Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Novel insight into the etiology of autism spectrum disorder gained by integrating expression data with genome-wide association statistics

Pain, Oliver, Pocklington, Andrew J. ORCID: https://orcid.org/0000-0002-2137-0452, Holmans, Peter A. ORCID: https://orcid.org/0000-0003-0870-9412, Bray, Nichloas J. ORCID: https://orcid.org/0000-0002-4357-574X, O'Brian, Heath E., Hall, Lynsey S., Pardinas, Antonio F. ORCID: https://orcid.org/0000-0001-6845-7590, O'Donovan, Michael C. ORCID: https://orcid.org/0000-0001-7073-2379, Owen, Michael J. ORCID: https://orcid.org/0000-0003-4798-0862 and Anney, Richard ORCID: https://orcid.org/0000-0002-6083-407X 2019. Novel insight into the etiology of autism spectrum disorder gained by integrating expression data with genome-wide association statistics. Biological Psychiatry 86 (4) , pp. 265-273. 10.1016/j.biopsych.2019.04.034

[thumbnail of 1-s2.0-S0006322319313344-main.pdf]
Preview
PDF - Published Version
Available under License Creative Commons Attribution.

Download (828kB) | Preview
License URL: http://creativecommons.org/licenses/by/4.0
License Start date: 11 May 2019

Abstract

Background A recent genome-wide association study (GWAS) of autism spectrum disorders (ASD) (Ncases=18,381, Ncontrols=27,969) has provided novel opportunities for investigating the aetiology of ASD. Here, we integrate the ASD GWAS summary statistics with summary-level gene expression data to infer differential gene expression in ASD, an approach called transcriptome-wide association study (TWAS). Methods Using FUSION software, ASD GWAS summary statistics were integrated with predictors of gene expression from 16 human datasets, including adult and fetal brain. A novel adaptation of established statistical methods was then used to test for enrichment within candidate pathways, specific tissues, and at different stages of brain development. The proportion of ASD heritability explained by predicted expression of genes in the TWAS was estimated using stratified linkage disequilibrium-score regression. Results This study identified 14 genes as significantly differentially expressed in ASD, 13 of which were outside of known genome-wide significant loci (±500kb). XRN2, a gene proximal to an ASD GWAS locus, was inferred to be significantly upregulated in ASD, providing insight into functional consequence of this associated locus. One novel transcriptome-wide significant association from this study is the downregulation of PDIA6, which showed minimal evidence of association in the GWAS, and in gene-based analysis using MAGMA. Predicted gene expression in this study accounted for 13.0% of the total ASD SNP-heritability. Conclusion This study has implicated several genes as significantly up-/down-regulated in ASD providing novel and useful information for subsequent functional studies. This study also explores the utility of TWAS-based enrichment analysis and compares TWAS results with a functionally agnostic approach.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Advanced Research Computing @ Cardiff (ARCCA)
MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG)
Medicine
Additional Information: This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Publisher: Elsevier
ISSN: 0006-3223
Date of First Compliant Deposit: 7 May 2019
Date of Acceptance: 25 April 2019
Last Modified: 26 Jul 2024 16:06
URI: https://orca.cardiff.ac.uk/id/eprint/122147

Citation Data

Cited 32 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics