期刊
GENOMICS
卷 103, 期 4, 页码 264-275出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ygeno.2013.12.007
关键词
Diabetes; Pancreatic beta cells; Cytokines; Gene expression; Meta-analysis; Time series; Network inference
资金
- Fonds National de la Recherche Scientifique (FNRS) Belgium
- Expert Center from the Dutch Diabetes Research Foundation [2008.40.001]
- European Union
- Swedish national strategic research initiative EXODIAB (Excellence Of Diabetes Research in Sweden)
- Juvenile Diabetes Research Foundation (JDRF) [31-2008-413, 4-2001-438, 42008-376]
- ECIT Islet for Basic Research Program
- Danish Council for Strategic Research [09-067036/DSF]
- Communaute Francaise de Belgique - Actions de Recherche Concertees (ARC)
Type I Diabetes (T1D) is an autoimmune disease where local release of cytokines such as IL-1 beta and IFN-gamma contributes to beta-cell apoptosis. To identify relevant genes regulating this process we performed a meta-analysis of 8 datasets of beta-cell gene expression after exposure to IL-1 beta and IFN-gamma. Two of these datasets are novel and contain time-series expressions in human islet cells and rat INS-1E cells. Genes were ranked according to their differential expression within and after 24 h from exposure, and characterized by function and prior knowledge in the literature. A regulatory network was then inferred from the human time expression datasets, using a time-series extension of a network inference method. The two most differentially expressed genes previously unknown in T1D literature (RIPK2 and ELF3) were found to modulate cytokine-induced apoptosis. The inferred regulatory network is thus supported by the experimental validation, providing a proof-of-concept for the proposed statistical inference approach. (C) 2014 Elsevier Inc. All rights reserved.
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