Evidence map›Paper›PMID 27375481›Full record

ArticleFrontiers in pharmacology2016

Comparative Transcriptome Analysis Identifies CCDC80 as a Novel Gene Associated with Pulmonary Arterial Hypertension.

Shota Sasagawa, Yuhei Nishimura, Hirofumi Sawada, Erquan Zhang, Shiko Okabe, Soichiro Murakami, Yoshifumi Ashikawa, Mizuki Yuge, Koki Kawaguchi, Reiko Kawase and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

23 citing papers in PubMed, 40 citations in OpenAlex.

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  19. C3orf70 Is Involved in Neural and Neurobehavioral Development.Pharmaceuticals (Basel, Switzerland) · 2019
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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

13 authors at 1 institution in 1 country.

Shota SasagawaDepartment of Molecular and Cellular Pharmacology, Pharmacogenomics and Pharmacoinformatics, Mie University Graduate School of Medicine, Tsu Japan.
Yuhei NishimuraDepartment of Molecular and Cellular Pharmacology, Pharmacogenomics and Pharmacoinformatics, Mie University Graduate School of Medicine, TsuJapan; Mie University Medical Zebrafish Research Center, TsuJapan; Department of Systems Pharmacology, Mie University Graduate School of Medicine, TsuJapan; Department of Omics Medicine, Mie University Industrial Technology Innovation Institute, TsuJapan; Department of Bioinformatics, Mie University Life Science Research Center, TsuJapan.
Hirofumi SawadaDepartment of Anesthesiology and Critical Care Medicine, Mie University Graduate School of Medicine, Tsu Japan.
Erquan ZhangDepartment of Anesthesiology and Critical Care Medicine, Mie University Graduate School of Medicine, Tsu Japan.
Shiko OkabeDepartment of Molecular and Cellular Pharmacology, Pharmacogenomics and Pharmacoinformatics, Mie University Graduate School of Medicine, Tsu Japan.
Soichiro MurakamiDepartment of Molecular and Cellular Pharmacology, Pharmacogenomics and Pharmacoinformatics, Mie University Graduate School of Medicine, Tsu Japan.
Yoshifumi AshikawaDepartment of Molecular and Cellular Pharmacology, Pharmacogenomics and Pharmacoinformatics, Mie University Graduate School of Medicine, Tsu Japan.
Mizuki YugeDepartment of Molecular and Cellular Pharmacology, Pharmacogenomics and Pharmacoinformatics, Mie University Graduate School of Medicine, Tsu Japan.
Koki KawaguchiDepartment of Molecular and Cellular Pharmacology, Pharmacogenomics and Pharmacoinformatics, Mie University Graduate School of Medicine, Tsu Japan.
Reiko KawaseDepartment of Molecular and Cellular Pharmacology, Pharmacogenomics and Pharmacoinformatics, Mie University Graduate School of Medicine, Tsu Japan.
Yoshihide MitaniDepartment of Pediatrics, Mie University Graduate School of Medicine, Tsu Japan.
Kazuo MaruyamaDepartment of Anesthesiology and Critical Care Medicine, Mie University Graduate School of Medicine, Tsu Japan.
Toshio TanakaDepartment of Molecular and Cellular Pharmacology, Pharmacogenomics and Pharmacoinformatics, Mie University Graduate School of Medicine, TsuJapan; Mie University Medical Zebrafish Research Center, TsuJapan; Department of Systems Pharmacology, Mie University Graduate School of Medicine, TsuJapan; Department of Omics Medicine, Mie University Industrial Technology Innovation Institute, TsuJapan; Department of Bioinformatics, Mie University Life Science Research Center, TsuJapan.
Mie University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pulmonary arterial hypertension (PAH) is a heterogeneous disorder associated with a progressive increase in pulmonary artery resistance and pressure. Although various therapies have been developed, the 5-year survival rate of PAH patients remains low. There is thus an important need to identify novel genes that are commonly dysregulated in PAH of various etiologies and could be used as biomarkers and/or therapeutic targets. In this study, we performed comparative transcriptome analysis of five mammalian PAH datasets downloaded from a public database. We identified 228 differentially expressed genes (DEGs) from a rat PAH model caused by inhibition of vascular endothelial growth factor receptor under hypoxic conditions, 379 DEGs from a mouse PAH model associated with systemic sclerosis, 850 DEGs from a mouse PAH model associated with schistosomiasis, 1598 DEGs from one cohort of human PAH patients, and 4260 DEGs from a second cohort of human PAH patients. Gene-by-gene comparison identified four genes that were differentially upregulated or downregulated in parallel in all five sets of DEGs. Expression of coiled-coil domain containing 80 (CCDC80) and anterior gradient two genes was significantly increased in the five datasets, whereas expression of SMAD family member six and granzyme A was significantly decreased. Weighted gene co-expression network analysis revealed a connection between CCDC80 and collagen type I alpha 1 (COL1A1) expression. To validate the function of CCDC80 in vivo, we knocked out ccdc80 in zebrafish using the clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 system. In vivo imaging of zebrafish expressing a fluorescent protein in endothelial cells showed that ccdc80 deletion significantly increased the diameter of the ventral artery, a vessel supplying blood to the gills. We also demonstrated that expression of col1a1 and endothelin-1 mRNA was significantly decreased in the ccdc80-knockout zebrafish. Finally, we examined Ccdc80 immunoreactivity in a rat PAHmodel and found increased expression in the hypertrophied media and adventitia of the pre-acinar pulmonary arteries (PAs) and in the thickened intima, media, and adventitia of the obstructed intra-acinar PAs. These results suggest that increased expression of CCDC80 may be involved in the pathogenesis of PAH, potentially by modulating the expression of endothelin-1 and COL1A1.

Indexed as

CCDC80COL1A1comparative transcriptome analysisEDN1pulmonary arterial hypertensionsystems pharmacologyweighted gene co-expression network analysis

Identifiers

PMID27375481
PMCPMC4894905
OpenAlexW2411781365

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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.