Ignite Creation Date:
2026-03-26 @ 3:14 PM
Ignite Modification Date:
2026-03-30 @ 4:22 AM
Study NCT ID:
NCT07452159
Status:
NOT_YET_RECRUITING
Last Update Posted:
2026-03-05
First Post:
2025-12-01
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Diabetes In Asians at Risk in Youth
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2026-03-25'}, 'interventionBrowseModule': {'meshes': [{'id': 'D005951', 'term': 'Glucose Tolerance Test'}, {'id': 'D000095583', 'term': 'Continuous Glucose Monitoring'}, {'id': 'D011795', 'term': 'Surveys and Questionnaires'}], 'ancestors': [{'id': 'D001774', 'term': 'Blood Chemical Analysis'}, {'id': 'D019963', 'term': 'Clinical Chemistry Tests'}, {'id': 'D019411', 'term': 'Clinical Laboratory Techniques'}, {'id': 'D019937', 'term': 'Diagnostic Techniques and Procedures'}, {'id': 'D003933', 'term': 'Diagnosis'}, {'id': 'D003940', 'term': 'Diagnostic Techniques, Endocrine'}, {'id': 'D008919', 'term': 'Investigative Techniques'}, {'id': 'D008991', 'term': 'Monitoring, Physiologic'}, {'id': 'D003625', 'term': 'Data Collection'}, {'id': 'D004812', 'term': 'Epidemiologic Methods'}, {'id': 'D017531', 'term': 'Health Care Evaluation Mechanisms'}, {'id': 'D011787', 'term': 'Quality of Health Care'}, {'id': 'D017530', 'term': 'Health Care Quality, Access, and Evaluation'}, {'id': 'D011634', 'term': 'Public Health'}, {'id': 'D004778', 'term': 'Environment and Public Health'}]}}, 'protocolSection': {'designModule': {'bioSpec': {'retention': 'SAMPLES_WITH_DNA', 'description': 'Serum, EDTA whole blood.'}, 'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 3000}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2026-03-18', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2026-02', 'completionDateStruct': {'date': '2029-01-02', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2026-03-01', 'studyFirstSubmitDate': '2025-12-01', 'studyFirstSubmitQcDate': '2026-03-01', 'lastUpdatePostDateStruct': {'date': '2026-03-05', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2026-03-05', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2029-01-02', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Diagnosis of diabetes', 'timeFrame': 'Baseline', 'description': 'Fasting glucose \\>/=7mmol/l or 2-hour glucose \\>/=11.1 mmol/l on oral glucose tolerance test or HbA1c \\>/=7%.'}], 'secondaryOutcomes': [{'measure': 'Diagnosis of pre-diabetes', 'timeFrame': 'Baseline', 'description': 'Fasting glucose \\>/=5.7mmol/l or 2-hour glucose \\>/=7,8 mmol/l on oral glucose tolerance test or HbA1c \\>/= 5.7%.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Young onset diabetes', 'Asian', 'Risk factors', 'contemporary'], 'conditions': ['Young Onset Asian Diabetes (Under 40 Years)']}, 'referencesModule': {'references': [{'pmid': '38629784', 'type': 'BACKGROUND', 'citation': 'Zahalka SJ, Galindo RJ, Shah VN, Low Wang CC. Continuous Glucose Monitoring for Prediabetes: What Are the Best Metrics? J Diabetes Sci Technol. 2024 Jul;18(4):835-846. doi: 10.1177/19322968241242487. Epub 2024 Apr 17.'}, {'pmid': '12164465', 'type': 'BACKGROUND', 'citation': 'Deurenberg P, Deurenberg-Yap M, Guricci S. Asians are different from Caucasians and from each other in their body mass index/body fat per cent relationship. Obes Rev. 2002 Aug;3(3):141-6. doi: 10.1046/j.1467-789x.2002.00065.x.'}, {'pmid': '37229472', 'type': 'BACKGROUND', 'citation': 'Kuang M, Lu S, Yang R, Chen H, Zhang S, Sheng G, Zou Y. Association of predicted fat mass and lean body mass with diabetes: a longitudinal cohort study in an Asian population. Front Nutr. 2023 May 9;10:1093438. doi: 10.3389/fnut.2023.1093438. eCollection 2023.'}, {'pmid': '25081582', 'type': 'BACKGROUND', 'citation': 'Yeung RO, Zhang Y, Luk A, Yang W, Sobrepena L, Yoon KH, Aravind SR, Sheu W, Nguyen TK, Ozaki R, Deerochanawong C, Tsang CC, Chan WB, Hong EG, Do TQ, Cheung Y, Brown N, Goh SY, Ma RC, Mukhopadhyay M, Ojha AK, Chakraborty S, Kong AP, Lau W, Jia W, Li W, Guo X, Bian R, Weng J, Ji L, Reyes-dela Rosa M, Toledo RM, Himathongkam T, Yoo SJ, Chow CC, Ho LL, Chuang LM, Tutino G, Tong PC, So WY, Wolthers T, Ko G, Lyubomirsky G, Chan JC. Metabolic profiles and treatment gaps in young-onset type 2 diabetes in Asia (the JADE programme): a cross-sectional study of a prospective cohort. Lancet Diabetes Endocrinol. 2014 Dec;2(12):935-43. doi: 10.1016/S2213-8587(14)70137-8. Epub 2014 Jul 28.'