Ignite Creation Date:
2025-12-26 @ 4:00 PM
Ignite Modification Date:
2026-02-20 @ 10:43 PM
Study NCT ID:
NCT03647306
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
2025-11-14
First Post:
2018-08-23
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Behavioral Chronotype: Impact on Sleep and Metabolism
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D002318', 'term': 'Cardiovascular Diseases'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'PREVENTION', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 200}}, 'statusModule': {'overallStatus': 'ACTIVE_NOT_RECRUITING', 'startDateStruct': {'date': '2018-02-02', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-11', 'completionDateStruct': {'date': '2027-01-01', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-11-13', 'studyFirstSubmitDate': '2018-08-23', 'studyFirstSubmitQcDate': '2018-08-23', 'lastUpdatePostDateStruct': {'date': '2025-11-14', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2018-08-27', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2023-03-13', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'MI-IS', 'timeFrame': '15 days', 'description': 'The primary outcome measure is the Matsuda Index of Insulin Sensitivity.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['peripheral circadian clock', 'central circadian clocks', 'chronotype', 'diet'], 'conditions': ['Type2 Diabetes Mellitus', 'Cardiovascular Diseases']}, 'referencesModule': {'references': [{'pmid': '24433933', 'type': 'RESULT', 'citation': 'Maury E, Hong HK, Bass J. Circadian disruption in the pathogenesis of metabolic syndrome. Diabetes Metab. 2014 Nov;40(5):338-46. doi: 10.1016/j.diabet.2013.12.005. Epub 2014 Jan 14.'}, {'pmid': '22424658', 'type': 'RESULT', 'citation': 'Peek CB, Ramsey KM, Marcheva B, Bass J. Nutrient sensing and the circadian clock. Trends Endocrinol Metab. 2012 Jul;23(7):312-8. doi: 10.1016/j.tem.2012.02.003. Epub 2012 Mar 16.'}, {'pmid': '25599827', 'type': 'RESULT', 'citation': 'Dibner C, Schibler U. Circadian timing of metabolism in animal models and humans. J Intern Med. 2015 May;277(5):513-27. doi: 10.1111/joim.12347. Epub 2015 Feb 6.'}, {'pmid': '21112026', 'type': 'RESULT', 'citation': 'Arble DM, Ramsey KM, Bass J, Turek FW. Circadian disruption and metabolic disease: findings from animal models. Best Pract Res Clin Endocrinol Metab. 2010 Oct;24(5):785-800. doi: 10.1016/j.beem.2010.08.003.'}, {'pmid': '25927923', 'type': 'RESULT', 'citation': 'Gerhart-Hines Z, Lazar MA. Circadian metabolism in the light of evolution. Endocr Rev. 2015 Jun;36(3):289-304. doi: 10.1210/er.2015-1007. Epub 2015 Apr 30.'}, {'pmid': '24829483', 'type': 'RESULT', 'citation': 'Summa KC, Turek FW. Chronobiology and obesity: Interactions between circadian rhythms and energy regulation. Adv Nutr. 2014 May 14;5(3):312S-9S. doi: 10.3945/an.113.005132. Print 2014 May.'}, {'pmid': '19255424', 'type': 'RESULT', 'citation': 'Scheer FA, Hilton MF, Mantzoros CS, Shea SA. Adverse metabolic and cardiovascular consequences of circadian misalignment. Proc Natl Acad Sci U S A. 2009 Mar 17;106(11):4453-8. doi: 10.1073/pnas.0808180106. Epub 2009 Mar 2.'}, {'pmid': '25870289', 'type': 'RESULT', 'citation': 'Morris CJ, Yang JN, Garcia JI, Myers S, Bozzi I, Wang W, Buxton OM, Shea SA, Scheer FA. Endogenous circadian system and circadian misalignment impact glucose tolerance via separate mechanisms in humans. Proc Natl Acad Sci U S A. 2015 Apr 28;112(17):E2225-34. doi: 10.1073/pnas.1418955112. Epub 2015 Apr 13.'}, {'pmid': '22496545', 'type': 'RESULT', 'citation': "Buxton OM, Cain SW, O'Connor SP, Porter JH, Duffy JF, Wang W, Czeisler CA, Shea SA. Adverse metabolic consequences in humans of prolonged sleep restriction combined with circadian disruption. Sci Transl Med. 2012 Apr 11;4(129):129ra43. doi: 10.1126/scitranslmed.3003200."}, {'pmid': '24458353', 'type': 'RESULT', 'citation': 'Leproult R, Holmback U, Van Cauter E. Circadian misalignment augments markers of insulin resistance and inflammation, independently of sleep loss. Diabetes. 2014 Jun;63(6):1860-9. doi: 10.2337/db13-1546. Epub 2014 Jan 23.'}, {'pmid': '25404342', 'type': 'RESULT', 'citation': 'McHill AW, Melanson EL, Higgins J, Connick E, Moehlman TM, Stothard ER, Wright KP Jr. Impact of circadian misalignment on energy metabolism during simulated nightshift work. Proc Natl Acad Sci U S A. 2014 Dec 2;111(48):17302-7. doi: 10.1073/pnas.1412021111. Epub 2014 Nov 17.'}, {'pmid': '26414564', 'type': 'RESULT', 'citation': 'Morris CJ, Garcia JI, Myers S, Yang JN, Trienekens N, Scheer FA. The Human Circadian System Has a Dominating Role in Causing the Morning/Evening Difference in Diet-Induced Thermogenesis. Obesity (Silver Spring). 2015 Oct;23(10):2053-8. doi: 10.1002/oby.21189.'