Earlier detection of autism, relying on markers in the blood, may help more children to take advantage of helpful behavioral therapies.
Diagnosing autism currently requires hours of observation by clinicians and a far from objective series of behavioral measures, but improvements in genetic testing could make the process more efficient.
In a study published in the journal PLOS ONE, researchers from Children's Hospital Boston describe a new experimental test to detect the developmental disorder, based on the differences in gene expression between kids with autism spectrum disorder (ASD) and those without the condition.
The blood-based test appears to predict autism relatively accurately, at least among boys, and has already been licensed to a company, SynapDx, for commercial development. In an e-mail statement to TIME, a spokeswoman for SynapDx said the company plans to start clinical trials of the new test in early 2013.As is so often the case, however, the actual research is much more tentative than the media coverage would suggest. In "Characteristics and Predictive Value of Blood Transcriptome Signature in Males with Autism Spectrum Disorders," Sek Won Kong and colleagues are pretty careful. From the abstract:
Our result suggests that the use of blood expression profiling for ASD detection may be feasible. Further study is required to determine the age at which such a test should be deployed, and what genetic characteristics of ASD can be identified.And from the conclusion:
In conclusion, this study of children with ASD describes a gene expression signature that shows promising accuracy in classifying children with ASD from controls. The ability of the ASD55 predictor to correctly classify ASD samples compares favorably to the DNA-based tests currently proposed for ASD diagnosis. The results presented here raise further questions that bear investigation but are outside this study's scope: At what age does this ASD55 signature manifest? Is it present at birth? Finally, we expect that larger studies can be used to determine whether particular characteristics of ASD can be classified or predicted from a gene expression signature (e.g. seizures and language delay) and thereby improve individualized treatment in the near future.