}, {'pmid': '41117210', 'type': 'BACKGROUND', 'citation': 'Rama Chandran S, Sng GGR, Wong CYH, Ang WM, Gardner D. Continuous Glucose Monitoring Metrics in Asians Without Diabetes: Differentiating Prediabetes From Normoglycemia. J Diabetes Sci Technol. 2025 Oct 21:19322968251384682. doi: 10.1177/19322968251384682. Online ahead of print.'}, {'pmid': '36219616', 'type': 'BACKGROUND', 'citation': 'Tan JK, Salim NNM, Lim GH, Chia SY, Thumboo J, Bee YM. Trends in diabetes-related complications in Singapore, 2013-2020: A registry-based study. PLoS One. 2022 Oct 11;17(10):e0275920. doi: 10.1371/journal.pone.0275920. eCollection 2022.'}], 'seeAlsoLinks': [{'url': 'http://www.thediary.sg', 'label': 'This is the study page which was created by the investigators to provide information to participants on the background, aims, and procedures of the study. They can also sign up and choose a data to participate in the study.'}]}, 'descriptionModule': {'briefSummary': 'This observational study aims to develop novel contemporary risk factor tools for detecting young onset diabetes (under 40y) in young Asians in Singapore. The investigators aim to recruit 3000 people not currently known to have diabetes, selected across age and Body Mass Index categories, and perform formal diagnostic tests for diabetes (oral glucose tolerance test and HbA1c). The participants will also undergo continuous glucose monitoring sensor, keep a food diary, and undergo body composition analysis using bioimpedance analysis, handgrip measurements for muscle strength, and sociobehavioural profiling through download of a curated list of social media interactions. The participants will also have a blood sample retrieved and stored for subsequent comparison between people with normal glucose versus abnormal glucose levels. The whole group will also have another blood sample stored for whole gene analysis.', 'detailedDescription': "Overarching aim: To improve the case detection rate of T2D in young Singaporeans adults aged 21-40y.\n\nSpecific Aim 1: To conduct a case-finding study for T2D and prediabetes through age- and BMI-stratified sampling in a contemporary population of young Singaporean adults aged 21-40y.\n\nSpecific Aim 2: To identify novel risk factors and develop a composite score to improve the detection rate for Asian YOD and prediabetes. These include non-traditional predictors such as glucometrics from continuous glucose monitoring (CGM), body composition measures, and socio-behavioural analyses.\n\nSpecific Aim 3: To identify the contribution of genomic differences to the risk of Asian Young Onset Diabetes\n\nTo fulfil Aim 1 within the first 1 to 2 years, the investigators plan to perform island-wide screening for diabetes or prediabetes amongst people aged 21-40y (n=3000). Recruitment will be stratified firstly by age categories (21-25y, 25-30y, 30-35y, 35-40y), aiming for n=750 per age category, followed by BMI categories of normal, overweight or obese by Asian thresholds (\\<23kgm2, 23-27.5kg/m2 and \\>=27.5kg/m2) within each age group. Participants will be recruited through online and print media including social media advertisements, word of mouth and /or referrals. A study poster advert will be posted online and in print, which will then direct participants to a webpage www.thdiary.sg which will explain the study design further and eligibility requirements and additional study details. The partiipants can proceed to register themselves via FORMSG on this webpage and if they meet the criteria they will be directed to CALSG to book an appointment with the study team.\n\nUpon consent and recruitment, the following will be done:\n\n1. Anthropometric measurements alongside traditional risk factors including blood pressure (BP), and waist-hip-ratio.\n2. Body Impedance Analysis. This is a painless way to measure what the body is made of and involves standing on a special scale and holding onto handles.\n3. Venipuncture will be conducted for an oral glucose tolerance test (OGTT) for 0 min, 1h and 2h glucose readings and HbA1c and storage.\n4. Download of selected social media data (not directly containing personal data or posts) for up to 1 year preceding the visit from facebook, instagram and tiktok.\n5. Continuous glucose monitor (CGM) sensor insertion. On the day of CGM insertion, a pre-insertion questionnaire (using form.sg, DIARY skin reaction form 1 before sensor wear) will be filled in which includes a picture of the site before sensor insertion.