Dr. Paul Curtin along with his colleagues from Icahn School of Medicine at Mount Sinai in New York City have discovered that autism spectrum disorder (ASD) can be predicted in advance, by looking at zinc and copper metabolic cycles in a baby’s teeth. This discovery could lead to the development of novel diagnostic tools with a 90% accuracy level.

By directly measuring the uptake of elements with the help of novel tooth-matrix biomarkers, the research team found that autism prone kids had disrupted zinc-copper rhythmicity during prenatal or in their earliest months after birth.  

Dr. Paul Curtin said, "We looked at the naturally shed teeth of children and explored them much as you would explore the growth rings of a tree, using them as a sort of retrospective biomarker to see what children were exposed to in the womb and in early life. When we derived measures of metabolic cycles and used machine-learning algorithms to predict which children would develop autism, we found out we were 90% accurate in our predictions."

Prenatal and new-born babies form a new tooth layer every day, which provides information about the chemicals circulating in the body and updates the exposure records. Zinc and copper pathways are considered as the central regulators of multiple metals. If there arises any disruption in the zinc and copper pathways, the metabolism of other essential elements and toxic metals would be affected.

Curtin said, "These cycles haven't been well documented in the past; here we are showing they are critical to neurodevelopment and when they are disrupted, we find that disruption is linked to autism and in fact, can be used to predict autism." He further added, "With this research, we are shifting the focus to looking at metabolic cycles to understand how children are processing nutrients, as opposed to just looking at their exposure to toxicants."