Vol 9, No 5 (2020)
Research paper
Published online: 2020-09-18

open access

Page views 675
Article views/downloads 663
Get Citation

Connect on Social Media

Connect on Social Media

Expression of Notch 2 and ABCC8 genes in patients with type 2 diabetes mellitus and their association with diabetic kidney disease

Yehia Ghanem, Azza Ismail, Rania Elsharkawy, Reem Fathalla, Amr El Feky
Clin Diabetol 2020;9(5):306-312.

Abstract

Background. The incidence of type 2 diabetes mellitus (T2DM) has increased over the past years and early identification and management of its complications especially diabetic kidney disease (DKD) is of great importance. T2DM and DKD are of multifactorial etiology with contribution of genetic and environmental factors. We aimed to study the expression of ABCC8 and Notch 2 genes in patients with T2DM and to find their association with DKD. Methods. The present work was carried on 80 patients with T2DM (40 with DKD and 40 without DKD) and 40 healthy subjects as a control group. Real time polymerase chain reaction was used to assess gene expression. Results. Altered expression of ABCC8 and Notch 2 genes were found in patients with T2DM compared to control group. ABCC8 expression had significant positive correlation with HbA1c while Notch 2 expression had significant positive correlation with fasting plasma glucose and HbA1c. Notch 2 expression was significantly higher in patients with DKD compared to those without DKD. Multivariate regression analysis showed that Notch 2 expression had independent relation with increased urinary albumin excretion and reduced estimated glomerular filtration rate. ABCC8 gene expression did not show significant difference between diabetic patients with DKD compared to those without DKD. Conclusion. Increased expression of ABCC8 and Notch 2 genes may play a role in pathogenesis of T2DM. Overexpression of Notch 2 gene may have a role in the development of albuminuria and DKD in patients with T2DM which may represent a possible diagnostic tool and a possible therapeutic target.

