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Investigating Genetic Predisposition to Gestational Diabetes Mellitus Among Black Women Residing eThekwini, KwaZulu-Natal, South Africa.

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2023

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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 xvi 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 xvii 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.

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Masters Degree. University of KwaZulu-Natal, Durban.

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