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Network-Based Integrative Analysis of Genomics, Epigenomics and Transcriptomics in Autism Spectrum Disorders

Current studies suggest that autism spectrum disorders (ASDs) may be caused by many genetic factors. In fact, collectively considering multiple studies aimed at characterizing the basic pathophysiology of ASDs, a large number of genes has been proposed. Addressing the problem of molecular data inter...

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Autores principales: Di Nanni, Noemi, Bersanelli, Matteo, Cupaioli, Francesca Anna, Milanesi, Luciano, Mezzelani, Alessandra, Mosca, Ettore
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6651137/
https://www.ncbi.nlm.nih.gov/pubmed/31323926
http://dx.doi.org/10.3390/ijms20133363
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author Di Nanni, Noemi
Bersanelli, Matteo
Cupaioli, Francesca Anna
Milanesi, Luciano
Mezzelani, Alessandra
Mosca, Ettore
author_facet Di Nanni, Noemi
Bersanelli, Matteo
Cupaioli, Francesca Anna
Milanesi, Luciano
Mezzelani, Alessandra
Mosca, Ettore
author_sort Di Nanni, Noemi
collection PubMed
description Current studies suggest that autism spectrum disorders (ASDs) may be caused by many genetic factors. In fact, collectively considering multiple studies aimed at characterizing the basic pathophysiology of ASDs, a large number of genes has been proposed. Addressing the problem of molecular data interpretation using gene networks helps to explain genetic heterogeneity in terms of shared pathways. Besides, the integrative analysis of multiple omics has emerged as an approach to provide a more comprehensive view of a disease. In this work, we carry out a network-based meta-analysis of the genes reported as associated with ASDs by studies that involved genomics, epigenomics, and transcriptomics. Collectively, our analysis provides a prioritization of the large number of genes proposed to be associated with ASDs, based on genes’ relevance within the intracellular circuits, the strength of the supporting evidence of association with ASDs, and the number of different molecular alterations affecting genes. We discuss the presence of the prioritized genes in the SFARI (Simons Foundation Autism Research Initiative) database and in gene networks associated with ASDs by other investigations. Lastly, we provide the full results of our analyses to encourage further studies on common targets amenable to therapy.
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spelling pubmed-66511372019-08-07 Network-Based Integrative Analysis of Genomics, Epigenomics and Transcriptomics in Autism Spectrum Disorders Di Nanni, Noemi Bersanelli, Matteo Cupaioli, Francesca Anna Milanesi, Luciano Mezzelani, Alessandra Mosca, Ettore Int J Mol Sci Article Current studies suggest that autism spectrum disorders (ASDs) may be caused by many genetic factors. In fact, collectively considering multiple studies aimed at characterizing the basic pathophysiology of ASDs, a large number of genes has been proposed. Addressing the problem of molecular data interpretation using gene networks helps to explain genetic heterogeneity in terms of shared pathways. Besides, the integrative analysis of multiple omics has emerged as an approach to provide a more comprehensive view of a disease. In this work, we carry out a network-based meta-analysis of the genes reported as associated with ASDs by studies that involved genomics, epigenomics, and transcriptomics. Collectively, our analysis provides a prioritization of the large number of genes proposed to be associated with ASDs, based on genes’ relevance within the intracellular circuits, the strength of the supporting evidence of association with ASDs, and the number of different molecular alterations affecting genes. We discuss the presence of the prioritized genes in the SFARI (Simons Foundation Autism Research Initiative) database and in gene networks associated with ASDs by other investigations. Lastly, we provide the full results of our analyses to encourage further studies on common targets amenable to therapy. MDPI 2019-07-09 /pmc/articles/PMC6651137/ /pubmed/31323926 http://dx.doi.org/10.3390/ijms20133363 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
Di Nanni, Noemi
Bersanelli, Matteo
Cupaioli, Francesca Anna
Milanesi, Luciano
Mezzelani, Alessandra
Mosca, Ettore
Network-Based Integrative Analysis of Genomics, Epigenomics and Transcriptomics in Autism Spectrum Disorders
title Network-Based Integrative Analysis of Genomics, Epigenomics and Transcriptomics in Autism Spectrum Disorders
title_full Network-Based Integrative Analysis of Genomics, Epigenomics and Transcriptomics in Autism Spectrum Disorders
title_fullStr Network-Based Integrative Analysis of Genomics, Epigenomics and Transcriptomics in Autism Spectrum Disorders
title_full_unstemmed Network-Based Integrative Analysis of Genomics, Epigenomics and Transcriptomics in Autism Spectrum Disorders
title_short Network-Based Integrative Analysis of Genomics, Epigenomics and Transcriptomics in Autism Spectrum Disorders
title_sort network-based integrative analysis of genomics, epigenomics and transcriptomics in autism spectrum disorders
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6651137/
https://www.ncbi.nlm.nih.gov/pubmed/31323926
http://dx.doi.org/10.3390/ijms20133363
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