Article available in PDF format

View PDF Download PDF file

References

  1. Magliano DJ, Islam RM, Barr ELM, et al. Trends in incidence of total or type 2 diabetes: systematic review. BMJ. 2019; 366: l5003.
  2. International Diabetes Federation. IDF Diabetes Atlas, 9th edn. Brussels, Belgium:International Diabetes Federation, 2019.
  3. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care 2019; 42 (Supplement 1): S13-28. 2019.
  4. Mambiya M, Shang M, Wang Y, et al. The Play of Genes and Non-genetic Factors on Type 2 Diabetes. Front Public Health. 2019; 7: 349.
  5. Fowler MJ. Microvascular and Macrovascular Complications of Diabetes. Clinical Diabetes. 2011; 29(3): 116–122.
  6. American Diabetes Association. Microvascular Complications and Foot Care. Diabetes Care 2019; 42 (Suppl. 1): S124–38.
  7. Chang AR, Grams ME, Ballew SH, et al. CKD Prognosis Consortium (CKD-PC), Chronic Kidney Disease Prognosis Consortium, Chronic Kidney Disease Prognosis Consortium. Associations of kidney disease measures with mortality and end-stage renal disease in individuals with and without diabetes: a meta-analysis. Lancet. 2012; 380(9854): 1662–1673.
  8. Busiah K, Verkarre V, Cavé H, et al. Human pancreas endocrine cell populations and activating ABCC8 mutations. Horm Res Paediatr. 2014; 82(1): 59–64.
  9. Tinker A, Aziz Q, Li Y, et al. ATP-Sensitive Potassium Channels and Their Physiological and Pathophysiological Roles. Compr Physiol. 2018; 8(4): 1463–1511.
  10. Bolós V, Grego-Bessa J, de la Pompa JL. Notch signaling in development and cancer. Endocr Rev. 2007; 28(3): 339–363.
  11. Siebel C, Lendahl U. Notch Signaling in Development, Tissue Homeostasis, and Disease. Physiol Rev. 2017; 97(4): 1235–1294.
  12. Florez JC. Leveraging Genetics to Advance Type 2 Diabetes Prevention. PLoS Med. 2016; 13(7): e1002102.
  13. Florez JC. Mining the Genome for Therapeutic Targets. Diabetes. 2017; 66(7): 1770–1778.
  14. Levey AS, Stevens LA. Estimating GFR using the CKD Epidemiology Collaboration (CKD-EPI) creatinine equation: more accurate GFR estimates, lower CKD prevalence estimates, and better risk predictions. Am J Kidney Dis. 2010; 55(4): 622–627.
  15. Kuang J, Yan Xu, Genders AJ, et al. An overview of technical considerations when using quantitative real-time PCR analysis of gene expression in human exercise research. PLoS One. 2018; 13(5): e0196438.
  16. DeFronzo RA, Ferrannini E, Groop L, et al. Type 2 diabetes mellitus. Nat Rev Dis Primers. 2015; 1: 15019.
  17. Scott RA, Langenberg C, Sharp SJ. The link between family history and risk of type 2 diabetes is not explained by anthropometric, lifestyle or genetic risk factors: the EPIC-InterAct study. Diabetologia. 2013; 56 (1): 60–69.
  18. Vana DR, Adapa D, Prasad VS, et al. Diabetes mellitus types: key genetic determinants and risk assessment. Genetics and Molecular Research. 2019; 18(2).
  19. Bonfanti DH, Alcazar LP, Arakaki PA, et al. ATP-dependent potassium channels and type 2 diabetes mellitus. Clin Biochem. 2015; 48(7-8): 476–482.
  20. Viji D, Aswathi P, Charmine PP, et al. Genetic association of ABCC8 rs757110 polymorphism with Type 2 Diabetes Mellitus risk: A case-control study in South India and a meta-analysis. Gene Reports. 2018; 13: 220–228.
  21. Sokolova EA, Bondar IA, Shabelnikova OY, et al. Replication of KCNJ11 (p.E23K) and ABCC8 (p.S1369A) Association in Russian Diabetes Mellitus 2 Type Cohort and Meta-Analysis. PLoS One. 2015; 10(5): e0124662.
  22. Qin LJ, Lv Y, Huang QY. Meta-analysis of association of common variants in the KCNJ11-ABCC8 region with type 2 diabetes. Genet Mol Res. 2013; 12(3): 2990–3002.
  23. Stefanski A, Majkowska L, Ciechanowicz A, et al. The common C49620T polymorphism in the sulfonylurea receptor gene (ABCC8), pancreatic beta cell function and long-term diabetic complications in obese patients with long-lasting type 2 diabetes mellitus. Exp Clin Endocrinol Diabetes. 2007; 115(5): 317–321.
  24. Zeggini E, Scott LJ, Saxena R, et al. Wellcome Trust Case Control Consortium. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nat Genet. 2008; 40(5): 638–645.
  25. Kim W, Shin YK, Kim BJ, et al. Notch signaling in pancreatic endocrine cell and diabetes. Biochem Biophys Res Commun. 2010; 392(3): 247–251.
  26. Niranjan T, Bielesz B, Gruenwald A, et al. The Notch pathway in podocytes plays a role in the development of glomerular disease. Nat Med. 2008; 14(3): 290–298.
  27. Bonegio R, Susztak K. Notch signaling in diabetic nephropathy. Exp Cell Res. 2012; 318(9): 986–992.
  28. Matoba K, Kawanami D, Nagai Y, et al. Rho-Kinase Blockade Attenuates Podocyte Apoptosis by Inhibiting the Notch Signaling Pathway in Diabetic Nephropathy. Int J Mol Sci. 2017; 18(8).
  29. Murea M, Park JK, Sharma S, et al. Expression of Notch pathway proteins correlates with albuminuria, glomerulosclerosis, and renal function. Kidney Int. 2010; 78(5): 514–522.
  30. Sharaf SA, Kantoush NA, Ayoub DF, et al. Altered expression of WFS1 and NOTCH2 genes associated with diabetic nephropathy in T2DM patients. Diabetes Res Clin Pract. 2018; 140: 304–313.