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Temporal shifts in adaptive immunity drive HIV-associated cryptococcal IRIS: mechanisms, models, and therapeutic
Marcus Hunter1, Luis R Martinez2,3,4,5,6
1Department of Oral Biology, University of Florida College of Dentistry, Gainesville, FL, USA.
Abstract:
Cryptococcal meningoencephalitis (CME) remains a leading cause of AIDS-related mortality, and up to one-quarter of persons living with HIV who survive CME develop cryptococcal immune reconstitution inflammatory syndrome (CME-IRIS) after antiretroviral therapy (ART) initiation. CME-IRIS arises when recovering immunity encounters a high residual fungal antigen burden, yet the temporal adaptive immune dynamics that distinguish protective reconstitution from damaging neuroinflammation are not fully defined. This review synthesizes clinical and experimental data to propose a temporal framework centered on CD4+ T cell polarization, regulatory failure, memory T cell quality, and T-B cell coordination. Before ART, many patients exhibit a Th2-skewed, low-inflammatory state with impaired Th1 responses, reduced antifungal IgM production, and deficient Tfh-B cell coordination, collectively favoring persistent Cryptococcus neoformans antigen burden. With ART, IL-7-driven T cell recovery, Th17/Treg imbalance, Th1/Th17-biased memory responses, and chemokine-guided trafficking of CXCR3+CCR5+ effector cells into the central nervous system can convert this antigen-rich milieu into fulminant neuroinflammation. We further discuss emerging mouse models that recapitulate unmasking CME-IRIS, the contrasting immune profile of Cryptococcus gattii-associated IRIS as a comparative model, and developing therapeutic strategies that include targeted immunomodulators, cell-based therapies, and vaccines. Finally, we highlight future directions - particularly single-cell and spatial transcriptomic profiling of blood and CSF - to resolve which adaptive immune populations drive neuroinflammation and to validate predictive biomarkers for CME-IRIS. A temporally informed view of adaptive immunity in CME-IRIS may refine ART timing, guide risk stratification, and identify new adjunctive interventions for cryptococcosis and related IRIS syndromes.
Insights
Cryptococcal immune reconstitution inflammatory syndrome (CME-IRIS) in HIV patients is linked to immune responses after antiretroviral therapy (ART). Understanding adaptive immunity dynamics is key to preventing neuroinflammation and improving outcomes.
Area of Science:
- Immunology
- Infectious Diseases
- Neuroscience
Background:
- Cryptococcal meningoencephalitis (CME) is a major cause of death in AIDS patients.
- Cryptococcal immune reconstitution inflammatory syndrome (CME-IRIS) affects up to 25% of HIV survivors after starting antiretroviral therapy (ART).
- The exact immune dynamics causing CME-IRIS after ART initiation are not fully understood.
Purpose of the Study:
- To synthesize clinical and experimental data on adaptive immunity in CME-IRIS.
- To propose a temporal framework for understanding the immune responses in CME-IRIS.
- To identify potential therapeutic strategies and future research directions.
Main Methods:
- Review of clinical and experimental data.
- Analysis of adaptive immune responses including T cell polarization, memory cell quality, and T-B cell coordination.
- Discussion of emerging mouse models and comparative immunology.
Main Results:
- Before ART, patients show impaired Th1 responses and reduced antifungal IgM, favoring persistent fungal burden.
- ART initiation can lead to T cell recovery, Th17/Treg imbalance, and effector cell trafficking into the CNS, potentially causing neuroinflammation.
- Immune profiles differ between *Cryptococcus neoformans* and *Cryptococcus gattii* associated IRIS.
Conclusions:
- A temporal framework highlights the role of CD4+ T cell polarization, regulatory failure, memory T cell quality, and T-B cell coordination in CME-IRIS.
- Understanding these dynamics can refine ART timing, risk stratification, and adjunctive therapies.
- Future research using advanced profiling techniques is needed to identify drivers of neuroinflammation and predictive biomarkers.
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