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New Study Identifies Genetic Variances Linked to Schizophrenia
Scientists from the University of North Carolina School of Medicine and colleagues have published new research seeking to advance the genetic basis of schizophrenia by identifying the genetic variances that have a causal effect in the development of the psychiatric condition.
Their findings were published in the journal Cell Genomics in September.
A team of researchers from the UNC School of Medicine, UCLA, Harvard, the University of Michigan, and Human Technopole in Italy analyzed 5000 genetic variants previously linked to a risk of schizophrenia through genome-wide association studies, attempting to single out variants with the potential for biological activity important for development schizophrenia.
The researchers used a massively parallel reporter assay (MPRA)—a genetic sequencing technique that can identify variants that trigger gene expression—by introducing the 5000 variants into in a dish with human brain cells that are essential to early brain development. The MPRA revealed 439 genetic variations with actual biological effects.
“Traditionally, scientists have used other epigenetic data, such as transcription factor binding and biochemically defined enhancers, to identify variants with biological effects,” study senior author Hyejung Won, PhD, associate professor genetics at the UNC School of Medicine, said in a news release. “However, these conventional methods failed to predict a large portion of variants we identified to have biological effects. Our work points to a wealth of unexplored variants with biological effects.”
Dr Won said the findings “propose a groundbreaking approach to decoding the cumulative effect of genetic variants on gene regulation in individuals with schizophrenia,” which could help facilitate more precise interventions and therapies that improve upon currently available medications.
“To find these 439 potentially causal variants is a big step, but we still have a lot of work ahead to figure out the complicated genetic architecture that leads an individual to develop this condition,” Dr Won said. “With that information in hand, we could begin to understand the biological mechanism underlying this complex disorder, which may eventually lead to targeted therapies.”
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