Association of vitamin D receptor polymorphisms with cardiometabolic conditions in Pakistani population

Apart from bone related effects, vitamin D has roles in immune modulation, hypertension, diabetes and cardiovascular diseases. Metabolic functions of vitamin D are mediated after binding with vitamin D receptor (VDR). VDR polymorphisms affect its physiological functions. Several VDR single nucleotide polymorphisms (SNPs) were reported previously. However, VDR polymorphisms causing influence on cardiovascular and metabolic disorders have not been investigated in the Pakistani population so far. Therefore, the present study was conducted to evaluate the role of VDR polymorphisms (rs2228570 and rs7975232) in the pathobiology of cardiometabolic disorders. In total, 400 cardiometabolic patients and 226 healthy control human adults were enrolled from Faisalabad, Pakistan. Biochemical parameters (serum glucose, liver function test, renal function test and lipid profile) were analyzed by standard kit methods. Genetic analysis was done by ARMS-PCR assay. Data was analyzed in SPSS v20. Regression analysis revealed that GG and AG genotypes of rs2228570 A>G polymorphism significantly increased the risk of hypertension in cardiovascular patients by 5.29 and 5.94 times respectively (GG: OR=5.29, 95% CI=1.63-17.2, p=0.005; AG: OR=5.94, 95% CI=1.70-20.7, p=0.005). However, rs7975232 C>A polymorphism was not correlated with cardiometabolic conditions. In conclusion, GG and AG genotypes of VDR SNP rs2228570 significantly contribute to hypertension in cardiovascular disease patients.

Association of Vitamin D Receptor Gene Polymorphisms With the Evolution of MODY Diabetes: Study in Tunisian Patients

Vitamin D (VD) cannot be considered as a true vitamin, but rather as a hormone, which exerts its action via a vitamin D receptor (VDR). Many genes have been shown to be involved in the evolution of diabetes in various populations, such as the vitamin D receptor gene. The aim of our study was to investigate if BsmI, TaqI, ApaI, FokI, and Tru9I, polymorphisms of VDR gene have an impact on MODY diabetes and its clinical aspects in a Tunisian population. A total of 95 patients and 153 controls were genotyped using PCR-RFLP. The comparison of the allelic and genotypic frequencies of the five polymorphisms between MODY subjects and control groups revealed the association of MODY diabetes with TaqI, Tru9I and BsmI polymorphisms and no significant differences were observed in the distributions for the ApaI and FokI polymorphisms. After stratification with biochemical and clinical parameters and TaqI, Tru9I and BsmI polymorphisms, we found an association between the three SNPs and different parameters such as age of diagnosis, therapy, hsCRP and HDL-C levels. Our results revealed that TaqI, Tru9I and BsmI polymorphisms may be more related to the progression of MODY diabetes. The possible role of vitamin D in the pathogenesis of MODY is far from being completely understood. Further knowledge on this issue may identify new candidate targets in the treatment and prevention of the disease. Our findings suggest that the TaqI, Tru9I and BsmI polymorphisms may be more related to the progression of MODY diabetes.

The Role of Apa-I Vitamin D Receptor Gene Polymorphism in Type 2 Diabetes Mellitus

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a chronic metabolic syndrome caused by insulin secretion abnormalities, insulin action, or both. Gene polymorphism is a risk factor of T2DM. AIM: This study aims to see the role of Apa-I Vitamin D receptor gene polymorphism on T2DM. METHODS: This study was an analytic observational with a case–control approach, consisting of 70 T2DM patients and 70 healthy subjects as a control. Genotyping of the Apa-I Vitamin D receptor gene polymorphism was performed using the polymerase chain reactions-restriction fragment length polymorphisms method. The role of the Apa-I Vitamin D receptor gene polymorphism and the risk of T2DM were analyzed using the Chi-square test. RESULTS: The results showed that there was a significant association between codominant (TT genotype); dominant; recessive models of the Apa-I Vitamin D receptor gene polymorphism with the risk of T2DM (p < 0.05; odds ratio [OR] = 0.204, 95% confidence interval [CI] = 0.063–0.662; OR = 0.337, 95% CI = 0.113–1.004; OR = 0.367, 95% CI = 0.180–0.747, respectively), but not in codominant (GT genotype) and over-dominant models (p > 0.05). CONCLUSION: This study shows a role of the codominant (TT genotype); dominant; recessive models of the Apa-I Vitamin D receptor gene polymorphism on T2DM, but not in codominant (GT genotype) and over-dominant models.

Artificial Neural Networks Model for Predicting Type 2 Diabetes Mellitus Based on VDR Gene FokI Polymorphism, Lipid Profile and Demographic Data

Type 2 diabetes mellitus (T2DM) is a multifactorial disease associated with many genetic polymorphisms; among them is the FokI polymorphism in the vitamin D receptor (VDR) gene. In this case-control study, samples from 82 T2DM patients and 82 healthy controls were examined to investigate the association of the FokI polymorphism and lipid profile with T2DM in the Jordanian population. DNA was extracted from blood and genotyped for the FokI polymorphism by polymerase chain reaction (PCR) and DNA sequencing. Lipid profile and fasting blood sugar were also measured. There were significant differences in high-density lipoprotein (HDL) cholesterol and triglyceride levels between T2DM and control samples. Frequencies of the FokI polymorphism (CC, CT and TT) were determined in T2DM and control samples and were not significantly different. Furthermore, there was no significant association between the FokI polymorphism and T2DM or lipid profile. A feed-forward neural network (FNN) was used as a computational platform to predict the persons with diabetes based on the FokI polymorphism, lipid profile, gender and age. The accuracy of prediction reached 88% when all parameters were included, 81% when the FokI polymorphism was excluded, and 72% when lipids were only included. This is the first study investigating the association of the VDR gene FokI polymorphism with T2DM in the Jordanian population, and it showed negative association. Diabetes was predicted with high accuracy based on medical data using an FNN. This highlights the great value of incorporating neural network tools into large medical databases and the ability to predict patient susceptibility to diabetes.