Amal MH Mackawy*, Entisar Abd-Alfarag Ahmed and Mohammed EH Badawy
Background: Type 2 diabetes (T2D) is a heterogeneous disorder that results from a combination of environmental and genetic factors. Insulin resistance (IR) is the core defect in T2D. The molecular mechanisms underlying IR are poorly understood. Protein tyrosine kinases and Protein tyrosine phosphatase 1B (PTPN1) are important regulators of insulin signal transduction. The association of PTPN1single-nucleotide polymorphisms (SNPs) with traits related to T2D has been investigated. The aim of this study was to determine the association of 1023C>A and 467T>C gene polymorphisms with Type 2 diabetes and its related metabolic traits.
Method: Polymerase chain reaction/restriction fragment length polymorphism (PCR-RFLP) analyses were carried out to detect the 1023C>A and 467T>C variants of PTPN1 gene in 100 Egyptian patients with T2D as compared to controls (n=80).
Results: The 1023C>A PTPN1genotype was significantly associated with T2DM (X2=7.816, P=0.02). The C allele was more frequent in the T2DM as compared to controls (p=0.001), odds ratio (OR) and 95% CI= 0.282 (0.131-0.606). We did not observe any significant difference in 467T>C PTPN1 genotypes between patients and control groups (X2=2.205, P=0.332). 1023C>A and 467T>C PTPN1 variants showed non-significant association with diabetic metabolic traits in both groups; plasma insulin levels, fasting blood glucose levels (FBG), HOMA-IR, the lipid profile parameters , diastolic blood pressure (DBP), systolic blood pressure (SBP), Waist circumference (WC) and body mass index (BMI).
Conclusion: The PTPN1 promoter variant 1023C>A was associated with presence of T2D, but it had no correlation with any of neither metabolic traits nor obesity in this study but we could not detect any association between 467T>C variants of PTPN1 gene with T2D Egyptian patients nor related traits in this study. Further studies must be done on a larger population to detect any potential metabolic association.
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Journal of Clinical & Medical Genomics received 391 citations as per Google Scholar report
