Genomic Analysis Yields Link Between Gene Networks, Schizophrenia Types

Schizophrenia comprises a group of related disorders that present with distinct clinical syndromes, and those syndromes now appear to be associated with eight separate networks of genetic mutations.

That’s the finding from a remarkable genetic analysis titled “Uncovering the Hidden Risk Architecture of the Schizophrenias: Confirmation in Three Independent Genome-Wide Association Studies” posted September 15 in AJP in Advance.

In a large genomewide association study of patients with schizophrenia and controls, researchers with the Molecular Genetics of Schizophrenia Consortium (an international group of researchers) examined single nucleotide polymorphisms (SNPs) that grouped or clustered together and assessed the risk for schizophrenia, comparing the DNA of 4,200 people with schizophrenia with that of 3,800 people without schizophrenia. They also looked at relationships between the SNP clusters and various ways that patients present symptomatically across three separate studies.

Claude Robert Cloninger, M.D., of Washington University School of Medicine and an author of the study, explained that the methods used in the study break new ground.

“Previous work on the genetics of schizophrenia had been able to measure only the extent to which individual genes contribute to the risk of schizophrenia, but the results have always been inconsistent from study to study and weak,” he said. “These studies were flawed in three major ways—they failed to consider the interactions of genes that have different effects depending on other genes with which they are combined; they failed to distinguish clinical variability among people with schizophrenia, which clinicians know varies widely in severity and symptoms; and they considered average effects of variables in groups of subjects, rather than focusing on what happens in individual people. All these points are critically important to psychiatrists because we treat individuals and need to distinguish the specific features that help us recognize that patients may have different causes of their illness and require different treatments.”

Cloninger and colleagues used pattern-recognition techniques from bioinformatics that he said are powerful in identifying the underlying components that are hidden in complex data. They identified 42 SNP sets associated with a 70 percent or greater risk of schizophrenia and confirmed 34 (81 percent) or more in two independent samples. These SNP sets, or genotypic networks, were linked to the different ways that patients present with schizophrenia, yielding eight distinct clinical syndromes varying in symptoms and severity.

“We found that these SNPs were markers for distinct sets of genes that influence brain development and neuronal signaling,” Cloninger told Psychiatric News. “Next we observed that the different sets of genes were strongly associated with distinct sets of clinical features. We could group these sets of clinical features into eight classes or subtypes of schizophrenia varying in severity and in combinations of positive and negative symptoms. This led us to conclude that schizophrenia was not one disease but really at least eight distinct disorders associated with different genes and distinct clinical features.

“We repeated the analysis in two independent samples with very strong and consistent results in all three,” he said.

Cloninger said the results have implications for early identification and possibly for prevention. “Our results provide the basis for a reliable diagnostic test for susceptibility to schizophrenia, which provides an opportunity for early detection of risk and interventions to promote health and well-being by targeting both the genes that are causal and providing experiences that could prevent illness or improve health,” he said.

“We found that some genetic pathways increasing susceptibility involved deficient control of healthy brain development, and other pathways involved increased susceptibility to brain injury and toxicity. Regulation of the plasticity of glutamate receptors was important in some classes of schizophrenia and not others.

“We are now able to focus on treatments appropriate for specific patients and soon should be able to provide a clinically practical test procedure that measures the genetic risk factors that lead to the diagnosis. That will allow us to tailor treatment to the causes of the disorder in individuals rather than just treat symptoms. Personalized treatment of the causes of illness should lead to stronger treatments with better clinical outcomes.” ■

“Uncovering the Hidden Risk Architecture in the Schizophrenias: Confirmation in Three Independent Genome-Wide Association Studies” can be accessed here.