ArticleBiological trace element research2026
Hair Elemental Homeostasis in Uruguayan Children with Autism Spectrum Disorder: A Multielement Biomonitoring Study.
Article in Biological trace element research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Hair elemental homeostasis has emerged as a potential source of information for understanding the interactions between environmental exposure, nutrition, and neurodevelopment in autism spectrum disorder (ASD). This study characterized the multielement hair profile of Uruguayan children with ASD and neurotypical (NT) controls using a multivariate biomonitoring approach. Scalp hair samples were collected from 223 children (127 ASD and 96 NT), digested by microwave-assisted acid digestion, and analyzed by microwave-induced plasma optical emission spectrometry for the determination of Al, Ba, Ca, Cr, Fe, Mg, Mn, Ni, Pb, and Zn. Global differences were evaluated by permutation-based multivariate analysis of variance (PERMANOVA), followed by univariate analyses with false discovery rate correction and principal component analysis (PCA). Significant differences were observed between the overall hair elemental profiles of ASD and NT children (PERMANOVA, pseudo-F = 5.83, R²=0.0257, p < 0.001). Children with ASD exhibited higher hair concentrations of Al, Cr, and Pb, whereas Ba, Ca, and Mg were higher in NT controls. No significant differences were found for Fe, Mn, Ni, or Zn. Biological sex represented the strongest determinant of hair elemental profile (R²=0.081, p < 0.001), whereas dietary restrictions, psychotropic medication use, and ASD support level showed limited or no independent influence. Beyond identifying subtle alterations in elemental homeostasis associated with ASD, this work provides the first comprehensive dataset of hair elemental concentrations in Uruguayan children and establishes a baseline for future biomonitoring studies. These findings demonstrate that multielement hair analysis combined with multivariate statistics is a valuable approach for investigating elemental homeostasis in childhood.
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