}, {'pmid': '26771705', 'type': 'RESULT', 'citation': 'Morris CJ, Purvis TE, Mistretta J, Scheer FA. Effects of the Internal Circadian System and Circadian Misalignment on Glucose Tolerance in Chronic Shift Workers. J Clin Endocrinol Metab. 2016 Mar;101(3):1066-74. doi: 10.1210/jc.2015-3924. Epub 2016 Jan 15.'}, {'pmid': '27271308', 'type': 'RESULT', 'citation': 'Grimaldi D, Carter JR, Van Cauter E, Leproult R. Adverse Impact of Sleep Restriction and Circadian Misalignment on Autonomic Function in Healthy Young Adults. Hypertension. 2016 Jul;68(1):243-50. doi: 10.1161/HYPERTENSIONAHA.115.06847. Epub 2016 Jun 6.'}, {'pmid': '26411343', 'type': 'RESULT', 'citation': 'Gill S, Panda S. A Smartphone App Reveals Erratic Diurnal Eating Patterns in Humans that Can Be Modulated for Health Benefits. Cell Metab. 2015 Nov 3;22(5):789-98. doi: 10.1016/j.cmet.2015.09.005. Epub 2015 Sep 24.'}, {'pmid': '26706567', 'type': 'RESULT', 'citation': 'Zarrinpar A, Chaix A, Panda S. Daily Eating Patterns and Their Impact on Health and Disease. Trends Endocrinol Metab. 2016 Feb;27(2):69-83. doi: 10.1016/j.tem.2015.11.007. Epub 2015 Dec 17.'}, {'pmid': '26564131', 'type': 'RESULT', 'citation': 'Arble DM, Bass J, Behn CD, Butler MP, Challet E, Czeisler C, Depner CM, Elmquist J, Franken P, Grandner MA, Hanlon EC, Keene AC, Joyner MJ, Karatsoreos I, Kern PA, Klein S, Morris CJ, Pack AI, Panda S, Ptacek LJ, Punjabi NM, Sassone-Corsi P, Scheer FA, Saxena R, Seaquest ER, Thimgan MS, Van Cauter E, Wright KP. Impact of Sleep and Circadian Disruption on Energy Balance and Diabetes: A Summary of Workshop Discussions. Sleep. 2015 Dec 1;38(12):1849-60. doi: 10.5665/sleep.5226.'}]}, 'descriptionModule': {'briefSummary': 'The purpose of this study is to examine how the timing of eating changes how the body makes and uses energy (metabolism). This study will also examine if metabolism changes with age.', 'detailedDescription': 'The timing of food intake and caloric distribution across the 24hr day are emerging as contributing factors to weight gain. The idea that not only what you eat, but when you eat can contribute to weight gain has garnered interest from both the scientific community and the public. In fact, the distribution of caloric intake over the 24hr day has been recently recognized as a potential source of "circadian misalignment" which can result in adverse health outcomes, including overeating, impaired glucose tolerance, insulin sensitivity, and cardiovascular disease risk. This study will provide proof-of-concept evidence on the impact of misalignment on glucose metabolism and blood pressure regulation. This study will focus on overweight individuals who are at high risk of obesity but are still on a trajectory that can potentially be reversed by lifestyle changes. Following a careful assessment of the subject\'s habitual sleep and meal timing and caloric distribution under real life conditions, a short laboratory study will determine 24hr profiles of hormones involved in circadian timing, food intake and cardiovascular risk in a session that will mimic habitual sleep/wake and caloric distribution. Participants will then be randomized to one of three groups in which caloric distribution across the day will either be equally distributed between 3 meals, or heavily weighted to the morning or heavily weighted to the evening. During a 6-day semi-ambulatory in patient intervention, combining laboratory and ambulatory procedures, study procedures will assess the effect of experimentally changing caloric distribution across the day, advancing versus delaying the dietary chronotype. After 7 days of this caloric distribution intervention, we will then repeat the short laboratory session to assess whether the intervention of caloric distribution altered any of the measured profiles. The outcome measures will be the timing of the dim light melatonin onset (DLMO), blood pressure dipping, and insulin sensitivity. The proposed work will provide unambiguous evidence related to the efficacy of a novel lifestyle intervention - that could be more acceptable than dietary restriction or exercise - to reduce the risk of T2DM and CVD in adults at risk due to age and degree of adiposity. Moreover, our project will examine both middle-aged adults and older adults. The younger age group is of interest because of a lesser burden of illness and of an opportunity to alter the trajectory of aging at an earlier stage. The older age group is expected to have more severe circadian disturbances at baseline, with the potential of a larger effect on CM risk. The combined examination of metabolic risk and CVD risk in the context of circadian function is also novel.