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Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: OBJECTIVE, BACKGROUND, METHODS, RESULTS. Meshes: Case-Control Studies, Databases, Genetic, Gene Expression Profiling, Gene Expression Regulation, Gene Regulatory Networks, Genetic Association Studies, Genetic Markers, Genetic Predisposition to Disease, Humans, Oligonucleotide Array Sequence Analysis, Phenotype, Spondylitis, Ankylosing.
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Does transcriptome network analysis reveal potential candidate genes for ankylosing spondylitis? Context: Ankylosing spondylitis (AS) is a chronic, inflammatory arthritis and autoimmune disease. The main symptom of AS is inflammatory spinal pain; with time, some patients develop ankylosis and spinal immobility. We aim to find cure available for ankylosing spondylitis. We used the GSE11886 series to identify potential genes that related to AS to construct a regulation network. In the network, some of TFs and target genes have been proved related with AS in previous study, such as NFKB1, STAT1, STAT4, TNFSF10, IL2RA, and IL2RB. We also found some new TFs (Franscription Factors) and target genes response to AS, such as BXDC5, and EGFR. Further analysis indicated some significant pathways are associated with AS, including antigen processing and presentation and cytokine-cytokine receptor interaction, etc.; although not significant, there was evident that they play an important role in AS progression, such as apoptosis and systemic lupus erythematosus.
assistant
Therefore, it is demonstrated that transcriptome network analysis is useful in identification of the candidate genes in AS. Final Decision: yes