New Study Shows Potential Way To Detect Autism

In 2013, Autistic Disorder, Asperger’s Disorder and Pervasive Developmental Disorder, NOS (not otherwise specified) were rolled into one umbrella category: Autism Spectrum Disorder (ASD).

ASD is characterized by developmental delays, communication problems, abnormal social skills, learning disabilities and behavioral problems—all ranging from mild to severe. While some symptoms are apparent during infancy, most children exhibit ASD symptoms between the ages of 1 and 2.

The frequency of being diagnosed with an ASD has increased over the past few decades. Recent statistics from the Centers for Disease Control estimate that ASD affects 1 in 68 children. Currently, 1 in 42 boys and 1 in 189 girls are diagnosed with it, making boys almost 5 times more likely than girls to have this disorder.

It is now known that ASD is not caused by just one thing. Rather, this broad condition can have many different causes. Similarly, there is not just one brain problem found in ASD, but actually 8-10 factors that can influence abnormal brain function.

After decades studying brain activity patterns, we have found that people with ASD tend to have areas of high and/or low activity:

High Activity Patterns:

• Increased activity in the anterior cingulate and lateral prefrontal cortex which can be related to symptoms like getting stuck on negative thoughts, repetitious behavior and problems with transitions and change
• A “Ring of Fire” pattern – This is overall increased activity throughout the brain, which may be associated with inflammation and underlie problems related to mood stability and anxiety

Low Activity Patterns:

• Smaller, less active cerebellum, contributing to impeded or poor motor skills, thought coordination and learning problems. Normally, the cerebellum should be the most active part of the brain because it contains 50% of the brain’s neurons (nerve or brain cells)
• Decreased posterior hemisphere activity, especially in the parietal and temporal lobes, that can affect learning, communication, sensory processing and understanding abstract concepts
• Overall decreased activity and scalloping, which is associated with environmental toxicity
• Sometimes a head injury pattern is revealed

The diagnosis of Autism Spectrum Disorder (ASD) relies on history and behavioral observation, lacking reliable biomarkers. Today, researchers from Amen Clinics and the University of Southern California performed what is believed to be the largest ever analysis of brain SPECT (single photon emission computed tomography) scans, a nuclear medicine study that evaluates blood flow and activity patterns, on 928 persons with ASD obtained 9 different sites to investigate whether these scans distinguish ASD from healthy controls. The age range of patients were from 13-67 years.

Using sophisticated machine learning algorithms, high levels of separation were obtained. The areas the most predicted ASD were found in the cerebellum, anterior cingulate gyrus, amygdala, frontal and temporal lobes.

Currently, the diagnosis of ASD includes a clinical history, mental status examination and structured screening tools, leaving clinicians in the dark as to the underlying physiology. At Amen Clinics, we frequently see increased activity in the anterior cingulate, leading to obsessive behavior, and decreases in the temporal lobes and cerebellum, which are often associated with learning issues. Having SPECT scans on ASD patients has helped us better target treatment.

This is the first brain SPECT imaging study demonstrating the use of machine learning methods to predict ASD from a HC. These results add to the growing body of literature validating the use of machine learning approaches with functional neuroimaging data to improve prediction and classification of individuals with psychiatric disorders like autism. Given the heterogeneity of ASD, this approach has important implications in the clinical setting in both the diagnosis, intervention and monitoring of treatment outcomes.

Find the full article here.

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About the Author:

Daniel G. Amen, M.D. is a double board-certified psychiatrist, professor and 10-time New York Times best-selling author. He is one of the world's foremost experts on using brain imaging tools to help optimize and treat patients. He is founder of Amen Clinics, which has the world’s largest database of functional brain scans relating to behavior.