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Blood transcriptome analysis in myasthenia gravis patients according to the disease activity
중증근무력증 환자에서 차세대 시퀀싱기법을 이용한 질병활성도에 따른 혈액전사체 연구

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Authors
박기홍
Advisor
이광우
Major
의과대학 의학과
Issue Date
2015-02
Publisher
서울대학교 대학원
Keywords
myasthenia gravisRNA-seqtranscriptome
Description
학위논문 (석사)-- 서울대학교 대학원 : 의학과, 2015. 2. 이광우.
Abstract
Background : Myasthenia gravis (MG) is an autoimmune disease affecting components of muscle membrane at the neuromuscular junction. Remission of the disease can be achieved by using immunosuppressants, but little is known about their mechanisms without biomarkers to monitor the response to treatment. With advent of next generation sequencing, it became possible to analyze whole transcriptome with RNA sequencing technique. We investigated transcriptome of peripheral blood mononuclear cells obtained from MG patients to identify molecular signatures of disease activity.

Methods : Quantitative global mRNA sequencing analysis of peripheral blood mononuclear cells (PBMC) was performed in 5 patients on active state and 5 patients on remission state. Active state was defined as de novo state or refractory symptoms despite of optimal treatment. Gene expression profiles were compared between two groups by using Cuffdiff and DESeq. Gene expression pathway analysis was done with DAVID Bioinformatics Resources and Ingenuity Pathway Analysis in the set of differentially expressed genes (DEG).

Results : By using Cuffdiff, we identified 98 differentially expressed transcripts at greater than two-fold change with raw p value < 0.05 (63 up-regulated, 35 down-regulated genes in remission group), whereas DESeq revealed 292 genes (165 up-regulated and 127 down-regulated). Among them, 28 genes were commonly observed as DEGs in both of analyses (23 up-regulated and 5 down-regulated). Top 5 genes of up-regulated genes were PFKFB3, CTSG, RAB20, S100P and BEX1, while down-regulated genes were S100B, OAS1, SLC25A20, MAP3K7CL and LINC00861. On pathway analysis, cell motion and cell migration clusters were differentially enriched between two groups. These clusters included ICAM1, CCL3, S100P and GAB2. Apoptosis pathway was also differentially enriched, and it contained NFKBIA, ZC3H12A, TNFAIP3 and PPP1R15A.

Conclusion : This study reveals the transcripts and functional clusterings associated with MG disease activity. Among the DEGs, S100B and CXCR3 were down-regulated in remission group and these may have potential to be biomarkers to indicate the disease activity. Cell migration and apoptosis pathways were differentially enriched between active and remission groups. Based on these results, further studies will be needed to understand the pathophysiology of MG and to find the therapeutic target.
Language
English
URI
https://hdl.handle.net/10371/132741
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College of Medicine/School of Medicine (의과대학/대학원)Dept. of Medicine (의학과)Theses (Master's Degree_의학과)
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