Evidence map›Paper›PMID 34603387›Full record

ArticleFrontiers in genetics2021

Identification of LINC00173 in Myasthenia Gravis by Integration Analysis of Aberrantly Methylated- Differentially Expressed Genes and ceRNA Networks.

Si Xu, Tianfeng Wang, Xiaoyu Lu, Huixue Zhang, Li Liu, Xiaotong Kong, Shuang Li, Xu Wang, Hongyu Gao, Jianjian Wang and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.8field-weighted citation impact, top 25% 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

8 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Expression of Tumor SuppressorInternational journal of molecular sciences · 2023
    Article
  5. Article
  6. Article
  7. Review
  8. 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

11 authors at 2 institutions in 1 country.

Si XuDepartment of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Tianfeng WangDepartment of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Xiaoyu LuDepartment of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Huixue ZhangDepartment of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Li LiuDepartment of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Xiaotong KongDepartment of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Shuang LiDepartment of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Xu WangDepartment of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Hongyu GaoDepartment of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Jianjian WangDepartment of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Lihua WangDepartment of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Second Affiliated Hospital of Harbin Medical University · CNHarbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Myasthenia gravis (MG) is an autoimmune disease associated with autoantibody production that leads to skeletal muscle weakness. The molecular mechanisms underlying MG are not fully understood. We analyzed the gene expression profile (GSE85452) and methylation profile (GSE85647) of MG samples from the GEO database to identify aberrantly methylated-differentially expressed genes. By integrating the datasets, we identified 143 hypermethylation-low expression genes and 91 hypomethylation-high expression genes. Then we constructed PPI network and ceRNA networks by these genes. Phosphatase and tensin homolog (PTEN) and Abelson tyrosine-protein kinase (ABL)1 were critical genes in both PPI networks and ceRNA networks. And potential MG associated lncRNAs were selected by comprehensive analysis of the critical genes and ceRNA networks. In the hypermethylation-low expression genes associated ceRNA network, sirtuin (SIRT)1 was the most important gene and the lncRNA HLA complex (HC) P5 had the highest connection degree. Meanwhile, PTEN was the most important gene and the lncRNA LINC00173 had the highest connection degree in the hypomethylation-high expression genes associated ceRNA network. LINC00173 was validated to be upregulated in MG patients by qRT-PCR (

Indexed as

biomarkerceRNAlncRNAmyasthenia gravisnetwork

Identifiers

PMID34603387
PMCPMC8481885
OpenAlexW3199249838

What OpenQuestion holds

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Registered trials

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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.