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '75 Years', 'minimumAge': '30 Years', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Healthy overweight and obese (25 kg/m2 ≤BMI\\< 40 kg/m2) men and women\n* aged 30-75 years\n* self-report sleeping at least 6.5-hrs/night but no more than 9-hrs/night, between 21:00 and 09:00\n* signed informed consent\n\nExclusion Criteria:\n\n* participation in a medically managed weight loss program within the past year\n* undergone bariatric surgery\n* dietary restrictions\n* Subjects will not have undergone surgery, donated a unit of blood, worked night shifts or crossed any time zones, or participated in another clinical study within a month prior to the study.\n* pregnancy in women\n* lactating women\n* Female subjects must not be actively going through menopause.\n* prisoners\n* inability to consent\n* members of the study team\n* Females with a hemoglobin \\< 11.5g/dL, and males with a hemoglobin \\< 13.5 g/dl will be excluded from the study.\n* presence of a sleep disorder such as moderate or severe sleep apnea (AHI≥15), a Circadian Rhythm Sleep Disorder (DSM-V criteria for advance sleep phase syndrome, delayed sleep phase syndrome, non 24-h sleep disorder, irregular sleep disorder and shift-work related sleep disorder),\n* a diagnosis of diabetes based on history or screening tests\n* other forms of endocrine dysfunction including PCOS;\n* a history of cognitive or other neurological disorders;\n* a history of major psychiatric disorder based on DSM-V criteria,\n* the presence of unstable or serious medical conditions,\n* any GI disease that requires dietary adjustment;\n* current, or use within the past month of melatonin, psychoactive, hypnotic, stimulant or pain medications (except occasionally); beta blockers; habitual smoking (6 or more cigarettes per week); caffeine consumption of greater than 500 mg per day'}, 'identificationModule': {'nctId': 'NCT03647306', 'briefTitle': 'Behavioral Chronotype: Impact on Sleep and Metabolism', 'organization': {'class': 'OTHER', 'fullName': 'University of Chicago'}, 'officialTitle': 'Behavioral Chronotype: Impact on Sleep and Metabolism', 'orgStudyIdInfo': {'id': 'IRB17-1768'}, 'secondaryIdInfos': [{'id': 'P01AG011412', 'link': 'https://reporter.nih.gov/quickSearch/P01AG011412', 'type': 'NIH'}]}, 'armsInterventionsModule': {'armGroups': [{'type': 'ACTIVE_COMPARATOR', 'label': 'Extended Overnight Fast', 'description': 'The extended overnight fast group will have scheduled meal times for the entire 6 day semi ambulatory and in lab session. Subjects will consume approximately 33% of their daily calories at breakfast, lunch and dinner, respectively. This is a model for fasting dietary chronotype.', 'interventionNames': ['Behavioral: Extended Overnight Fast']}, {'type': 'EXPERIMENTAL', 'label': 'Early Total Caloric Intake', 'description': 'The Early Total Caloric Intake study group will have scheduled meal times for the entire 6 day semi ambulatory and in lab session and will consume 60% of their daily calories during breakfast. The remaining 40% of daily calories will be consumed during lunch and dinner. This is a model for early dietary chronotype.', 'interventionNames': ['Behavioral: Early Total Caloric Intake']}, {'type': 'EXPERIMENTAL', 'label': 'Late Total Caloric Intake', 'description': 'The Late Total Caloric Intake study group will have scheduled meal times for the entire 6 day semi ambulatory and in lab session and will consume 40% of daily calories during breakfast and lunch. The remaining 60% of daily calories will be consumed during dinner. This is a model for late dietary chronotype.', 'interventionNames': ['Behavioral: Late Total Caloric Intake']}], 'interventions': [{'name': 'Early Total Caloric Intake', 'type': 'BEHAVIORAL', 'description': 'Provide subjects a regimented amount of calories at each meal.', 'armGroupLabels': ['Early Total Caloric Intake']}, {'name': 'Late Total Caloric Intake', 'type': 'BEHAVIORAL', 'description': 'Provide subjects a regimented amount of calories at each meal.', 'armGroupLabels': ['Late Total Caloric Intake']}, {'name': 'Extended Overnight Fast', 'type': 'BEHAVIORAL', 'description': 'Provide subjects a regimented amount of calories at each meal.', 'armGroupLabels': ['Extended Overnight Fast']}]}, 'contactsLocationsModule': {'locations': [{'zip': '60637', 'city': 'Chicago', 'state': 'Illinois', 'country': 'United States', 'facility': 'University of Chicago', 'geoPoint': {'lat': 41.85003, 'lon': -87.65005}}], 'overallOfficials': [{'name': 'Eve Van Cauter, PhD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'University of Chicago'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of Chicago', 'class': 'OTHER'}, 'collaborators': [{'name': 'National Institute on Aging (NIA)', 'class': 'NIH'}, {'name': 'Northwestern University', 'class': 'OTHER'}], 'responsibleParty': {'type': 'SPONSOR'}}}}