Transcriptome-wide Association Analysis of Brain Structures Yields Insights into Pleiotropy with Complex Neuropsychiatric Traits

Overview

Journal Nat Commun

Specialty Biology

Date 2021 May 18

PMID 34001886

Citations 23

Authors

Bingxin Zhao

Yue Shan

Yue Yang

Zhaolong Yu

Tengfei Li

Xifeng Wang

Tianyou Luo

Ziliang Zhu

Patrick Sullivan

Hongyu Zhao

Yun Li

Hongtu Zhu

Affiliations

Soon will be listed here.

Abstract

Structural variations of the human brain are heritable and highly polygenic traits, with hundreds of associated genes identified in recent genome-wide association studies (GWAS). Transcriptome-wide association studies (TWAS) can both prioritize these GWAS findings and also identify additional gene-trait associations. Here we perform cross-tissue TWAS analysis of 211 structural neuroimaging and discover 278 associated genes exceeding Bonferroni significance threshold of 1.04 × 10. The TWAS-significant genes for brain structures have been linked to a wide range of complex traits in different domains. Through TWAS gene-based polygenic risk scores (PRS) prediction, we find that TWAS PRS gains substantial power in association analysis compared to conventional variant-based GWAS PRS, and up to 6.97% of phenotypic variance (p-value = 7.56 × 10) can be explained in independent testing data sets. In conclusion, our study illustrates that TWAS can be a powerful supplement to traditional GWAS in imaging genetics studies for gene discovery-validation, genetic co-architecture analysis, and polygenic risk prediction.

Citing Articles

The landscape of plasma proteomic links to human organ imaging.

Fan Z, Chirinos J, Yang X, Shu J, Li Y, OBrien J medRxiv. 2025; .

PMID: 39867388 PMC: 11759249. DOI: 10.1101/2025.01.14.25320532.

Fine-mapping causal tissues and genes at disease-associated loci.

Strober B, Zhang M, Amariuta T, Rossen J, Price A Nat Genet. 2025; 57(1):42-52.

PMID: 39747598 DOI: 10.1038/s41588-024-01994-2.

Co-expression-wide association studies link genetically regulated interactions with complex traits.

Malakhov M, Pan W medRxiv. 2024; .

PMID: 39711708 PMC: 11661334. DOI: 10.1101/2024.10.02.24314813.

Multilayer Analysis of RNA Sequencing Data in Alzheimer's Disease to Unravel Molecular Mysteries.

Uzuner D, Ilgun A, Duz E, Bozkurt F, Cakir T Adv Neurobiol. 2024; 41:219-246.

PMID: 39589716 DOI: 10.1007/978-3-031-69188-1_9.

Proteome-wide association studies for blood lipids and comparison with transcriptome-wide association studies.

Zhang D, Gao B, Feng Q, Manichaikul A, Peloso G, Tracy R HGG Adv. 2024; 6(1):100383.

PMID: 39543875 PMC: 11650301. DOI: 10.1016/j.xhgg.2024.100383.

References

Bis J, DeCarli C, Smith A, van der Lijn F, Crivello F, Fornage M . Common variants at 12q14 and 12q24 are associated with hippocampal volume. Nat Genet. 2012; 44(5):545-51. PMC: 3427729. DOI: 10.1038/ng.2237. View

Gamazon E, Wheeler H, Shah K, Mozaffari S, Aquino-Michaels K, Carroll R . A gene-based association method for mapping traits using reference transcriptome data. Nat Genet. 2015; 47(9):1091-8. PMC: 4552594. DOI: 10.1038/ng.3367. View

Herold C, Hooli B, Mullin K, Liu T, Roehr J, Mattheisen M . Family-based association analyses of imputed genotypes reveal genome-wide significant association of Alzheimer's disease with OSBPL6, PTPRG, and PDCL3. Mol Psychiatry. 2016; 21(11):1608-1612. PMC: 4970971. DOI: 10.1038/mp.2015.218. View

Lam M, Hill W, Trampush J, Yu J, Knowles E, Davies G . Pleiotropic Meta-Analysis of Cognition, Education, and Schizophrenia Differentiates Roles of Early Neurodevelopmental and Adult Synaptic Pathways. Am J Hum Genet. 2019; 105(2):334-350. PMC: 6699140. DOI: 10.1016/j.ajhg.2019.06.012. View

