Tissue-Specific Molecular Biomarker Signatures of Type 2 Diabetes: An Integrative Analysis of Transcriptomics and Protein-Protein Interaction Data

OMICS A Journal of Integrative Biology

Volumn 19, Issue 9, 2015, Pages 563-573

  Calimlioglu, Beste ^a,b   Karagoz, Kubra ^a   Sevimoglu, Tuba ^a   Kilic, Elif ^a   Gov, Esra ^a   Arga, Kazim Yalcin ^a  

^a MARMARA UNIVERSITY   (Turkey)

^b ISTANBUL MEDENIYET UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACID; BIOLOGICAL MARKER; CARNITINE; CELL NUCLEUS RECEPTOR; CHOLESTEROL; COENZYME A; MALIC ACID; MICRORNA; MICRORNA 16; MIRN335 MICRORNA, HUMAN; PROTEIN BINDING;

ARTERIAL TISSUE; ARTICLE; BLOOD CLOTTING; CELLS; CELLS BY BODY ANATOMY; DEGENERATIVE DISEASE; GENE INTERACTION; LIVER; METABOLISM; METABOLOME; NON INSULIN DEPENDENT DIABETES MELLITUS; PANCREAS ISLET; PERIPHERAL BLOOD MONONUCLEAR CELL; PRIORITY JOURNAL; PROTEIN INTERACTION; PROTEIN PROTEIN INTERACTION; SKELETAL MUSCLE; TRANSCRIPTOMICS; GENE EXPRESSION PROFILING; GENETICS; HUMAN; PROCEDURES;

BIOMARKERS; DIABETES MELLITUS, TYPE 2; GENE EXPRESSION PROFILING; HUMANS; MICRORNAS; PROTEIN BINDING;

EID: 84941114874     PISSN: 15362310     EISSN: 15578100     Source Type: Journal    
DOI: 10.1089/omi.2015.0088     Document Type: Article

References (61)

