Brain Changes at 6 Months of Age Linked to Autism

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Back in the 1990s, researchers first started noticing that children with autism had larger brains than those without the condition. Specifically, retrospective studies following 2-year-old children at age 4 have shown increased head circumference and brain volume.

Based on these observations, it was hypothesized that brain growth could somehow be used as a biomarker for early identification of autism in infants. (A biomarker is a blend of the words “biological” and “marker” and refers to objective indications or signs that can be measured in accurate and reproducible ways.) However, the timing of brain enlargement and the relationship between this phenomenon and behavioral changes typical of autism spectrum disorder (ASD) remained unknown.

Research published in the journal Nature shows that brain changes leading to brain overgrowth begin as early as age 6 months in children later diagnosed with autism. This research suggests that early diagnostic imaging (i.e., magnetic resonance imaging or MRI) in children at high-risk of developing autism may help predict a future diagnosis of this condition.

Autism Spectrum Disorder Examined

Autism spectrum disorder refers to a wide range of clinical symptoms, skills, and levels of disability. Here are some common characteristics indicative of autism:

  • Difficulty communicating with others
  • Difficulty interacting with others
  • Limited interests or activities
  • Repetitive behaviors
  • Stereotyped interests
  • Preoccupation with objects or parts of objects
  • Lack of spontaneity
  • Impairments in eye-to-eye gaze, facial expression, and body posture
  • Unusual sensitivity to the inanimate environment
  • Difficulty with social functioning, work, and personal life

These symptoms typically begin to manifest around 2 years of age—before this time, autism isn’t definitively diagnosed. In other words, children who end up being diagnosed with ASD between 2 and 3 years of age don’t usually appear to have ASD before the first year of life.

Some people with autism experience only mild impairment, such as those with Asperger syndrome who are often described as “high functioning.” Other people with autism experience severe disability. Twenty percent or more of children with autism go on to live self-sufficient and independent lives. Positive prognostic signs include the ability to communicate using speech by age five or six and normal nonverbal skills.

Although there is neither a cure nor a medication specifically for autism, certain treatments can help improve functioning and mitigate symptoms. Treatment requires input from several types of health professionals and focuses on social, language, and adaptive (self-help) skills.

The U.S Centers for Disease Control and Prevention (CDC) estimates that one in 68 children has been identified with ASD, and these conditions affect people from all races, ethnicities, and socioeconomic backgrounds. ASD is about 4.5 times more likely in boys than it is in girls. In those infants at high risk or those with an older sibling with ASD, chances of developing the condition jump to one in five.

Although certain rare mutations have been linked to the development of autism, most incidences can’t be traced back to identify genetic risk factors or specific mutations. Consequently, there’s been great recent interest in the development of non-genetic diagnostic tools to shed light on ASD.

Potential Role of Early Brain Scans in ASD

In the Nature study referenced above, researchers used MRI to scan the brains of 106 high-risk infants for brain changes. These high-risk infants also had older siblings with ASD. The infants were scanned at six, 12, and 24 months. Additionally, the researchers scanned the brains of 42 infants at low risk for ASD.

Fifteen of the high-risk infants were later diagnosed with ASD at 2 years of age. In these infants, brain changes began to show between 6 and 12 months of age. Furthermore, these changes were followed by brain overgrowth between 12 and 24 months. More specifically, the researchers showed that between 6 and 12 months of age, there was a hyper-expansion of cortical surface areas of the occipital and, to a lesser extent, temporal and frontal lobes of the brain. The growth of the cortical surface area is a measure of the size of the folds on the outside of the brain. And the occipital lobe is involved in the processing of sensory information. 

These changes in the surface area of the cortex were linked to later brain overgrowth and ultimately social deficits in children diagnosed with ASD at two years of age. Furthermore, this pattern of hyper-expansion resembles a normal, albeit more restrained, increase in the cortical surface area seen in infants without autism.

According to the researchers:

“Prediction models developed from behaviourally based algorithms during infancy have not provided sufficient predictive power to be clinically useful. We found that a deep-learning algorithm primarily using surface area information from brain MRI at 6 and 12 months of age-predicted the 24-month diagnosis of autism in children at high familial risk for autism.”

Using the deep-learning algorithm, the researchers suggest that they can predict autism in eight of 10 infants at high-risk for this condition.


Without a doubt, the results of this brain-scan study are exciting and potentially game-changing. Again, according to the researchers:

“This finding may have implications for early detection and intervention, given that this period is before consolidation of the defining features of ASD and the typical age for diagnosis. The latter part of the first and early second years of life are characterized by greater neural plasticity relative to later ages and is a time when the social deficits associated with autism are not yet well established. Intervention at this age may prove more efficacious than later in development.”

In other words, the researchers suggest that their algorithm could pave the way for earlier detection and earlier intervention in high-risk infants—interventions that could prove more effective because the infant's brain is much more mutable and adaptable. Earlier intervention could also help scientists better test interventions and see if a treatment is working much earlier on than previously possible.

Currently, it is unknown whether early intervention can improve long-term clinical outcomes in patients with autism. However, many experts support the idea that such early interventions offer treatment despite a lack of research in the field.

Notably, results from the Parent Autism Communication Trial (PACT)—the largest and longest study of autism interventions so far—support that teaching parents of children with autism how to better interact with their children provides benefits that can extend for years.

However, these training interventions were focused on parents of children with core autism aged between 2 and 4 years and not the children themselves. Furthermore, the effects of these interventions decreased over time and were substantially questionable. Instead of lessening anxiety, the PACT intervention decreased repetitive behaviors and improved communication skills.

It should be noted that the brain-scan study examines infants at high-risk of developing ASD and not the larger population of children with ASD who don’t have older siblings with the condition. Nevertheless, this work does provide proof of concept that could later be applied to others at risk for ASD. In order to be applied to the general population, however, development of a “growth-chart for the brain” that has wide applicability would have to be realized—something that’s ostensibly far off.

Moreover, before these findings have clinical applicability, large follow-up studies need to be performed to support these research findings. Future research should also examine whether the potential of the current study’s algorithm can be combined with other types of predictors, including behavior, electrophysiology, molecular genetics, and other imaging modalities, such as whole brain functional MRI. Of note, as mentioned earlier, we have not yet elucidated genetic mutations responsible for the vast majority of autism cases. However, the analysis of such genetic factors remains an active area of research and interest to many.

Finally, differences in MRI scanners and data-extraction methods could make replication of these findings difficult. In other words, MRI scanners are different and these differences could make it hard to replicate subtle, yet significant, changes observed in the current study.

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Article Sources

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