Open Access

Identification of core genes and pathways in type 2 diabetes mellitus by bioinformatics analysis

  • Authors:
    • Linchao Ding
    • Lei Fan
    • Xiaodong Xu
    • Jianfei Fu
    • Yadong Xue
  • View Affiliations

  • Published online on: July 24, 2019     https://doi.org/10.3892/mmr.2019.10522
  • Pages: 2597-2608
  • Copyright: © Ding et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Type 2 diabetes mellitus (T2DM) is a metabolic disorder. Numerous proteins have been identified that are associated with the occurrence and development of T2DM. This study aimed to identify potential core genes and pathways involved in T2DM, through exhaustive bioinformatic analyses using GSE20966 microarray profiles of pancreatic β‑cells obtained from healthy controls and patients with T2DM. The original microarray data were downloaded from the Gene Expression Omnibus database. Data were processed by the limma package in R software and the differentially expressed genes (DEGs) were identified. Gene Ontology functional analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were carried out to identify potential biological functions and pathways of the DEGs. Key transcription factors were identified using the WEB‑based GEne SeT AnaLysis Toolkit (WebGestalt) and Enrichr. The Search Tool for the Retrieval of Interacting Genes (STRING) database was used to establish a protein‑protein interaction (PPI) network for the DEGs. In total, 329 DEGs were involved in T2DM, with 208 upregulated genes enriched in pancreatic secretion and the complement and coagulation cascades, and 121 downregulated genes enriched in insulin secretion, carbohydrate digestion and absorption, and the Toll‑like receptor pathway. Furthermore, hepatocyte nuclear factor 1‑alpha (HNF1A), signal transducer and activator of transcription 3 (STAT3) and glucocorticoid receptor (GR) were key transcription factors in T2DM. Twenty important nodes were detected in the PPI network. Finally, two core genes, serpin family G member 1 (SERPING1) and alanyl aminopeptidase, membrane (ANPEP), were shown to be associated with the development of T2DM. On the whole, the findings of this study enhance our understanding of the potential molecular mechanisms of T2DM and provide potential targets for further research.

References

1 

Ogurtsova K, da Rocha Fernandes JD, Huang Y, Linnenkamp U, Guariguata L, Cho NH, Cavan D, Shaw JE and Makaroff LE: IDF diabetes atlas: Global estimates for the prevalence of diabetes for 2015 and 2040. Diabetes Res Clin Pract. 128:40–50. 2017. View Article : Google Scholar : PubMed/NCBI

2 

Zhao Q, Zhang A, Zong W, An N, Zhang H, Luan Y, Sun H, Wang X and Cao H: Exploring potential biomarkers and determining the metabolic mechanism of type 2 diabetes mellitus using liquid chromatography coupled to high-resolution mass spectrometry. RSC Adv. 7:441862017. View Article : Google Scholar

3 

Leibowitz G, Kaiser N and Cerasi E: Balancing needs and means: The dilemma of the beta-cell in the modern world. Diabetes Obes Metab. 11 (Suppl 4):S1–S9. 2009. View Article : Google Scholar

4 

Hoshino A, Ariyoshi M, Okawa Y, Kaimoto S, Uchihashi M, Fukai K, Iwai-Kanai E, Ikeda K, Ueyama T, Ogata T and Matoba S: Inhibition of p53 preserves Parkin-mediated mitophagy and pancreatic β-cell function in diabetes. Proc Natl Acad Sci USA. 111:3116–3121. 2014. View Article : Google Scholar : PubMed/NCBI

5 

Chaurasia B and Summers SA: Ceramides-lipotoxic inducers of metabolic disorders. Trends Endocrinol Metab. 26:538–550. 2015. View Article : Google Scholar : PubMed/NCBI

6 

Park YJ, Lee S, Kieffer TJ, Warnock GL, Safikhan N, Speck M, Hao Z, Woo M and Marzban L: Deletion of Fas protects islet beta cells from cytotoxic effects of human islet amyloid polypeptide. Diabetologia. 1–Feb;2012.(Epub ahead of print). View Article : Google Scholar :

