Schizophrenia is a severe mental disorder with significant genetic effects. However, the nature and the identity of the genetic factors remain elusive. Recent genome-wide association studies (GWASs) have made substantial progress, identifying several promising candidate genes with common variants. However, these candidates only account for a small proportion of observed heritability. More recently, sequencing and copy number variation (CNV) analyses have documented many rare de novo mutations associated with the risks to this disorder. Combined with what we have learned from GWASs, it is clear that both common and rare variants contribute to genetic risks to schizophrenia. Our current knowledge of schizophrenia is overwhelmingly derived from the study of Caucasian populations. The limited investigations of other ethnicities and the lack of systematic examination of the differences between populations are noticeable in the field. These weaknesses may impede our understanding of the etiology of the disorder. In responding to the request for application AI- 12-021 """"""""U.S.-China Program for Biomedical Collaborative Research (R01)"""""""", we propose studies aiming at the understanding of the genetic architecture of schizophrenia in the Han Chinese population and investigating the shared and ethnic-specific risk factors between the Han Chinese and Caucasian populations.
Our aims are: 1. to conduct exome sequencing for 140 nuclear Han Chinese families with multiple affected individuals to discover single nucleotide variations (SNVs) and copy number variations (CNVs) predisposing to the disorder. We plan to use families with both parents (affected or unaffected), 2 affected and 1 unaffected siblings and families with 1 parent, 2 affected and 1 unaffected siblings. The use of families with affected and unaffected siblings allows us to simultaneously discover and characterize transmitted and de novo risk variants. The unaffected siblings in the families are better controls than subjects from the general population, as they can help to distinguish potentially pathological variants from many benign variants observed in the families. 2. To genotype 5,000 cases and 5,000 controls of Han Chinese samples for up to 100 of the most promising risk variants discovered in Aim 1 above to verify their association with SCZ. We will apply a set of sophisticated statistical, bioinformatics and functional filters to select the most promising SNVs. We will focus on those rare variants (including de novo variants) with potential functional consequences and variants occurred at multiple sites in the same genes and biological pathways. 3. To perform comparative analyses using GWAS datasets from both Caucasian and Han Chinese populations to estimate the overlap of genetic risk between the two populations, and to discover and characterize the shared- and ethnic-specific risk genes. We propose to use polygenic analyses to examine the correlation between the PGC and Chinese GWASs to estimate the overlap of risk factors between these populations, and to examine the genetic structure of SCZ in these two ethnic groups.

Public Health Relevance

In recent literature, there is evidence that mutations with low frequencies are important contributor of genetic risk to schizophrenia. This application proposes to discover and test these mutations by exome sequencing of multiplex Han Chinese families with affected and unaffected siblings. The application also plans to conduct comparative analyses to determine the shared and ethnic specific factors between the Chinese and Caucasian populations.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
1R01MH101054-01
Application #
8547507
Study Section
Special Emphasis Panel (ZMH1-ERB-X (03))
Program Officer
Addington, Anjene M
Project Start
2013-09-26
Project End
2016-08-31
Budget Start
2013-09-26
Budget End
2014-08-31
Support Year
1
Fiscal Year
2013
Total Cost
$199,999
Indirect Cost
$68,852
Name
Virginia Commonwealth University
Department
Psychiatry
Type
Schools of Medicine
DUNS #
105300446
City
Richmond
State
VA
Country
United States
Zip Code
23298
Jia, Peilin; Chen, Xiangning; Xie, Wei et al. (2018) Mega-analysis of Odds Ratio: A Convergent Method for a Deep Understanding of the Genetic Evidence in Schizophrenia. Schizophr Bull :
Chen, Jingchun; Wu, Jian-Shing; Mize, Travis et al. (2018) Prediction of Schizophrenia Diagnosis by Integration of Genetically Correlated Conditions and Traits. J Neuroimmune Pharmacol 13:532-540
Sharma, Surbhi; Young, Richard J; Chen, Jingchun et al. (2018) Minimotifs dysfunction is pervasive in neurodegenerative disorders. Alzheimers Dement (N Y) 4:414-432
Chen, Jingchun; Bacanu, Silviu-Alin; Yu, Hui et al. (2016) Genetic Relationship between Schizophrenia and Nicotine Dependence. Sci Rep 6:25671
Chen, Jingchun; Cao, Fei; Liu, Lanfen et al. (2015) Genetic studies of schizophrenia: an update. Neurosci Bull 31:87-98
Zhao, Zhongming; Xu, Jiabao; Chen, Jingchun et al. (2015) Transcriptome sequencing and genome-wide association analyses reveal lysosomal function and actin cytoskeleton remodeling in schizophrenia and bipolar disorder. Mol Psychiatry 20:563-572
Kendler, K S (2015) A joint history of the nature of genetic variation and the nature of schizophrenia. Mol Psychiatry 20:77-83
Duan, Jubao; Shi, Jianxin; Fiorentino, Alessia et al. (2014) A rare functional noncoding variant at the GWAS-implicated MIR137/MIR2682 locus might confer risk to schizophrenia and bipolar disorder. Am J Hum Genet 95:744-53