Autism spectrum disorder (ASD) is a "blanket" diagnosis applied to individuals with vastly differing behavioral as well as co-occurring medical conditions. Using very large medical-record data sets, researchers from Rensselaer Polytechnic Institute (RPI) have found that, not only can children be broken into subgroups based upon those co-occurring conditions, but that those subgroups are also associated with differing maternal prenatal risk factors. The research is published today in the journal Autism Research.

The research, led by Juergen Hahn, the head of the Department of Biomedical Engineering at Rensselaer, builds upon his team's previous discoveries, including the development of a blood-based test for autism and prenatal risk factors for ASD.

"Autism has always been diagnosed as one condition. Through our research, we sought to determine differences within the condition," said Dr. Hahn, who is also a member of RPI's Center for Biotechnology and Interdisciplinary Studies (CBIS). "Now this work not only shows that there are subgroups of children with different co-occurring conditions, but that there are different prenatal risk factors associated with these subgroups. Given the significant differences we are seeing for risk factors, this raises the questions to what degree other aspects of ASD research would be affected by this type of subgrouping. Ultimately, diagnosis and interventions may also be influenced by the presentation of ASD and just using one medical diagnostic category for ASD may not be sufficient in the future."

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