Evidence map›Paper›PMID 27314336›Full record

SynthesisInternational journal of molecular sciences2016

Meta-Analysis of Differential Connectivity in Gene Co-Expression Networks in Multiple Sclerosis.

Teresa Maria Creanza, Maria Liguori, Sabino Liuni, Nicoletta Nuzziello, Nicola Ancona

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in International journal of molecular sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 31% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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

5 authors at 2 institutions in 1 country.

Teresa Maria CreanzaInstitute of Intelligent Systems for Automation, National Research Council of Italy, 70126 Bari, Italy. creanza@ba.issia.cnr.it.
Maria LiguoriInstitute of Biomedical Technologies, National Research Council of Italy, 70126 Bari, Italy. maria.liguori@ba.itb.cnr.it.
Sabino LiuniInstitute of Biomedical Technologies, National Research Council of Italy, 70126 Bari, Italy. sabino.liuni@ba.itb.cnr.it.
Nicoletta NuzzielloInstitute of Biomedical Technologies, National Research Council of Italy, 70126 Bari, Italy. nicoletta.nuzziello@gmail.com.
Nicola AnconaInstitute of Intelligent Systems for Automation, National Research Council of Italy, 70126 Bari, Italy. ancona@ba.issia.cnr.it.
Institute of Biomedical Technologies · ITInstitute of Intelligent Systems for Automation · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Differential gene expression analyses to investigate multiple sclerosis (MS) molecular pathogenesis cannot detect genes harboring genetic and/or epigenetic modifications that change the gene functions without affecting their expression. Differential co-expression network approaches may capture changes in functional interactions resulting from these alterations. We re-analyzed 595 mRNA arrays from publicly available datasets by studying changes in gene co-expression networks in MS and in response to interferon (IFN)-β treatment. Interestingly, MS networks show a reduced connectivity relative to the healthy condition, and the treatment activates the transcription of genes and increases their connectivity in MS patients. Importantly, the analysis of changes in gene connectivity in MS patients provides new evidence of association for genes already implicated in MS by single-nucleotide polymorphism studies and that do not show differential expression. This is the case of amiloride-sensitive cation channel 1 neuronal (ACCN1) that shows a reduced number of interacting partners in MS networks, and it is known for its role in synaptic transmission and central nervous system (CNS) development. Furthermore, our study confirms a deregulation of the vitamin D system: among the transcription factors that potentially regulate the deregulated genes, we find TCF3 and SP1 that are both involved in vitamin D3-induced p27Kip1 expression. Unveiling differential network properties allows us to gain systems-level insights into disease mechanisms and may suggest putative targets for the treatment.

Indexed as

Gene Expression ProfilingGene Expression RegulationGene Regulatory NetworksTranscriptomeComputational BiologyHumansInterferonsMicroRNAsMultiple SclerosisRNA InterferenceRNA, MessengerTranscription FactorsInterferonsMicroRNAsRNA, MessengerTranscription Factorsgene expressiongene networksmultiple sclerosis

Identifiers

PMID27314336
PMCPMC4926469
OpenAlexW2430346293

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.