Metformin Pharmacogenetics: Effects of SLC22A1, SLC22A2, and SLC22A3 Polymorphisms on Glycemic Control and HbA1c Levels.
Laith Naser Al-EitanBasima A AlmomaniAhmad M NassarBarakat Z ElsaqaNesreen A SaadehPublished in: Journal of personalized medicine (2019)
Type 2 diabetes mellitus (T2DM) constitutes a major portion of Jordan's disease burden, and incidence rates are rising at a rapid rate. Due to variability in the drug's response between ethnic groups, it is imperative that the pharmacogenetics of metformin be investigated in the Jordanian population. The objective of this study was to investigate the relationship between twenty-one single nucleotide polymorphisms (SNPs) in the SLC22A1, SLC22A2, and SLC22A3 genes and their effects on metformin pharmacogenetics in Jordanian patients diagnosed with type 2 diabetes mellitus. Blood samples were collected from 212 Jordanian diabetics who fulfilled the inclusion criteria, which were then used in SNP genotyping and determination of HbA1c levels. The rs12194182 SNP in the SLC22A3 gene was found to have a significant association (p < 0.05) with lower mean HbA1c levels, and this association more pronounced in patients with the CC genotype (i.e., p-value was significant before correcting for multiple testing). Moreover, the multinomial logistic regression analysis showed that SNP genotypes within the SLC22A1, SLC22A2, and SLC22A3 genes, body mass index (BMI) and age of diagnosis were significantly associated with glycemic control (p < 0.05). The results of this study can be used to predict response to metformin and other classes of T2DM drugs, making treatment more individualized and resulting in better clinical outcomes.
Keyphrases
- glycemic control
- genome wide
- type diabetes
- blood glucose
- body mass index
- dna methylation
- weight loss
- insulin resistance
- end stage renal disease
- risk factors
- emergency department
- ejection fraction
- newly diagnosed
- chronic kidney disease
- genetic diversity
- cardiovascular disease
- peritoneal dialysis
- high throughput
- single cell
- metabolic syndrome
- high density
- adipose tissue
- cardiovascular risk factors
- quantum dots
- skeletal muscle
- drug induced
- electronic health record
- genome wide association
- patient reported
- smoking cessation