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Protocol Modification is pending
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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Cohort 1 | Patients infected with HIV off antiretroviral therapy |
| |
| Cohort 2 | Patients infected with HIV experiencing virologic control, but with blunted immunologic recovery |
| |
| Cohort 3 | Matched healthy volunteers |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Observational | Other | 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. |
| Measure | Description | Time Frame |
|---|---|---|
| Time-of-day fluctuations in core clock gene expression | 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) | 48 hours |
| Measure | Description | Time Frame |
|---|---|---|
| Variance explained [R^2 values] | 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). |
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Inclusion Criteria:
Exclusion Criteria:
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Cohort 1: patients infected with HIV off antiretroviral therapy;
Cohort 2: patients infected with HIV experiencing virologic control, but with blunted immunologic recovery;
Cohort 3: matched healthy volunteers.
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| Name | Affiliation | Role |
|---|---|---|
| Carsten Skarke, MD | University of Pennsylvania | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Institute for Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania School of Medicine | Philadelphia | Pennsylvania | 19104 | United States |
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| ID | Term |
|---|---|
| D000163 | Acquired Immunodeficiency Syndrome |
| ID | Term |
|---|---|
| D015658 | HIV Infections |
| D000086982 | Blood-Borne Infections |
| D003141 | Communicable Diseases |
| D007239 | Infections |
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| ID | Term |
|---|---|
| D057832 | Watchful Waiting |
| ID | Term |
|---|---|
| D017063 | Outcome Assessment, Health Care |
| D010043 | Outcome and Process Assessment, Health Care |
| D011787 | Quality of Health Care |
| D006298 | Health Services Administration |
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Biospecimen = None for Cohort 1. Completed Cohort 1.
| 48 hours |
| Variance explained [R^2 values] | 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. | up to 4 months |
| D015229 |
| Sexually Transmitted Diseases, Viral |
| D012749 | Sexually Transmitted Diseases |
| D016180 | Lentivirus Infections |
| D012192 | Retroviridae Infections |
| D012327 | RNA Virus Infections |
| D014777 | Virus Diseases |
| D012897 | Slow Virus Diseases |
| D000091662 | Genital Diseases |
| D000091642 | Urogenital Diseases |
| D007153 | Immunologic Deficiency Syndromes |
| D007154 | Immune System Diseases |