Viewing Study NCT03133559


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Study NCT ID: NCT03133559
Status: SUSPENDED
Last Update Posted: 2025-09-10
First Post: 2016-12-21
Is Gene Therapy: True
Has Adverse Events: False

Brief Title: Mapping the Human HIV Chronobiome
Sponsor:
Organization:

Raw JSON

{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D000163', 'term': 'Acquired Immunodeficiency Syndrome'}], 'ancestors': [{'id': 'D015658', 'term': 'HIV Infections'}, {'id': 'D000086982', 'term': 'Blood-Borne Infections'}, {'id': 'D003141', 'term': 'Communicable Diseases'}, {'id': 'D007239', 'term': 'Infections'}, {'id': 'D015229', 'term': 'Sexually Transmitted Diseases, Viral'}, {'id': 'D012749', 'term': 'Sexually Transmitted Diseases'}, {'id': 'D016180', 'term': 'Lentivirus Infections'}, {'id': 'D012192', 'term': 'Retroviridae Infections'}, {'id': 'D012327', 'term': 'RNA Virus Infections'}, {'id': 'D014777', 'term': 'Virus Diseases'}, {'id': 'D012897', 'term': 'Slow Virus Diseases'}, {'id': 'D000091662', 'term': 'Genital Diseases'}, {'id': 'D000091642', 'term': 'Urogenital Diseases'}, {'id': 'D007153', 'term': 'Immunologic Deficiency Syndromes'}, {'id': 'D007154', 'term': 'Immune System Diseases'}]}, 'interventionBrowseModule': {'meshes': [{'id': 'D057832', 'term': 'Watchful Waiting'}], 'ancestors': [{'id': 'D017063', 'term': 'Outcome Assessment, Health Care'}, {'id': 'D010043', 'term': 'Outcome and Process Assessment, Health Care'}, {'id': 'D011787', 'term': 'Quality of Health Care'}, {'id': 'D006298', 'term': 'Health Services Administration'}]}}, 'protocolSection': {'designModule': {'bioSpec': {'retention': 'SAMPLES_WITH_DNA', 'description': 'Biospecimen = None for Cohort 1. Completed Cohort 1.'}, 'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'CASE_CONTROL'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 80}, 'patientRegistry': False}, 'statusModule': {'whyStopped': 'Protocol Modification is pending', 'overallStatus': 'SUSPENDED', 'startDateStruct': {'date': '2017-04-19', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-09', 'completionDateStruct': {'date': '2029-08', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-09-03', 'studyFirstSubmitDate': '2016-12-21', 'studyFirstSubmitQcDate': '2017-04-25', 'lastUpdatePostDateStruct': {'date': '2025-09-10', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2017-04-28', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2027-02', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Time-of-day fluctuations in core clock gene expression', 'timeFrame': '48 hours', 'description': 'Relative expression normalized to housekeeping genes (GAPDH, ACTB) plotted by time of day (morning, afternoon, evening, night with target times of 08:00, 14:00, 20:00, 02:00 +/- 1 hour)'}], 'secondaryOutcomes': [{'measure': 'Variance explained [R^2 values]', 'timeFrame': '48 hours', 'description': 'To evaluate the linear relationships between every pairwise combination of variables in the integrated dataset, the R\\^2, or coefficient of determination, will be calculated for each pair using linear regression. A heat map of the proportion of variance in each variable (e.g. mobility, light exposure, systolic blood pressure) explained by each other variable will then be constructed to allow an integrative exploration of these data. This approach allows to integrate multiple measurements with different units of measure. The measurements include communication (number of phone calls and text messages), mobility (miles traveled), light exposure, blood pressure, heart rate, heart rate variability, sleep/wake times, body core temperature, multiomics outputs (abundance of metabolites, proteins, microbiota) and markers of cellular and inflammatory function and disease state (HIV infection).'}, {'measure': 'Variance explained [R^2 values]', 'timeFrame': 'up to 4 months', 'description': 'To evaluate the linear relationships between every pairwise combination of variables in the integrated dataset, the R\\^2, or coefficient of determination, will be calculated for each pair using linear regression. A heat map of the proportion of variance in each variable (e.g. mobility, light exposure, systolic blood pressure) explained by each other variable will then be constructed to allow an integrative exploration of these data. This approach allows to integrate multiple measurements with different units of measure. The measurements include communication (number of phone calls and text messages), mobility (miles traveled), light exposure, and sleep/wake times.'