Diagnosing Autism Spectrum Disorder

1 in 59 children is diagnosed with Autism Spectrum Disorder. Symptoms include communication and interaction impairments and restrictive or repetitive behaviors. Currently, the only tool available for diagnosis is to do a behavioral assessment which means that many children in the spectrum go undiagnosed until the age of three while effective treatment is not in place until the age of four. Many signs are present before that but they are not as obvious and are often missed by physicians.

The paper “Neural correlates of face processing in etiologically-distinct 12-month-old infants at high-risk of autism spectrum disorder” explores the possibility of defining biobehavioral markers related to later emeragence of ASD. Other than furthering our understanding of how ASD works, how it affects the brain and how those changes produce characteristic behaviors, understanding the nature of neural communication in the brain of infants with ASD can be key to obtaining an early diagnosis. By examining patterns in ERPs this paper shows that there are key differences in how infants at high risk of being diagnosed with ASD such as ASIBs (infant siblings of children with ASD) and other linked disorders such as Fragile X Syndrome (60-70% children with FXS meet criteria for ASD) respond to faces and toys. The study showed that were differences between the two high-risk groups suggesting that the patterns for each group are unique. These differences in patterns found in the responses for face processing could be key in allowing children with high risk of being diagnosed later in their life to start treatment early since these differences can emerge within an infant’s first year.

The timing of treatment is crucial for the effects that it can have on the infant’s life. Age of diagnosis has remained the same for the last decade means that even with all the technology that is available, no precise method of diagnosis has provided an improvement. There is constantly more evidence signaling that earlier intervention can lead to better results in improving social skills in children with ASD. Late diagnosis does not only affect the children but also the parents that need to struggle for longer without the knowledge and proper tools on how to help their own children. This can lead to frustration from the parents which leads to a non-ideal environment for the children since support can have a significant effect on the development of children with autism. The problem is that there is not enough understanding of what the signs of ASD are. The fact that it is a spectrum means that there is great variability in the children and physicians, as well as parents, are not able to identify the early signs.

As seen on a study conducted at Newcastle University, boys tend to be diagnosed earlier than girls and infants with Asperger Syndrome. Dr. Parr and his team at Newcastle University directed a study with 2134 children and found that mostly children who were non-verbal or who communicated only through single words were diagnosed earlier. Seeing the results of this study, Jon Spiers (chief executive of Autistica, the company that provided the funds for Dr. Parr’s research) said “We need research to find ways to speed up diagnosis and to help identify those left isolated for too long, such as girls with autism” and this is exactly what Dr. Guy is doing through her research. ERPs are relatively easy to measure in children and they are also inexpensive when compared with other tests. The differences in patterns found in Dr. Guy’s research could be key in formulating a more accurate form of early diagnosis leading to a better quality of life in children with ASD.

References:

Autism diagnosis taking too long, experts say. (2016, April 01). Retrieved from https://www.sciencedaily.com/releases/2016/04/160401220659.htm

Guy, M. W., Richards, J. E., Tonnsen, B. L., & Roberts, J. E. (2018). Neural correlates of face processing in etiologically-distinct 12-month-old infants at high-risk of autism spectrum disorder. Developmental Cognitive Neuroscience,29, 61-71. doi:10.1016/j.dcn.2017.03.002