Using this next-generation RNA sequencing, a team from UCLA believes that it’s identified some striking similarities between the patterns of gene expression found in the brains of people who suffered from five different psychiatric conditions: autism, schizophrenia, bipolar disorder, major depressive disorder, and alcohol abuse disorder.
The UCLA researchers sequenced messenger RNA from 700 postmortem brains of individuals diagnosed with one of the major psychiatric disorders and compared the expression levels of 10,000 genes against those found in healthy brains. The analysis revealed significant genetic overlap between the conditions and may point the way to more targeted treatments, according to a paper published in the journal Science.
Michael Gandal isan assistant professor of psychiatry and biobehavioral sciences at UCLA and lead author of the RNA sequencing paper. He told Seeker that the big question researchers are trying to answer is how genetic variations work from a biological standpoint. What are the underlying mechanisms that increase risk for disorders like autism or schizophrenia?
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The answers may lie in the transcriptome, a term that describes the entire set of genes in an organism and their different expression levels. If the genome is the blueprint, the transcriptome is how those instructions are put into action.
In the study, Gandal and his colleague Daniel Geschwind, director of the UCLA Center for Autism Research and Treatment, were specifically analyzing the transcriptome of the brain. With RNA sequencing, they could see which specific genes in affected brains were expressed at higher levels (upregulated) and lower levels (downregulated) than healthy brains from the same population demographic.
When examined from a “10,000-foot view,” patterns and clusters began to emerge in the data, said Gandal. Genes associated with neuronal and synaptic processes, for example, were downregulated in the brains of people with autism, schizophrenia, and bipolar disorder.
“Our study was able to look in human brain tissue and show that there are reproducible patterns in the brain tissue itself that we think reflects the genetic risk for disease,” said Gandal. “This can give us a sense for what we think might be the primary pathology in these different disorders, at least in terms of how these genetic risk factors are playing out in the brain.”
While it’s too early to link patterns of gene expression to specific symptoms of psychiatric illnesses, Gandal said that his team is already using the RNA cluster data to explore potential targets for treatment.
For example, their RNA sequencing analysis showed that autism alone was associated with an upregulation of the genes that control for microglial cells, a cell that functions as a first responder in the brain’s immune system. Overexpression of microglia could lead to inflammation, which may contribute to some of the cognitive and behavioral impairments associated with autism.
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To test this theory, Gandal and his UCLA colleagues have launched a proof-of-concept trial for adults with autism. Using brain imaging, they will measure inflammation in the brain, then treat the subjects with an anti-inflammatory antibiotic for 12 weeks.
“And while that’s happening, we’ll be measuring a whole host of cognitive and behavioral symptoms to see if we can potentially intervene on this genetic signature and what the functional and clinical consequences may be,” said Gandal.
To be clear, this inflammation approach is treating one symptom of a psychiatric disorder, not going after the underlying genetic variation. Gandal said using gene therapy or genetic editing to tweak gene expression on an RNA level would be “quite challenging,” since psychiatric illnesses are an accumulation of complex traits with thousands of genetic variants.
“To use a gene therapy approach would require potentially intervening on dozens to hundreds of very small-effect-size variants, which I don’t think at the moment is something that’s really feasible,” said Gandal.