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Metabolomics and Communication Skills Development in Children; Evidence from the Ages and Stages Questionnaire
We hypothesized metabolomic profiling could be utilized to identify children who scored poorly on the communication component of the Ages and Stages Questionnaire (ASQ); which assesses development in childhood, and to provide candidate biomarkers for autism spectrum disorders (ASD). In a population...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6468693/ https://www.ncbi.nlm.nih.gov/pubmed/30841573 http://dx.doi.org/10.3390/metabo9030042 |
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author | Kelly, Rachel S. Boulin, Adrianna Laranjo, Nancy Lee-Sarwar, Kathleen Chu, Su H. Yadama, Aishwarya P. Carey, Vincent Litonjua, Augusto A. Lasky-Su, Jessica Weiss, Scott T. |
author_facet | Kelly, Rachel S. Boulin, Adrianna Laranjo, Nancy Lee-Sarwar, Kathleen Chu, Su H. Yadama, Aishwarya P. Carey, Vincent Litonjua, Augusto A. Lasky-Su, Jessica Weiss, Scott T. |
author_sort | Kelly, Rachel S. |
collection | PubMed |
description | We hypothesized metabolomic profiling could be utilized to identify children who scored poorly on the communication component of the Ages and Stages Questionnaire (ASQ); which assesses development in childhood, and to provide candidate biomarkers for autism spectrum disorders (ASD). In a population of three-year-old children, 15 plasma metabolites, were significantly (p < 0.05) different between children who were categorized as having communication skills that were “on schedule” (n = 365 (90.6%)) as compared to those “requiring further monitoring/evaluation” (n = 38 (9.4%)) according to multivariable regression models. Five of these metabolites, including three endocannabinoids, were also dysregulated at age one (n = 204 “on schedule”, n = 24 “further monitoring/evaluation”) in the same children. Stool metabolomic profiling identified 11 significant metabolites. Both the plasma and stool results implicated a role for tryptophan and tyrosine metabolism; in particular, higher levels of N-formylanthranilic acid were associated with an improved communication score in both biosample types. A model based on the significant plasma metabolites demonstrated high sensitivity (88.9%) and specificity (84.5%) for the prediction of autism by age 8. These results provide evidence that ASQ communication score and metabolomic profiling of plasma and/or stool may provide alternative approaches for early diagnosis of ASD, as well as insights into the pathobiology of these conditions. |
format | Online Article Text |
id | pubmed-6468693 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64686932019-04-22 Metabolomics and Communication Skills Development in Children; Evidence from the Ages and Stages Questionnaire Kelly, Rachel S. Boulin, Adrianna Laranjo, Nancy Lee-Sarwar, Kathleen Chu, Su H. Yadama, Aishwarya P. Carey, Vincent Litonjua, Augusto A. Lasky-Su, Jessica Weiss, Scott T. Metabolites Article We hypothesized metabolomic profiling could be utilized to identify children who scored poorly on the communication component of the Ages and Stages Questionnaire (ASQ); which assesses development in childhood, and to provide candidate biomarkers for autism spectrum disorders (ASD). In a population of three-year-old children, 15 plasma metabolites, were significantly (p < 0.05) different between children who were categorized as having communication skills that were “on schedule” (n = 365 (90.6%)) as compared to those “requiring further monitoring/evaluation” (n = 38 (9.4%)) according to multivariable regression models. Five of these metabolites, including three endocannabinoids, were also dysregulated at age one (n = 204 “on schedule”, n = 24 “further monitoring/evaluation”) in the same children. Stool metabolomic profiling identified 11 significant metabolites. Both the plasma and stool results implicated a role for tryptophan and tyrosine metabolism; in particular, higher levels of N-formylanthranilic acid were associated with an improved communication score in both biosample types. A model based on the significant plasma metabolites demonstrated high sensitivity (88.9%) and specificity (84.5%) for the prediction of autism by age 8. These results provide evidence that ASQ communication score and metabolomic profiling of plasma and/or stool may provide alternative approaches for early diagnosis of ASD, as well as insights into the pathobiology of these conditions. MDPI 2019-03-05 /pmc/articles/PMC6468693/ /pubmed/30841573 http://dx.doi.org/10.3390/metabo9030042 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kelly, Rachel S. Boulin, Adrianna Laranjo, Nancy Lee-Sarwar, Kathleen Chu, Su H. Yadama, Aishwarya P. Carey, Vincent Litonjua, Augusto A. Lasky-Su, Jessica Weiss, Scott T. Metabolomics and Communication Skills Development in Children; Evidence from the Ages and Stages Questionnaire |
title | Metabolomics and Communication Skills Development in Children; Evidence from the Ages and Stages Questionnaire |
title_full | Metabolomics and Communication Skills Development in Children; Evidence from the Ages and Stages Questionnaire |
title_fullStr | Metabolomics and Communication Skills Development in Children; Evidence from the Ages and Stages Questionnaire |
title_full_unstemmed | Metabolomics and Communication Skills Development in Children; Evidence from the Ages and Stages Questionnaire |
title_short | Metabolomics and Communication Skills Development in Children; Evidence from the Ages and Stages Questionnaire |
title_sort | metabolomics and communication skills development in children; evidence from the ages and stages questionnaire |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6468693/ https://www.ncbi.nlm.nih.gov/pubmed/30841573 http://dx.doi.org/10.3390/metabo9030042 |
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