Autism is grabbing all kinds of headlines this week, with a major study by UC Davis MIND Institute finding a correlation between maternal diabetes and obesity and a child having an autism spectrum disorder (ASD) or other developmental disorder.
In the study, currently published online at Pediatrics, diabetic or obese moms were 67 percent more likely to have a child with ASD or other developmental disorder than normal-weight mothers without diabetes or hypertension.
Moreover, the children of such mothers were 'more disabled,' that is, showed "greater deficits in language comprehension and production and adaptive communication" than those born to healthy mothers. All exhibited social impairments.
"Over a third of U.S. women in their childbearing years are obese, and nearly one-tenth have gestational or type 2 diabetes during pregnancy," said Paula Krakowiak, a PhD Candidate in Epidemiology affiliated with the MIND Institute. "And while the study does not conclude that diabetes and obesity cause ASD and developmental delays, it suggests that fetal exposure to elevated glucose and maternal inflammation levels adversely affect fetal development."
It is thought that poorly regulated maternal glucose can result in chronic fetal exposure to high levels of insulin, which in turn may result in depleted oxygen and iron supply for the fetus, thereby affecting fetal brain development.
This, at a time when incidences of autism are at record highs -- 1 out of every 88 children -- according to the latest figures released by U.S. Centers for Disease Control and Prevention. This, at a time when the diagnostic definition of autism (Diagnostic and Statistical Manual of Mental Disorders (DSM-5)) is about to be revised, with a drastic drop estimated for said figures by 2013.
Clearly the need to find accurate diagnostic testing is crucial. That's why Dennis Wall, an associate professor at the Center for Biomedical Informatics at Harvard Medical School, has been beavering away to come up with new testing, now published online at Translational Psychiatry.
The algorithms combine a brief set of questions and a short home video of the subject, to allow for faster, more accurate assessments. Wall estimates that the online testing will cut the lengthy waiting time for diagnosis by some 95 per cent. The tool will help parents determine early on whether intervention may be needed.
"We believe this approach will make it possible for more children to be accurately diagnosed during the early critical period when behavioural therapies are most effective," said Wall.