7 

Marselli L, Thorne J, Dahiya S, Sgroi DC, Sharma A, Bonner-Weir S, Marchetti P and Weir GC: Gene expression profiles of beta-cell enriched tissue obtained by laser capture microdissection from subjects with type 2 diabetes. PLoS One. 5:e114992010. View Article : Google Scholar : PubMed/NCBI

8 

Troyanskaya O, Cantor M, Sherlock G, Brown P, Hastie T, Tibshirani R, Botstein D and Altman RB: Missing value estimation methods for DNA microarrays. Bioinformatics. 17:520–525. 2001. View Article : Google Scholar : PubMed/NCBI

9 

Bolstad BM, Irizarry RA, Astrand M and Speed TP: A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics. 19:185–193. 2003. View Article : Google Scholar : PubMed/NCBI

10 

Livak KJ and Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods. 25:402–408. 2001. View Article : Google Scholar : PubMed/NCBI

11 

Espina V, Wulfkuhle JD, Calvert VS, VanMeter A, Zhou W, Coukos G, Geho DH, Petricoin EF III and Liotta LA: Laser-capture microdissection. Nat Protoc. 1:586–603. 2006. View Article : Google Scholar : PubMed/NCBI

12 

Lontchi-Yimagou E, Sobngwi E, Matsha TE and Kengne AP: Diabetes mellitus and inflammation. Curr Diab Rep. 13:435–444. 2013. View Article : Google Scholar : PubMed/NCBI

13 

Velloso LA, Eizirik DL and Cnop M: Type 2 diabetes mellitus-an autoimmune disease? Nat Rev Endocrinol. 9:750–755. 2013. View Article : Google Scholar : PubMed/NCBI

14 

Arystarkhova E, Liu YB, Salazar C, Stanojevic V, Clifford RJ, Kaplan JH, Kidder GM and Sweadner KJ: Hyperplasia of pancreatic beta cells and improved glucose tolerance in mice deficient in the FXYD2 subunit of Na,K-ATPase. J Biol Chem. 288:7077–7085. 2013. View Article : Google Scholar : PubMed/NCBI

15 

Arystarkhova E: Beneficial renal and pancreatic phenotypes in a mouse deficient in FXYD2 regulatory subunit of Na,K-ATPase. Front Physiol. 7:882016. View Article : Google Scholar : PubMed/NCBI

16 

Markiewski MM and Lambris JD: The role of complement in inflammatory diseases from behind the scenes into the spotlight. Am J Pathol. 171:715–727. 2007. View Article : Google Scholar : PubMed/NCBI

17 

Huang C, Fisher KP, Hammer SS, Navitskaya S, Blanchard GJ and Busik JV: Plasma exosomes contribute to microvascular damage in diabetic retinopathy by activating classical complement pathway. Diabetes. 67:1639–1649. 2018. View Article : Google Scholar : PubMed/NCBI

18 

Flyvbjerg A: The role of the complement system in diabetic nephropathy. Nat Rev Nephrol. 13:311–318. 2017. View Article : Google Scholar : PubMed/NCBI

19 

Uldry M and Thorens B: The SLC2 family of facilitated hexose and polyol transporters. Pflugers Arch. 447:480–489. 2004. View Article : Google Scholar : PubMed/NCBI

20 

Laukkanen O, Lindström J, Eriksson J, Valle TT, Hämäläinen H, Ilanne-Parikka P, Keinänen-Kiukaanniemi S, Tuomilehto J, Uusitupa M and Laakso M; Finnish Diabetes Prevention Study, : Polymorphisms in the SLC2A2 (GLUT2) gene are associated with the conversion from impaired glucose tolerance to type 2 diabetes: The finnish diabetes prevention study. Diabetes. 54:2256–2260. 2005. View Article : Google Scholar : PubMed/NCBI

