Integrative analysis of transcriptome-wide association study and gene expression profiling identifies candidate genes associated with stroke

Jian Yang; Bin Yan; Yajuan Fan; Lihong Yang; Binbin Zhao; Xiaoyan He; Qingyan Ma; Wei Wang; Ling Bai; Feng Zhang; Xiancang Ma

doi:10.7717/peerj.7435

Integrative analysis of transcriptome-wide association study and gene expression profiling identifies candidate genes associated with stroke

PeerJ. 2019 Jul 29:7:e7435. doi: 10.7717/peerj.7435. eCollection 2019.

Authors

Jian Yang^#^{1

2}, Bin Yan^#^{1

2}, Yajuan Fan³, Lihong Yang¹, Binbin Zhao³, Xiaoyan He³, Qingyan Ma³, Wei Wang³, Ling Bai¹, Feng Zhang⁴, Xiancang Ma^{2

3}

Affiliations

¹ Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
² Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
³ Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
⁴ Health Science Center, Xi'an Jiaotong University, Xi'an, China.

^# Contributed equally.

Abstract

Background: Stroke is a major public health burden worldwide. Although genetic variation is known to play a role in the pathogenesis of stroke, the specific pathogenic mechanisms are still unclear. Transcriptome-wide association studies (TWAS) is a powerful approach to prioritize candidate risk genes underlying complex traits. However, this approach has not been applied in stroke.

Methods: We conducted an integrative analysis of TWAS using data from the MEGASTROKE Consortium and gene expression profiling to identify candidate genes for the pathogenesis of stroke. Gene ontology (GO) enrichment analysis was also conducted to detect functional gene sets.

Results: The TWAS identified 515 transcriptome-wide significant tissue-specific genes, among which SLC25A44 (P = 5.46E-10) and LRCH1 (P = 1.54E-6) were significant by Bonferroni test for stroke. After validation with gene expression profiling, 19 unique genes were recognized. GO enrichment analysis identified eight significant GO functional gene sets, including regulation of cell shape (P = 0.0059), face morphogenesis (P = 0.0247), and positive regulation of ATPase activity (P = 0.0256).

Conclusions: Our study identified multiple stroke-associated genes and gene sets, and this analysis provided novel insights into the genetic mechanisms underlying stroke.

Keywords: Gene ontology; Pathogenesis; Stroke; Transcriptome-wide association study.

Grants and funding

This work was supported by the Clinical Research Award of the First Affiliated Hospital of Xi’an Jiaotong University, China (No. XJTU1AF-CRF-2017-025). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.