Determination of molecular signatures and pathways common to brain tissues of autism spectrum disorder: insights from comprehensive bioinformatics approach

Article

Bristy, Sadia Afrin, Islam, AM Humyra, Andalib, KM Salim, Khan, Umama, Awal, Md Abdul and Rahman, Md Habibur. 2022. "Determination of molecular signatures and pathways common to brain tissues of autism spectrum disorder: insights from comprehensive bioinformatics approach." Informatics in Medicine Unlocked. 29. https://doi.org/10.1016/j.imu.2022.100871
Article Title

Determination of molecular signatures and pathways common to brain tissues of autism spectrum disorder: insights from comprehensive bioinformatics approach

ERA Journal ID212809
Article CategoryArticle
AuthorsBristy, Sadia Afrin, Islam, AM Humyra, Andalib, KM Salim, Khan, Umama, Awal, Md Abdul and Rahman, Md Habibur
Journal TitleInformatics in Medicine Unlocked
Journal Citation29
Article Number100871
Number of Pages13
Year2022
PublisherElsevier
Place of PublicationUnited Kingdom
ISSN2352-9148
Digital Object Identifier (DOI)https://doi.org/10.1016/j.imu.2022.100871
Web Address (URL)https://www.sciencedirect.com/science/article/pii/S2352914822000259
Abstract

Autism spectrum disorder (ASD) is a collection of neurological disabilities marked by difficulties with behavior, speech, language, and interaction. It is a complicated and behaviorally defined static disorder of the developing brain. Recently it has become a serious concern across the world. The goal of this project was to use bioinformatics tools and network biology to uncover the molecular signatures and pathways of ASD. We investigated brain transcriptomics gene expression datasets and determined 47 dysregulated differentially expressed common genes. Several kinds of crucial neurodegeneration-related molecular mechanisms in the signaling structures were determined as a result of these investigations. We implemented gene set enrichment analysis (GSEA) using bimolecular pathways and gene ontology (GO) terms to determine the role of these differentially expressed genes (DEGs), as well as protein-protein interactions (PPI), transcriptional factor interactions, and post-transcriptional factor interactions. PPI network collected the top ten hub genes including KIT, PIN1, GATA1, GRIN2A, PBX2, BLK, ATP6V1B1, TCF7L1, TRAF1, and HSPG2. The PPI network also revealed the existence of two sub-networks. Moreover, several transcription factors (NFIC, USF2, TFAP2A, RELA, FOXL1, GATA2, YY1, FOXC1, NFKB1, and E2F1) and post-transcription factors (mir-335-5p, mir-26b-5p, mir-124-3p, mir-192-5p, mir-1-3p, mir-215-5p, mir-6825-5p, mir-146a-5p, mir-8485, and mir-93-5p) were found throughout this study. Some drug-like molecules were also predicted that might have a beneficial effect against ASD. We detected potentially novel links between pathogenic conditions in ASD patient's brain tissues. This work offers molecular biomarkers at the gene expression level and protein bases that could aid in a better understanding of molecular pathways, as well as potential pharmacological approaches and therapies for developing effective ASD treatments.

KeywordsBioinformatics ; Autism spectrum disorder ; Hub gene ; Protein-protein interaction ; Transcriptional factors ; Post-transcriptional factors ; Gene ontology
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020310202. Biological network analysis
Byline AffiliationsBioinformatics and Biomedical Research Network of Bangladesh, Bangladesh
Khulna University, Bangladesh
Islamic University, Bangladesh
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