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Significant Association of Candidate Genes (AGTR1 and TGF-Β1) Polymorphism with Diabetic Nephropathy in Diabetes Mellitus Type 2 Patients

糖尿病肾病 医学 内科学 糖尿病 肾病 肌酐 内分泌学 2型糖尿病 胃肠病学 基因分型 2型糖尿病 基因型 生物 基因 遗传学
作者
Madeeha Ihsan,Najeeb Ullah Khan
出处
期刊:Cellular Physiology and Biochemistry [Cell Physiol Biochem Press GmbH and Co KG]
卷期号:58 (3): 203-211
标识
DOI:10.33594/000000702
摘要

Background/Aims: Diabetic nephropathy (DN) is one of the complications of diabetes mellitus (DM). This study aimed to investigate the association between genetic polymorphisms, specifically AGTR1 (rs5186) and TGF-β1 (rs1800470), and the risk of developing Diabetic nephropathy (DN) in type 2 diabetes mellitus patients, compared to those without DN and healthy controls. Methods: A case-control study was conducted on 165 diabetic patients (59 with diabetic nephropathy (DN) and 54 without DN (DM)), and 52 healthy controls (HC). The genotyping was done using amplification refractory mutation system method (ARMS-PCR). Age, gender, and duration of diabetes were matched across groups. Clinical parameters including FBS, RBS, HbA1C, creatinine, urea, SBP, DBP, total cholesterol, triglycerides, LDL, and BMI were assessed. Results: Diabetic patients with nephropathy exhibited significantly higher levels of clinical parameters compared to those without nephropathy and healthy controls. The risk allele of AGTR1 , C (p <0.0001), and risk allele containing genotypes AC (p <0.0001) and CC (p - 0.0010) were significantly higher in DN patients compared to DM and HC groups. Similarly, the TGF-β1 risk allele C (p - 0.0001), and corresponding genotypes TC (p - 0.0038) and CC (p - 0.0027) were significantly associated with increased risk of diabetic nephropathy compared to DM and HC groups. Conclusion: The data showed significant association of AGTR1 (rs5186) and TGF-β1 (rs1800470) polymorphism with an increased risk of diabetic nephropathy in type 2 diabetes mellitus patients. More investigation will be required to disseminate the results, while increasing the samples size and using whole genome sequencing.

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