Another Breakthrough Study Predicting Autism?

06 Mar 2017
MRI for babies

(Photo via Wellcome Trust)

Just a couple of weeks ago, we posted about a scientific study that produced the potential for predicting autism in high-risk infants through a combination of magnetic resonance imaging (MRI) scans, a computer program and an algorithm. Monday, a study published in the journal Biological Psychaiatry reported another potential breakthrough in predicting autism, this time by observing the amount of cerebrospinal fluid in the brains of infants.

Researchers Identify Possible Autism Biomarker

By examining the amount of cerebrospinal fluid in 6, 12 and 24 month-old infants, researchers found that it is possible to predict autism with approximately 70 percent accuracy. Of the 334 infants examined, 221 were considered high-risk because of an older sibling with autism. In those later diagnosed with autism, there was a “significantly higher” volume of cerebrospinal fluid in their brains than in those who were neurotypical. Also, the volume of cerebrospinal fluid was determined to be an indicator of the severity of a child’s autism, with those with more cerebrospinal fluid as infants showing weaker motor skills.

If our understanding of autism is compared to the solving of a puzzle, consider two more tiny pieces of that puzzle being put into place in less than a month. We are closing in on the answers that we so badly need, so continue to support scientific research in all forms. Someday soon, we will learn what causes autism, ushering-in a new frontier of research, more heavily focused on cures.



  1. That makes sense considering the abnormalities of the autisits brain. Great information! Thanks

  2. This study represents a first step in understanding how SCN2A mutations lead to autism and developmental delay, which the authors hope will both be immediately helpful to the families of patients with these mutations and also lead to better understanding of the mechanisms of ASD more generally.

  3. These studies led to the identification of 65 genes with a strong likelihood of contributing to autism when mutated and confirmed SCN2A as one of the top hits.

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