Ignite Creation Date:
2025-12-24 @ 10:15 PM
Ignite Modification Date:
2025-12-25 @ 7:49 PM
Study NCT ID:
NCT05769335
Status:
COMPLETED
Last Update Posted:
2025-05-09
First Post:
2023-03-01
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Calories or Time Restriction to Alter Biomarkers of Aging and Diabetes
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D009765', 'term': 'Obesity'}, {'id': 'D007249', 'term': 'Inflammation'}], 'ancestors': [{'id': 'D050177', 'term': 'Overweight'}, {'id': 'D044343', 'term': 'Overnutrition'}, {'id': 'D009748', 'term': 'Nutrition Disorders'}, {'id': 'D009750', 'term': 'Nutritional and Metabolic Diseases'}, {'id': 'D001835', 'term': 'Body Weight'}, {'id': 'D012816', 'term': 'Signs and Symptoms'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}, {'id': 'D010335', 'term': 'Pathologic Processes'}]}}, 'documentSection': {'largeDocumentModule': {'largeDocs': [{'date': '2024-12-19', 'size': 441628, 'label': 'Statistical Analysis Plan', 'hasIcf': False, 'hasSap': True, 'filename': 'SAP_000.pdf', 'typeAbbrev': 'SAP', 'uploadDate': '2024-12-19T18:35', 'hasProtocol': False}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'BASIC_SCIENCE', 'interventionModel': 'PARALLEL', 'interventionModelDescription': 'The OMIT study will be a parallel, single-blinded, 3-arm randomised controlled trial.'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 114}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2023-03-15', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-05', 'completionDateStruct': {'date': '2025-04-17', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2025-05-08', 'studyFirstSubmitDate': '2023-03-01', 'studyFirstSubmitQcDate': '2023-03-13', 'lastUpdatePostDateStruct': {'date': '2025-05-09', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2023-03-15', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2024-12-10', 'type': 'ACTUAL'}}, 'outcomesModule': {'otherOutcomes': [{'measure': 'Postprandial glucose and insulin AUC of each meal', 'timeFrame': '8 weeks', 'description': 'Postprandial glucose and insulin AUC of breakfast, lunch, dinner'}, {'measure': 'Non-esterified fatty acids (fasting, postprandial AUC)', 'timeFrame': '8 weeks', 'description': 'Change in free fatty acids fasting, postprandial AUC of each meal, and sum of 3 meals'}, {'measure': 'Triglycerides (fasting, postprandial AUC)', 'timeFrame': '8 weeks', 'description': 'Change in triglycerides as fasting, postprandial AUC of each meal, postprandial AUC sum of 3 meals'}, {'measure': 'Insulin secretion rate', 'timeFrame': '8 weeks', 'description': 'calculated from C-peptide response to each meal, and overall'}, {'measure': 'Insulin sensitivity (calculated by Matsuda index where a higher score means greater insulin sensitivity)', 'timeFrame': '8 weeks', 'description': 'Change in insulin sensitivity'}, {'measure': '24 h glucometrics on ward (by continuous glucose monitor [CGM])', 'timeFrame': '8 weeks', 'description': 'Change in 24 h glucose on ward by CGM (iAUC, mean nocturnal glucose \\[2400-0400\\], ,mean, time in range, time above range, time below range, mean amplitude of glycemic excursions \\[MAGE\\])'}, {'measure': 'HOMA-IR', 'timeFrame': '8 weeks', 'description': 'Change in HOMA-IR calculated as \\[fasting insulin ug/ml\\]\\*\\[fasting glucose mmol/L\\]/22.5'}, {'measure': 'Fasting C-peptide', 'timeFrame': '8 weeks', 'description': 'change in fasting C-peptide'}, {'measure': 'Total cholesterol', 'timeFrame': '8 weeks', 'description': 'Change in total cholesterol'}, {'measure': 'HDL cholesterol', 'timeFrame': '8 weeks', 'description': 'Change in HDL cholesterol'}, {'measure': 'LDL cholesterol', 'timeFrame': '8 weeks', 'description': 'Change in LDL cholesterol'}, {'measure': 'C-reactive protein (CRP)', 'timeFrame': '8 weeks', 'description': 'Change in hs-CRP'}, {'measure': 'Physical activity by activity monitor', 'timeFrame': '8 weeks', 'description': 'Change sitting time, standing