Detecting autistic-like traits in a general population of monkeys

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Detecting autistic-like traits in a general population of monkeys

Translational animal models are a necessary step to uncovering the biological basis of human disorders like Autism Spectrum Disorder (ASD) which affects 1 in every 54 children in the United States. Kate Talbot, Ph.D. and her colleagues in the Neuroscience and Behavior Unit at the California National Research Primate Center have optimized a screening tool based on an ASD diagnostic tool used in humans to rapidly identify nonhuman primates as potential participants in translational ASD studies.

Despite its prevalence in the human population, research has yet to pinpoint a cause, early diagnostic tool, or cure for ASD. Talbot pointed out, “studying disease biology directly in ASD patients is extraordinarily difficult [and] other animal models (e.g., mice) fundamentally lack the complex social cognitive abilities that are impaired in people with autism.” Fortunately, there is a subset of rhesus monkeys within the natural population illustrating low-social behavior similar to what is observed in humans with ASD. The trick is quickly identifying enough of these animals to conduct the necessary translational research.

ASD is classified by the National Institute of Mental Health as a developmental disorder that effects communication and behavior. As a spectrum disorder, autism can present differently in symptoms and severity across individuals. This variability is part of what makes treatment of ASD more complicated; rather than a primary treatment for ASD, doctors and patients must work together to develop a specific treatment program. Research shows that early identification and treatment of ASD is crucial. Animal models of ASD could more thoroughly investigate the biology of ASD so doctors can identify and begin treatment before behavioral symptoms are apparent.

The original macaque social responsiveness scale (mSRS) was a 36-item observation-based instrument created by eliminating items related to language from the Social Responsiveness Scale originally developed for children. The original mSRS was based on a relatively small sample majorly composed of females. Due to the sample size and the fact that ASD is a particularly male biased disorder (4 males for every 1 female) the mSRS was difficult to translate to the human screening tool. Talbot and her colleagues refined the mSRS by rigorously applying it to hundreds of male rhesus macaques across their development in hopes of developing a reliable tool for translational ASD research.

Utilizing an extensive behavioral observation program at the CNPRC Talbot could compare experimenter responses to the questionnaire directly to behavioral data collected on the animals throughout their lives. The exhaustive study identified 17 items with high inter-rater reliability and intra-rater reliability that now make up the mSRS-R.

The revised tool can determine the extremes of the population 96% accuracy, That is, which monkeys qualify as particularly low-social animals and which monkeys qualify as particularly high-social compared to their peers. Low-social animals are significantly more likely to display autistic-like traits and thus are suitable for translational research. When asked about the importance of their findings Talbot replied, “This instrument will be indispensable for advancing the field’s understanding of the developmental trajectory of core autistic symptomology in rhesus and other macaque monkeys, and it can be used as a primary outcome measure in fast-fail preclinical therapeutic testing efforts.”

You can read the original research article here: https://onlinelibrary.wiley.com/doi/10.1002/aur.2335

Contributing authors: Catherine F. Talbot, Joseph P. Garner, Alyssa C. Maness, Brenda McCowan, John P. Capitanio, and Karen J. Parker
Contact Author: ctalbot@fit.edu

Financial Support: Simons Foundation (SFARI #342873 to KJP), National Institutes of Health (R01 HD087048, R24 OD011136, R24 OD010962, and P51OD011107 CNPRC base operating grant)

Post Written by Logan Savidge
lesavidge@ucdavis.edu

2021-01-06T02:03:14+00:00October 15th, 2020|