title: Knowledge-Guided Bioinformatics Model for Identifying Autism Spectrum Disorder Diagnostic MicroRNA Biomarkers.
abstract: Autism spectrum disorder (ASD) is a severe neurodevelopmental disease with a high incidence and effective biomarkers are urgently needed for its diagnosis. A few previous studies have reported the detection of miRNA biomarkers for autism diagnosis, especially those based on bioinformatics approaches. In this study, we developed a knowledge-guided bioinformatics model for identifying autism miRNA biomarkers. We downloaded gene expression microarray data from the GEO Database and extracted genes with expression levels that differed in ASD and the controls. We then constructed an autism-specific miRNA-mRNA network and inferred candidate autism biomarker miRNAs based on their regulatory modes and functions. We defined a novel parameter called the autism gene percentage as autism-specific knowledge to further facilitate the identification of autism-specific biomarker miRNAs. Finally, 11 miRNAs were screened as putative autism biomarkers, where eight miRNAs (72.7%) were significantly dysregulated in ASD samples according to previous reports. Functional enrichment results indicated that the targets of the identified miRNAs were enriched in autism-associated pathways, such as Wnt signaling (in KEGG and IPA), cell cycle (in KEGG), and glioblastoma multiforme signaling (in IPA), thereby supporting the predictive power of our model.
authors.affiliation: Center for Systems Biology, Soochow University, Suzhou, 215006, China.|Institute of Biological Sciences and Biotechnology, Donghua University, Shanghai, 201620, China.
authors.forename: Li
authors.initials: L
authors.lastname: Shen
authors.affiliation: Center for Systems Biology, Soochow University, Suzhou, 215006, China.
authors.forename: Yuxin
authors.initials: Y
authors.lastname: Lin
authors.affiliation: Center for Systems Biology, Soochow University, Suzhou, 215006, China.
authors.forename: Zhandong
authors.initials: Z
authors.lastname: Sun
authors.affiliation: Center for Systems Biology, Soochow University, Suzhou, 215006, China.
authors.forename: Xuye
authors.initials: X
authors.lastname: Yuan
authors.affiliation: Key laboratory of Systems Biology, Shanghai Institute of Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
authors.forename: Luonan
authors.initials: L
authors.lastname: Chen
authors.affiliation: Center for Systems Biology, Soochow University, Suzhou, 215006, China.
authors.forename: Bairong
authors.initials: B
authors.lastname: Shen
mesh_terms: D000067877:Autism Spectrum Disorder / Q000235:genetics* / Q000378:metabolism*; D015415:Biomarkers / Q000378:metabolism; D019295:Computational Biology; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D006801:Humans; D000069550:Machine Learning; D035683:MicroRNAs / Q000235:genetics*; D015398:Signal Transduction; D012984:Software
chemical_list: D015415:Biomarkers; D035683:MicroRNAs