Dataset Information

Expression and Regulatory Network Analysis of miR-140-3p, a New Potential Serum Biomarker for Autism Spectrum Disorder.

ABSTRACT: Given its prevalence and social impact, Autism Spectrum Disorder (ASD) is drawing much interest. Molecular basis of ASD is heterogeneous and only partially known. Many factors, including disorders comorbid with ASD, like TS (Tourette Syndrome), complicate ASD behavior-based diagnosis and make it vulnerable to bias. To further investigate ASD etiology and to identify potential biomarkers to support its precise diagnosis, we used TaqMan Low Density Array technology to profile serum miRNAs from ASD, TS, and TS+ASD patients, and unaffected controls (NCs). Through validation assays in 30 ASD, 24 TS, and 25 TS+ASD patients and 25 NCs, we demonstrated that miR-140-3p is upregulated in ASD vs.: NC, TS, and TS+ASD (Tukey's test, p-values = 0.03, = 0.01, < 0.0001, respectively). ΔCt values for miR-140-3p and YGTSS (Yale Global Tic Severity Scale) scores are positively correlated (Spearman r = 0.33; Benjamini-Hochberg p = 0.008) and show a linear relationship (p = 0.002). Network functional analysis showed that nodes controlled by miR-140-3p, especially CD38 and NRIP1 which are its validated targets, are involved in processes convergingly dysregulated in ASD, such as synaptic plasticity, immune response, and chromatin binding. Biomarker analysis proved that serum miR-140-3p can discriminate among: (1) ASD and NC (Area under the ROC curve, AUC: 0.70; sensitivity: 63.33%; specificity: 68%); (2) ASD and TS (AUC: 0.72; sensitivity: 66.66%; specificity: 70.83%); (3) ASD and TS+ASD (AUC: 0.78; sensitivity: 73.33%; specificity: 76%). Characterization of miR-140-3p network would contribute to further clarify ASD etiology. Serum miR-140-3p could represent a potential non-invasive biomarker for ASD, easy to test through liquid biopsy.

SUBMITTER: Cirnigliaro M

PROVIDER: S-EPMC5554380 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Expression and Regulatory Network Analysis of miR-140-3p, a New Potential Serum Biomarker for Autism Spectrum Disorder.

Cirnigliaro Matilde M Barbagallo Cristina C Gulisano Mariangela M Domini Carla N CN Barone Rita R Barbagallo Davide D Ragusa Marco M Di Pietro Cinzia C Rizzo Renata R Purrello Michele M

Frontiers in molecular neuroscience 20170810

Given its prevalence and social impact, Autism Spectrum Disorder (ASD) is drawing much interest. Molecular basis of ASD is heterogeneous and only partially known. Many factors, including disorders comorbid with ASD, like TS (Tourette Syndrome), complicate ASD behavior-based diagnosis and make it vulnerable to bias. To further investigate ASD etiology and to identify potential biomarkers to support its precise diagnosis, we used TaqMan Low Density Array technology to profile serum miRNAs from ASD ...[more]

PMID: 28848387

Similar Datasets

Project description:BackgroundAutism 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.MethodsThe 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.ResultsIn 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.ConclusionThis 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.