\n6. A survey will also be conducted to ascertain sociodemographic (employment, type of residence) and educational status, family history of diabetes and comorbid conditions (if any), the individual's dietary intake, physical activity levels, and health-seeking behaviour. This survey will also include a section to fill in their average daily step count for 7/30 days. The participant will be guided to look for their step count data over 7 or 30 days (depending on what is available) from their smartphone activity tracker (this includes Apple Health, Samsung Health or Google Fit or any other activity tracker). This information will then be entered into the survey form on form.sg. No screenshots or data export is required.\n7. Handgrip measurements\n8. Second and third venipunctures for second part of OGTT.\n9. Collection of dietary data via a digital food log\n\nIn Aim 2, the investigators aim to identify novel contemporary risk markers associated with T2D or prediabetes in young adults. This aim will not require another study visit from participants. Stored samples from Aim 1 baseline OGTT venipuncture will be used as well as the data retrieved from the study procedures in aim 1. Those who are diagnosed with T2D and prediabetes (estimated n=200 each), together with a normoglycaemic group (n=200) from Aim 1 will have the following done to enable diabetes subtyping: lipids, C-peptide, Insulin levels, Glutamic Acid Decarboxylase (GAD), Islet Antigen 2 (IA-2) Antibodies (Ab) and Zinc Transport 8 (ZnT8) Ab.\n\nA composite score will then be developed for the diagnosis of prediabetes and diabetes. The dataset will be split into development and validation sets. Logistic regression modelling and Receiver Operating Characteristics (ROC) curve analysis will be employed to develop a composite score in identifying people with T2D or prediabetes, based on the sample with 200 newly diagnosed T2D, 200 prediabetes and 200 normoglycaemic participants. With the development set, two models will be fitted to predict a subject belongs to T2D, prediabetes or normoglycaemia: (a) candidate predictor variables of all abovementioned indicators and their derivatives, including sociodemographic, family history of diabetes and comorbid conditions, dietary intake, physical activity levels, body composition metrics, health-seeking behaviours, as well as CGM biomarkers, and (b) candidate predictor variables of all these variables except those extracted / derived from CGM. Variable selection methods will be employed to determine final models with optimal predictability, parsimony and model fit indices. Two composite scores, including and not including CGM biomarkers, will then be defined by the final selected models.\n\nTo fulfil aim 3, stored blood from participants will be used in ongoing large scale genomic studies such as the National Precision Medicine's Phase 3 programme. In this program, participants will have whole genome sequencing performed under research, with a cluster specific centralized genomics team made up of clinical geneticists, bioinformaticians, variant curators, and genetic counsellors available to process the genetic specimens end to end (genomics innovation hub). This would involve curating genes relevant to the disease subtype, in this case, diabetes, but also returning incidental findings that are Tier 1 American College of Medical Genetics and Genomics (ACMG) conditions. VCF files from the participants of this study will be returned to this study team so that further research can be done to determine if genomic information can further help risk stratify Asian YOD."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT'], 'maximumAge': '39 Years', 'minimumAge': '21 Years', 'samplingMethod': 'PROBABILITY_SAMPLE', 'studyPopulation': 'Islandwide across Singapore', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Asian/Part Asian ethnicity living in Singapore, not known to have diabetes\n\nExclusion Criteria:\n\n* Pregnancy women\n* Non-Asian ethnicity\n* On active cancer/steroid therapy\n* Haemoglobinopathies or haemolytic anaemia\n* Previous bariatric surgery\n* Previous partial/total pancreatectomy'}, 'identificationModule': {'nctId': 'NCT07452159', 'acronym': 'DIARY', 'briefTitle': 'Diabetes In Asians at Risk in Youth', 'organization': {'class': 'OTHER', 'fullName': 'Singapore General Hospital'}, 'officialTitle': 'Diabetes in Asians at Risk in Youth', 'orgStudyIdInfo': {'id': 'DIARY : CIRB 2025-0719'}, 'secondaryIdInfos': [{'id': 'Tanoto Foundation MRF', 