Evidence map›Paper›PMID 24337368›Full record

ArticleInternational journal of molecular medicine2014

Comparison of gene expression profiles and related pathways in chronic thromboembolic pulmonary hypertension.

Song Gu, Pixiong Su, Jun Yan, Xitao Zhang, Xiangguang An, Jie Gao, Rui Xin, Yan Liu

Open access · hybridAbstract read
In one paragraph

Article in International journal of molecular medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
0.5field-weighted citation impact, top 30% 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

17 citing papers in PubMed, 25 citations in OpenAlex.

  1. Observational
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Molecular Research in Chronic Thromboembolic Pulmonary Hypertension.International journal of molecular sciences · 2019
    Review
  13. Chronic thromboembolic pulmonary hypertension.The European respiratory journal · 2019
    Review
  14. A Review of Transcriptome Analysis in Pulmonary Vascular Diseases.Methods in molecular biology (Clifton, N.J.) · 2018
    Article
  15. The pathophysiology of chronic thromboembolic pulmonary hypertension.European respiratory review : an official journal of the European Respiratory Society · 2017
    Review
  16. Article
  17. 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

8 authors at 2 institutions in 1 country.

Song GuDepartment of Cardiac Surgery, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, P.R. China.
Pixiong SuDepartment of Cardiac Surgery, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, P.R. China.
Jun YanDepartment of Cardiac Surgery, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, P.R. China.
Xitao ZhangDepartment of Cardiac Surgery, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, P.R. China.
Xiangguang AnDepartment of Cardiac Surgery, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, P.R. China.
Jie GaoDepartment of Cardiac Surgery, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, P.R. China.
Rui XinDepartment of Cardiac Surgery, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, P.R. China.
Yan LiuDepartment of Cardiac Surgery, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, P.R. China.
Capital Medical University · CNBeijing Chao-Yang Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic thromboembolic pulmonary hypertension (CTEPH) is one of the main causes of severe pulmonary hypertension. However, despite treatment (pulmonary endarterectomy), in approximately 15-20% of patients, pulmonary vascular resistance and pulmonary arterial pressure continue to increase. To date, little is known about the changes that occur in gene expression in CTEPH. The identification of genes associated with CTEPH may provide insight into the pathogenesis of CTEPH and may aid in diagnosis and treatment. In this study, we analyzed the gene expresion profiles of pulmonary artery endothelial cells from 5 patients with CTEPH and 5 healthy controls using oligonucleotide microarrays. Bioinformatics analyses using the Gene Ontology (GO) and KEGG databases were carried out to identify the genes and pathways specifically associated with CTEPH. Signal transduction networks were established to identify the core genes regulating the progression of CTEPH. A number of genes were found to be differentially expressed in the pulmonary artery endothelial cells from patients with CTEPH. In total, 412 GO terms and 113 pathways were found to be associated with our list of genes. All differential gene interactions in the Signal-Net network were analyzed. JAK3, GNA15, MAPK13, ARRB2 and F2R were the most significantly altered. Bioinformatics analysis may help gather and analyze large amounts of data in microarrays by means of rigorous experimental planning, scientific statistical analysis and the collection of complete data. In this study, a novel differential gene expression pattern was constructed. However, further studies are required to identify novel targets for the diagnosis and treatment of CTEPH.

Indexed as

TranscriptomeAdultCase-Control StudiesChronic DiseaseComputational BiologyEndothelial CellsFemaleGene ExpressionGTP-Binding Protein alpha Subunits, Gq-G11HumansHypertension, PulmonaryJanus Kinase 3LungMaleMiddle AgedMitogen-Activated Protein Kinase 13G protein alpha 16GTP-Binding Protein alpha Subunits, Gq-G11JAK3 protein, humanJanus Kinase 3Mitogen-Activated Protein Kinase 13Vascular Cell Adhesion Molecule-1

Identifiers

PMID24337368
PMCPMC3896458
OpenAlexW2022791820

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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.