Abstract Body

Background: HIV is transmitted via mucosal and intravenous routes, replicating initially in CD4+ T cells at mucosal sites and draining lymph nodes. Following systemic dissemination, a major reservoir of infection is established in gut-associated lymphoid tissues (GALT), which eventually leads to depletion of GALT CD4+ T cells, altered mucosal defenses, gut mucosal injury, and microbial translocation. Despite host immune responses and antiviral therapies that suppress viral replication, viral reservoirs persist in long-lived memory CD4+ T cells, including a stem-cell like population (Tscm). Additional reservoirs of viral persistence are established in macrophages in the brain and other macrophage-rich tissues. Chronic immune activation, a hallmark of HIV infection, is a strong predictor of disease progression, morbidity, and mortality that has also been linked to accelerated aging and age-related end-organ comorbidities involving the cardiovascular system, kidneys, liver, brain, endocrine system, and bone. Underlying causes of chronic immune activation include ongoing viral replication, persistently elevated interferon responses, and microbial translocation. Cofactors associated with the HIV epidemic, such as HCV and other co-infections, and substance abuse, can also increase innate immune activation and end-organ comorbidities. The mechanisms underlying immune dysregulation, chronic immune activation, and accelerated aging phenotypes in HIV infection are multifactorial and complex. Given this complexity, large multivariate datasets, systems biology, and computational approaches are needed to achieve systems-level understanding of HIV pathogenesis. Conclusions: This talk will provide a systems-level overview of temporal events, pathogenic processes, and inter-relationships between immune dysregulation and end-organ dysfunction during the course of HIV infection. A better understanding of these processes at the cellular and host level, integration of knowledge from diverse types of high-density data, and temporal modeling of causal relationships and dependency networks is important for developing new therapies, and progress toward the ultimate goals of prevention and eradication.