'type': 'OTHER', 'domain': 'Tanoto'}]}, 'armsInterventionsModule': {'armGroups': [{'label': 'Singaporeans of Asian ethnicity under 40 years', 'description': 'Not previously known to have diabetes', 'interventionNames': ['Diagnostic Test: Oral glucose tolerance test and HbA1c', 'Other: Anthropometric measurements', 'Diagnostic Test: Body impedance Analysis', 'Diagnostic Test: Handgrip measurement', 'Diagnostic Test: Continuous glucose monitoring', 'Other: Food diary recording over days 2 and 3 of continuous glucose monitoring', 'Other: Survey', 'Other: Skin reaction information', 'Other: Download of social media data', 'Diagnostic Test: Whole genome sequencing']}], 'interventions': [{'name': 'Oral glucose tolerance test and HbA1c', 'type': 'DIAGNOSTIC_TEST', 'description': 'Following overnight fasting for 8 hours', 'armGroupLabels': ['Singaporeans of Asian ethnicity under 40 years']}, {'name': 'Anthropometric measurements', 'type': 'OTHER', 'description': 'Body Mass Index, Waist-Hip ratio, Blood pressure', 'armGroupLabels': ['Singaporeans of Asian ethnicity under 40 years']}, {'name': 'Body impedance Analysis', 'type': 'DIAGNOSTIC_TEST', 'description': 'Body composition analysis', 'armGroupLabels': ['Singaporeans of Asian ethnicity under 40 years']}, {'name': 'Handgrip measurement', 'type': 'DIAGNOSTIC_TEST', 'description': 'Handgrip strength measured using Jamar Dynanometer', 'armGroupLabels': ['Singaporeans of Asian ethnicity under 40 years']}, {'name': 'Continuous glucose monitoring', 'type': 'DIAGNOSTIC_TEST', 'description': 'Use of Retrospective continuous glucose monitoring sensor (Freestyle Libre Pro IQ)', 'armGroupLabels': ['Singaporeans of Asian ethnicity under 40 years']}, {'name': 'Food diary recording over days 2 and 3 of continuous glucose monitoring', 'type': 'OTHER', 'description': 'Including written food records and photographs for all food and drink intake', 'armGroupLabels': ['Singaporeans of Asian ethnicity under 40 years']}, {'name': 'Survey', 'type': 'OTHER', 'description': 'Retrieval of sociodemographic details, family history of diabetes and comorbid conditions, information on dietary intake, physical activity levels, and health seeking behaviour. This includes average daily step count for 7/30 days.', 'armGroupLabels': ['Singaporeans of Asian ethnicity under 40 years']}, {'name': 'Skin reaction information', 'type': 'OTHER', 'description': 'Form to feedback on any sensor skin reactions', 'armGroupLabels': ['Singaporeans of Asian ethnicity under 40 years']}, {'name': 'Download of social media data', 'type': 'OTHER', 'description': 'This will involve a highly curated list of information to be retrieved from Facebook, Instagram and TikTok to enable AI-led sociobehavioural profiling. This will not retrieve any information on posts, photos, likes, comments, reactions or any item that will express intent.', 'armGroupLabels': ['Singaporeans of Asian ethnicity under 40 years']}, {'name': 'Whole genome sequencing', 'type': 'DIAGNOSTIC_TEST', 'description': 'Whole blood sample will be retrieved and stored before being sent for whole genome sequencing at a later stage.', 'armGroupLabels': ['Singaporeans of Asian ethnicity under 40 years']}]}, 'contactsLocationsModule': {'centralContacts': [{'name': 'Daphne SL Gardner, BA, BMBCh (Oxon), MRCP (UK)', 'role': 'CONTACT', 'email': 'daphne.gardner@singhealth.com.sg', 'phone': '+6563214654'}, {'name': 'Navreen Kaur', 'role': 'CONTACT', 'email': 'navreen.k.g.singh@singhealth.com.sg'}], 'overallOfficials': [{'name': 'Daphne SL Gardner, BA, BMBCh(Oxon), MRCP (UK)', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Singapore Health'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO', 'description': 'This is an observational study, only aggregated data will be provided. In addition, there is a part of the study that retrieves information social media activity. There is a potential that individual level data can lead to sensitive personal information being revealed.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Singapore General Hospital', 'class': 'OTHER'}, 'collaborators': [{'name': 'SingHealth Duke-NUS Academic Medical Centre', 'class': 'UNKNOWN'}, {'name': 'Duke-NUS Centre of Quantitative Medicine', 'class': 'UNKNOWN'}, {'name': 'Data Science and Artificial intelligence Laboratory, SGH', 'class': 'UNKNOWN'}, {'name': 'Translational Research and Innovation Lab, SingHealth', 'class': 'UNKNOWN'}], 'responsibleParty': {'type': 'SPONSOR'}}}}