Exp Clin Endocrinol Diabetes 2014; 122(08): 477-483
DOI: 10.1055/s-0034-1372599
Article
© J. A. Barth Verlag in Georg Thieme Verlag KG Stuttgart · New York

Bioinformatics Analysis of Gene Expression in Peripheral Blood Mononuclear Cells from Children with Type 1 Diabetes in 3 Periods

H. Liu
1   Department of Pediatrics, Qilu Hospital of Shandong University, Jinan, China
,
R. Xu
1   Department of Pediatrics, Qilu Hospital of Shandong University, Jinan, China
,
X. Liu
1   Department of Pediatrics, Qilu Hospital of Shandong University, Jinan, China
,
R. Sun
1   Department of Pediatrics, Qilu Hospital of Shandong University, Jinan, China
,
Q. Wang
2   Department of Anesthesiology, Qingdao Municipal Hospital, Qingdao, China
› Author Affiliations
Further Information

Publication History

received 27 September 2013
first decision 05 December 2013

accepted 21 March 2014

Publication Date:
16 May 2014 (online)

Abstract

Objective:

To explore the expression changes of potential key genes and relevant biological processes in peripheral blood mononuclear cells of children with newly diagnosis of type 1 diabetes (T1D).

Methods:

Microarray data GSE9006 were downloaded from Gene Expression Omnibus (GEO) database, including peripheral blood mononuclear cells samples from 43 children with newly diagnosed T1D (NEW), 19 one-month (1-MO) follow-up samples, 19 4-month (4-MO) follow-up samples and 24 healthy controls. The differentially expressed genes (DEGs) were identified using Affy package in R, and cluster analysis of DEGs were performed following functional enrichment analysis with Database for Annotation, Visualization and Integrated Discovery (DAVID) and construction of protein-protein interaction (PPI) network with STRING database.

Results:

We identified 73, 73, 96 DEGs in NEW group, 1-MO group and 4-MO group, respectively by comparing with healthy controls with |logFC|>0.58 and P-value<0.05. The cluster analysis of these DEGs showed that 4 genes, including human leukocyte antigen (HLA-DQA1), HLA-DRB4, integrin 3 (ITGB3) and killer cell lectin-like receptor subfamily F member 1 (KLRF1) were all significantly expressed in 3 groups, which were significantly enriched in asthma, T1D and intestinal immune network for IgA production pathway. And 57 genes enriched in cluster 5, which were only differentially expressed in NEW group, were involved in response to wounding, inflammatory response and blood coagulation as well as chemokine signaling pathway. Besides, the hub genes in PPI network of cluster 5 were identified, containing FOS, pro-platelet basic protein (PPBP), interleukin 8 (IL8), formyl peptide receptor-like 2 (FPR2) and platelet factor 4 (PF4).

Conclusion:

HLA-DQA1, HLA-DRB4, ITGB3 and KLRF1 might be targets for treatment of T1D, and 5 hub proteins, FOS, PPBP, IL8, FPR2 and PF4, were likely to be new markers for diagnosis of T1D.

