PD-1 negative subsets of Env- and Gag- specific CD8+ T cells   PD

PD-1 negative subsets of Env- and Gag- specific CD8+ T cells.  PD-1-negative HIV-specific T cells may theoretically represent ‘true’ effector T cell capacity against the virus. PD-1-negative CD8+ T cell responses were also dominated by Gag and Nef, but the predominance of CD8+ Gag compared to Env responses (×5–6) became less pronounced (×3) among CD8+ PD-1-negative T cells (P < 0·01) (Table 2). However, when PD-1 expression on specific T cells was related to prospective CD4 loss rates and CD38, Gag-specific CD8+ PD-1-negative

T cells were again superior to the corresponding Env- and Nef-specificities (Table 3). The impact of PD-1-negative Gag-specific cells was supported by lower CD38 levels in patients with a high number of Gag PD-1-negative CD8+ cells [5698 (highest Gag tertile) versus 7634 CD38 molecules/cell (lowest tertile); medians, P = 0·01]. Interestingly, Env-specific cells correlated Daporinad in vivo with current CD4 change rate (r = −0·41), but inversely, so compared with the corresponding selleck chemical Gag subsets (r = 0·79, prospective CD4 change rate) (Table 3). In fact, Env-specific CD8+ T cells were the only cells where high PD-1 was favourable in terms of positive correlation with CD4 change (r = 0·37, Table 3). These results correspond with the hypothesis that Env-specific CD8+ T cells may be directly or indirectly harmful [20,37]. The ratio between Env- and Gag- specific CD8+ T cells. 

The inverse correlations between CD4+ T cell change rates for Gag- and Env-specific CD8+ responses (positive and negative correlations, respectively; see above) combined with the lack of correlation between these two antigen responses

(r = 0·09, n.s.) prompted us to analyse the Env/Gag CD8+ response ratio (E/G). The E/G ratio for PD-1-negative CD8+ T cell subsets (E/G neg) were also included in the analyses, as the E/G and E/G neg ratios did not correlate completely (r = 0·79, P < 0·01). It should be noted that the inverted Gag/Env ratios correlated more strongly with CD4 change rates, but were mathematically inapplicable Atezolizumab in three of the 31 cases due to undetectable Env-responses (data not shown). The E/G and E/G neg ratios correlated more favourably than all of the other pseudomarkers tested with the two CD4 change rate parameters (Table 3, Fig. 2b). This was supported by significantly higher current CD4 change rates in patients with low E/G ratio (approx. −50 CD4 cells/µl/year, lower tertile) compared with those having a high ratio (approximately −200 CD4 cells/µl/year, highest tertile, P < 0·01) (Fig. 2a). The same was true for the E/G neg ratios (P < 0·01, data not shown). E/G ratio best predictor of CD4 loss in logistic regression analysis.  All predictive markers were compared in a binary logistic regression analysis where the median current absolute and relative CD4 change rates represented the binary breakpoints (−158 CD4+ T cells/µl/year and −38·2%/year, respectively).

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