Evidence map›Paper›PMID 25086961›Full record

ArticleBMC genomics2014

Prediction of miRNA-mRNA associations in Alzheimer's disease mice using network topology.

Haneul Noh, Charny Park, Soojun Park, Young Seek Lee, Soo Young Cho, Hyemyung Seo

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.

  1. Pooled it
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  16. Understanding the Role of miR-33 in Brain Lipid Metabolism: Implications for Alzheimer's Disease.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2016
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 4 institutions in 2 countries.

Haneul Noh
Charny Park
Soojun Park
Young Seek Lee
Soo Young ChoDepartment of Molecular & Life Sciences, Hanyang University, 1271 Sa-dong, Sangrok-gu, Ansan, Gyeonggi-do, South Korea. singylu@hanmail.net.
Hyemyung Seo
Hanyang University · KRElectronics and Telecommunications Research Institute · KREwha Womans University · KRMary Lyon Centre at MRC Harwell · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLittle is known about the relationship between miRNA and mRNA expression in Alzheimer's disease (AD) at early- or late-symptomatic stages. Sequence-based target prediction algorithms and anti-correlation profiles have been applied to predict miRNA targets using omics data, but this approach often leads to false positive predictions. Here, we applied the joint profiling analysis of mRNA and miRNA expression levels to Tg6799 AD model mice at 4 and 8 months of age using a network topology-based method. We constructed gene regulatory networks and used the PageRank algorithm to predict significant interactions between miRNA and mRNA.

resultsIn total, 8 cluster modules were predicted by the transcriptome data for co-expression networks of AD pathology. In total, 54 miRNAs were identified as being differentially expressed in AD. Among these, 50 significant miRNA-mRNA interactions were predicted by integrating sequence target prediction, expression analysis, and the PageRank algorithm. We identified a set of miRNA-mRNA interactions that were changed in the hippocampus of Tg6799 AD model mice. We determined the expression levels of several candidate genes and miRNA. For functional validation in primary cultured neurons from Tg6799 mice (MT) and littermate (LM) controls, the overexpression of ARRDC3 enhanced PPP1R3C expression. ARRDC3 overexpression showed the tendency to decrease the expression of miR139-5p and miR3470a in both LM and MT primary cells. Pathological environment created by Aβ treatment increased the gene expression of PPP1R3C and Sfpq but did not significantly alter the expression of miR139-5p or miR3470a. Aβ treatment increased the promoter activity of ARRDC3 gene in LM primary cells but not in MT primary cells.

conclusionsOur results demonstrate AD-specific changes in the miRNA regulatory system as well as the relationship between the expression levels of miRNAs and their targets in the hippocampus of Tg6799 mice. These data help further our understanding of the function and mechanism of various miRNAs and their target genes in the molecular pathology of AD.

Indexed as

AlgorithmsGene Regulatory NetworksAlzheimer DiseaseAmyloid beta-PeptidesAnimalsArrestinsGenomicsIntracellular Signaling Peptides and ProteinsMiceMice, TransgenicMicroRNAsMutationPhenotypePTB-Associated Splicing FactorRNA-Binding ProteinsRNA, MessengerAmyloid beta-PeptidesARRDC3 protein, mouseArrestinsIntracellular Signaling Peptides and ProteinsMicroRNAsPpp1r3c protein, mousePTB-Associated Splicing FactorRNA-Binding ProteinsRNA, Messenger

Identifiers

PMID25086961
PMCPMC4132902
OpenAlexW2061909101

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.