The broad goal of this project is to initiate a genome-wide study of gene expression of schizophrenia (SZ), targeting over 25,000 annotated genes, in a repository sample with available genome-wide association study (GWAS) data. The basic hypothesis of this proposal is that gene regulation mechanisms are involved in the etiology of SZ, and that gene expression data will be instrumental to the interpretation of SZ GWAS results and for guiding laboratory efforts, including large re-sequencing initiatives.
The specific aims are:
AIM 1 - Determine genome-wide gene expression levels utilizing the Illumina HT-12 array in a well-powered sample comprised of Epstein Barr Virus (EBV) transformed B lymphocytes (lymphoblastoid cell lines, LCLs) from 1,011 severely affected cases and 1,011 psychiatrically screened controls from the Molecular Genetics of SZ (MGS) sample. The experiment will proceed with full attention to quality control (QC) and the experimental design will allow for the systematic analysis of genetic and non-genetic variance.
AIM 2 - Search for eQTLs that regulate the expression of genes associated with SZ. First, expressed sequences that show case-control differences will be sought, and for these gene transcripts, association between the expression levels and SNPs in cis in the gene expression sample (1,011 cases and 1,011 controls) will be tested. Next association between these identified SNPs and SZ will be tested in the rest of the MGS EA sample (1,671 cases and 1,643 controls). A genome-wide search for trans eQTLs will also be performed, however, with decreased statistical power compared to cis eQTLs. While the field of gene expression in human disease is growing at an accelerated pace, this proposal addresses the dearth of well-powered microarray expression studies in SZ (and psychiatric) genetics. This proposal only asks for support for the measurements of DNA transcription, and statistical and bioinformatic analyses thereof. The proposed GWES will greatly augment the value of this public sample, which has been the most accessed clinical sample for NIMH in dbGAP, greatly amplifying the overall impact of the proposed experiments. An already established LCL NIMH resource at the Rutgers University Cell and DNA Repository (RUCDR) will be accessed, and the gene expression results will be rapidly shared with the scientific community through an NIMH sponsored mechanism. Future plans include extending our study of gene expression to the full transcriptome with the aim of integrating genome variation, DNA transcription, and proteomic data relevant to the study of SZ genetics (and biomedical sciences in general), and participating in meta-analyses of gene expression in SZ. SZ is a devastating and costly psychiatric disorder exhibiting complex genetics. The joint analysis of expression and GWAS data is expected to lead to discoveries of mechanisms of SZ susceptibility otherwise obscured to either method in isolation, and create new research opportunities by motivating mechanistically based experiments, e.g., models where pharmacology can be tested hopefully rapidly leading to new treatment strategies.

Public Health Relevance

This study aims to uncover information about differences in gene expression between individuals with schizophrenia versus controls, their relationship to previously studied genetic variation, and the joint analysis thereof. Besides informing important areas of biology, the study especially aims to better understand genetic contributions to schizophrenia, as a means to better understand how disease develops. This knowledge should assist in efforts to prevent and treat this devastating and costly illness.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
High Impact Research and Research Infrastructure Programs (RC2)
Project #
Application #
Study Section
Special Emphasis Panel (ZMH1-ERB-C (A4))
Program Officer
Koester, Susan E
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Northshore University Healthsystem
United States
Zip Code
Kos, Mark Z; Duan, Jubao; Sanders, Alan R et al. (2018) Dopamine perturbation of gene co-expression networks reveals differential response in schizophrenia for translational machinery. Transl Psychiatry 8:278
Duan, Jubao; Göring, Harald H H; Sanders, Alan R et al. (2018) Transcriptomic signatures of schizophrenia revealed by dopamine perturbation in an ex vivo model. Transl Psychiatry 8:158
Sanders, A R; Drigalenko, E I; Duan, J et al. (2017) Transcriptome sequencing study implicates immune-related genes differentially expressed in schizophrenia: new data and a meta-analysis. Transl Psychiatry 7:e1093
Duan, Jubao; Sanders, Alan R; Moy, Winton et al. (2015) Transcriptome outlier analysis implicates schizophrenia susceptibility genes and enriches putatively functional rare genetic variants. Hum Mol Genet 24:4674-85
Rees, E; Kirov, G; Sanders, A et al. (2014) Evidence that duplications of 22q11.2 protect against schizophrenia. Mol Psychiatry 19:37-40
Duan, Jubao; Shi, Jianxin; Ge, Xijin et al. (2013) Genome-wide survey of interindividual differences of RNA stability in human lymphoblastoid cell lines. Sci Rep 3:1318
Sanders, Alan R; Göring, Harald H H; Duan, Jubao et al. (2013) Transcriptome study of differential expression in schizophrenia. Hum Mol Genet 22:5001-14
Gejman, Pablo V; Sanders, Alan R; Kendler, Kenneth S (2011) Genetics of schizophrenia: new findings and challenges. Annu Rev Genomics Hum Genet 12:121-44
Duan, Jubao; Sanders, Alan R; Gejman, Pablo V (2010) Genome-wide approaches to schizophrenia. Brain Res Bull 83:93-102