A large-scale integrative analysis of GWAS and common meQTLs across whole life course identifies genes, pathways and tissue/cell types for three major psychiatric disorders. (December 2018)

• Record Type: Journal Article
• Authors: Zhao, Yan; Liang, Xiao; Zhu, Feng; Wen, Yan; Xu, Jiawen; Yang, Jian; Ding, Miao; Cheng, Bolun; Ma, Mei; Zhang, Lu; Cheng, Shiqiang; Wu, Cuiyan; Wang, Sen; Wang, Xi; Ning, Yujie; Guo, Xiong; Zhang, Feng
• Is Part Of: Neuroscience and biobehavioral reviews. Volume 95(2018)
• Page Start: 347
• Page End: 352
• Publication Date: 2018-12
• Subjects: Psychiatric disorders -- Methylation quantitative trait loci -- Integrative analysis; Psychophysiology -- Periodicals; Human behavior -- Periodicals; Animal behavior -- Periodicals; Neurology -- Periodicals; Behavior -- Periodicals; Ethology -- Periodicals; Neurology -- Periodicals; Psychophysiologie -- Périodiques; Comportement humain -- Périodiques; Animaux -- Mœurs et comportement -- Périodiques; Neurologie -- Périodiques; Animal behavior; Human behavior; Neurology; Psychophysiology; Periodicals; Electronic journals; 573.8
• DOI: 10.1016/j.neubiorev.2018.10.005
• Languages: English
• ISSNs: 0149-7634

Abstract

Highlights: A large-scale integrative analysis for three major psychiatric disorders. Combined GWAS and life course consistent meQTLs data sets. Both common and disease specific genes, pathways and tissue/cell types were successfully identified. Abstract: Attention deficit hyperactivity disorder (ADHD), bipolar disorder (BP) and schizophrenia (SCZ) are complex psychiatric disorders. We conducted a large-scale integrative analysis of genome-wide association studies (GWAS) and life course consistent methylation quantitative trait loci (meQTLs) datasets. The GWAS data of ADHD (including 20, 183 cases and 35, 191 controls), BP (including 7481 cases and 9250 controls) and SCZ (including 36, 989 cases and 113, 075 controls) were derived from published GWAS. Life course consistent meQTLs dataset was obtained from a longitudinal meQTLs analysis of 1018 mother–child pairs. Gene prioritization, pathway and tissue/cell type enrichment analysis were conducted by DEPICT. We identified multiple genes and pathways with common or disease specific effects, such as NISCH ( P = 9.87 × 10 −3 for BP and 2.49 × 10 −6 for SCZ), ST3GAL3 ( P = 1.19 × 10 −2 for ADHD), and KEGG_MAPK_SIGNALING_PATHWAY ( P = 1.56 × 10 −3 for ADHD, P = 4.71 × 10 −2 for BP, P = 4.60 × 10 −4 for SCZ). Our study provides novel clues for understanding the genetic mechanism of ADHD, BP and SCZ.