1. Agren R, Liu L, Shoaie S, Vongsangnak W, Nookaew I, and Nielsen J. (2013). The RAVEN toolbox and its use for generating a genome-scale metabolic model for Penicillium chrysogenum. PLoS Comput Biol 9, e1002980.
2. Alzahrani SH, and Ajjan, RA. (2010). Coagulation and fibrinolysis in diabetes. Diab Vasc Dis Res 7, 260-273.
3. Barrett T, Wilhite SE, Ledoux P, et al. (2013). NCBI GEO: Archive for functional genomics data sets-update. Nucleic Acids Res 41, D991-D995.
4. Cangemi C, Skov V, Poulsen MK, et al. (2011). Fibulin-1 is a marker for arterial extracellular matrix alterations in type 2 diabetes. Clin Chem 57, 1556-1565.
5. Chacko BK, Scott DW, Chandler RT, and Patel RP. (2011). Endothelial surface N-glycans mediate monocyte adhesion and are targets for anti-inflammatory effects of peroxisome proliferator-activated receptor c ligands. J Biol Chem 286, 38738-38747.
6. Chagoyen M, and Pazos F. (2011). MBRole: Enrichment analysis of metabolomic data. Bioinformatics 27, 730-731.
7. Chin CH, Chen SH, Wu HH, Ho CW, Ko MT, and Lin CY. (2014). cytoHubba. BMC Systems Biology 8, S11.
8. Corsten MF, Papageorgiou A, Verhesen W, et al. (2012). MicroRNA profiling identifies microRNA-155 as an adverse mediator of cardiac injury and dysfunction during acute viral myocarditis. Circ Res 111, 415-425.
9. Del Guerra S, Lupi R, Marselli L, et al. (2005). Functional and molecular defects of pancreatic islets in human type 2 diabetes. Diabetes 54, 727-735.
10. Dominguez V, Raimondi C, Somanath S, et al. (2011). Class II phosphoinositide 3-kinase regulates exocytosis of insulin granules in pancreatic b cells. J Biol Chem 286, 4216-4225.
11. Elena JW, Steplowski E, Yu K, et al. (2013). Diabetes and risk of pancreatic cancer: A pooled analysis from the pancreatic cancer cohort consortium. Cancer Causes Control 24, 13-25.
12. Erem C, Hacihasanoglu A, Celik S, et al. (2005). Coagulation and fibrinolysis parameters in type 2 diabetic patients with and without diabetic vascular complications. Med Princ Pract 14, 22-30.
13. Fujita T. (2013). Extra-immunological role of complement activation in diabetic nephropathy. Biomedicine 1, 1-5.
14. Garcia Barrado MJ, Iglesias Osma MC, Blanco EJ, et al. (2015). Dopamine modulates insulin release and is involved in the survival of rat pancreatic beta cells. PLoS One 10, e0123197.
15. Giovannucci E, Harlan DM, Archer MC, et al. (2010). Diabetes and cancer: CA 60, 207-221.
16. Günther OP, Shin H, Ng RT, McMaster WR, McManus BM, Keown PA, Tebbutt SJ, and Le Cao KA. (2014). Novel multivariate methods for integration of genomics and proteomics data: Applications in a kidney transplant rejection study. OMICS 18, 682-695.
17. Hsu SD, Tseng YT, Shrestha S, et al. (2014). miRTarBase update 2014: An information resource for experimentally validated miRNA-target interactions. Nucleic Acids Res 42, D78-D85.
18. Hu G, Jousilahti P, Bidel S, Antikainen R, and Tuomilehto J. (2007). Type 2 diabetes and the risk of Parkinson's disease. Diabetes Care 30, 842-847.
19. Huang DW, Sherman BT, and Lempicki RA. (2009). Bioinformatics enrichment tools: Paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res 37, 1-13.
20. Huang Y, Shen XJ, Zou Q, Wang SP, Tang SM, and Zhang GZ. (2011). Biological functions of microRNAs: A review. J Physiol Biochem 67, 129-139.
21. Irizarry RA, Hobbs B, Collin F, et al. (2003). Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4, 249-264.
22. Kaizer EC, Glaser CL, Chaussabel D, Banchereau J, Pascual V, and White PC. (2007). Gene expression in peripheral blood mononuclear cells from children with diabetes. J Clin Endocrinol Metab 92, 3705-3711.
23. Kanehisa M, Goto S, Sato Y, Furumichi M, and Tanabe M. (2011). KEGG for integration and interpretation of largescale molecular data sets. Nucleic Acids Res 988,1-6.
24. Karagoz K, Sinha R, and Arga KY. (2015). Triple negative breast cancer: A multi-Omics network discovery strategy for candidate targets and driving pathways. Omics 19, 115-130.
25. Keller MP, Choi Y, Wang P, et al. (2008). A gene expression network model of type 2 diabetes links cell cycle regulation in islets with diabetes susceptibility. Genome Res 18, 706-716.
26. Liu XX, Li XJ, Zhang B, et al. (2011). MicroRNA-26b is under expressed in human breast cancer and induces cell apoptosis by targeting SLC7A11. FEBS Lett 585, 1363-1367.
27. Ma YL, Zhang P, Wang F, et al. (2011). Human embryonic stem cells and metastatic colorectal cancer cells shared the common endogenous human microRNA-26b. J Cell Mol Med 15, 1941-1954.
28. Mardinoglu A, Agren R, Kampf C, Asplund A, Uhlen M, and Nielsen J. (2014). Genome-scale metabolic modelling of hepatocytes reveals serine deficiency in patients with nonalcoholic fatty liver disease. Nat Commun 5, 3083.
29. Marselli L, Thorne J, Dahiya S, et al (2010). Gene Expression Profiles of Beta-cell Enriched Tissue Obtained by Laser Capture Microdissection from Subjects with Type 2 diabetes PLoS One 5 e11499
30. Misu H, Takamura T, Takayama H, et al. (2010). A liverderived secretory protein, selenoprotein P, causes insulin resistance. Cell Metab 12, 483-495.
31. Montague E, Stanberry L, Higdon R, et al. (2014). MOPED 2. 5-An integrated multi-omics resource: Multi-omics profiling expression database now includes transcriptomics data. OMICS 18, 335-343.
