Autism affects a large number of individuals globally. Experts have long stressed the importance of early autism diagnosis for better treatment; however, the current diagnostic tools are behavioral and not entirely predictable.
Recent research proposes a biological method approach, a first-of-its-kind that accurately predicts if a child will develop autism in later stages of life.
The worldwide estimate of individuals being diagnosed with autism is 1.5 percent and the numbers are greater in the United States, with one in 68 children being diagnosed with autism. In the USA alone, there has been a spike in autism cases and estimates show a disturbing 30 percent rise in ASD cases compared to previous years.
The Centre for Disease Control and Prevention (CDC) highlights the necessity of early detection. The current diagnosis practices and the available tools rely solely on behavioral sign detection, which is a growing concern.
A bit more about the Research
Researchers from Rensselaer Polytechnic University based out of New York have identified a new method for autism prediction using blood samples.
The team analyzed blood samples from 76 Neuro-typical children and 83 autistic children. The data was collected by Arkansas Children’s Hospital Research Institute. The children were in the age bracket of 3 to 10 years old.
The scientists are analysing and measuring the metabolite concentration that is a by-product of two metabolic processes:
- Folate One Carbon Metabolism (FOCM)
- Trans Sulfuration (TS) pathways
Historically, the above substances are altered in individuals when the risk of ASD increases. The new tool is further observed to have an accuracy of 98 percent. Further, the researchers have developed a variable statistical model that is designed to accurately classify autistic children based on their neurological status.
Hahn and team used these tools and were able to correctly identify 97.6 percent of young children who were autistic and 96.1 percent of those who were Neuro-typical.
Lead researcher and author Hahn further comments, “This level of accuracy for classification as well as severity prediction is very encouraging.”
“The method presented in this work is the only one of its kind that can classify an individual as being on the autism spectrum or as being Neuro-typical. We are not aware of any other method using any type of biomarker that can do this, much less with the degree of accuracy that we see in our work.”
The above study was led by Juergen Hahn and Daniel Howsmon and was published in PLOS computational Biology.
Hahn also notes that the research in its initial stages and stresses the importance of more research to validate the results. Further, the researchers aim to decode TS- and FOCM-based treatment that could be useful in alleviating ASD symptoms.
I am Ash and I celebrate Neurodiversity! Growing up with an elder brother with severe Autism was tough – but it has also taught me essential life lessons. I don’t believe that people with Autism are necessarily or have any disorder (except in extreme cases). They are just different! And that is something to be proud of! I am passionate about helping other families who may have Autism conditions in their family. So please reach out and drop me a note. I will be glad to help 🙂
