We and others have postulated that a constant number of T lymphocytes is normally maintained without regard to CD4+ or CD8+ phenotype ('blind' T-cell homeostasis). Here we confirm essentially constant T-cell levels (despite marked decline in CD4+ T cells and increase in CD8+ T cells) in homosexual men with incident human immunodeficiency virus, type 1 (HIV-1), infection who remained free of acquired immunodeficiency syndrome (AIDS) for up to eight years after seroconversion. In contrast, seroconverters who developed AIDS exhibited rapidly declining T cells (both CD4+ and CD8+) for approximately two years before AIDS, independent of the time between seroconversion and AIDS, suggesting that homeostasis failure is an important landmark in HIV disease progression. Given the high rate of T-cell turnover in HIV-1 infection, blind T-cell homeostasis may contribute to HIV pathogenesis through a CD8+ T lymphocytosis that interferes with regeneration of lost CD4+ T cells.

No abstract

Subsets of activated CD8+ lymphocytes defined by membrane expression of the activation antigens HLA-DR and CD38 were counted by three-color flow cytometry in homosexual men who subsequently became seropositive for human immunodeficiency virus type 1 (HIV). Profound CD8+ cell activation was seen in all subjects at seroconversion and 6 and 12 months later. The HLA-DR+ CD38+ CD8+ cell population, which has potent direct HIV cytotoxic T cell activity, was markedly elevated at seroconversion in all subjects. In some men, these levels remained elevated throughout the first year of infection. During the next 5 years, these men had stable CD4+ cell levels, whereas the others did not. Long-term survivors (seropositive for 9 years, > 800 CD4+ cells/mm3) also had elevated levels of this subset, despite few other activated CD8+ cells. Thus, selective elevation of HLA-DR+ CD38- CD8+ cells was a marker of subsequent stable HIV disease.

Persons infected with human immunodeficiency virus (HIV) for > 8 years were studied to delineate virologic and immunologic attributes of long-term survival. Whereas those with 300-700 CD4+ cells/microL often had circulating cytotoxic T lymphocytes (CTL) against HIV antigens, those with > 1000 CD4+ cells/microL did not. The subjects with > 1000 CD4+ cells/microL had low virus burden, low levels of Gag-specific CTL precursors, and minimal CD8+ cell activation. Overall, elevated levels of CD8+ cells, CD38 antigen expression on CD8+ cells, and anti-HIV functions were correlated with increased virus burden, provirus load, and HIV plasma RNA levels. A factor that suppressed HIV replication was spontaneously secreted from CD8+ cells of most subjects but not from those with high CD4+ cell counts. CD8+ cell activities, therefore, may reflect chronic viral stimulation of the immune system. Long-term survivors with high levels of CD4+ cells maintained control of viral replication but lacked the CD8+ cell activities.

Flow Cytometry has become a mainstay technique for measuring fluorescent and physical attributes of single cells in a suspended mixture. These data are reduced during analysis using a manual or semiautomated process of gating. Despite the need to gate data for traditional analyses, it is well recognized that analyst-to-analyst variability can impact the dataset. Moreover, cells of interest can be inadvertently excluded from the gate, and relationships between collected variables may go unappreciated because they were not included in the original analysis plan. A multivariate non-gating technique was developed and implemented that accomplished the same goal as traditional gating while eliminating many weaknesses. The procedure was validated against traditional gating for analysis of circulating B cells in normal donors (n 5 20) and persons with Systemic Lupus Erythematosus (n 5 42). The method recapitulated relationships in the dataset while providing for an automated and objective assessment of the data. Flow cytometry analyses are amenable to automated analytical techniques that are not predicated on discrete operator-generated gates. Such alternative approaches can remove subjectivity in data analysis, improve efficiency and may ultimately enable construction of large bioinformatics data systems for more sophisticated approaches to hypothesis testing. '