21 

Leturque A, Brot-Laroche E and Le Gall M: GLUT2 mutations, translocation, and receptor function in diet sugar managing. Am J Physiol Endocrinol Metab. 296:E985–E992. 2009. View Article : Google Scholar : PubMed/NCBI

22 

Takeda K, Kaisho T and Akira S: Toll-like receptors. Annu Rev Immunol. 21:335–376. 2003. View Article : Google Scholar : PubMed/NCBI

23 

Dasu MR, Devaraj S, Zhao L, Hwang DH and Jialal I: High glucose induces toll-like receptor expression in human monocytes: Mechanism of activation. Diabetes. 57:3090–3098. 2008. View Article : Google Scholar : PubMed/NCBI

24 

Miyahara S, Kiryu J, Yamashiro K, Miyamoto K, Hirose F, Tamura H, Katsuta H, Nishijima K, Tsujikawa A and Honda Y: Simvastatin inhibits leukocyte accumulation and vascular permeability in the retinas of rats with streptozotocin-induced diabetes. Am J Pathol. 164:1697–1706. 2004. View Article : Google Scholar : PubMed/NCBI

25 

Rajamani U and Jialal I: Hyperglycemia induces Toll-like receptor-2 and −4 expression and activity in human microvascular retinal endothelial cells: Implications for diabetic retinopathy. J Diabetes Res. 2014:7909022014. View Article : Google Scholar : PubMed/NCBI

26 

Chiu KC, Chuang LM, Chu A, Yoon C and Wang M: Comparison of the impact of the I27L polymorphism of the hepatocyte nuclear factor-1alpha on estimated and measured beta cell indices. Eur J Endocrinol. 148:641–647. 2003. View Article : Google Scholar : PubMed/NCBI

27 

Morita K, Saruwatari J, Tanaka T, Oniki K, Kajiwara A, Otake K, Ogata Y and Nakagawa K: Associations between the common HNF1A gene variant p.I27L (rs1169288) and risk of type 2 diabetes mellitus are influenced by weight. Diabetes Metab. 41:91–94. 2015. View Article : Google Scholar : PubMed/NCBI

28 

Gu N, Tsuda M, Matsunaga T, Adachi T, Yasuda K, Ishihara A and Tsuda K: Glucose regulation of dipeptidyl peptidase IV gene expression is mediated by hepatocyte nuclear factor-1alpha in epithelial intestinal cells. Clin Exp Pharmacol Physiol. 35:1433–1439. 2008.PubMed/NCBI

29 

Pedersen KB, Chhabra KH, Nguyen VK, Xia H and Lazartigues E: The transcription factor HNF1α induces expression of angiotensin-converting enzyme 2 (ACE2) in pancreatic islets from evolutionarily conserved promoter motifs. Biochim Biophys Acta. 1829:1225–1235. 2013. View Article : Google Scholar : PubMed/NCBI

30 

Banes-Berceli AK, Ketsawatsomkron P, Ogbi S, Patel B, Pollock DM and Marrero MB: Angiotensin II and endothelin-1 augment the vascular complications of diabetes via JAK2 activation. Am J Physiol Heart Circ Physiol. 293:H1291–H1299. 2007. View Article : Google Scholar : PubMed/NCBI

31 

Tiano JP, Delghingaro-Augusto V, Le May C, Liu S, Kaw MK, Khuder SS, Latour MG, Bhatt SA, Korach KS, Najjar SM, et al: Estrogen receptor activation reduces lipid synthesis in pancreatic islets and prevents β cell failure in rodent models of type 2 diabetes. J Clin Invest. 121:3331–3342. 2011. View Article : Google Scholar : PubMed/NCBI

32 

Ezzat S, Zheng L, Florez JC, Stefan N, Mayr T, Hliang MM, Jablonski K, Harden M, Stančáková A, Laakso M, et al: The cancer-associated FGFR4-G388R polymorphism enhances pancreatic insulin secretion and modifies the risk of diabetes. Cell Metab. 17:929–940. 2013. View Article : Google Scholar : PubMed/NCBI

