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Publication - Dr Dheeraj Rai

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


    Curtin, P, Austin, C, Curtin, A, Gennings, C, Arora, M, , Tammimies, K, Willfors, C, Berggren, S, Siper, P, Rai, D, Meyering, K, Kolevzon, A, Mollon, J, David, AS, Lewis, G, Zammit, S, Heilbrun, L, Palmer, RF, Wright, RO, Bölte, S & Reichenberg, A, 2018, ‘Dynamical features in fetal and postnatal zinc-copper metabolic cycles predict the emergence of autism spectrum disorder’. Science Advances, vol 4.


    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

    Full details in the University publications repository