The effect of fructosamine 3 kinase (FN3K) genotypes on the glycation gap in type 2 diabetic and non-diabetic mixed ancestry population of South Africa

Motshwari, Dipuo Dephney (2018-12)

Thesis (MMed)--Stellenbosch University, 2018.

Thesis

ENGLISH ABSTRACT: Introduction In2017 the International Diabetes Federation (IDF) reported that approximately 425 million adults aged 20-79 years were estimated to have diabetes mellitus (DM) worldwide. The nonenzymatic glycation reactions of proteins such as haemoglobin have been associated with the development of diabetic related complications. These reactions were believed to be irreversible until the discovery of a protein repair enzyme fructosamine 3 kinase (FN3K). This enzyme deglycates glycated haemoglobin (HbA1c) in erythrocytes and other glycated proteins in other tissues. Animal model studies found that the activity of this enzyme varies between individuals leading to differences in HbA1c levels. This results in discrepancies between HbA1c and other glycaemic measures which is termed the glycation gap. The glycation gap is consistent over time within individuals and is associated with diabetic complications. Genetic variants in the FN3K gene have been associated with altered enzyme activity. Therefore, the aim of this study was to examine the role of FN3K genotypes on the glycation gap Methods A total of 1412 subjects (925 normal, 216 pre-diabetic and 271 type 2 diabetics), with 339 males and 1073 females aged ≥ 20 years of mixed ancestry descent, residing in Bellville South, South Africa were included in this study. The diabetics were diagnosed using the oral glucose tolerance test. The glycation gap was determined according to a formula: Glycation gap= HbA1c - FHbA1c, (FHbA1c = {[(fructosamine- mean fructosamine)/SD fructosamine] X SD HbA1c} + mean HbA1c). DNA was extracted from whole blood using the salt extraction method. FN3K single nucleotide polymorphisms (SNPs) were genotyped with the Applied Biosystems™ QuantStudio™ 7 Flex Real-Time PCR System 96 well fast from Thermo Fisher Scientific. HbA1c was measured using HPLC (Biorad Variant Turbo) and fructosamine was measured using a colorimetric test nitro-blue-tetrazolium (NBT). Results SNP c. -232A/T deviated from Hardy Weinberg Equilibrium (HWE) and was left out for the rest of the statistical analysis. The polymorphism G900C followed the Hardy-Weinberg Equilibrium and was therefore studied. The genotype frequencies for SNP G900C in the glycaemic sub-groups were as follows, GG: 45.9 %, GC: 43.7 %, CC: 10.4 % in normal subjects; GG: 48.6 %, GC: 41.7 %, CC: 9.7% in pre-diabetics and GG: 41.7 %, GC: 46.5 %, CC: 11.8 % in diabetics, and they followed the Hardy-Weinberg equilibrium. There were no significant differences in the SNP G900C genotype frequencies between the glycaemic subgroups. The glycation gap significantly decreased across the GG, GC and CC genotype variants in males, mean ± SD were -0.13±0.86, -0.25±0.72 and -0.80±1.04 respectively, (P=0.0239). However the difference was not observed in females. Moreover the glycation gap showed a positive correlation with non glycaemic factors including body mass index (BMI) (r=0.3694, p<0.0001), waist circumference (waistC) (r=0.3749, p<0.0001), hip circumference (hipC) (r0.3151, p<0.0001), triglycerides (r=0.2540, p<0.0001) and a negative correlation with high density lipoprotein cholesterol (HDL-Chol) (r=-0.2031, p<0.0001). Conclusion In conclusion the present study found that the glycation gap might be influenced by genetic In conclusion the present study found that the glycation gap might be influenced by genetic active mechanisms in the intracellular erythrocyte compartment. Identification of the G900C polymorphism in an early stage of diabetes could be useful especially in therapeutic decisions and prediction of improved prognosis. However, there are other confounding factors influencing the glycation gap and future studies are required to confirm these findings.

AFRIKAANSE OPSOMMING: Geen opsomming

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