Integrating genome-wide association study and methylation functional annotation data identified candidate genes and pathways for schizophrenia.

Clicks: 314
ID: 11875
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #24 of 133 articles by views in progress in neuro-psychopharmacology & biological psychiatry

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 133 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Schizophrenia (SCZ) is a severe mental disorder. Both environmental and genetic factors contribute to the development of SCZ. The estimated heritability of SCZ is about 80%. Previous genetic studies of SCZ mainly focused on the genetic variations associated the risk of SCZ. Limited efforts are paid to explore the roles and biological mechanism of nuclear acid methylation implicated in the pathogenesis of SCZ.A two-stage integrative analysis of SCZ GWAS and nuclear acid methylation functional annotation data (including meQTLs and m6A) was performed in this study. First, the discovery GWAS of SCZ was aligned with genomic meQTLs and m6A annotation data to identify the candidate genes associated with SCZ. Second, another independent replication GWAS dataset of SCZ was applied to validate the discovery results. Furthermore, the functional relevance of identified candidate genes with SCZ were validated by the mRNA expression profiling of SCZ brain tissues. Gene ontology (GO) and pathway enrichment analysis of identified candidate genes was performed by the DAVID tool.The two-stage integrative analysis detected 106 meQTLs related candidate genes for SCZ. After comparing with the differentially expressed genes in SCZ brain tissues, 49 overlapped genes were identified for meQTLs, such as ZSCAN12, BTN3A2 and HLA-DQA1. Besides, for meQTLs, 29 SCZ associated pathways and 56 SCZ associated GO terms were detected, such as cell adhesion molecules and asthma. For m6A, 25 candidate genes were detected by the two-stage integrative analysis for SCZ, such as ZSCAN12, HLA-DQA1 and SNX19. Furthermore, 17 of the 25 genes were detected in the mRNA expression profiling of SCZ brain tissues.This study identified multiple SCZ associated genes and pathways, supporting the implication of nuclear acid methylation in the pathogenesis of SCZ.
Reference Key
qi2019integratingprogress Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Qi, Xin;Guan, Fanglin;Wen, Yan;Li, Ping;Ma, Mei;Cheng, Shiqiang;Zhang, Lu;Liang, Chujun;Cheng, Bolun;Zhang, Feng;
Journal progress in neuro-psychopharmacology & biological psychiatry
Year 2019
DOI
S0278-5846(19)30196-4
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.