33 

Geelen CC, van Greevenbroek MM, van Rossum EF, Schaper NC, Nijpels G, 't Hart LM, Schalkwijk CG, Ferreira I, van der Kallen CJ and Sauerwein HP: BclI glucocorticoid receptor polymorphism is associated with greater body fatness: The Hoorn and CODAM studies. J Clin Endocrinol Metab. 98:E595–E599. 2013. View Article : Google Scholar : PubMed/NCBI

34 

Syed AA, Halpin CG, Irving JA, Unwin NC, White M, Bhopal RS, Redfern CP and Weaver JU: A common intron 2 polymorphism of the glucocorticoid receptor gene is associated with insulin resistance in men. Clin Endocrinol (Oxf). 68:879–884. 2008. View Article : Google Scholar : PubMed/NCBI

35 

Lu L, Pu LJ, Xu XW, Zhang Q, Zhang RY, Zhang JS, Hu J, Yang ZK, Lu AK, Ding FH, et al: Association of serum levels of glycated albumin, C-reactive protein and tumor necrosis factor-alpha with the severity of coronary artery disease and renal impairment in patients with type 2 diabetes mellitus. Clin Biochem. 40:810–816. 2007. View Article : Google Scholar : PubMed/NCBI

36 

Jin C, Lu L, Zhang RY, Zhang Q, Ding FH, Chen QJ and Shen WF: Association of serum glycated albumin, C-reactive protein and ICAM-1 levels with diffuse coronary artery disease in patients with type 2 diabetes mellitus. Clin Chim Acta. 408:45–49. 2009. View Article : Google Scholar : PubMed/NCBI

37 

Rodiño-Janeiro BK, González-Peteiro M, Ucieda-Somoza R, González-Juanatey JR and Alvarez E: Glycated albumin, a precursor of advanced glycation end-products, up-regulates NADPH oxidase and enhances oxidative stress in human endothelial cells: Molecular correlate of diabetic vasculopathy. Diabetes Metab Res Rev. 26:550–558. 2010. View Article : Google Scholar : PubMed/NCBI

38 

Ichihara A, Sakoda M, Mito-Kurauchi A and Itoh H: Activated prorenin as a therapeutic target for diabetic nephropathy. Diabetes Res Clin Pract. 82 (Suppl 1):S63–S66. 2008. View Article : Google Scholar : PubMed/NCBI

39 

Yokota H, Nagaoka T, Tani T, Takahashi A, Sato E, Kato Y and Yoshida A: Higher levels of prorenin predict development of diabetic retinopathy in patients with type 2 diabetes. J Renin Angiotensin Aldosterone Syst. 12:290–294. 2011. View Article : Google Scholar : PubMed/NCBI

40 

Kamiyama M, Urushihara M, Morikawa T, Konishi Y, Imanishi M, Nishiyama A and Kobori H: Oxidative stress/angiotensinogen/renin-angiotensin system axis in patients with diabetic nephropathy. Int J Mol Sci. 14:23045–23062. 2013. View Article : Google Scholar : PubMed/NCBI

41 

Engström G, Hedblad B, Eriksson KF, Janzon L and Lindgärde F: Complement C3 is a risk factor for the development of diabetes: A population-based cohort study. Diabetes. 54:570–575. 2005. View Article : Google Scholar : PubMed/NCBI

42 

Yang S, Li Q, Song Y, Tian B, Cheng Q, Qing H, Zhong L and Xia W: Serum complement C3 has a stronger association with insulin resistance than high-sensitivity C-reactive protein in women with polycystic ovary syndrome. Fertil Steril. 95:1749–1753. 2011. View Article : Google Scholar : PubMed/NCBI

43 

Wlazlo N, van Greevenbroek MM, Ferreira I, Feskens EJ, van der Kallen CJ, Schalkwijk CG, Bravenboer B and Stehouwer CD: Complement factor 3 is associated with insulin resistance and with incident type 2 diabetes over a 7-year follow-up period: The CODAM study. Diabetes Care. 37:1900–1909. 2014. View Article : Google Scholar : PubMed/NCBI

