Compartmentalized T cell profile in the lungs of patients with HIV-1-associated pulmonary Kaposi sarcoma

Pulmonary Kaposi sarcoma (pKS) caused by Human herpesvirus 8 (HHV-8) is a devastating form of KS in patients with advanced acquired immunodeficiency syndrome (AIDS) and is associated with increased morbidity and mortality. Blood T cells play a central role in the response of HIV-1 and HHV-8. However, little information is available on T cells in the alveolar space of HIV-1-associated pKS patients.Therefore, we examined CD8+ and CD4+ T cells in the alveolar space in comparison with the blood of patients with pKS. We recruited 26 HIV-1 positive patients with KS, including 15 patients with pKS. Bronchoalveolar lavage (BAL) cells and blood mononuclear cells were analyzed for T cell memory phenotypes, surface markers associated with exhaustion, and intracellular cytokine staining (ICS) using flow cytometry. HIV-1 and HHV-8 viral loads were measured in plasma by quantitative PCR.BAL T cells showed reduced inflammatory capacities and significantly diminished polyfunctionality compared to blood T cells from patients with pKS. This was not accompanied by increased expression of exhaustion markers, such as TIM-3 and PD-1.More importantly, we found a negative correlation between the production of MIP1-β and TNF-α in T cells in BAL and blood, indicating compartmentalised immune responses to pKS and accentuated chronic HIV-1/HHV-8 pathogenesis via T cells in the lungs of people with pKS.

Antibody Responses in HIV-Infected Patients With Advanced Immunosuppression and Asymptomatic Cryptococcal Antigenemia

Background

There are no host biomarkers of risk for HIV-associated cryptococcal meningitis (CM) except CD4+ T-cell deficiency. At present, serum cryptococcal antigen (CrAg) screening of those with CD4 <100 cells/µL is used to identify persons at risk for HIV-associated CM. We determined if plasma antibody profiles could discriminate CrAg+ from CrAg- patients.

Methods

We performed serological analyses of 237 HIV-infected asymptomatic Zimbabwean patients with CD4 <100 cells/µL; 125 CrAg- and CrAg+ but cerebrospinal fluid CrAg- by CrAg lateral flow assay. We measured plasma immunoglobulin M (IgM), immunoglobulin G (IgG) 1, and IgG2 concentrations by Luminex, and titers of Cryptococcus neoformans (Cn) glucuronoxylomannan (GXM) polysaccharide and naturally occurring Laminarin (natural Lam, a β-(1–3)-glucan linked polysaccharide)-binding IgM and IgG by enzyme-linked immunosorbent assay.

Results

GXM-IgG, -IgM, and -IgG2 levels were significantly higher in CrAg+ patients, whereas natural Lam-IgM and Lam-IgG were higher in CrAg- patients before and after adjustment for age, sex, and CD4 T-cell count, despite overlap of values. To address this variability and better discriminate the groups, we used Akaike Information Criteria to select variables that independently predicted CrAg+ status and included them in a receiver operating characteristic curve to predict CrAg status. By inclusion of CD4, GXM-IgG, GXM-IgM, and Lam-IgG, -IgG2, and -IgM, this model had an 80.4% probability (95% confidence interval, 0.75–0.86) of predicting CrAg+ status.

Conclusions

Statistical models that include multiple serological variables may improve the identification of patients at risk for CM and inform new directions in research on the complex role that antibodies may play in resistance and susceptibility to CM.