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Women post-gestational diabetes mellitus (GDM) have more than 7-fold increased risk of having future type 2 diabetes mellitus (T2DM). While a healthful dietary pattern reduces the risk of diabetes in post-GDM, no data support a dietary pattern tailored to the Malaysian diet. To address this issue, the investigators propose to determine the effects of dietary patterns and plasma metabolites in predicting the risk of T2DM known as the Nutritype model. The aim of this study is to identify Nutritype signatures of T2DM risk in women post-GDM using metabolomics approach.
Full description
Women with a history of gestational diabetes mellitus (GDM) or post-GDM are at high risk of developing type 2 diabetes (T2DM). This is important in the present context because T2DM has reached epidemic proportions. In Malaysia, the prevalence of T2DM has increased by almost 80% in just over a 10 year period. Current recommendation supports early screening at 6 weeks postpartum via oral glucose tolerance testing (OGTT) after GDM. However, the screening of women after GDM remains suboptimal, with a very low compliance rate up to almost 20%. Also, none of the recommendations highlights the need of having nutrition screening assessments despite the fact that nutritional stimuli are highly relevant to expedite disease progression in women post-GDM.
As such, the metabolomics technique can be used as a tool to measure the full profile of small-molecule metabolites in bio-fluids. This technique has been expanded beyond biological disciplines towards nutrition research leading to the emerging concept of Nutritype. Nutritype refers to the expression of overall dietary intake in metabolites; work that capable to classify individuals into a certain dietary pattern based on the metabolomics profiles. While the role of metabolomics is significance, no exploration of the Nutritype signatures has been established.
Potential significant determinants for the progression from GDM to T2DM include genetics, factors during the index pregnancy, exogenous modifiable risk factors and factors specific to intermediate biological mechanisms with no data on metabolites profile. Although the metabolomic signatures predicting GDM transition to T2DM in women post-GDM have been identified, its metabolites related to a protective dietary pattern is unknown.
This concept is timely needed as the objective assessment of dietary intake is a huge challenge that lacks biological validation. Although several biomarkers of foods exist, identification of metabolites signature that reflects overall dietary patterns is scarce. While a healthful dietary pattern such as the alternate Healthy Eating Index (aHEI) reduces the risk of T2DM among women post-GDM, none of the patterns tailored to Malaysian diet. Direct extrapolation of these findings to the overall Malaysian diet is unknown.
Therefore, the study aims to discover and identify the Nutritype signatures which combine information on dietary pattern biomarkers and metabolites profiles of T2DM risk in women post-GDM using metabolomics approach. The data will then be used to identify a predictive model of Nutritype signatures to develop protective dietary pattern works according to individuals' metabolite in preventing T2DM among women post-GDM. The findings aid in establishing an early measure of T2DM prevention in women post-GDM based on the metabolite profile that reflects the overall diet. This new exciting work leads to the goal of achieving precision diabetes-nutrition prevention using a multi-pronged strategy.
This is a cross-sectional comparative study involving women post-GDM. Women with a history of GDM will have their nutritional status, metabolite profile, dietary pattern and lifestyle practices assessed. They will undergo Oral Glucose Tolerance Test (OGTT) to determine T2DM diagnosis, based on Clinical Practice Guidelines Malaysia. Based on their OGTT results, they will be divided into 3 groups: T2DM, prediabetes (impaired fasting glucose [IFG] or impaired glucose tolerance [IGT]), or non-T2DM.
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270 participants in 3 patient groups
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Farah Yasmin Hasbullah, MSc; Barakatun Nisak Mohd. Yusof, PhD
Data sourced from clinicaltrials.gov
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