NDLI: Biomarker prediction in autism spectrum disorder using a network-based approach

Content Provider	Springer Nature : BioMed Central
Author	Rastegari, Maryam Salehi, Najmeh Zare-Mirakabad, Fatemeh
Abstract	Background Autism is a neurodevelopmental disorder that is usually diagnosed in early childhood. Timely diagnosis and early initiation of treatments such as behavioral therapy are important in autistic people. Discovering critical genes and regulators in this disorder can lead to early diagnosis. Since the contribution of miRNAs along their targets can lead us to a better understanding of autism, we propose a framework containing two steps for gene and miRNA discovery. Methods The first step, called the FA_gene algorithm, finds a small set of genes involved in autism. This algorithm uses the WGCNA package to construct a co-expression network for control samples and seek modules of genes that are not reproducible in the corresponding co-expression network for autistic samples. Then, the protein–protein interaction network is constructed for genes in the non-reproducible modules and a small set of genes that may have potential roles in autism is selected based on this network. The second step, named the DMN_miRNA algorithm, detects the minimum number of miRNAs related to autism. To do this, DMN_miRNA defines an extended Set Cover algorithm over the mRNA–miRNA network, consisting of the selected genes and corresponding miRNA regulators. Results In the first step of the framework, the FA_gene algorithm finds a set of important genes; TP53, TNF, MAPK3, ACTB, TLR7, LCK, RAC2, EEF2, CAT, ZAP70, CD19, RPLP0, CDKN1A, CCL2, CDK4, CCL5, CTSD, CD4, RACK1, CD74; using co-expression and protein–protein interaction networks. In the second step, the DMN_miRNA algorithm extracts critical miRNAs, hsa-mir-155-5p, hsa-mir-17-5p, hsa-mir-181a-5p, hsa-mir-18a-5p, and hsa-mir-92a-1-5p, as signature regulators for autism using important genes and mRNA–miRNA network. The importance of these key genes and miRNAs is confirmed by previous studies and enrichment analysis. Conclusion This study suggests FA_gene and DMN_miRNA algorithms for biomarker discovery, which lead us to a list of important players in ASD with potential roles in the nervous system or neurological disorders that can be experimentally investigated as candidates for ASD diagnostic tests.
Related Links	https://bmcmedgenomics.biomedcentral.com/counter/pdf/10.1186/s12920-023-01439-5.pdf
Ending Page	13
Page Count	13
Starting Page	1
File Format	HTM / HTML
ISSN	17558794
DOI	10.1186/s12920-023-01439-5
Journal	BMC Medical Genomics
Issue Number	1
Volume Number	16
Language	English
Publisher	BioMed Central
Publisher Date	2023-01-23
Access Restriction	Open
Subject Keyword	Human Genetics Microarrays Gene Expression miRNA Co-expression network Set cover
Content Type	Text
Resource Type	Article
Subject	Genetics (clinical) Genetics
Journal Impact Factor	2.1/2023
5-Year Journal Impact Factor	2.5/2023

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A network clustering based feature selection strategy for classifying autism spectrum disorder

Circulating microRNA panels for multi-cancer detection and gastric cancer screening: leveraging a network biology approach

Network-based drug sensitivity prediction

Autworks: a cross-disease network biology application for Autism and related disorders

Pathway-based outlier method reveals heterogeneous genomic structure of autism in blood transcriptome

Novel link prediction for large-scale miRNA-lncRNA interaction network in a bipartite graph

Mutation screening of melatonin-related genes in patients with autism spectrum disorders

miRDM-rfGA: Genetic algorithm-based identification of a miRNA set for detecting type 2 diabetes

Animal model integration to AutDB, a genetic database for autism

Biomarker prediction in autism spectrum disorder using a network-based approach

Similar Documents

A network clustering based feature selection strategy for classifying autism spectrum disorder

Circulating microRNA panels for multi-cancer detection and gastric cancer screening: leveraging a network biology approach

Network-based drug sensitivity prediction

Autworks: a cross-disease network biology application for Autism and related disorders

Pathway-based outlier method reveals heterogeneous genomic structure of autism in blood transcriptome

Novel link prediction for large-scale miRNA-lncRNA interaction network in a bipartite graph

Mutation screening of melatonin-related genes in patients with autism spectrum disorders

miRDM-rfGA: Genetic algorithm-based identification of a miRNA set for detecting type 2 diabetes

Animal model integration to AutDB, a genetic database for autism

Biomarker prediction in autism spectrum disorder using a network-based approach