Personalized and Precision Medicine Journal

Abstract Precision medicine is a medical approach that involves customizing therapy for an individual by using extensive biological and external data. The rapid progress in the disciplines of molecular biology, gene sequencing, machine learning, and related technologies has facilitated the use of precision medicine. This approach utilizes the wealth of comprehensive information obtained from these advancements to improve the decision-making process in clinical treatment for individuals, particularly in real-time scenarios during the progression of a disease. Diabetes mellitus is a significant worldwide health issue, requiring the implementation of novel strategies to enhance patient outcomes. The efficacy of conventional treatment options that use a uniform approach has been shown to be limited in effectively addressing the heterogeneous character of the illness. In recent times, personalized medicine has surfaced as a revolutionary resolution, customizing treatment strategies in accordance with an individual's health attributes, lifestyle choices, and genetic composition. This review underscores the significance of genetic screening in forecasting susceptibility to diabetes and treatment response, while also emphasizing the potential of pharmacogenomics to optimize medication selection.

Abstract Diabetes mellitus (DM) is a major public health issue in worldwide. Type 2 diabetes does not have a clear pattern of inheritance, although many affected individuals have at least one close family member, such as a parent or sibling, with the disease. The KCNJ11 gene is a member of the potassium channel gene family. polymorphisms  in KCNJ11  result  in  neonatal  diabetes and congenital hyper-insulinaemia, wherein the E23K (rs5219) polymorphism is linked with diabetes susceptibility where the K allele plays an important role in insulin secretion. In this study, we evaluate the frequency of these polymorphisms in a Kurdish population of 85 with type 2 diabetes. E23K polymorphism of KCNJ11 gene was genotyped by PCR-RFLP method. heterozygous carriers for AG are more in non‑diabetic patients (P = 0.034).