Exploring Nutritype Signature of Type 2 Diabetes Risks in Women Post-Gestational Diabetes Mellitus

Type 2 Diabetes Clinical Trial

Official title:

Exploring Nutritype Signature of Type 2 Diabetes Risks in Women Post-Gestational Diabetes Mellitus

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT04190199
• Other study ID #: 5540099
• Status: Not yet recruiting
• Start date: May 2020
• Est. completion date: May 2021

Study information

• Verified date: December 2019
• Source: Universiti Putra Malaysia
• Contact: Barakatun Nisak Mohd. Yusof, PhD
• Phone: +603-97692606
• Email: bnisak[@]upm.edu.my
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

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.

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.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 270
• Est. completion date: May 2021
• Est. primary completion date: May 2021
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: Female
• Age group: 18 Years to 50 Years

Eligibility

Inclusion Criteria:

• Malaysian women at childbearing age of 18-50 years old

• 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

• Pregnant women

• 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.

Related Conditions & MeSH terms

• Diabetes Mellitus
• Diabetes Mellitus, Type 2
• Diabetes, Gestational
• Gestational Diabetes
• Type 2 Diabetes

Intervention

Other:
• Observational
Cross-sectional only

Locations

Country	Name	City	State
Malaysia	Universiti Putra Malaysia	Serdang	Selangor

Sponsors (3)

Lead Sponsor	Collaborator
Universiti Putra Malaysia	Ministry of Health, Malaysia, Universiti Teknologi Mara

Country where clinical trial is conducted

Malaysia, 

References & Publications (10)

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. — View Citation

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. — View Citation

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.

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. Review. — View Citation

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. Review. — View Citation

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. Review. — View Citation

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. Review. — View Citation

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. — View Citation

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, Strøm 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. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Nutritype signature of T2DM risks in women post-GDM	To identify the nutritype signatures of T2DM risks in women post-GDM using proton nuclear magnetic resonance (1H NMR) based metabolomics approach.	Through study completion, an average of 1 year
Secondary	Prevalence of glucose intolerance	To determine prevalence of glucose intolerance (T2DM and pre-diabetes) among women post-GDM	Through study completion, an average of 1 year
Secondary	Socio-demographic background	Difference in socio-demographic background between T2DM, pre-diabetes and non-T2DM groups.	Through study completion, an average of 1 year
Secondary	Obstetric history	Difference in obstetric history between T2DM, pre-diabetes and non-T2DM groups.	Through study completion, an average of 1 year
Secondary	Nutritional status	Difference in nutritional status between T2DM, pre-diabetes and non-T2DM groups.	Through study completion, an average of 1 year
Secondary	Metabolite profile	Difference in metabolite profile between T2DM, pre-diabetes and non-T2DM groups.; Metabolite profile will be analyzed based plasma blood and urine samples, using 1H NMR metabolomics approach.	Through study completion, an average of 1 year
Secondary	Dietary pattern	Difference in dietary pattern between T2DM, pre-diabetes and non-T2DM groups. Dietary pattern will be assessed using Food Frequency Questionnaire.	Through study completion, an average of 1 year
Secondary	Sleeping pattern	Difference in sleeping pattern between T2DM, pre-diabetes and non-T2DM groups. Sleeping pattern will be assessed using a questionnaire.	Through study completion, an average of 1 year
Secondary	Perceived Stress Scale score	Difference in Perceived Stress Scale score between T2DM, pre-diabetes and non-T2DM groups.; PSS scores are obtained by reversing responses (e.g., 0 = 4, 1 = 3, 2 = 2, 3 = 1 & 4 = 0) to the four positively stated items (items 4, 5, 7, & 8) and then summing across all scale items. Minimum score is 10, whereas maximum score is 40.	Through study completion, an average of 1 year
Secondary	Physical activity level	Difference in physical activity level between T2DM, pre-diabetes and non-T2DM groups. Physical activity level will be assessed by International Physical Activity Questionnaire (IPAQ).	Through study completion, an average of 1 year
Secondary	Smoking habit and exposure	Difference in smoking habit and exposure between T2DM, pre-diabetes and non-T2DM groups. Questions on smoking habit and exposure are based on the Global Adult Tobacco Survey.	Through study completion, an average of 1 year