A recent study carried out by a team from Chongqing University of Posts and Telecommunications has revealed three new types of autism in males. The investigation, published in the journal Autism Research, has used an AI algorithm to identify brain patterns in people diagnosed with ASD (Autism Spectrum Disorder), which opens new doors to the exploration of its possible and varied causes.
Three new types of autism identified using a machine learning algorithm
ASD or Autism Spectrum Disorder (ASD) affects millions of people around the world. According to data from the WHO (World Health Organization), it is estimated that one in every 100 children suffers from some type of autism, and the number affected continues to grow.
Currently, there is no truly effective cure for ASD, which means that multiple investigations are dedicated to trying to understand its functioning and causes in greater depth. The recent study carried out by the team of Professor Xinwei Li, from Chongqing University of Posts and Telecommunications, seems to have advanced the exploration of this complex disorder.
What is ASD or Autism Spectrum Disorder?
ASD or Autism Spectrum Disorder is a complex disorder that presents various symptoms related to various aspects of the person. Those affected by ASD can present everything from difficulty in social interaction to repetitive behaviors, including communication problems.
However, the diagnosis of ASD is not at all simple. To the most obvious symptoms related to learning and social interaction, others can be added, such as special sensory sensitivity and different motor and cognitive abilities. In short, it is one of the most complex disorders and difficult to diagnose properly.
On the other hand, not all people who suffer from ASD present the same difficulties, nor in the same areas. Besides, The degree of difficulty can vary considerably from one person to another; There are patients who can lead an independent life without problems, but there are also other patients whose daily life represents a real challenge.
A new look at autism
The starting point of this study is the evident limitations in the diagnosis of autism, mostly based on the clearest symptoms. This approach is not sufficient, since, as the results of the study demonstrate, two people can present the same level of social and/or cognitive difficulties and, at the same time, have a completely different brain structure.
Therefore, it is essential to keep in mind that brain biology can play an important role in the emergence of autism, beyond the obvious symptoms. The objective, in summary, is to understand in greater depth how brain structures affect the appearance and development of ASD.
As stated by the aforementioned Xiwen Li, the heterogeneity of people’s brain structures may be the key to better diagnosis and treatment of the disorder, by facilitating a deeper understanding of its functioning.
An algorithm to detect types of ASD
The research from the Chongqing University of Posts and Telecommunications was based on a data set called Autism Brain Imaging Data Exchange, which they applied to two groups: one, made up of 225 people diagnosed with ASD; another (the control group) with 255 people who did not suffer from autism.
The ages of the volunteers ranged from 10 to 20 years old, and all the people were men. The team considered this option to be more appropriate, since it is proven that ASD mainly affects men. However, the same researchers recognize that this can be a significant limitation when validating the resulting data.
Using magnetic resonance images, the brain structures of the group members were analyzed and, then, new networks were built based on the similarity of the gray matter of some specific areas of the brain. Gray matter is one of the basic elements to understand how our brain processes information. From here, they managed to divide the brain structure of the volunteers into three subtypes of ASD. which we analyze below.
The 3 new types of autism according to the study
Based on the aforementioned procedure, the researchers discovered 3 types of autism, each related to the connections of specific regions of the brain:
In addition to this, the study also indicated that people from subtype 3 obtained higher scores in verbal intelligence tests, while those from subtype 1 had greater difficulty in communication and social interaction.
All of this, points out Professor Xinwei Li, demonstrates the enormous complexity of the disorder investigated. Even more studies are required that shed light on the many questions that are still present, and that also establish groups of people with greater diversity as a basis. For example, research from Chongqing University of Posts and Telecommunications has not taken into account ASD in women, which is an important bias to be aware of.
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This article has been reviewed by our editorial team at PsychologyFor to ensure accuracy, clarity, and adherence to evidence-based research. The content is for educational purposes only and is not a substitute for professional mental health advice.
