Evidence map›Paper›PMID 26329309›Full record

ArticleMolecular medicine reports2015

In silico analysis of the molecular mechanism of postmenopausal osteoporosis.

Yanqing Liu, Yueqiu Wang, Nailong Yang, Suning Wu, Yanhua Lv, Lili Xu

Open access · hybridAbstract read
In one paragraph

Article in Molecular medicine reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
0.9field-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

13 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Circulating miRNAs associated with bone mineral density in healthy adult baboons.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2022
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Medical Treatment for Osteoporosis: From Molecular to Clinical Opinions.International journal of molecular sciences · 2019
    Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. 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 3 institutions in 1 country.

Yanqing LiuDepartment of Geriatric Medicine, Jining No. 1 People's Hospital, Jining, Shandong 272011, P.R. China.
Yueqiu WangDepartment of Joint Brach, Jining No. 2 People's Hospital, Jining, Shandong 272000, P.R. China.
Nailong YangDepartment of Endocrinology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong 266003, P.R. China.
Suning WuDepartment of Geriatric Medicine, Jining No. 1 People's Hospital, Jining, Shandong 272011, P.R. China.
Yanhua LvDepartment of Obstertrics and Gynecology, The Affiliated Hospital of Jining Medical College, Jining, Shandong 272000, P.R. China.
Lili XuDepartment of Endocrinology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong 266003, P.R. China.
Jining First People's Hospital · CNQingdao University · CNAffiliated Hospital of Jining Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Postmenopausal osteoporosis (PO) is a common disease in females >50 years of age worldwide and is becoming an increasing burden to society. The present study aimed to assess the molecular mechanism of PO using bioinformatic methods. The gene expression data from patients with PO and normal controls were downloaded from the ArrayExpress database provided by European Bioinformatics Institute. Following the screening of the differentially expressed genes (DEGs) using the Limma package in R language, Kyoto Encyclopedia of Genes and Genomes pathways enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery online tools. Sequentially, modulators of the DEGs, including transcription factors (TFs) and microRNAs, were predicted by the ChIP Enrichment Analysis databases and WEB‑based GEne SeT AnaLysis Toolkit system, respectively. In addition, the protein‑protein interaction network of DEGs was constructed via the search tool for the retrieval of interacting genes and then the functional modules were further analyzed via the clusterMaker package and The Biological Networks Gene Ontology package within the Cytoscape software. A total of 482 DEGs, including 279 upregulated and 203 downregulated DEGs, were screened out. DEGs were predominantly enriched in the pathways of fatty acid metabolism, cardiac muscle contraction and DNA replication. TFs, including SMAD4, in addition to microRNAs, including the microRNA‑125 (miR‑125) family, miR‑331 and miR‑24, may be the modulators of the DEGs in PO. In addition, the five largest modules were identified with TTN, L1G1, ACADM, UQCRC2 and TRIM63 as the hub proteins, and they were associated with the biological processes of muscle contraction, DNA replication initiation, lipid modification, generation of precursor metabolites and energy, and regulation of acetyl‑CoA biosynthetic process, respectively. SMAD4, CACNG1 and TRIM63 are suggested to be important factors in the molecular mechanisms of PO, and miR‑331 may be novel potential biomarker for PO.

Indexed as

Gene Regulatory NetworksProtein Interaction MapsAgedAged, 80 and overComputer SimulationFemaleGene Expression ProfilingGene Expression RegulationGenomicsHumansMicroRNAsMiddle AgedOligonucleotide Array Sequence AnalysisOsteoporosis, PostmenopausalSignal TransductionMicroRNAs

Identifiers

PMID26329309
PMCPMC4626159
OpenAlexW2139338365

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.