机构:[1]Department of Traumatology, The Second Affiliated Hospital of Kunming Medical University, Kunming, 650011, Yunnan Province, China[2]Department of Orthopedics, First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan Province, China外科科室骨科昆明医科大学附属第一医院[3]Department of Orthopedics, The Second Affiliated Hospital of Kunming Medical University, Kunming, 650011, Yunnan Province, China
Background: Pathway analysis is the first choice for gaining insight into the underlying biology of disease, as it reduces complexity 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.
第一作者机构:[1]Department of Traumatology, The Second Affiliated Hospital of Kunming Medical University, Kunming, 650011, Yunnan Province, China
通讯作者:
通讯机构:[*1]Department of Orthopedics, The Second Affiliated Hospital of Kunming Medical University, No.374 on Kunrui Road,Wuhua District, Kunming, 650011, Yunnan Province, China
推荐引用方式(GB/T 7714):
Wang Zhi-Hua,Xiang Dong,Dong Jun-Jie,et al.Identification of Dysregulated Pathways Associated with Ankylosing Spondylitis Using Pathway Interaction Network[J].IRANIAN RED CRESCENT MEDICAL JOURNAL.2017,19(10):doi:10.5812/ircmj.14172.
APA:
Wang, Zhi-Hua,Xiang, Dong,Dong, Jun-Jie,He, Shao-Xuan,Guo, Li-Min...&Shu, Jun.(2017).Identification of Dysregulated Pathways Associated with Ankylosing Spondylitis Using Pathway Interaction Network.IRANIAN RED CRESCENT MEDICAL JOURNAL,19,(10)
MLA:
Wang, Zhi-Hua,et al."Identification of Dysregulated Pathways Associated with Ankylosing Spondylitis Using Pathway Interaction Network".IRANIAN RED CRESCENT MEDICAL JOURNAL 19..10(2017)