Xu Z, Wu C, Wei P, Pan W . A Powerful Framework for Integrating eQTL and GWAS Summary Data. Genetics. 2017; 207(3):893-902. PMC: 5676241. DOI: 10.1534/genetics.117.300270. View

Ioannidis N, Wang W, Furlotte N, Hinds D, Bustamante C, Jorgenson E . Gene expression imputation identifies candidate genes and susceptibility loci associated with cutaneous squamous cell carcinoma. Nat Commun. 2018; 9(1):4264. PMC: 6189170. DOI: 10.1038/s41467-018-06149-6. View

Gusev A, Ko A, Shi H, Bhatia G, Chung W, Penninx B . Integrative approaches for large-scale transcriptome-wide association studies. Nat Genet. 2016; 48(3):245-52. PMC: 4767558. DOI: 10.1038/ng.3506. View

Satterthwaite T, Elliott M, Ruparel K, Loughead J, Prabhakaran K, Calkins M . Neuroimaging of the Philadelphia neurodevelopmental cohort. Neuroimage. 2013; 86:544-53. PMC: 3947233. DOI: 10.1016/j.neuroimage.2013.07.064. View

Shungin D, Winkler T, Croteau-Chonka D, Ferreira T, Locke A, Magi R . New genetic loci link adipose and insulin biology to body fat distribution. Nature. 2015; 518(7538):187-196. PMC: 4338562. DOI: 10.1038/nature14132. View

10.

Zeng P, Zhou X . Non-parametric genetic prediction of complex traits with latent Dirichlet process regression models. Nat Commun. 2017; 8(1):456. PMC: 5587666. DOI: 10.1038/s41467-017-00470-2. View

11.

Stevanin G, Fujigasaki H, Lebre A, Camuzat A, Jeannequin C, Dode C . Huntington's disease-like phenotype due to trinucleotide repeat expansions in the TBP and JPH3 genes. Brain. 2003; 126(Pt 7):1599-603. DOI: 10.1093/brain/awg155. View

12.

de Leeuw C, Mooij J, Heskes T, Posthuma D . MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput Biol. 2015; 11(4):e1004219. PMC: 4401657. DOI: 10.1371/journal.pcbi.1004219. View

13.

den Braber A, Bohlken M, Brouwer R, van t Ent D, Kanai R, Kahn R . Heritability of subcortical brain measures: a perspective for future genome-wide association studies. Neuroimage. 2013; 83:98-102. DOI: 10.1016/j.neuroimage.2013.06.027. View

14.

Wen W, Thalamuthu A, Mather K, Zhu W, Jiang J, de Micheaux P . Distinct Genetic Influences on Cortical and Subcortical Brain Structures. Sci Rep. 2016; 6:32760. PMC: 5011703. DOI: 10.1038/srep32760. View

15.

OConnor E, Topf A, Muller J, Cox D, Evangelista T, Colomer J . Identification of mutations in the MYO9A gene in patients with congenital myasthenic syndrome. Brain. 2016; 139(Pt 8):2143-53. PMC: 4958899. DOI: 10.1093/brain/aww130. View

16.

Hofer E, Roshchupkin G, Adams H, Knol M, Lin H, Li S . Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults. Nat Commun. 2020; 11(1):4796. PMC: 7508833. DOI: 10.1038/s41467-020-18367-y. View

17.

Barbeira A, Dickinson S, Bonazzola R, Zheng J, Wheeler H, Torres J . Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics. Nat Commun. 2018; 9(1):1825. PMC: 5940825. DOI: 10.1038/s41467-018-03621-1. View

18.

Grasby K, Jahanshad N, Painter J, Colodro-Conde L, Bralten J, Hibar D . The genetic architecture of the human cerebral cortex. Science. 2020; 367(6484). PMC: 7295264. DOI: 10.1126/science.aay6690. View

19.

Goes F, McGrath J, Avramopoulos D, Wolyniec P, Pirooznia M, Ruczinski I . Genome-wide association study of schizophrenia in Ashkenazi Jews. Am J Med Genet B Neuropsychiatr Genet. 2015; 168(8):649-59. DOI: 10.1002/ajmg.b.32349. View

20.

Zhao B, Zhang J, Ibrahim J, Luo T, Santelli R, Li Y . Large-scale GWAS reveals genetic architecture of brain white matter microstructure and genetic overlap with cognitive and mental health traits (n = 17,706). Mol Psychiatry. 2019; 26(8):3943-3955. PMC: 7190426. DOI: 10.1038/s41380-019-0569-z. View