De novo mutations disturb early brain development more frequently than common variants in schizophrenia.
Toshiyuki ItaiPeilin JiaYulin DaiJingchun ChenXiangning ChenZhong-Ming ZhaoPublished in: American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics (2023)
Investigating 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.
Keyphrases
- genome wide
- genome wide identification
- gene expression
- single cell
- copy number
- poor prognosis
- dna methylation
- genome wide analysis
- bioinformatics analysis
- bipolar disorder
- end stage renal disease
- pregnant women
- transcription factor
- cell therapy
- rna seq
- newly diagnosed
- intellectual disability
- white matter
- ejection fraction
- chronic kidney disease
- binding protein
- cerebral ischemia
- electronic health record
- long non coding rna
- cell cycle arrest
- multiple sclerosis
- peritoneal dialysis
- adipose tissue
- brain injury
- artificial intelligence
- deep learning
- early life
- patient reported
- wild type
- cerebral blood flow