}]}, 'oversightModule': {'oversightHasDmc': False}, 'conditionsModule': {'conditions': ['Hiv', 'Healthy']}, 'descriptionModule': {'briefSummary': 'Individuals infected with HIV have a high risk of developing metabolic comorbidities not traditionally associated with the immune dysregulation and deficiency associated with HIV infection and AIDS. Many of these comorbidities in HIV uninfected individuals have been linked to a disordered circadian clock function. The study investigators will further evaluate the circadian clock in HIV infection as a mechanism underlying the metabolic dysregulation in this population.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT'], 'maximumAge': '50 Years', 'minimumAge': '25 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Cohort 1: patients infected with HIV off antiretroviral therapy;\n\nCohort 2: patients infected with HIV experiencing virologic control, but with blunted immunologic recovery;\n\nCohort 3: matched healthy volunteers.', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Cohort 1: Diagnosis of HIV infection with CD4+ counts \\<500 cells/mm3 while untreated;\n* Cohort 2: Diagnosis of HIV infection with CD4+ counts \\<300 cells/mm3 on ARV;\n* Cohort 3: Volunteers must be in good health as based on medical history, physical examination, vital signs, and laboratory tests as deemed by PI;\n* Volunteers are capable of giving informed consent;\n* 25-50 years of age;\n* Own a smartphone which installs the remote sensing applications;\n* Non-smoking;\n* Male subjects only if feasible during recruitment; and\n* In case female volunteers are invited to enroll: non-pregnant, female subjects must consent to a urine pregnancy test.\n* Females of child bearing potential will be asked to use a medically accepted method of birth control (such as oral contraceptives, intra-uterine device (IUD), or condom with spermicide) while you participate in the study.\n* The use of contraception will NOT be required for male participants.\n\nExclusion Criteria:\n\n* Recent travel across more than two (2) time zones (within the past month);\n* Planned travel across more than two (2) time zones during the planned study activities;\n* Volunteers with irregular work hours, e.g. night shifts or becoming a parent;\n* Use of illicit drugs;\n* High dose vitamins (Vitamin A, Vitamin C, Vitamin E, Beta Carotene, Folic Acid and Selenium), alcohol and any over-the counter NSAID in the (2) two weeks before the start of the 48 hour deep phenotyping period (Females who are taking birth control pills can continue so for the duration of this study).;\n* History of abdominal surgery;\n* Subjects, who have received an experimental drug, used an experimental medical device within 30 days prior to screening, or who gave a blood donation of ≥ one pint within 8 weeks prior to screening;\n* Subjects with any abnormal laboratory value or physical finding that according to the investigator may interfere with interpretation of the study results, be indicative of an underlying disease state, or compromise the safety of a potential subject.\n* Women who are breastfeeding.'}, 'identificationModule': {'nctId': 'NCT03133559', 'acronym': 'HCB', 'briefTitle': 'Mapping the Human HIV Chronobiome', 'organization': {'class': 'OTHER', 'fullName': 'University of Pennsylvania'}, 'officialTitle': 'Mapping the Human Immunodeficiency Virus Chronobiome, (HIV)', 'orgStudyIdInfo': {'id': '825626'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Cohort 1', 'description': 'Patients infected with HIV off antiretroviral therapy', 'interventionNames': ['Other: Observational']}, {'label': 'Cohort 2', 'description': 'Patients infected with HIV experiencing virologic control, but with blunted immunologic recovery', 'interventionNames': ['Other: Observational']}, {'label': 'Cohort 3', 'description': 'Matched healthy volunteers', 'interventionNames': ['Other: Observational']}], 'interventions': [{'name': 'Observational', 'type': 'OTHER', 'description': 'We will use a deep phenotyping approach to collect multidimensional datasets from individuals infected with HIV compared to healthy controls to define circadian rhythm disruptions associated with HIV infection.', 'armGroupLabels': ['Cohort 1', 'Cohort 2', 'Cohort 3']}]}, 'contactsLocationsModule': {'locations': [{'zip': '19104', 'city': 'Philadelphia', 'state': 'Pennsylvania', 'country': 'United States', 'facility': 'Institute for Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania School of Medicine', 'geoPoint': {'lat': 39.95238, 'lon': -75.16362}}], 'overallOfficials': [{'name': 'Carsten Skarke, MD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'University of Pennsylvania'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'YES', 'description': 'To be determined'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of Pennsylvania', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Research Assistant Professor', 'investigatorFullName': 'Carsten Skarke, MD', 'investigatorAffiliation': 'University of Pennsylvania'}}}}