time, stepping time, mean daily steps'}, {'measure': 'Sleep metrics', 'timeFrame': '8 weeks', 'description': 'Change in sleep metrics (including sleep duration, sleep latency, light:deep:REM sleep, apnoea hypopnoea index, arousals)'}, {'measure': 'Adherence', 'timeFrame': '8 weeks', 'description': 'Adherence to the prescribed eating window(+/- 1 hour) by smart phone application; includes number of days adherent, length of eating window, 95% eating window'}, {'measure': 'Energy and macronutrient intake', 'timeFrame': '8 weeks', 'description': 'Calculated total energy intake, intake of carbohydrate, protein, fat, saturated fat, fibre, alcohol'}, {'measure': 'Blood pressure', 'timeFrame': '8 weeks', 'description': 'Change in office blood pressure'}, {'measure': 'Body weight', 'timeFrame': '8 weeks', 'description': 'Change in body weight'}, {'measure': 'Appetite sensations', 'timeFrame': '8 weeks', 'description': 'Changes in measures of appetite assessed by validated visual analog scale assessed on a 10 cm scale whereby 0 is very low and 10 is very high.'}, {'measure': 'Gastrointestinal hormones', 'timeFrame': '8 weeks', 'description': 'Change in appetite hormone AUC after each meal and sum of 3 meals (ghrelin, glucagon-like peptide-1 \\[GLP-1\\])'}], 'primaryOutcomes': [{'measure': 'Glucose area under curve (AUC) after 3 meals', 'timeFrame': '8 weeks', 'description': 'Change in glucose AUC after 3 meals'}], 'secondaryOutcomes': [{'measure': 'Insulin area under the curve (AUC)', 'timeFrame': '8 weeks', 'description': 'Change in insulin AUC (sum of 3 meals)'}, {'measure': 'Fasting insulin', 'timeFrame': '8 weeks', 'description': 'Change in fasting insulin'}, {'measure': 'Fasting glucose', 'timeFrame': '8 weeks', 'description': 'Change in fasting glucose'}, {'measure': 'Change in glycated hemoglobin (HbA1c)', 'timeFrame': '8 weeks', 'description': 'Change in glycated hemoglobin'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Dietary intervention', 'Inflammation', 'Circadian rhythms', 'Cardiometabolic health'], 'conditions': ['Obesity']}, 'descriptionModule': {'briefSummary': 'Type 2 diabetes and cardiovascular disease are an increasing problem in Australia and around the world, and are partly linked to increased rates of obesity, together with sedentary lifestyles. This study will compare caloric restriction (CR) diets that restrict the amount of food that is eaten with CR diets that also restrict the time that the food is eaten, to either early or late in the day, on risk factors for type 2 diabetes and cardiovascular diseases over 2 months.', 'detailedDescription': 'In a parallel groups design, a total of 114 individuals will be recruited. After a two-week lead in and collection of data from activity monitors and continuous glucose monitors, plus a 28 hour (h) metabolic ward in-patient stay, participants will be randomised into one of three groups (eCR, 8-hour early time restriction + calorie restriction (e.g. 8:00-16:00); dCR, 8-hour delayed time restriction + calorie restriction (e.g. 12:00-20:00); CR, caloric restriction (\\>12 hour eating window (e.g. 8:00-20:00). All participants will receive individualised menus and foods that will be delivered to their homes by a supermarket delivery service at energy balance for 1 week (baseline) and at 70% of energy balance for a further 8 weeks. Repeat assessment occurs from 6-8 weeks with the final metabolic ward stay at 8-weeks to assess changes in primary and secondary outcomes.\n\nThere are three preplanned sub-studies from the parent trial:\n\nA. OMIT-Immune sub-study All participants will have blood samples collected at six timepoints over 24 hours and stool samples will be collected at two timepoints in a subset. The aims of this sub-study are to 1) characterize the changes in 24 h rhythm (mesor, amplitude and acrophase) of immune cells by flow cytometry over 24 hours, 2) describe the changes in the diversity of bacterial in response to intervention and 3) compare the effects of 8 weeks of CR versus eCR and dCR on immune profiles and gut microbiome.