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Sci Adv. 2018 May 30;4(5):eaat1293. doi: 10.1126/sciadv.aat1293. eCollection 2018 May.

Dynamical features in fetal and postnatal zinc-copper metabolic cycles predict the emergence of autism spectrum disorder.

Author information

1
Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1057, New York, NY 10029, USA.
2
Center of Neurodevelopmental Disorders, Division of Neuropsychiatry, Department of Women's and Children's Health, Karolinska Institutet, Floor 8, Gävlegatan 22, SE-11330 Stockholm, Sweden.
3
Child and Adolescent Psychiatry, Center for Psychiatry Research, Stockholm County Council, Norra Stationsgatan 69, Plan 7, SE-11364 Stockholm, Sweden.
4
Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
5
Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
6
Centre for Academic Mental Health, School of Social and Community Medicine, University of Bristol, Bristol, England.
7
Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, England.
8
Division of Psychiatry, Faculty of Brain Sciences, University College London, Maple House, London, England.
9
Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neuroscience, Cardiff University, Cardiff, Wales.
10
Family and Community Medicine, School of Medicine, University of Texas Health Sciences Center, San Antonio, TX 78229, USA.

Abstract

Metals are critical to neurodevelopment, and dysregulation in early life has been documented in autism spectrum disorder (ASD). However, underlying mechanisms and biochemical assays to distinguish ASD cases from controls remain elusive. In a nationwide study of twins in Sweden, we tested whether zinc-copper cycles, which regulate metal metabolism, are disrupted in ASD. Using novel tooth-matrix biomarkers that provide direct measures of fetal elemental uptake, we developed a predictive model to distinguish participants who would be diagnosed with ASD in childhood from those who did not develop the disorder. We replicated our findings in three independent studies in the United States and the UK. We show that three quantifiable characteristics of fetal and postnatal zinc-copper rhythmicity are altered in ASD: the average duration of zinc-copper cycles, regularity with which the cycles recur, and the number of complex features within a cycle. In all independent study sets and in the pooled analysis, zinc-copper rhythmicity was disrupted in ASD cases. In contrast to controls, in ASD cases, the cycle duration was shorter (F = 52.25, P < 0.001), regularity was reduced (F = 47.99, P < 0.001), and complexity diminished (F = 57.30, P < 0.001). With two distinct classification models that used metal rhythmicity data, we achieved 90% accuracy in classifying cases and controls, with sensitivity to ASD diagnosis ranging from 85 to 100% and specificity ranging from 90 to 100%. These findings suggest that altered zinc-copper rhythmicity precedes the emergence of ASD, and quantitative biochemical measures of metal rhythmicity distinguish ASD cases from controls.

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