ASDmiR: A Stepwise Method to Uncover miRNA Regulation Related to Autism Spectrum Disorder

Xiong, Chenchen; Sun, Shaoping; Jiang, Weili; Zhang, Junpeng

doi:10.3389/fgene.2020.562971

Cited by 5 publications

(3 citation statements)

References 81 publications

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“…miRNAs are at the core of a ceRNA network. There have been many reports of abnormal expression of multiple miRNAs in the brain tissue and peripheral blood of ASD patients ( Xiong et al, 2020 ). Given that one miRNA can simultaneously regulate expression of multiple genes, and that each gene is also regulated by multiple miRNAs, an “miRNA imbalance” may explain the heterogeneity among ASD patients.…”

Section: Discussionmentioning

confidence: 99%

Construction of an immune-related ceRNA network to screen for potential diagnostic markers for autism spectrum disorder

Sun

Chen²,

Chen³

2022

Front. Genet.

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Purpose: The diagnosis of autism spectrum disorder (ASD) is reliant on evaluation of patients’ behavior. We screened the potential diagnostic and therapeutic targets of ASD through bioinformatics analysis.Methods: Four ASD-related datasets were downloaded from the Gene Expression Omnibus database. The “limma” package was employed to analyze differentially expressed messenger (m)RNAs, long non-coding (lnc)RNAs, and micro (mi)RNAs between ASD patients and healthy volunteers (HVs). We constructed a competing endogenous-RNA (ceRNA) network. Enrichment analyses of key genes were undertaken using the Gene Ontology database and Kyoto Encyclopedia of Genes and Genomes database. The ImmucellAI database was used to analyze differences in immune-cell infiltration (ICI) in ASD and HV samples. Synthetic analyses of the ceRNA network and ICI was done to obtain a diagnostic model using LASSO regression analysis. Analyses of receiver operating characteristic (ROC) curves were done for model verification.Results: The ceRNA network comprised 49 lncRNAs, 30 miRNAs, and 236 mRNAs. mRNAs were associated with 41 cellular components, 208 biological processes, 39 molecular functions, and 35 regulatory signaling pathways. Significant differences in the abundance of 10 immune-cell species between ASD patients and HVs were noted. Using the ceRNA network and ICI results, we constructed a diagnostic model comprising five immune cell-associated genes: adenosine triphosphate-binding cassette transporter A1 (ABCA1), DiGeorge syndrome critical region 2 (DGCR2), glucose-fructose oxidoreductase structural domain gene 1 (GFOD1), glutaredoxin (GLRX), and SEC16 homolog A (SEC16A). The diagnostic performance of our model was revealed by an area under the ROC curve of 0.923. Model verification was done using the validation dataset and serum samples of patients.Conclusion:ABCA1, DGCR2, GFOD1, GLRX, and SEC16A could be diagnostic biomarkers and therapeutic targets for ASD.

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Section: Discussionmentioning

confidence: 99%

Construction of an immune-related ceRNA network to screen for potential diagnostic markers for autism spectrum disorder

Sun

Chen²,

Chen³

2022

Front. Genet.

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“…There is an opinion about the role of microRNA in the formation of aberrant neuroplasticity since microRNA is capable of inhibiting protein synthesis by transcription repression and destabilization and destruction of mRNA. The necessity of continuing investigations in this direction is also noted by the authors [ 139 ].…”

Section: Systemic Approaches To the Study Of Autism Spectrum Disordersmentioning

confidence: 94%

Molecular Mechanisms of Aberrant Neuroplasticity in Autism Spectrum Disorders (Review)

Anashkina¹,

Ерлыкина²

2021

Sovrem Tehnol Med

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This review presents the analysis and systematization of modern data on the molecular mechanisms of autism spectrum disorders (ASD) development. Polyetiology and the multifactorial nature of ASD have been proved. The attempt has been made to jointly review and systematize current hypotheses of ASD pathogenesis at the molecular level from the standpoint of aberrant brain plasticity. The mechanism of glutamate excitotoxicity formation, the effect of imbalance of neuroactive amino acids and their derivatives, neurotransmitters, and hormones on the ASD formation have been considered in detail. The strengths and weaknesses of the proposed hypotheses have been analyzed from the standpoint of evidence-based medicine. The conclusion has been drawn on the leading role of glutamate excitotoxicity as a biochemical mechanism of aberrant neuroplasticity accompanied by oxidative stress and mitochondrial dysfunction. The mechanism of aberrant neuroplasticity has also been traced at the critical moments of the nervous system development taking into account the influence of various factors of the internal and external environment. New approaches to searching for ASD molecular markers have been considered.

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“…As mentioned, some studies try to find a small set of genes involved in autism and some others concentrate on finding relevant miRNAs. Although there is evidence that miRNAs and their corresponding targets might contribute to understanding autism [ 17 ], there are few studies that focus on investigating both. Hence, we propose a framework in two steps, one for finding a small set of genes involved in autism and the other for finding a minimum set of miRNAs regulators.…”

Section: Introductionmentioning

confidence: 99%

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

2023

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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.

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ASDmiR: A Stepwise Method to Uncover miRNA Regulation Related to Autism Spectrum Disorder

Cited by 5 publications

References 81 publications

Construction of an immune-related ceRNA network to screen for potential diagnostic markers for autism spectrum disorder

Construction of an immune-related ceRNA network to screen for potential diagnostic markers for autism spectrum disorder

Molecular Mechanisms of Aberrant Neuroplasticity in Autism Spectrum Disorders (Review)

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

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