Researchers Find Multiple Genes that Contribute to Schizophrenia Risk

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According to an international study led by researchers from the Virginia Commonwealth University (VCU) School of Pharmacy, multiple genes contribute to risk for schizophrenia and appear to function in pathways related to transmission of signals in the brain and immunity [1]. The discovery provides scientists with a better understanding the molecular and biological mechanisms involved with schizophrenia that may improve disease management and identify new drug targets. The study is published in the April issue of JAMA Psychiatry.


Schizophrenia is a complex metal disorder that affects more than 1 percent of the world’s population and causes severe mental disturbances that disrupt normal thoughts, speech, and behavior. Schizophrenia makes it hard to think clearly, have normal emotional responses, act normally in social situations, and tell the difference between what is real and what isn’t.

In the study, researchers integrated results from a meta-analysis (i.e. a study of other studies) of 18 genome-wide association studies (GWAS) involving nearly 22,000 patients and over 1 million genetic markers called ‘SNPs’ (pronounced “snips”) that appeared to point to schizophrenia risk. SNPs are DNA sequence variations that occur when a single nucleotide — Adenine, Thymine, Cytosine and Guanine — in the genome is changed. These small variations in DNA sequence make up almost 90% of all human genetic variation.

Scientists then systematically collected results from other kinds of biological schizophrenia studies that studied 6,298 individuals from 1,811 nuclear families and combined all the results using a novel data integration approach.

Nuclear family: a term used to define a family group consisting of a pair of adults and their children; also called elementary family.

The 9,380 most promising SNPs were then genotyped against a large, independent collection of families with schizophrenia patients, an experimental design that avoids issues that have troubled previous genetic studies of schizophrenia.

SNPs in the genes Transcription Factor 4 (TCF4) and Notch Homolog 4 (Drosophila) (NOTCH4) were among the most robust findings. More novel findings included POM121L2, Arsenic (+3 oxidation state) Methyltransferase (AS3MT), Cyclin M2 (CNNM2), and 5-Prime, Cytosolic II Nucleotidase (NT5C2).

Biological pathway analysis showed that the most significant pathways associated with genes that contribute to risk for schizophrenia were involved in neuronal function and the immune system. VCU researchers are already pursuing tests to study TCF4, which controls the expression of other brain genes.

According to principal investigator Edwin van den Oord, Ph.D., professor and director of the Center for Biomarker Research and Personalized Medicine in the Department of Pharmacotherapy and Outcomes Science at the VCU School of Pharmacy [2]:

Now that we have genes that are robustly associated with schizophrenia, we can begin to design much more specific experiments to understand how disruption of these genes may affect brain development and function. Also, some of these genes provide excellent targets for the development of new drugs.

The research included efforts from scientists in Denmark, Sweden, the United Kingdom, Norway and the United States. A similar international study in 2012 also mapped the genomic and biological landscape for schizophrenia, and, among others, identified the TCF4 gene and implicated neuronal pathways [3].


  1. Aberg et al. A Comprehensive Family-Based Replication Study of Schizophrenia Genes. JAMA Psychiatry. 2013 Feb 1;70(2):1-9. doi: 10.1001/jamapsychiatry.2013.288.
    View abstract
  2. Researchers Confirm Multiple Genes Robustly Contribute to Schizophrenia Risk in Replication Study. Virginia Commonwealth Univeristy. 2013 Apr 9.
  3. Ayalew et al. Convergent functional genomics of schizophrenia: from comprehensive understanding to genetic risk prediction. Mol Psychiatry. 2012 Sep;17(9):887-905. doi: 10.1038/mp.2012.37. Epub 2012 May 15.
    View abstract
About the Author

Walter Jessen, Ph.D. is a Data Scientist, Digital Biologist, and Knowledge Engineer. His primary focus is to build and support expert systems, including AI (artificial intelligence) and user-generated platforms, and to identify and develop methods to capture, organize, integrate, and make accessible company knowledge. His research interests include disease biology modeling and biomarker identification. He is also a Principal at Highlight Health Media, which publishes Highlight HEALTH, and lead writer at Highlight HEALTH.