Affiliation:
1. Center for Precision Health, School of Biomedical Informatics The University of Texas Health Science Center at Houston Houston Texas USA
2. Nevada Institute of Personalized Medicine University of Nevada Las Vegas Las Vegas Nevada USA
3. Human Genetics Center, School of Public Health The University of Texas Health Science Center at Houston Houston Texas USA
4. Faillace Department of Psychiatry and Behavioral Sciences, McGovern Medical School The University of Texas Health Science Center at Houston Houston Texas USA
Abstract
AbstractInvestigating functional, temporal, and cell‐type expression features of mutations is important for understanding a complex disease. Here, we collected and analyzed common variants and de novo mutations (DNMs) in schizophrenia (SCZ). We collected 2,636 missense and loss‐of‐function (LoF) DNMs in 2,263 genes across 3,477 SCZ patients (SCZ‐DNMs). We curated three gene lists: (a) SCZ‐neuroGenes (159 genes), which are intolerant to LoF and missense DNMs and are neurologically important, (b) SCZ‐moduleGenes (52 genes), which were derived from network analyses of SCZ‐DNMs, and (c) SCZ‐commonGenes (120 genes) from a recent GWAS as reference. To compare temporal gene expression, we used the BrainSpan dataset. We defined a fetal effect score (FES) to quantify the involvement of each gene in prenatal brain development. We further employed the specificity indexes (SIs) to evaluate cell‐type expression specificity from single‐cell expression data in cerebral cortices of humans and mice. Compared with SCZ‐commonGenes, SCZ‐neuroGenes and SCZ‐moduleGenes were highly expressed in the prenatal stage, had higher FESs, and had higher SIs in fetal replicating cells and undifferentiated cell types. Our results suggested that gene expression patterns in specific cell types in early fetal stages might have impacts on the risk of SCZ during adulthood.
Funder
National Institutes of Health
Subject
Cellular and Molecular Neuroscience,Psychiatry and Mental health,Genetics (clinical)