Next Article in Journal
Short Tandem Repeat Expansions and RNA-Mediated Pathogenesis in Myotonic Dystrophy
Previous Article in Journal
Genetic Structure Analysis of a Collection of Tunisian Durum Wheat Germplasm
Previous Article in Special Issue
High Functioning Autism with Missense Mutations in Synaptotagmin-Like Protein 4 (SYTL4) and Transmembrane Protein 187 (TMEM187) Genes: SYTL4- Protein Modeling, Protein-Protein Interaction, Expression Profiling and MicroRNA Studies
Article Menu
Issue 13 (July-1) cover image

Export Article

Open AccessArticle

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

1
Institute of Biomedical Technologies, Italian National Research Council, Via Fratelli Cervi 93, 20090 Segrate (MI), Italy
2
Department of Industrial and Information Engineering, University of Pavia, Via Ferrata 5, 27100 Pavia, Italy
3
Department of Physics and Astronomy, University of Bologna, Via B. Pichat 6/2, 40127 Bologna, Italy
4
National Institute of Nuclear Physics (INFN), 40127 Bologna, Italy
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2019, 20(13), 3363; https://doi.org/10.3390/ijms20133363
Received: 14 June 2019 / Revised: 5 July 2019 / Accepted: 6 July 2019 / Published: 9 July 2019
  |  
PDF [1391 KB, uploaded 9 July 2019]
  |  

Abstract

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. View Full-Text
Keywords: autism spectrum disorders; biological networks; genomics; multi-omics; network diffusion; data integration autism spectrum disorders; biological networks; genomics; multi-omics; network diffusion; data integration
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Supplementary material

SciFeed

Share & Cite This Article

MDPI and ACS Style

Di Nanni, N.; Bersanelli, M.; Cupaioli, F.A.; Milanesi, L.; Mezzelani, A.; Mosca, E. Network-Based Integrative Analysis of Genomics, Epigenomics and Transcriptomics in Autism Spectrum Disorders. Int. J. Mol. Sci. 2019, 20, 3363.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Int. J. Mol. Sci. EISSN 1422-0067 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top