Association of vitamin D receptor gene polymorphisms with type 2 diabetes mellitus in Taif population: a case-control study.
Adel Qlayel AlkhedaideA MerganiAdel AldhahraniA SabryMohamed Mohamed SolimanMohamed Abdo NassanTamer Ahmed IsmailPublished in: Brazilian journal of biology = Revista brasleira de biologia (2021)
Several reasons may underlie the dramatic increase in type2 diabetes mellitus. One of these reasons is the genetic basis and variations. Vitamin D receptor polymorphisms are associated with different diseases such as rheumatoid arthritis and diabetes. The aim of this study is to investigate the possible association of two identified mutations ApaI (rs7975232) and TaqI (rs731236). Eighty-nine healthy individuals and Fifty-six Type 2 Diabetic (T2D) patients were investigated using RFLP technique for genotyping and haplotyping as well. The distribution of Apal genotypes was not statistically significant among the control (P=0.65) as well as for diabetic patients (P=0.58). For Taql allele frequencies of T allele was 0.61 where of G allele was 0.39. The frequency distribution of Taql genotypes was not statistically significant among the control (P=0.26) as well as diabetic patients (P=0.17). Relative risk of the allele T of Apa1 gene is 1.28 and the odds ratio of the same allele is 1.53, while both estimates were < 1.0 of the allele G. Similarly, with the Taq1 gene the relative risk and the odds ratio values for the allele T are 1.09 and 1.27 respectively and both estimates of the allele C were 0.86 for the relative risk and 0.79 for the odds ratio. The pairwise linkage disequilibrium between the two SNPs Taq1/apa1 was statistically significant in control group (D = 0.218, D' = 0.925 and P value < 0.001) and similar data in diabetic groups (D = 0.2, D' = 0.875 and P value < 0.001). These data suggest that the T allele of both genes Apa1 and Taq1 is associated with the increased risk of type 2 diabetes. We think that we need a larger number of volunteers to reach a more accurate conclusion.
Keyphrases
- genome wide
- rheumatoid arthritis
- type diabetes
- end stage renal disease
- ejection fraction
- dna methylation
- chronic kidney disease
- big data
- electronic health record
- machine learning
- high resolution
- prognostic factors
- high throughput
- metabolic syndrome
- gene expression
- genome wide identification
- peritoneal dialysis
- mass spectrometry
- patient reported outcomes
- hiv infected
- data analysis
- weight loss
- genetic diversity
- antiretroviral therapy
- atomic force microscopy