Project description:BackgroundMicroRNAs (miRNAs) in circulation have emerged as promising biomarkers. In this study, we aimed to identify a circulating miRNA signature for osteoarthritis (OA) patients and in combination with bioinformatics analysis to evaluate the utility of selected differentially expressed miRNAs in the serum as potential OA biomarkers.MethodsSerum samples were collected from 12 primary OA patients, and 12 healthy individuals were screened using the Agilent Human miRNA Microarray platform interrogating 2549 miRNAs. Receiver Operating Characteristic (ROC) curves were constructed to evaluate the diagnostic performance of the deregulated miRNAs. Expression levels of selected miRNAs were validated by quantitative real-time PCR (qRT-PCR) in all serum and in articular cartilage samples from OA patients (n = 12) and healthy individuals (n = 7). Bioinformatics analysis was used to investigate the involved pathways and target genes for the above miRNAs.ResultsWe identified 279 differentially expressed miRNAs in the serum of OA patients compared to controls. Two hundred and five miRNAs (73.5%) were upregulated and 74 (26.5%) downregulated. ROC analysis revealed that 77 miRNAs had area under the curve (AUC) > 0.8 and p < 0.05. Bioinformatics analysis in the 77 miRNAs revealed that their target genes were involved in multiple signaling pathways associated with OA, among which FoxO, mTOR, Wnt, pI3K/akt, TGF-β signaling pathways, ECM-receptor interaction, and fatty acid biosynthesis. qRT-PCR validation in seven selected out of the 77 miRNAs revealed 3 significantly downregulated miRNAs (hsa-miR-33b-3p, hsa-miR-671-3p, and hsa-miR-140-3p) in the serum of OA patients, which were in silico predicted to be enriched in pathways involved in metabolic processes. Target-gene analysis of hsa-miR-140-3p, hsa-miR-33b-3p, and hsa-miR-671-3p revealed that InsR and IGFR1 were common targets of all three miRNAs, highlighting their involvement in regulation of metabolic processes that contribute to OA pathology. Hsa-miR-140-3p and hsa-miR-671-3p expression levels were consistently downregulated in articular cartilage of OA patients compared to healthy individuals.ConclusionsA serum miRNA signature was established for the first time using high density resolution miR-arrays in OA patients. We identified a three-miRNA signature, hsa-miR-140-3p, hsa-miR-671-3p, and hsa-miR-33b-3p, in the serum of OA patients, predicted to regulate metabolic processes, which could serve as a potential biomarker for the evaluation of OA risk and progression.

Project description:BACKGROUND:In recent studies, microRNAs have been demonstrated as stable detectable biomarkers in blood for cancer. In addition, computer-aided biomarker discovery has now become an attractive paradigm for precision diagnosis. METHODS:In this study, we identified and evaluated miR-139-3p as a biomarker for screening of esophageal squamous cell carcinoma using the Cancer Genome Atlas and Gene Expression Omnibus database analyses. We identified possible miR-139-3p target genes through the predicted database and esophageal squamous cell carcinoma upregulated genes from the Cancer Genome Atlas and Gene. Bioinformatics analysis was performed to determine key miR-139-3p targets and pathways associated with esophageal carcinoma. Finally, the expression and expected significance of hub genes were evaluated via the Genotype-Tissue Expression project. RESULTS:MiR-139-3p was significantly downregulated in patients with esophageal squamous cell carcinoma/esophageal carcinoma. In GSE 122497, the area under the curve-receiver operating characteristic value, sensitivity, and specificity for serum miR-139-3p were 0.754, 67.49%, and 80.00%, respectively. The pattern specification process, skeletal system development, and regionalization process were the most enriched interactions in esophageal carcinoma. In addition, Epstein-Barr virus infection, human T-cell leukemia virus 1 infection, and human cytomegalovirus infection were identified as crucial pathways. Six hub genes (CD1A, FCGR2A, ANPEP, CD1B, membrane metalloendopeptidase, and TWIST1) were found, and FCGR2A and membrane metalloendopeptidase were further confirmed by genotype-tissue expression. High expression of membrane metalloendopeptidase correlated with a better overall survival but not with disease-free survival of patients with esophageal carcinoma. CONCLUSIONS:MiR-139-3p was identified as a candidate biomarker for predicting esophageal squamous cell carcinoma based on network analysis. MiR-139-3p acted as a tumor suppressor by targeting membrane metalloendopeptidase in esophageal carcinoma, and low expression of membrane metalloendopeptidase may indicate a better prognosis of patients with esophageal carcinoma.

Dataset Information

Expression and Regulatory Network Analysis of miR-140-3p, a New Potential Serum Biomarker for Autism Spectrum Disorder.

Publications

Expression and Regulatory Network Analysis of miR-140-3p, a New Potential Serum Biomarker for Autism Spectrum Disorder.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets