AsianScientist (Sep. 8, 2017) – Scientists in Japan have identified a rare mutation that could be used to predict of schizophrenia and autism. They published their work in the journal Translational Psychiatry.
Huntington’s disease, cystic fibrosis and muscular dystrophy are all diseases that can be traced to a single mutation. Diagnosis in asymptomatic patients for these diseases is relatively simple—a specific mutation predicts risk of disease. Complex diseases such as some neurodevelopmental disorders, on the other hand, do not have a clear mutational footprint.
In this study, a team of scientists led by Professor Toshihide Yamashita of Osaka University conducted a statistical analysis of the CX3CR1 gene in over 7,000 schizophrenia and autism patients and healthy subjects. In the brain, CX3CR1 is only expressed in microglia, and mutations in this receptor are known to affect synapse connectivity and cause abnormal social behavior in mice. The scientists identified one mutant candidate, a single amino acid switch from alanine to threonine, as a potential marker for prediction.
“Rare variants alter gene function but occur at a low frequency in a population. They are of high interest for the study of complex diseases that have no clear mutational cause,” said Yamashita, who added that the alanine threonine substitution was a rare variant.
The structure of CX3CR1 includes a domain known as Helix 8, which is important for initiating a signaling cascade. Computer models showed that one amino acid change is enough to compromise the signaling.
“The variant changes the region from hydrophobic to hydrophilic and destabilizes Helix 8. We overexpressed the mutant gene in cells and found that Akt signaling was disrupted,” explained Yamashita.
According to Yamashita, the findings are the first to connect a genetic variation in microglia with neurodevelopment disorders. Moreover, he hopes that the discovery could become a basis for predictive diagnostics.
“There is no reliable way to diagnose schizophrenia or autism in asymptomatic patients. A deeper understanding of the genetic risk factors will help us develop preventive measures.”
Source: Osaka University; Photo: Shutterstock.
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