the plasma proteome on complex diseases. Nat Genet. 2020; 52(10):1122-1131. PMC: 7610464. DOI: 10.1038/s41588-020-0682-6. View

15.

Mansour H, Fawzy H, El-Khatib A, Khattab M . Repurposed anti-cancer epidermal growth factor receptor inhibitors: mechanisms of neuroprotective effects in Alzheimer's disease. Neural Regen Res. 2022; 17(9):1913-1918. PMC: 8848623. DOI: 10.4103/1673-5374.332132. View

16.

Wingo A, Liu Y, Gerasimov E, Gockley J, Logsdon B, Duong D . Integrating human brain proteomes with genome-wide association data implicates new proteins in Alzheimer's disease pathogenesis. Nat Genet. 2021; 53(2):143-146. PMC: 8130821. DOI: 10.1038/s41588-020-00773-z. View

17.

Sun B, Chiou J, Traylor M, Benner C, Hsu Y, Richardson T . Plasma proteomic associations with genetics and health in the UK Biobank. Nature. 2023; 622(7982):329-338. PMC: 10567551. DOI: 10.1038/s41586-023-06592-6. View

18.

Ma X, Prudencio M, Koike Y, Vatsavayai S, Kim G, Harbinski F . TDP-43 represses cryptic exon inclusion in the FTD-ALS gene UNC13A. Nature. 2022; 603(7899):124-130. PMC: 8891019. DOI: 10.1038/s41586-022-04424-7. View

19.

DAntonio M, Nguyen J, Arthur T, Matsui H, DAntonio-Chronowska A, Frazer K . SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues. Cell Rep. 2021; 37(7):110020. PMC: 8563343. DOI: 10.1016/j.celrep.2021.110020. View

20.

Das S, Forer L, Schonherr S, Sidore C, Locke A, Kwong A . Next-generation genotype imputation service and methods. Nat Genet. 2016; 48(10):1284-1287. PMC: 5157836. DOI: 10.1038/ng.3656. View