Identification of dysregulated pathways associated with ankylosing spondylitis using pathway interaction network
Joint Authors
Wei, Wei
Xiang, Dong
Shu, Jun
Wang, Zhi Hua
Dong, Jun Jie
He, Shao Xuan
Guo, Li Min
Lv, Jia
Kou, Nan Nan
Source
Iranian Red Crescent Medical Journal
Issue
Vol. 19, Issue 10 (31 Oct. 2017), pp.1-6, 6 p.
Publisher
Publication Date
2017-10-31
Country of Publication
United Arab Emirates
No. of Pages
6
Main Subjects
Abstract EN
Background: Pathway analysis is the first choice for gaining insight into the underlying biology of disease, as it reducescomplexity and increases explanatory power.
Objectives: The purpose of our paper was to investigate dysregulated pathways between ankylosing spondylitis (AS) patients as well as normal controls based on the pathway interaction network (PIN) related analysis.
Methods: This is a case-control bioinformatics analysis using already published microarray data of AS.
It was conducted in Kunming, China from October 2015 to June 2016.
We recruited the gene expression profile of AS from the ArrayExpress database (http://www.ebi.ac.uk/arrayexpress/) with the accessing number of E-GEOD-25101.
E-GEOD-25101 existed on A-MEXP-1171 - Illumina HumanHT-12 v3.0 Expression BeadChip Platform and was comprised of 32 samples (16 AS samples and 16 normal samples).
Meanwhile, the protein-protein interaction (PPI) data and pathway data were retrieved from Search Tool for the retrieval of interacting genes/proteins (STRING, http://string-db.org/) as well as Reactome databases, respectively.
Furthermore, according to the principal component analysis (PCA) method, the seed pathway was selected by computing the activity score for each pathway.
A PIN was constructed dependent on the data and Pearson correlation coefficient (PCC).
Dysregulated pathways were captured from the PIN by utilizing the seed pathway and the area under the receiver operating characteristics curve (AUROC) index.
Results: The PIN consisted of 1022 pathways and 7314 interactions, of which, 3’-UTR-mediated translational regulation was the seed pathway (absolute change of activity score = 10.962).
Starting from the seed pathway, a minimum set of pathways with AUROC = 0.902 was extracted from the PIN.
Consequently, a total of 11 dysregulated pathways were identified for AS compared with normal controls, such as L13a-mediated translational silencing of Ceruloplasmin expression, GTP hydrolysis, as well as joining of the 60S ribosomal subunit.
Conclusions: These results might be available to provide potential biomarkers to diagnose AS as well as give a hand to reveal pathological mechanism of this disease.
American Psychological Association (APA)
Wang, Zhi Hua& Xiang, Dong& Dong, Jun Jie& He, Shao Xuan& Guo, Li Min& Lv, Jia…[et al.]. 2017. Identification of dysregulated pathways associated with ankylosing spondylitis using pathway interaction network. Iranian Red Crescent Medical Journal،Vol. 19, no. 10, pp.1-6.
https://search.emarefa.net/detail/BIM-805429
Modern Language Association (MLA)
Wang, Zhi Hua…[et al.]. Identification of dysregulated pathways associated with ankylosing spondylitis using pathway interaction network. Iranian Red Crescent Medical Journal Vol. 19, no. 10 (Oct. 2017), pp.1-6.
https://search.emarefa.net/detail/BIM-805429
American Medical Association (AMA)
Wang, Zhi Hua& Xiang, Dong& Dong, Jun Jie& He, Shao Xuan& Guo, Li Min& Lv, Jia…[et al.]. Identification of dysregulated pathways associated with ankylosing spondylitis using pathway interaction network. Iranian Red Crescent Medical Journal. 2017. Vol. 19, no. 10, pp.1-6.
https://search.emarefa.net/detail/BIM-805429
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 6
Record ID
BIM-805429