Virally suppressed people with HIV (PWH) remain at risk for developing comorbidities due to chronic inflammation with one potential contributor being the HIV reservoir. Associations between the CD4-reservoir and inflammation have been extensively characterized, while the role the monocyte-reservoir is poorly understood despite evidence that inflammatory monocytes play a role in HIV-associated comorbidities. Additionally, most studies focus on a single cellular reservoir, while it is highly likely that these reservoirs are interdependent. In a cohort of 164 PWH, we used the intact proviral DNA assay to quantify cell-specific reservoirs, applied unsupervised clustering to identify reservoir phenotypes, and then determined if reservoir phenotypes were associated with distinct immune signatures compared to people without HIV. Five unique reservoir clusters emerged driven primarily by variability in the monocyte reservoir, and each associated with a distinct immune landscape. These included profiles characterized by systemic inflammation, leukocyte–vascular activation, T cell activation with vascular and neuronal injury, enhanced CD8 activation and NK cell recovery, and altered monocyte survival, activation, and migration. This multidimensional approach provides a framework to identify reservoir-immune profiles that may explain heterogeneity in inflammation despite viral suppression and may inform strategies to mitigate HIV-associated comorbidities.
Ruoyu Wang, Aparna B. Bhattacharyya, Lily Pohlenz, Erin N. Shirk, Hayley S. Romero, Katherine Haas, Jennifer M. Coughlin, Raha M. Dastgheyb, Leah H. Rubin, Rebecca T. Veenhuis
Usage data is cumulative from May 2026 through May 2026.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 76 | 0 |
| 39 | 0 | |
| Supplemental data | 52 | 0 |
| Citation downloads | 9 | 0 |
| Totals | 176 | 0 |
| Total Views | 176 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.