Modeling HIV Rebound: Role of SIVmac251 Functional Reservoirs and Biomarkers of Reactivation
Modeling HIV Rebound: Role of SIVmac251 Functional Reservoirs and Biomarkers of Reactivation
批准号:
9322137
负责人:
JANICE E CLEMENTS
金额:
$162.82万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-06-23 至 2022-05-31
关键词:
AddressAnimal ModelAnti-Retroviral AgentsAssesBiological AssayBiological MarkersBloodCD4 Positive T LymphocytesCell LineageCellsCerebrospinal FluidChronicComputer AnalysisComputer SimulationDataDiseaseGeneticGenomeGoldHIVHIV-1HumanIndividualInfectionInterruptionKineticsLatent VirusLengthLifeLiquid substanceLungLymphoid TissueMacacaMacaca mulattaMeasuresModelingMyelogenousMyeloid CellsPathway interactionsPlasmaRestRoleSIVSiteSourceSpleenTimeTissuesTranslationsViralViral GenomeViral reservoirVirusVirus Latencyantiretroviral therapycell typedesigngastrointestinalgenome analysisimprovedinsightlymph nodesmacrophagememory CD4 T lymphocytenonhuman primateprogramsviral reboundvirology
中文摘要
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英文摘要
Abstract
Despite fully suppressive ART for long periods of time, HIV rebounds in the majority of
individuals when ART is interrupted. Studies in this proposal will define and quantitate
the functional SIV latent reservoirs in tissue to understand the contributions of both
CD4+T cells and macrophages to the functional viral reservoir and viral rebound after
ART interruption. The SIVmac251 ART suppressed model will be used to quantitate the
functional viral reservoir in CD4+ T cells and macrophages to asses their contribution to
viral rebound. Depletion of CD4 cells and reduction of the latent reservoir will be done to
address whether CD4 cells are the major HIV reservoir or if latently infected
macrophages significantly contribute to HIV rebound. The projects in this Program will
1) Identify the differential contribution of resting CD4+ T cells and resident macrophages
to viral rebound after antiretroviral treatment interruption; 2) Identify the source of viral
rebound using SIV proviral genome analysis; and 3) Use computational modeling and
analyses of SIV virus rebound to understand HIV rebound.
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