32. Mootha VK, Lindgren CM, Eriksson KF, et al. (2003). PGC-1aresponsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nature Genetics 34, 267-273.
33. Mudunuri U, Che A, Yi M, and Stephens RM. (2009). bioDBnet: The biological database network. Bioinformatics 25, 555-556.
34. Mukai R, Tomimaru Y, Nagano H, et al. (2015). miR-615-3p expression level in bone marrow is associated with tumor recurrence in hepatocellular carcinoma. Mol Clin Oncol 3, 487-494.
35. Musselman DL, Betan E, Larsen H, and Phillips LS. (2003). Relationship of depression to diabetes types 1 and 2: Epidemiology, biology, and treatment. Biol Psychiatr 54, 317-329.
36. Oikonomopoulou K, Ricklin D, Ward PA and Lambris JD. (2012). Interactions between coagulation and complement-Their role in inflammation. Semin Immunopathol 34, 151-165.
37. Portales Casamar E, Thongjuea S, Kwon AT, et al. (2010). JASPAR 2010: The greatly expanded open-access database of transcription factor binding profiles. Nucleic Acids Res 38, 105-110.
38. Prentki M, and Nolan CJ. (2006). Islet b-cell failure in type 2 diabetes. J Clin Investig 116, 1802-1812.
39. Razick S, Magklaras G, and Donaldson IM. (2008). iRefIndex: A consolidated protein interaction database with provenance. BMC Bioinformatics 9, 405.
40. Retnakaran R, Cull CA, Thorne KI, Adler AI, and Holman RR. (2006). Risk factors for renal dysfunction in type 2 diabetes UK Prospective Diabetes Study 74. Diabetes 55, 1832-1839.
41. Sahu J, Sen P, Choudhury MD, Dehury B, Barooah M, Modi MK, and Talukdar AD. (2014). Rediscovering medicinal plants' potential with OMICS: microsatellite survey in expressed sequence tags of eleven traditional plants with potent antidiabetic properties. OMICS 18, 298-309.
42. Santiago JA, Scherzer CR, and Potashkin JA. (2013). Specific splice variants are associated with Parkinson's disease. Mov Disord 28, 1724-1727.
43. Sevimoglu T, and Arga KY. (2014). The role of protein interaction networks in systems biomedicine. Comput Struct Biotechnol J 11, 22-27.
44. Shan ZX, Lin QX, Deng CY, et al. (2010). miR-1/miR-206 regulate Hsp60 expression contributing to glucose-mediated apoptosis in cardiomyocytes. FEBS Lett 584, 3592-3600.
45. Shannon P, Markiel A, Ozier O, et al. (2003). Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res 13, 2498-2504.
46. Skov V, Knudsen S, Olesen M, Hansen ML, and Rasmussen LM. (2012). Global gene expression profiling displays a network of dysregulated genes in non-atherosclerotic arterial tissue from patients with type 2 diabetes. Cardiovasc. Diabetol 11, 15.
47. Smyth GK. (2005). Limma: Linear models for microarray data. In: Bioinformatics and Computational Biology Solutions Using R and Bioconductor. Springer, New York.
48. Sun T, Fu M, Bookout AL, Kliewer SA, and Mangelsdorf DJ. (2009). MicroRNA let-7 regulates 3T3-L1 adipogenesis. Mol Endocrinol 23, 925-931.
49. Taneera J, Fadista J, Ahlqvist E, Zhang M, Wierup N, Renström E, and Groop L. (2013). Expression profiling of cell cycle genes in human pancreatic islets with and without type 2 diabetes. Mol Cell Endocrinol 375, 35-42.
50. Taneera J, Lang S, Sharma A, et al. (2012). A systems genetics approach identifies genes and pathways for type 2 diabetes in human islets. Cell Metab 16, 122-134.
51. Thiele I, Swainston N, Fleming RMT, et al. (2013). A community-driven global reconstruction of human metabolism. Nat Biotechnol 31, 419-425.
52. Tsilidis KK, Kasimis JC, Lopez DS, Ntzani EE, and Ioannidis JP. (2015). Type 2 diabetes and cancer: Umbrella review of meta-analyses of observational studies. BMJ 350, 7607.
53. Van Tienen FHJ, Praet SFE, de Feyter HM, et al. (2012). Physical activity is the key determinant of skeletal muscle mitochondrial function in type 2 diabetes. J Clin Endocrinol Metab 97, 3261-3269.
54. Vinciguerra M, Sgroi A, Veyrat-Durebex C, Rubbia-Brandt L, Buhler LH, and Foti M. (2009). Unsaturated fatty acids inhibit the expression of tumor suppressor phosphatase and tensin homolog (PTEN) via microRNA-21 up-regulation in hepatocytes. Hepatology 49, 1176-1184.
55. Wang XH Qian RZ, Zhang W, Chen SF, Jin HM, and Hu RM. (2009). MicroRNA-320 expression in myocardial microvas-cular endothelial cells and its relationship with insulin-like growth factor-1 in type 2 diabetic rats. Clin Exp Pharmacol Physiol 36,181-188.
56. Xu CX., Zhu HH, and Zhu YM. (2014). Diabetes and cancer: Associations, mechanisms, and implications for medical practice. World J Diabetes 5, 372.
57. Yang J, Li S, and Liu YX. (2013). Systematic analysis of diabetes-and glucose metabolism-related proteins and its application to Alzheimer's disease. J Biomed Sci Eng 6, 615-644.
58. Yürekli BPS, Ozcebe OI, Kirazli S, and Gürlek A. (2006). Global assessment of the coagulation status in type 2 diabetes mellitus using rotation thromboelastography. Blood Coagul Fibrinolysis 17, 545-549.
59. Zhang L, Zhou M, Wang Y, Huang W, Qin G, Weintraub NL, and Tang Y. (2014). miR-92a inhibits vascular smooth muscle cell apoptosis: Role of the MKK4-JNK pathway. Apoptosis 19, 975-983.
60. Zhang X, Gao L, Liu ZP, and Chen L. (2015). Identifying module biomarker in type 2 diabetes mellitus by discriminative area of functional activity. BMC Bioinformat 16, 92.
61. Zhu L, Chen L, Shi CM, et al. (2014). MiR-335, an adipogenesis-related microRNA, is involved in adipose tissue inflammation. Cell Biochem Biophys 68, 283-290.