Investigating Genetic Predisposition to Gestational Diabetes Mellitus Among Black Women Residing eThekwini, KwaZulu-Natal, South Africa.
Date
2023
Authors
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Abstract
Gestational Diabetes Mellitus (GDM) is regarded as a “silent killer” determined by an abnormal
glucose tolerance firstly recognised at any time during pregnancy and disappear after delivery.
Carrying a large baby (>4000g), being obese (BMI: .>40kg), HIV positive and multiple
pregnancy may increase the risk of postpartum haemorrhage (Hadley et al., 2021). Postpartum
haemorrhage is a leading cause of maternal death , affecting 75% of maternal death worldwide
(Maternal Mortality, Who Fact sheet, February 2023). Women previously diagnosed with GDM
are at higher risk of subsequent type 2 diabetes mellitus (T2DM), and development of GDM in
the early gestational week of pregnancy. Babies born from GDM mothers may develop T2DM,
and GDM (Farahvar et al., 2019) and become obese or overweight in their young and adolescence
life ( Egeland & Meltzer, 2010; Lowe at al., 2019; Martinez-Cruz et al., 2021). Previous studies
have shown that genetic polymorphisms, obesity /overweight, and environmental risk factors may
predispose women to GDM. However, the data in KwaZulu-Natal is limited. Furthermore,
screening of GDM in women previously diagnosed with GDM has become compulsory every
third year to help those mothers who may have pre-existing DM during pregnancy. Therefore, in
this study, we selected black African women previously diagnosed with GDM and aimed to
determine the prevalence rate and associated risk factors of GDMin the eThekwini district. Again,
we investigated the association between SNP genotypes (MTNR1B rs1387153, PPARα rs4253778,
and TCF7L2 rs12255372) and the development of GDM and obesity.
Methods
Firstly, primary data- the self-data report (a well-structured questionnaire) was performed to
determine the GDM prevalence amongst black SA women living eThekwini district. Pregnant
and non-pregnant women were randomly recruited from three local health district facilities:
KwaMashu CHC, KwaDabeka CHC, and KEVIII Tertiary hospital in KwaZulu-Natal. This study
used 87 black South African women with GDM history which included experimental group
(twenty-five women with GDM) and control group (sixty-two women without GDM); aged 15-
45 years of age, residing in eThekwini district and, attending clinics from the first to the third
trimester of pregnancy. The GDM confirmation was performed by the relevant antenatal care
clinic on women with GDM, using a standard procedure of 2hr- 75g OGTT as per the Guideline
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for maternity Care in SA, (2016:98). Blood samples between 2-4ml were collected from each
participant into vacutainer EDTA tube (BD Diagnostic, SA) for molecular analysis. The blood
samples were collected for DNA extraction to perform the genetic polymorphisms’ investigation
and GDM and quantitative metabolic traits in pregnant and non-pregnant women within
eThekwini district and its impacts on maternal health. The secondary data was obtained from the
healthcare registry system for the pregnant women in the antenatal care clinic. The aim was to
measure the initial maternal data of antenatal visits and compare those data with the existing data
during the research collection. Secondly, the data was analysed using R. Statistical Computing
Software of the R. core Team, 2020, version 3.6.3. Women with a previous diagnosis of GDM
were regarded as current GDM and analysed as dependent variables and risk factors as
independent predictive variables. Thirdly, BMI was measured as kg/m2, and the following genetic
variants: MTNR1B (rs1387153), PPARα (rs4253778), and TCF7L2 (rs12255372) were genotyped
for each participant using the PCR-RFLP technique. Sanger Sequencing confirmed results at
Central Analytical Facilities (CAF), Stellenbosch University, SA. All results of p-value <0.05
were considered statistically significant.
Results
Approximately 25 women reported GDM, and sixty two had no GDM. GDM prevalence rate is
estimated at 28.7 %. GDM was significantly associated with older age above 36 years (p˂0.05),
family history of diabetes mellitus (p˂0.05), women with 1 or 2 children (p<0.01), pre-existing
diabetes mellitus (p<0.01). BMI (≥25 kg/m2) odds ratio: 6.9; 95%CI; 1.35-5.48; p=0.03, ARV
treatment (OR: 3.3 95%CI: 1.10-11.310; p=0.010), and pre-existing DM (OR: 0.23; 95CI: 0.07-
0.71; p=0.014) remained risk factors for GDM. All pregnant women with and without GDM had
a homozygous G-allele of TCF7L2 rs12255372. Genetic polymorphism C-allele of MTNR1B
(rs1387153) and PPARα (rs4253778) were not associated with the risk of GDM and obesity
(p>0.05). After the combination of three SNPs profiles (rs1387153, rs12255372, 4253778),
genotype CC (rs4253778), CC (rs1387153), and GG (rs12255372) were significantly higher in
the pregnant women without gestational diabetes mellitus and obese participants (p<0.05).
Conclusion
The GDM prevalence rate was 28.7%, and associated risk factors were as follows: age, parity,
pre-existing DM, and family history of diabetes mellitus. ARV treatment, pre-existing DM, and
overweight were independent risk factors of GDM. In this study G homozygous of TCF7L2
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rs12255372 was a genetic marker in the population of black SA women in eThekwini, KwaZulu-
Natal. Women with CC and GG genotype are at high risk of developing GDM and obesity.
This study shows that SNP genotypes CC MTNR1B rs1387153, PPARα rs4253778 CC genotype,
and GG genotype of TCF7L2 rs12255372 are susceptible to women developing obesity.
Description
Masters Degree. University of KwaZulu-Natal, Durban.