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:	Ray O Bahado-Singh, Sangeetha Vishweswaraiah, Buket Aydas, Uppala Radhakrishna
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/5664f392ed594656b803784aa3ab2aa2
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spelling	oai:doaj.org-article:5664f392ed594656b803784aa3ab2aa22021-12-02T20:05:03ZPlacental DNA methylation changes and the early prediction of autism in full-term newborns.1932-620310.1371/journal.pone.0253340https://doaj.org/article/5664f392ed594656b803784aa3ab2aa22021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0253340https://doaj.org/toc/1932-6203Autism 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.Ray O Bahado-SinghSangeetha VishweswaraiahBuket AydasUppala RadhakrishnaPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 7, p e0253340 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ray O Bahado-Singh Sangeetha Vishweswaraiah Buket Aydas Uppala Radhakrishna Placental DNA methylation changes and the early prediction of autism in full-term newborns.
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.
format	article
author	Ray O Bahado-Singh Sangeetha Vishweswaraiah Buket Aydas Uppala Radhakrishna
author_facet	Ray O Bahado-Singh Sangeetha Vishweswaraiah Buket Aydas Uppala Radhakrishna
author_sort	Ray O Bahado-Singh
title	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_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_sort	placental dna methylation changes and the early prediction of autism in full-term newborns.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/5664f392ed594656b803784aa3ab2aa2
work_keys_str_mv	AT rayobahadosingh placentaldnamethylationchangesandtheearlypredictionofautisminfulltermnewborns AT sangeethavishweswaraiah placentaldnamethylationchangesandtheearlypredictionofautisminfulltermnewborns AT buketaydas placentaldnamethylationchangesandtheearlypredictionofautisminfulltermnewborns AT uppalaradhakrishna placentaldnamethylationchangesandtheearlypredictionofautisminfulltermnewborns
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Placental DNA methylation changes and the early prediction of autism in full-term newborns.

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