\n\nB. OMIT-BP sub-study All participants will have blood and urine samples collected at six timepoints over 24 hours. A subset of participants will wear 24 h ambulatory blood pressure monitors. The aims of this sub-study are to compare the effects of CR versus eCR and dCR on 1) the 24-hour profile of blood pressure assessed by ambulatory blood pressure monitoring, 2) Plasma markers of blood pressure regulation and 3) markers of renal function. We hypothesise that both eCR and dCR will alter and enhance these parameters and markers in comparison to CR. Changes in the circadian mesor, amplitude and acrophase in: systolic blood pressure, diastolic blood pressure, heart rate, pulse pressure, mean arterial pressure, nocturnal blood pressure dipping, morning blood pressure surge, plasma renin, aldosterone, creatinine, Urinary potassium, sodium, cortisol, creatinine.\n\nC. OMIT- Six month follow up. All participants will be instructed to continue their respective diet intervention and return to the clinic after an additional 16 weeks for a fasting blood sample and assessment of body composition. The aims of this sub-study are to 1) compare the 6 months effects of CR versus eCR and dCR on body composition and fasting blood samples metabolic health from baseline; 2) explore the factors that drive the intention-behaviour gap (describing the failure to translate intentions into action) relation to diet adherence. We hypothesize that participants will maintain the intervention-induced improvements in behavioural and metabolic health outcomes. Additionally, changes in body weight, waist and hip circumference, lean mass, fat mass, blood pressure, glycated hemoglobin, fasting plasma glucose, insulin, total cholesterol, LDL, HDL, triglycerides are assessed.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '75 Years', 'minimumAge': '35 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Overweight or obesity (BMI 25.1 - 44.9 kg/m2)\n* Elevated waist circumference (race specific),\n* Elevated fasting blood glucose (\\>5.6 mmol/L).\n\nExclusion Criteria:\n\nA personal history/diagnosis (self-reported) of:\n\n* diabetes (type 1 or 2)\n* major psychiatric disorders (schizophrenia, major depressive disorder, bipolar disorder, eating disorders)\n* gastrointestinal disorders/disease (including malabsorption)\n* haematological disorders (i.e. thalassemia, iron-deficiency anaemia)\n* insomnia\n* obstructive sleep apnea\n* night eating syndrome\n* diagnosis or treatment of cancer in the past 3 years (excluding non-melanoma skin cancer)\n* significant liver or kidney diseases that require ongoing medical care\n* previous or planned gastro-intestinal surgery (including bariatric surgery)\n* Congestive heart failure (NYHA stage 2 or above)\n* Previous myocardial infarction or significant cardiac event ≤ 6 months prior to screening\n* Previous cerebrovascular event ≤ 12 months prior to screening\n* Any autoimmune disease (i.e. rheumatoid arthritis)\n* Coeliac disease\n* Score less than 12 of the Australian Diabetes (AUSD) risk assessment tool\n* Do not eat for a 12 hour window each day for 5 or more days per week\n* Have extreme or restricted patterns of eating (i.e. following an intermittent fasting diet) or already engage in CR\n* Other dietary restrictions including vegans, gluten or nut allergies\n* Night shift-workers (\\>3 shifts per month)\n* pregnant, planning a pregnancy or currently breastfeeding\n* those who have lost or gained \\>5% of body weight in the last 6 months\n* donated blood in past 3 months\n* current smokers of cigarettes/marijuana/e-cigarettes/vaporisers\n* anyone unable to comprehend the study protocol or provide informed consent (i.e. due to English language or cognitive difficulties)\n* do not own, or are not comfortable using, a smart phone and applications\n\nCurrently taking the following medications:\n\n* Anti-diabetic medications that lower blood glucose including, but not limited to: SGLT2 inhibitors, metformin, sulfonylureas, glucagon-like peptide-1 (GLP-1) analogues \\[i.e. semaglutide\\], thiazolidinediones\n* affecting weight, appetite or gut motility, including, but not limited to semaglutide, domperidone, cisapride, orlistat, phentermine, topiramate.