Dental News - New study on primary dentition takes first steps toward early autism diagnosis

Dental Tribune International

Mon. 25. June 2018

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NEW YORK, U.S.: According to the Autism Society of America, more than 3.5 million Americans have some form of autism spectrum disorder. With prevalence of the disorder reportedly increasing by 6–15 percent annually over the period of 2002–2010, the need for early detection is critical. In a new study, researchers have found that a close examination of primary dentition may help with this and give an insight into the origin of the disorder.

Speaking to Dental Tribune Online, senior author of the study Dr. Manish Arora, Professor of Dentistry and of Environmental Medicine and Public Health at the Icahn School of Medicine at Mount Sinai, New York, U.S., said: “We had undertaken a study in 2016 on twins living in Sweden and found that metal uptake was different in the sibling affected by autism spectrum disorder. The strongest signal was for zinc, which was lower in the affected twin. Interestingly, this only persisted in the third trimester and for a few weeks after birth.”

For the current study, the team of researchers set out to develop an algorithm through the replication of their findings from 2016 to help with early detection. Focusing on four populations, two in the U.S. and one in the U.K., and cross-referencing them to the Swedish study, Arora and his colleagues found that it was not the concentration of metals that was the difference, but rather the rhythms of the cyclic processes underlying the metabolism of the metals that were being disrupted.

By employing two distinct classification models that used metal rhythmicity data, the researchers were then able to achieve 90 percent accuracy in classifying cases and controls, with sensitivity to autism spectrum disorder diagnosis ranging from 85 to 100 percent and specificity from 90 to 100 percent. However, despite the positive results, Arora was quick to point out that there is still a great deal of development required before any concrete markers can be set.

“The algorithm that we developed uses metal uptake signatures from the prenatal and early childhood periods to identify those health trajectories that are leading to an autism diagnosis later in life. This is not a diagnostic test, but it is a first step toward one.”

The study, titled “Dynamical features in fetal and postnatal zinc-copper metabolic cycles predict the emergence of autism spectrum disorder,” was published online in Science Advances on May 30.

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