Unknown

Dataset Information

0

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


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.

SUBMITTER: Di Nanni N 

PROVIDER: S-EPMC6651137 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

altmetric image

Publications

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

Di Nanni Noemi N   Bersanelli Matteo M   Cupaioli Francesca Anna FA   Milanesi Luciano L   Mezzelani Alessandra A   Mosca Ettore E  

International journal of molecular sciences 20190709 13


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 compr  ...[more]

Similar Datasets

| S-EPMC6629004 | biostudies-literature
| S-EPMC4300495 | biostudies-literature
| PRJEB34754 | ENA
| S-EPMC6390171 | biostudies-literature
| S-EPMC8298259 | biostudies-literature
2020-09-30 | GSE113690 | GEO
| S-EPMC4262896 | biostudies-literature