IDENTIFICATION OF DYSREGULATED PATHWAYS ASSOCIATED WITH ANKYLOSINGSPONDYLITIS USING PATHWAY INTERACTION NETWORK

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WANG ZHI HUA; XIANG DONG; DONG JUN JIE; HE SHAO XUAN; GUO LI MIN; LV JIA; WEI WEI; KOU NAN NAN; SHU JUN

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Journal Paper

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Journal: Iranian Red Crescent Medical Journal Year:2017 | Volume:19 | Issue:10 Page(s): 0-0

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Title

IDENTIFICATION OF DYSREGULATED PATHWAYS ASSOCIATED WITH ANKYLOSINGSPONDYLITIS USING PATHWAY INTERACTION NETWORK

Author(s)

Keywords

ANKYLOSING

SPONDYLITIS

PATHWAY

INTERACTION

NETWORK

Abstract

Background: PATHWAY analysis is the first choice for gaining insight into the underlying biology of disease, as it reducescomplexityand increases explanatory power. Objectives: The purpose of our paper was to investigate dysregulated PATHWAYs between ANKYLOSING SPONDYLITIS (AS) patients aswell 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-IlluminaHumanHT-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 interactinggenes/proteins (STRING, http: //string-db. org/) as well as Reactome databases, respectively. Furthermore, according to the principalcomponent analysis (PCA) method, the seed PATHWAY was selected by computing the activity score for each PATHWAY. A PIN was constructeddependent on the data and Pearson correlation coefficient (PCC). Dysregulated PATHWAYs were captured from the PIN byutilizing 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 seedpathway (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 normalcontrols, such as L13a-mediated translational silencing of Ceruloplasmin expression, GTP hydrolysis, as well as joining of the 60Sribosomal subunit. Conclusions: These results might be available to provide potential biomarkers to diagnose AS as well as give a hand to reveal pathologicalmechanism of this disease.

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APA: Copy

WANG, ZHI HUA, XIANG, DONG, DONG, JUN JIE, HE, SHAO XUAN, GUO, LI MIN, LV, JIA, WEI, WEI, KOU, NAN NAN, & SHU, JUN. (2017). IDENTIFICATION OF DYSREGULATED PATHWAYS ASSOCIATED WITH ANKYLOSINGSPONDYLITIS USING PATHWAY INTERACTION NETWORK. IRANIAN RED CRESCENT MEDICAL JOURNAL (IRCMJ), 19(10), 0-0. SID. https://sid.ir/paper/293772/en

Vancouver: Copy

WANG ZHI HUA, XIANG DONG, DONG JUN JIE, HE SHAO XUAN, GUO LI MIN, LV JIA, WEI WEI, KOU NAN NAN, SHU JUN. IDENTIFICATION OF DYSREGULATED PATHWAYS ASSOCIATED WITH ANKYLOSINGSPONDYLITIS USING PATHWAY INTERACTION NETWORK. IRANIAN RED CRESCENT MEDICAL JOURNAL (IRCMJ)[Internet]. 2017;19(10):0-0. Available from: https://sid.ir/paper/293772/en

IEEE: Copy

ZHI HUA WANG, DONG XIANG, JUN JIE DONG, SHAO XUAN HE, LI MIN GUO, JIA LV, WEI WEI, NAN NAN KOU, and JUN SHU, “IDENTIFICATION OF DYSREGULATED PATHWAYS ASSOCIATED WITH ANKYLOSINGSPONDYLITIS USING PATHWAY INTERACTION NETWORK,” IRANIAN RED CRESCENT MEDICAL JOURNAL (IRCMJ), vol. 19, no. 10, pp. 0–0, 2017, [Online]. Available: https://sid.ir/paper/293772/en

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