In a remarkable feat of collaboration and scale, U of T researchers have helped identify novel risk factors associated with the development of schizophrenia. Their work incorporates data from over 40,000 individuals analyzed by scientists around the globe. This multinational team of researchers makes up the working group of the Psychiatric Genomics Consortium, which seeks to examine the correlation between copy number variation (CNV) and schizophrenia.

Certain sections of the human genome are repeated more than once, and the number of times these sections are repeated varies across individuals. This variation is known as CNV. In this study, scientists looked at the association between the copy number of certain genetic factors and the presence of schizophrenia.

Dr. Christian Marshall,  co-author of the study and Assistant Professor in Laboratory Medicine and Pathobiology at U of T, said, “The biggest challenge is probably the fact that there are many groups involved.” Dr. Marshall also serves as Associate Director of genome diagnostics at The Centre for Applied Genomics at SickKids Hospital.

The “analysis was being co-led by our group and one in San Diego, with the [actual] analysis being run [in the] Netherlands. So you can imagine there needed to be lots of coordination and communication to pull everything off… and we have had biweekly [conference] calls for the last 5 years in order to make this happen,” explained Marshall.

This study is the largest of its kind and was published in Nature Genetics on November 21. Marshall described it as “a meta-analysis of many smaller studies.” By incorporating such a large number of data points, the researchers were able to identify statistically significant correlations that are otherwise hard to observe.

The study analyzed genomic data from patients and sought correlations between the frequency of certain genetic factors and the incidence of schizophrenia.

In order to effectively study CNV, scientists use a technique called DNA microarray to analyze human genome sequences. As Marshall noted, however, “there [are] many different [techniques] used for detection of copy number variants and this can lead to technical bias and potentially false associations. A major strength of the study is that we were able to… analyze [the data] in a central place… using rigorous quality control steps. Because of this standardization and the large numbers of cases and controls, we were able to… find new associations of genetic loci with schizophrenia.”

The CNV and schizophrenia working groups used these techniques to show that schizophrenia is often associated with a higher copy number for certain genes than that found in healthy individuals. This confirmed previous studies and also brought new genetic risk factors to light. The group also discovered that schizophrenia patients are more likely to have deletions in gene sets that are important for connections between neurons.

The findings in this study have important consequences for the clinical diagnosis of schizophrenia. Marshall pointed out that only approximately “5% of the schizophrenia cases that are run on clinical microarrays will have a clinically significant finding. This is obviously important for families since it establishes a reason for the disorder. I think studies like the one we did will just add to the evidence and help increase that diagnostic rate.”

The technique used in this experiment is powerful and is being used to address other disorders as well, including attention deficit hyperactivity disorder, autism spectrum disorder, and others. In fact, the methodology used in this experiment was specifically designed to be used on multiple disorders and could have important consequences for the future of psychiatric diagnoses.

Despite the success of this study, Marshall believes that there is still room to improve. “Although this was a very large study, we need to do more and in my opinion this includes analysis of even more samples so we can replicate what was found. Additionally, we need to start looking at the genome using higher resolution techniques, like whole genome sequencing, as this will help increase… understanding of the genetic underpinnings of schizophrenia.”

This study is especially important given the complexity of mental illnesses. While schizophrenia impacts around 1 per cent of Canadians, it is impossible to diagnose using simple scans for isolated biomarkers. This finding gives clinicians and researchers vital information to make accurate diagnoses.