 
  • References

  • 1 Epstein FH, Atkinson MA, Maclaren NK. The pathogenesis of insulin-dependent diabetes mellitus. New Engl J Med 1994; 331: 1428-1436
  • 2 Kaizer EC, Glaser CL, Chaussabel D et al. Gene expression in peripheral blood mononuclear cells from children with diabetes. J Clin Endocr Metab 2007; 92: 3705-3711
  • 3 Donath MY, Størling J, Maedler K et al. Inflammatory mediators and islet β-cell failure: a link between type 1 and type 2 diabetes. Int J Mol Med 2003; 81: 455-470
  • 4 Basu S, Larsson A, Vessby J et al. Type 1 diabetes is associated with increased cyclooxygenase- and cytokine-mediated inflammation. Diabetes care 2005; 28: 1371-1375
  • 5 Patterson CC, Dahlquist GG, Gyürüs E et al. Incidence trends for childhood type 1 diabetes in Europe during 1989–2003 and predicted new cases 2005–20: a multicentre prospective registration study. The Lancet 373: 2027-2033
  • 6 Harjutsalo V, Sjöberg L, Tuomilehto J. Time trends in the incidence of type 1 diabetes in Finnish children: a cohort study. The Lancet 371: 1777-1782
  • 7 Bowman MA, Campbell L, Darrow BL et al. Immunological and metabolic effects of prophylactic insulin therapy in the NOD-scid/scid adoptive transfer model of IDDM. Diabetes 1996; 45: 205-208
  • 8 Bertrand S, De Paepe M, Vigeant C et al. Prevention of adoptive transfer in BB rats by prophylactic insulin treatment. Diabetes 1992; 41: 1273-1277
  • 9 Keller R, Jackson R, Eisenbarth G et al. Insulin prophylaxis in individuals at high risk of type 1 diabetes. The Lancet 1993; 341: 927-928
  • 10 Füchtenbusch M, Rabl W, Grassl B et al. Delay of type I diabetes in high risk, first degree relatives by parenteral antigen administration: the Schwabing Insulin Prophylaxis Pilot Trial. Diabetologia 1998; 41: 536-541
  • 11 Plotnick LP, Clark LM, Brancati FL et al. Safety and effectiveness of insulin pump therapy in children and adolescents with type 1 diabetes. Diabetes care 2003; 26: 1142-1146
  • 12 Bergenstal RM, Tamborlane WV, Ahmann A et al. Effectiveness of sensor-augmented insulin-pump therapy in type 1 diabetes. New Engl J Med 2010; 363: 311-320
  • 13 Gautier L, Cope L, Bolstad BM et al. affy – analysis of Affymetrix GeneChip data at the probe level. Bioinformatics 2004; 20: 307-315
  • 14 Irizarry RA, Hobbs B, Collin F. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 2003; 4: 249-264
  • 15 Diboun I, Wernisch L, Orengo C et al. Microarray analysis after RNA amplification can detect pronounced differences in gene expression using limma. BMC genomics 2006; 7: 252
  • 16 Chen H, Boutros P. VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R. BMC bioinformatics 2011; 12: 35
  • 17 Da Wei Huang BTS, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 2008; 4: 44-57
  • 18 Von Mering C, Huynen M, Jaeggi D et al. STRING: a database of predicted functional associations between proteins. Nucleic Acids Res 2003; 31: 258-261
  • 19 Cheng S, Baisch J, Krco C et al. Expression and function of HLA-DQ8 (DQA1* 0301/DQB1* 0302) genes in transgenic mice. Int J Immunogenet 1996; 23: 15-20
  • 20 Badenhoop K, Walfish PG, Rau H et al. Susceptibility and resistance alleles of human leukocyte antigen (HLA) DQA1 and HLA DQB1 are shared in endocrine autoimmune disease. J Clin Endocr Metab 1995; 80: 2112-2117
  • 21 Nepom GT. A unified hypothesis for the complex genetics of HLA associations with IDDM. Diabetes 1990; 39: 1153-1157
  • 22 Rot A, von Andrian UH. Chemokines in innate and adaptive host defense: basic chemokinese grammar for immune cells. Annu Rev Immunol 2004; 22: 891-928
  • 23 Luster AD. The role of chemokines in linking innate and adaptive immunity. Curr Opin Immunol 2002; 14: 129-135
  • 24 Sallusto F. The role of chemokine receptors in primary, effector and memory immune response. Exp Dermato 2002; 11: 476-478
  • 25 Eizirik DL, Colli ML, Ortis F. The role of inflammation in insulitis and β-cell loss in type 1 diabetes. Nat Rev Endocrinol 2009; 5: 219-226
  • 26 Cameron MJ, Arreaza GA, Grattan M et al. Differential Expression of CC Chemokines and the CCR5 Receptor in the Pancreas Is Associated with Progression to Type I Diabetes. J Immunol 2000; 165: 1102-1110
  • 27 Dubois-Laforgue D, Hendel H, Caillat-Zucman S et al. A common stromal cell-derived factor-1 chemokine gene variant is associated with the early onset of type 1 diabetes. Diabetes 2001; 50: 1211-1213
  • 28 Hanifi-Moghaddam P, Kappler S, Seissler J et al. Altered chemokine levels in individuals at risk of Type 1 diabetes mellitus. Diabetic Med 2006; 23: 156-163
  • 29 Chacko SA, Sul J, Song Y et al. Magnesium supplementation, metabolic and inflammatory markers, and global genomic and proteomic profiling: a randomized, double-blind, controlled, crossover trial in overweight individuals. Am J Clin Nutr 2011; 93: 463-473
  • 30 Glowacka E, Banasik M, Lewkowicz P et al. The Effect of LPS on Neutrophils from Patients with High Risk of Type 1 Diabetes Mellitus in relation to IL-8, IL-10 and IL-12 Production and Apoptosis In Vitro. Scand J Immunol 2002; 55: 210-217
  • 31 Lo H-C, Lin S-C, Wang Y-M. The relationship among serum cytokines, chemokine, nitric oxide, and leptin in children with type 1 diabetes mellitus. Clin Biochem 2004; 37: 666-672
  • 32 Migeotte I, Communi D, Parmentier M. Formyl peptide receptors: a promiscuous subfamily of G protein-coupled receptors controlling immune responses. Cytokine Growth F R 2006; 17: 501-519
  • 33 Chen K, Le Y, Liu Y et al. Cutting edge: a critical role for the G protein-coupled receptor mFPR2 in airway inflammation and immune responses. J Immunol 2010; 184: 3331-3335
  • 34 Carr ME. Diabetes mellitus: A hypercoagulable state. J Diabetes Complicat 2001; 15: 44-54