Schizophrenia is a major cause of suffering and an enormous burden to patients and society. Biological factors have been strongly implicated and large-scale genome-wide association studies have now converged on several loci, suggesting that the first valid genes for schizophrenia have been identified. Arguably, the most exceptional empirical evidence is for TCF4 (transcription factor 4), a gene that consistently ranked among the top findings in the largest schizophrenia genetic studies to date. Crucially, our group recentl replicated the TCF4 association in a large family-based sample (6,298 individuals, including 3,286 cases, from 1,811 nuclear families). Family-based designs preclude the possibility of artifacts due to population stratification. Additionally, TCF4 is associated with schizophrenia endophenotypes, interacts biologically with other known schizophrenia genes and demonstrates fascinating biological plausibility. The time is right to further characterize the function of TCF and the pathways in which it participates, to obtain better insight into schizophrenia pathogenesis. The protein encoded by TCF4 is a basic helix-loop-helix transcription factor, known to recognize an Ephrussi-box ('E-box') DNA binding site ('CANNTG'). This motif is too small and non-specific to identify the binding sites of TCF4 computationally, and no empirical study has yet mapped TCF4 binding sites on a genome-wide level. Obtaining this map is our primary experimental aim. The main tool for investigating protein-DNA binding is chromatin immunoprecipitation (ChIP). Recently, this technique has been coupled with next generation sequencing (NGS), in a procedure known as ChIP-seq, to discover protein binding sites on a genome-wide level. In ChIP-seq, protein-bound DNA is co-precipitated with an antibody specific to the protein of interest, purified and sequenced on an NGS instrument. Millions of sequence tags are generated and mapped back to a reference genome, allowing determination of the genomic regions bound to the protein. Owing to the rapid progress of in ChIP-seq over the last 5 years, the laboratory and computational methods used in mapping transcription factor binding sites are well worked out. Once we have obtained the map of TCF4-binding sites, we will look for evidence of co-regulation in genome-wide gene expression studies, to validate our experimental findings. We will then test for association of the TCF4 gene network with schizophrenia, by examining GWAS meta-analysis data on 11,185 cases plus 10,768 controls, in addition to our methylome-wide case-control study (750 cases, 750 controls), and post- mortem gene expression studies of brain tissue from schizophrenia cases and controls. Our group is ideally suited to perform a thorough investigation of TCF4 using these methods, having a history of innovation in psychiatric genetics and our own NGS equipment. All generated data will be deposited in the appropriate public repository.

Public Health Relevance

Large-scale genetics studies are finally converging on specific risk genes for schizophrenia, and TCF4 is arguably the gene displaying the best supporting evidence of all. TCF4 is involved in the regulation of other genes, so here we propose cutting- edge DNA sequencing technologies to discover the network of genes under TCF4 control. We will then study this genetic network in multiple biological datasets of schizophrenia cases and controls, in order to advance our understanding of how TCF4 may affect risk for the disorder.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21MH099419-01
Application #
8429938
Study Section
Behavioral Genetics and Epidemiology Study Section (BGES)
Program Officer
Meinecke, Douglas L
Project Start
2012-09-19
Project End
2014-06-30
Budget Start
2012-09-19
Budget End
2013-06-30
Support Year
1
Fiscal Year
2012
Total Cost
$299,000
Indirect Cost
$99,000
Name
Virginia Commonwealth University
Department
Type
Schools of Pharmacy
DUNS #
105300446
City
Richmond
State
VA
Country
United States
Zip Code
23298
Xia, Hanzhang; Jahr, Fay M; Kim, Nak-Kyeong et al. (2018) Building a schizophrenia genetic network: transcription factor 4 regulates genes involved in neuronal development and schizophrenia risk. Hum Mol Genet 27:3246-3256
Kronfol, Mohamad M; Dozmorov, Mikhail G; Huang, Rong et al. (2017) The role of epigenomics in personalized medicine. Expert Rev Precis Med Drug Dev 2:33-45