\n* Diuretics (i.e. frusemide, thiazides) or combination blood pressure medications containing a diuretic\n* Beta-blockers\n* Glucocorticoids\n* Anti-epileptic medications (i.e. pregabalin and gabapentin)\n* Tricyclic antidepressants\n* Some serotonin and norepinephrine reuptake inhibitors (i.e. vortioxetine, mirtazapine and venlafaxine)\n* Regular use of benzodiazepines or other sleep aids, including melatonin\n* Antipsychotic medications\n* Opioid medications unless combined with paracetamol in a single formulation and used occasionally on as needs basis'}, 'identificationModule': {'nctId': 'NCT05769335', 'acronym': 'OMIT', 'briefTitle': 'Calories or Time Restriction to Alter Biomarkers of Aging and Diabetes', 'organization': {'class': 'OTHER', 'fullName': 'University of Adelaide'}, 'officialTitle': 'The Effects of Caloric Restriction Plus Time Restriction on Glycemia, Circadian Rhythms and Cardiometabolic Health', 'orgStudyIdInfo': {'id': 'H-2022-199'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'early calorie restriction (eCR)', 'description': 'Individuals will be provided with menus prescribed at 70% of calculated energy requirements and instructed to eat within 8 h/day (e.g. 8:00 - 16:00) every day for 8 weeks, except 1 evening meal per week off the program (i.e. Saturday nights) to assist with overall adherence.', 'interventionNames': ['Other: eCR']}, {'type': 'EXPERIMENTAL', 'label': 'delayed calorie restriction (dCR)', 'description': 'Individuals will be provided with menus prescribed at 70% of calculated energy requirements and instructed to eat within 8 h/day (e.g 12:00 - 20:00) every day for 8 weeks, except 1 evening meal per week off the program (i.e. Saturday nights) to assist with overall adherence.', 'interventionNames': ['Other: dCR']}, {'type': 'ACTIVE_COMPARATOR', 'label': 'Calorie restriction (CR)', 'description': 'Individuals will be provided with menus prescribed at 70% of calculated energy requirements every day for 8 weeks. The menus will encourage breakfast and after-dinner consumption of the snack to eat over at least a 12 hour time frame per day (e.g. 8:00 - 20:00), except 1 evening meal per week off the program (i.e. Saturday nights) to assist with overall adherence.', 'interventionNames': ['Other: CR']}], 'interventions': [{'name': 'eCR', 'type': 'OTHER', 'description': 'Eating time window from 8:00 to 16:00', 'armGroupLabels': ['early calorie restriction (eCR)']}, {'name': 'dCR', 'type': 'OTHER', 'description': 'Eating time window from 12:00 to 20:00', 'armGroupLabels': ['delayed calorie restriction (dCR)']}, {'name': 'CR', 'type': 'OTHER', 'description': 'Eating time window from 8:00 to 20:00', 'armGroupLabels': ['Calorie restriction (CR)']}]}, 'contactsLocationsModule': {'locations': [{'zip': '5000', 'city': 'Adelaide', 'state': 'South Australia', 'country': 'Australia', 'facility': 'South Australian Health and Medical Research Institute / The University of Adelaide', 'geoPoint': {'lat': -34.92866, 'lon': 138.59863}}], 'overallOfficials': [{'name': 'Leonie Heilbronn, PhD.', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'The University of Adelaide'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of Adelaide', 'class': 'OTHER'}, 'collaborators': [{'name': 'University of Sydney', 'class': 'OTHER'}, {'name': 'Salk Institute for Biological Studies', 'class': 'OTHER'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Group Leader, Obesity and Metabolism', 'investigatorFullName': 'A/Prof Leonie Heilbronn', 'investigatorAffiliation': 'University of Adelaide'}}}}