We appreciate Dr Williams comments on our recently published article (Khan et al., 2017). We thank Dr Williams for appreciating our data and interpretation and we are very grateful to the editors for providing the opportunity to clarify the points raised by Dr Williams related to our work. High-resolution metabolomics is a promising tool to aid in providing insight to answer a biological question, by documenting a set of affected endogenous metabolites (end products of cellular processes) due to the relevance of affected metabolic pathways varying according to the physiology, developmental or pathological state (Deidda et al., 2015; Dias and Koal, 2016). Metabolomics uses principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA), hierarchical clustering analysis (HCA), Heatmaps, and pairwise t test, as tools to identify the differences between the sample groups and the relevant altered metabolites connected with each group. The underlying mechanism for the health risks associated with bisphenol A (BPA) exposure are completely undefined and/or controversial, which leads to delays in identifying the potential role of BPA in pathophysiological conditions. Our work was an attempt to the use the power of metabolomics which can allow unparalleled opportunity to query the molecular mechanisms of BPA-related gender-specific health risks in children. We investigated the potential correlation of BPA exposure with alteration both in urine and serum metabolites among male and female children and showed steroidogenesis pathway and amino acid metabolism as the main targets of perturbation by BPA in preadolescent girls. Considering the BPA concentration and BMI of subjects, we performed a very careful selection of children for proceeding analysis. A total of 414 children participated in the pre-adolescence period from 2010 to 2013 (Total number of participants by age: 7 years:50; 8 years:215; 9 years of age: 49). A total of 67 subjects who were not detected for BPA concentration among the participants were excluded. A total of 347 children with detectable BPA levels were further divided into quartiles; first quartile (BPA: <6.593 μg/g_cr), second quartile (BPA: 6.593–12.341 μg/g_cr), third quartile (BPA: 12.342–28.407 μg/g_cr), and fourth quartile (BPA: >28.408 μg/g_cr). Subjects with the lowest quartile (BPA: <6.593 μg/g_cr, n = 87) and the highest quartile (BPA: >28.408 μg/g_cr n = 86) were selected. Then, each quartile group was divided into 3 groups according to BMI status, and 9 subjects were selected for low or high BMI group considering their BPA concentrations. In short, even though a total of 414 urine and serum samples were collected, only 18 children were finally included in this study. Of these 9 children were with high concentrations of BPA level (501.59 ± 237.86 mg/g_cr), whereas 9 children were with low concentrations of BPA (4.09 ± 1.75 mg/g_cr). Among low and high groups, there were equal number of male and female subjects, and we also compared the age, BMI, maternal education and economic status between groups. There was no statistically significant association between monthly income and BMI status in the fisher’s exact test (p < .05). The only significant difference among the selected subjects proceeded with metabolomic analysis, was in their urinary BPA concentration. Comparing low and high BPA males and females children in our study, it was found that female urine and serum were mainly perturbed for steroidogenesis pathway and amino acid metabolism. Therefore, in our opinion, considering our careful selection criterion of children and highly significant difference in BPA concentration, we believe that perturbation of steroidogenesis pathway and amino acid metabolism among the preadolescent girls was mainly caused by BPA. Furthermore, based on BPA difference among same aged children, PCA and heatmap significantly differentiated low BPA from high BPA urine and serum. Nonetheless, high BPA females were clearly differentiated from high BPA males, which proposed these associations were caused due to difference in their BPA levels. In addition, several key tools were considered for selection criteria of metabolites, such as variable importance in projection, p value, area under the receiver operating characteristic (ROC) curve, sensitivity, and specificity. In this way among several hundred of significant metabolites, 35 metabolites fitted to our selection criterion and were analyzed with their intensity in urine sample followed by validation in serum set (Obuchowski et al., 2004; Wang et al., 2012). These metabolites were mainly related to steroidogenesis pathway and amino acid metabolism and were specifically perturbed among high BPA preadolescent females in comparison with males. We believe that associations cannot be indexed as causation unless the associations are exceedingly strong among high BPA children, especially females. We are currently developing a more comprehensive study, using several doses of BPA in animal model that we hope will provide more mechanistic insight to the metabolic affects especially steroidogenesis pathway perturbation caused by BPA in a sex and/or dose dependent manner. We believe that our work will be a useful contribution to the field of metabolomics and toxicology, and will help to provide a foundation for further mechanistic studies focusing on steroidogenesis (molecular targets), nucleotide metabolism (lysine/tyrosine metabolism), amino acid biosynthesis (tryptophan metabolism), and also will provide further insight into gender differences for BPA-induced health hazards. REFERENCES Deidda M. , Piras C. , Bassareo P. P. , Cadeddu Dessalvi C. , Mercuro G. ( 2015 ). Metabolomics, a promising approach to translational research in cardiology . IJC Metab. Endocrine 9 , 31 – 38 . Google Scholar CrossRef Search ADS Dias D. A. , Koal T. ( 2016 ). Progress in metabolomics standardisation and its significance in future clinical laboratory medicine . EJIFCC 27 , 331 – 343 . Google Scholar PubMed Khan A. , Park H. , Lee H. A. , Park B. , Gwak H. S. , Lee H. R. , Jee S. H. , Park Y. H. ( 2017 ). Elevated metabolites of steroidogenesis and amino acid metabolism in preadolescent female children with high urinary bisphenol A levels: A high resolution metabolomics study . Toxicol. Sci . 160 : 371 – 385 . Google Scholar CrossRef Search ADS PubMed Obuchowski N. A. , Lieber M. L. , Wians F. H. Jr. ( 2004 ). ROC curves in clinical chemistry: Uses, misuses, and possible solutions . Clin. Chem. 50 , 1118 – 1125 . Google Scholar CrossRef Search ADS PubMed Wang X. , Zhang A. , Han Y. , Wang P. , Sun H. , Song G. , Dong T. , Yuan Y. , Yuan X. , Zhang M. et al. , . ( 2012 ). Urine metabolomics analysis for biomarker discovery and detection of jaundice syndrome in patients with liver disease . Mol. Cell. Proteomics 11 , 370 – 380 . Google Scholar CrossRef Search ADS PubMed © The Author(s) 2018. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please e-mail: email@example.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)
Toxicological Sciences – Oxford University Press
Published: Apr 14, 2018
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