44 

Ribbing J, Hamrén B, Svensson MK and Karlsson MO: A model for glucose, insulin, and beta-cell dynamics in subjects with insulin resistance and patients with type 2 diabetes. J Clin Pharmacol. 50:861–872. 2010. View Article : Google Scholar : PubMed/NCBI

45 

Atanes P, Ruz-Maldonado I, Pingitore A, Hawkes R, Liu B, Zhao M, Huang GC, Persaud SJ and Amisten S: C3aR and C5aR1 act as key regulators of human and mouse β-cell function. Cell Mol Life Sci. 75:715–726. 2018. View Article : Google Scholar : PubMed/NCBI

46 

Dos Santos RS, Marroqui L, Grieco FA, Marselli L, Suleiman M, Henz SR, Marchetti P, Wernersson R and Eizirik DL: Protective role of complement C3 against cytokine-mediated β-cell apoptosis. Endocrinology. 158:2503–2521. 2017. View Article : Google Scholar : PubMed/NCBI

47 

Nawaz MI, Van Raemdonck K, Mohammad G, Kangave D, Van Damme J, Abu El-Asrar AM and Struyf S: Autocrine CCL2, CXCL4, CXCL9 and CXCL10 signal in retinal endothelial cells and are enhanced in diabetic retinopathy. Exp Eye Res. 109:67–76. 2013. View Article : Google Scholar : PubMed/NCBI

48 

Liu ZH, Chen LL, Deng XL, Song HJ, Liao YF, Zeng TS, Zheng J and Li HQ: Methylation status of CpG sites in the MCP-1 promoter is correlated to serum MCP-1 in Type 2 diabetes. J Endocrinol Invest. 35:585–589. 2012.PubMed/NCBI

49 

Ninomiya H, Katakami N, Osonoi T, Saitou M, Yamamoto Y, Takahara M, Kawamori D, Matsuoka TA, Yamasaki Y and Shimomura I: Association between new onset diabetic retinopathy and monocyte chemoattractant protein-1 (MCP-1) polymorphism in Japanese type 2 diabetes. Diabetes Res Clin Pract. 108:e35–e37. 2015. View Article : Google Scholar : PubMed/NCBI

50 

Mina-Osorio P: The moonlighting enzyme CD13: Old and new functions to target. Trends Mol Med. 14:361–371. 2008. View Article : Google Scholar : PubMed/NCBI

51 

Pedersen HK, Gudmundsdottir V and Brunak S: Pancreatic islet protein complexes and their dysregulation in type 2 diabetes. Front Genet. 8:432017. View Article : Google Scholar : PubMed/NCBI

52 

Locke JM, Hysenaj G, Wood AR, Weedon MN and Harries LW: Targeted allelic expression profiling in human islets identifies cis-regulatory effects for multiple variants identified by type 2 diabetes genome-wide association studies. Diabetes. 64:1484–1491. 2015. View Article : Google Scholar : PubMed/NCBI

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Copy and paste a formatted citation
APA
Ding, L., Fan, L., Xu, X., Fu, J., & Xue, Y. (2019). Identification of core genes and pathways in type 2 diabetes mellitus by bioinformatics analysis. Molecular Medicine Reports, 20, 2597-2608. https://doi.org/10.3892/mmr.2019.10522
MLA
Ding, L., Fan, L., Xu, X., Fu, J., Xue, Y."Identification of core genes and pathways in type 2 diabetes mellitus by bioinformatics analysis". Molecular Medicine Reports 20.3 (2019): 2597-2608.
Chicago
Ding, L., Fan, L., Xu, X., Fu, J., Xue, Y."Identification of core genes and pathways in type 2 diabetes mellitus by bioinformatics analysis". Molecular Medicine Reports 20, no. 3 (2019): 2597-2608. https://doi.org/10.3892/mmr.2019.10522