Exploring Nutritype Signature of Type 2 Diabetes Risks in Women Post-Gestational Diabetes Mellitus
NCT ID: NCT04190199
Last Updated: 2019-12-09
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
270 participants
OBSERVATIONAL
2020-05-31
2021-05-31
Brief Summary
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Detailed Description
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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.
Conditions
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Keywords
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Study Design
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OTHER
CROSS_SECTIONAL
Study Groups
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Type 2 diabetes mellitus (T2DM)
Subjects in this group are diagnosed with type 2 diabetes mellitus. They receive no intervention. Their nutritional status, metabolite profile, dietary pattern, and lifestyle practices will be assessed.
Observational
Cross-sectional only
Pre-diabetes (IFG or IGT)
Subjects in this group are diagnosed with pre-diabetes (impaired fasting glucose \[IFG\] or impaired glucose tolerance \[IGT\]). They receive no intervention. Their nutritional status, metabolite profile, dietary pattern, and lifestyle practices will be assessed.
Observational
Cross-sectional only
Non-type 2 diabetes mellitus (healthy)
Subjects in this group are not diagnosed with type 2 diabetes mellitus or pre-diabetes (healthy). They receive no intervention. Their nutritional status, metabolite profile, dietary pattern, and lifestyle practices will be assessed.
Observational
Cross-sectional only
Interventions
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Observational
Cross-sectional only
Eligibility Criteria
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Inclusion Criteria
* Have a history of GDM
* Women with known case of impaired fasting glucose (IFG) or impaired glucose tolerance (IGT) with or without medications
Exclusion Criteria
* Those with prior history of type 1 or type 2 diabetes
* Recent hospitalization (within 6 weeks)
* Presence of reported or previously diagnosed medical conditions
* Receiving drugs (such as steroids and weight-reducing agents)
* Have a significant weight loss of 10% from original body weight within 3 months.
18 Years
50 Years
FEMALE
Yes
Sponsors
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Ministry of Health, Malaysia
OTHER_GOV
Universiti Teknologi Mara
OTHER
Universiti Putra Malaysia
OTHER
Responsible Party
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Barakatun Nisak Bt Mohd Yusof
Associate Professor
Principal Investigators
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Barakatun Nisak Mohd. Yusof, PhD
Role: PRINCIPAL_INVESTIGATOR
Universiti Putra Malaysia
Farah Yasmin Hasbullah, MSc
Role: PRINCIPAL_INVESTIGATOR
Universiti Putra Malaysia
Geeta Appannah, PhD
Role: PRINCIPAL_INVESTIGATOR
Universiti Putra Malaysia
Rohana Abdul Ghani, PhD
Role: PRINCIPAL_INVESTIGATOR
Universiti Teknologi Mara (UiTM)
Zulfitri 'Azuan Mat Daud, PhD
Role: PRINCIPAL_INVESTIGATOR
Universiti Putra Malaysia
Winnie Chee, PhD
Role: PRINCIPAL_INVESTIGATOR
International Medical University (IMU)
Locations
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Universiti Putra Malaysia
Serdang, Selangor, Malaysia
Countries
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Central Contacts
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References
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Allalou A, Nalla A, Prentice KJ, Liu Y, Zhang M, Dai FF, Ning X, Osborne LR, Cox BJ, Gunderson EP, Wheeler MB. A Predictive Metabolic Signature for the Transition From Gestational Diabetes Mellitus to Type 2 Diabetes. Diabetes. 2016 Sep;65(9):2529-39. doi: 10.2337/db15-1720. Epub 2016 Jun 23.
Bhupathiraju SN, Hu FB. One (small) step towards precision nutrition by use of metabolomics. Lancet Diabetes Endocrinol. 2017 Mar;5(3):154-155. doi: 10.1016/S2213-8587(17)30007-4. Epub 2017 Jan 13. No abstract available.
Institute for Public Health [IPH]. 2015. Vol. II: Non-communicable diseases, risk factors and other health problems. National Health and Morbidity Survey (NHMS 2015). Kuala Lumpur, Malaysia: IPH, Ministry of Health.
Malaysian Endocrine & Metabolic Society [MEMS] and Ministry of Health [MOH] Malaysia. 2015. Management of type 2 diabetes mellitus (5th Edition). Kuala Lumpur, Malaysia: MEMS & MOH.
Nielsen KK, Kapur A, Damm P, de Courten M, Bygbjerg IC. From screening to postpartum follow-up - the determinants and barriers for gestational diabetes mellitus (GDM) services, a systematic review. BMC Pregnancy Childbirth. 2014 Jan 22;14:41. doi: 10.1186/1471-2393-14-41.
O'Gorman A, Brennan L. The role of metabolomics in determination of new dietary biomarkers. Proc Nutr Soc. 2017 Aug;76(3):295-302. doi: 10.1017/S0029665116002974. Epub 2017 Jan 16.
Tee ES, Yap RWK. Type 2 diabetes mellitus in Malaysia: current trends and risk factors. Eur J Clin Nutr. 2017 Jul;71(7):844-849. doi: 10.1038/ejcn.2017.44. Epub 2017 May 17.
Tobias DK, Hu FB, Chavarro J, Rosner B, Mozaffarian D, Zhang C. Healthful dietary patterns and type 2 diabetes mellitus risk among women with a history of gestational diabetes mellitus. Arch Intern Med. 2012 Nov 12;172(20):1566-72. doi: 10.1001/archinternmed.2012.3747.
Zhang C, Hu FB, Olsen SF, Vaag A, Gore-Langton R, Chavarro JE, Bao W, Yeung E, Bowers K, Grunnet LG, Sherman S, Kiely M, Strom M, Hansen S, Liu A, Mills J, Fan R; DWH study team. Rationale, design, and method of the Diabetes & Women's Health study--a study of long-term health implications of glucose intolerance in pregnancy and their determinants. Acta Obstet Gynecol Scand. 2014 Nov;93(11):1123-30. doi: 10.1111/aogs.12425. Epub 2014 Jun 9.
Kim C, Newton KM, Knopp RH. Gestational diabetes and the incidence of type 2 diabetes: a systematic review. Diabetes Care. 2002 Oct;25(10):1862-8. doi: 10.2337/diacare.25.10.1862.
Other Identifiers
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5540099
Identifier Type: -
Identifier Source: org_study_id