Dataset Information

Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes.

ABSTRACT:

Background

MicroRNAs (miRNAs) are important post-transcriptional regulators that have been demonstrated to play an important role in human diseases. Elucidating the associations between miRNAs and diseases at the systematic level will deepen our understanding of the molecular mechanisms of diseases. However, miRNA-disease associations identified by previous computational methods are far from completeness and more effort is needed.

Results

We developed a computational framework to identify miRNA-disease associations by performing random walk analysis, and focused on the functional link between miRNA targets and disease genes in protein-protein interaction (PPI) networks. Furthermore, a bipartite miRNA-disease network was constructed, from which several miRNA-disease co-regulated modules were identified by hierarchical clustering analysis. Our approach achieved satisfactory performance in identifying known cancer-related miRNAs for nine human cancers with an area under the ROC curve (AUC) ranging from 71.3% to 91.3%. By systematically analyzing the global properties of the miRNA-disease network, we found that only a small number of miRNAs regulated genes involved in various diseases, genes associated with neurological diseases were preferentially regulated by miRNAs and some immunological diseases were associated with several specific miRNAs. We also observed that most diseases in the same co-regulated module tended to belong to the same disease category, indicating that these diseases might share similar miRNA regulatory mechanisms.

Conclusions

In this study, we present a computational framework to identify miRNA-disease associations, and further construct a bipartite miRNA-disease network for systematically analyzing the global properties of miRNA regulation of disease genes. Our findings provide a broad perspective on the relationships between miRNAs and diseases and could potentially aid future research efforts concerning miRNA involvement in disease pathogenesis.

SUBMITTER: Shi H

PROVIDER: S-EPMC4124764 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

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Publications

Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes.

Shi Hongbo H Xu Juan J Zhang Guangde G Xu Liangde L Li Chunquan C Wang Li L Zhao Zheng Z Jiang Wei W Guo Zheng Z Li Xia X

BMC systems biology 20131008

<h4>Background</h4>MicroRNAs (miRNAs) are important post-transcriptional regulators that have been demonstrated to play an important role in human diseases. Elucidating the associations between miRNAs and diseases at the systematic level will deepen our understanding of the molecular mechanisms of diseases. However, miRNA-disease associations identified by previous computational methods are far from completeness and more effort is needed.<h4>Results</h4>We developed a computational framework to ...[more]

PMID: 24103777

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Project description:BackgroundCurrently, there are no efficient therapies for Alzheimer's disease (AD) among the elderly, although it is the most common etiology of dementia among the elderly. Quercetin, which has a variety of therapeutic properties, may pave the way for novel approaches to AD treatment. In the AD patients' frontal cortex, current study aims to identify the potential mechanisms of quercetin's pharmacological targets.Materials and methodsThe pharmacological targets of quercetin have been studied from DrugBank and SwissTarget. In order to distinguish AD-associated genes targeted by quercetin (Q-ADGs), we utilized an integrated intersection of gene expressions of the frontal cortex in combination with transcriptome analysis. To detect cortex-related Q-ADGs and immune-related Q-ADGs, a drug screening database and the immune infiltration analysis was utilized. The Q-ADGs were then linked with the AD severity scores (MMSE scores) to find severity-associated Q-ADGs. In addition, the miRNA-seq datasets were examined to identify severity-associated Q-ADG-miRNAs. Twelve genes, more frequently related to AD by previous studies among all the genes identified in the present study, were subjected to the verification of qRT-PCR in AD cell model.ResultsIn the frontal lobe of AD, 207 Q-ADGs were discovered and found that axonogenesis, glial differentiation, and other biological processes had been enriched. There were 155 immune-related Q-ADGs (e.g., COX2, NOS2, HMGB1) and 65 cortex-related Q-ADGs (e.g., FOXO1, CXCL16, NOTCH3). Sixteen Q-ADGs (e.g., STAT3, RORA, BCL6) and 28 miRNAs (e.g., miR-142-5p, miR-17-5p) were found to be related to MMSE scores. In the qRT-PCR results, six out of twelve genes were significantly regulated by quercetin. DYRK1A, FOXO1, NOS2, NGF, NQO1, and RORA genes were novel target of quercetin in AD. DYRK1A, NOS2, and NQO1 genes targeted by quercetin have benefits in the treatment of AD. However, FOXO1, NGF, and RORA genes targeted by quercetin might have a negative impact on AD.ConclusionThe role of quercetin in AD appears to be multifaceted, and it can affect patients' frontal cortex in a variety of pathways, such as axonogenesis, immune infiltration, and glial cell differentiation. DYRK1A, NOS2, and NQO1 might be potential novel effective drug targets for quercetin in AD.

Dataset Information

Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes.

Background

Results

Conclusions

Publications

Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes.

Similar Datasets

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