Identification of new key genes for type 1 diabetes through construction and analysis of protein-protein interaction networks based on blood and pancreatic islet transcriptomes.
BACKGROUND
Type 1 diabetes (T1D) is an autoimmune disease in which pancreatic β-cells are destroyed by infiltrating immune cells. Bilateral cooperation of pancreatic β-cells and immune cells has been proposed in the progression of T1D, but as yet no systems study has investigated this possibility. The aims of the study were to elucidate the underlying molecular mechanisms and identify key genes associated with T1D risk using a network biology approach.


METHODS
Interactome (protein-protein interaction [PPI]) and transcriptome data were integrated to construct networks of differentially expressed genes in peripheral blood mononuclear cells (PBMCs) and pancreatic β-cells. Centrality, modularity, and clique analyses of networks were used to get more meaningful biological information.


RESULTS
Analysis of genes expression profiles revealed several cytokines and chemokines in β-cells and their receptors in PBMCs, which is supports the dialogue between these two tissues in terms of PPIs. Functional modules and complexes analysis unraveled most significant biological pathways such as immune response, apoptosis, spliceosome, proteasome, and pathways of protein synthesis in the tissues. Finally, Y-box binding protein 1 (YBX1), SRSF protein kinase 1 (SRPK1), proteasome subunit alpha1/ 3, (PSMA1/3), X-ray repair cross complementing 6 (XRCC6), Cbl proto-oncogene (CBL), SRC proto-oncogene, non-receptor tyrosine kinase (SRC), phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), phospholipase C gamma 1 (PLCG1), SHC adaptor protein1 (SHC1) and ubiquitin conjugating enzyme E2 N (UBE2N) were identified as key markers that were hub-bottleneck genes involved in functional modules and complexes.


CONCLUSIONS
This study provide new insights into network biomarkers that may be considered potential therapeutic targets.
Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Nahid
N
Safari-Alighiarloo
Bioinformatics Department, Institute of Biochemistry and Biophysics, Tehran University, Tehran, Iran.
Mohammad
M
Taghizadeh
Medical Informatics Department, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Seyyed Mohammad
SM
Tabatabaei
Biostatistics Department, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Soodeh
S
Shahsavari
Department of Immunology, Faculty of Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Saeed
S
Namaki
Department of Epidemiology, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Soheila
S
Khodakarim
Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mostafa
M
Rezaei-Tavirani
D003922:Diabetes Mellitus, Type 1 / Q000097:blood / Q000235:genetics*; D020869:Gene Expression Profiling; D006801:Humans; D007515:Islets of Langerhans / Q000378:metabolism*; D060066:Protein Interaction Maps; D000090063:Proto-Oncogene Mas; D059467:Transcriptome
1型糖尿病; protein-protein interaction network; topology; transcriptome; type 1 diabetes; 拓扑; 蛋白质-蛋白质相互作用网络; 转录组