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Placental DNA methylation changes and the early prediction of autism in full-term newborns

Autism spectrum disorder (ASD) is associated with abnormal brain development during fetal life. Overall, increasing evidence indicates an important role of epigenetic dysfunction in ASD. The placenta is critical to and produces neurotransmitters that regulate fetal brain development. We hypothesized...

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Autores principales: Bahado-Singh, Ray O., Vishweswaraiah, Sangeetha, Aydas, Buket, Radhakrishna, Uppala
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8279352/
https://www.ncbi.nlm.nih.gov/pubmed/34260616
http://dx.doi.org/10.1371/journal.pone.0253340
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author Bahado-Singh, Ray O.
Vishweswaraiah, Sangeetha
Aydas, Buket
Radhakrishna, Uppala
author_facet Bahado-Singh, Ray O.
Vishweswaraiah, Sangeetha
Aydas, Buket
Radhakrishna, Uppala
author_sort Bahado-Singh, Ray O.
collection PubMed
description Autism spectrum disorder (ASD) is associated with abnormal brain development during fetal life. Overall, increasing evidence indicates an important role of epigenetic dysfunction in ASD. The placenta is critical to and produces neurotransmitters that regulate fetal brain development. We hypothesized that placental DNA methylation changes are a feature of the fetal development of the autistic brain and importantly could help to elucidate the early pathogenesis and prediction of these disorders. Genome-wide methylation using placental tissue from the full-term autistic disorder subtype was performed using the Illumina 450K array. The study consisted of 14 cases and 10 control subjects. Significantly epigenetically altered CpG loci (FDR p-value <0.05) in autism were identified. Ingenuity Pathway Analysis (IPA) was further used to identify molecular pathways that were over-represented (epigenetically dysregulated) in autism. Six Artificial Intelligence (AI) algorithms including Deep Learning (DL) to determine the predictive accuracy of CpG markers for autism detection. We identified 9655 CpGs differentially methylated in autism. Among them, 2802 CpGs were inter- or non-genic and 6853 intragenic. The latter involved 4129 genes. AI analysis of differentially methylated loci appeared highly accurate for autism detection. DL yielded an AUC (95% CI) of 1.00 (1.00–1.00) for autism detection using intra- or intergenic markers by themselves or combined. The biological functional enrichment showed, four significant functions that were affected in autism: quantity of synapse, microtubule dynamics, neuritogenesis, and abnormal morphology of neurons. In this preliminary study, significant placental DNA methylation changes. AI had high accuracy for the prediction of subsequent autism development in newborns. Finally, biologically functional relevant gene pathways were identified that may play a significant role in early fetal neurodevelopmental influences on later cognition and social behavior.
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spelling pubmed-82793522021-07-31 Placental DNA methylation changes and the early prediction of autism in full-term newborns Bahado-Singh, Ray O. Vishweswaraiah, Sangeetha Aydas, Buket Radhakrishna, Uppala PLoS One Research Article Autism spectrum disorder (ASD) is associated with abnormal brain development during fetal life. Overall, increasing evidence indicates an important role of epigenetic dysfunction in ASD. The placenta is critical to and produces neurotransmitters that regulate fetal brain development. We hypothesized that placental DNA methylation changes are a feature of the fetal development of the autistic brain and importantly could help to elucidate the early pathogenesis and prediction of these disorders. Genome-wide methylation using placental tissue from the full-term autistic disorder subtype was performed using the Illumina 450K array. The study consisted of 14 cases and 10 control subjects. Significantly epigenetically altered CpG loci (FDR p-value <0.05) in autism were identified. Ingenuity Pathway Analysis (IPA) was further used to identify molecular pathways that were over-represented (epigenetically dysregulated) in autism. Six Artificial Intelligence (AI) algorithms including Deep Learning (DL) to determine the predictive accuracy of CpG markers for autism detection. We identified 9655 CpGs differentially methylated in autism. Among them, 2802 CpGs were inter- or non-genic and 6853 intragenic. The latter involved 4129 genes. AI analysis of differentially methylated loci appeared highly accurate for autism detection. DL yielded an AUC (95% CI) of 1.00 (1.00–1.00) for autism detection using intra- or intergenic markers by themselves or combined. The biological functional enrichment showed, four significant functions that were affected in autism: quantity of synapse, microtubule dynamics, neuritogenesis, and abnormal morphology of neurons. In this preliminary study, significant placental DNA methylation changes. AI had high accuracy for the prediction of subsequent autism development in newborns. Finally, biologically functional relevant gene pathways were identified that may play a significant role in early fetal neurodevelopmental influences on later cognition and social behavior. Public Library of Science 2021-07-14 /pmc/articles/PMC8279352/ /pubmed/34260616 http://dx.doi.org/10.1371/journal.pone.0253340 Text en © 2021 Bahado-Singh et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Bahado-Singh, Ray O.
Vishweswaraiah, Sangeetha
Aydas, Buket
Radhakrishna, Uppala
Placental DNA methylation changes and the early prediction of autism in full-term newborns
title Placental DNA methylation changes and the early prediction of autism in full-term newborns
title_full Placental DNA methylation changes and the early prediction of autism in full-term newborns
title_fullStr Placental DNA methylation changes and the early prediction of autism in full-term newborns
title_full_unstemmed Placental DNA methylation changes and the early prediction of autism in full-term newborns
title_short Placental DNA methylation changes and the early prediction of autism in full-term newborns
title_sort placental dna methylation changes and the early prediction of autism in full-term newborns
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8279352/
https://www.ncbi.nlm.nih.gov/pubmed/34260616
http://dx.doi.org/10.1371/journal.pone.0253340
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