Abstract
BackgroundStroke 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.MethodsWe 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.ResultsThe 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).ConclusionsOur study identified multiple stroke-associated genes and gene sets, and this analysis provided novel insights into the genetic mechanisms underlying stroke.
Highlights
Stroke is the second leading cause of death and the third leading cause of disability-adjusted life-years lost worldwide (Feigin, Norrving & Mensah, 2017; Hankey, 2017)
We identified 515 transcriptome-wide significant gene-stroke features (PTWAS < 0.05 and Ppermutation < 0.05) for 446 unique genes, including 58 genes that were significant in more than one panel (Table S1)
SLC25A44 and LRCH1 were the only two genes passing the Bonferroni correction threshold (P < 0.05/11,826) for all gene-stroke features, which implied that they were strongly associated with stroke
Summary
Stroke is the second leading cause of death and the third leading cause of disability-adjusted life-years lost worldwide (Feigin, Norrving & Mensah, 2017; Hankey, 2017). Integrative analysis of transcriptome-wide association study and gene expression profiling identifies candidate genes associated with stroke. Transcriptome-wide association studies (TWAS) is a powerful approach to prioritize candidate risk genes underlying complex traits. This approach has not been applied in stroke. 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. Our study identified multiple stroke-associated genes and gene sets, and this analysis provided novel insights into the genetic mechanisms underlying stroke
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