Janes Holly E, Cohen Kristen W, Frahm Nicole, De Rosa Stephen C, Sanchez Brittany, Hural John, Magaret Craig A, Karuna Shelly, Bentley Carter, Gottardo Raphael, Finak Greg, Grove Douglas, Shen Mingchao, Graham Barney S, Koup Richard A, Mulligan Mark J, Koblin Beryl, Buchbinder Susan P, Keefer Michael C, Adams Elizabeth, Anude Chuka, Corey Lawrence, Sobieszczyk Magdalena, Hammer Scott M, Gilbert Peter B, McElrath M Juliana
Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, and.
The Statistical Center for HIV/AIDS Research and Prevention, Fred Hutchinson Cancer Research Center, Seattle, Washington.
J Infect Dis. 2017 May 1;215(9):1376-1385. doi: 10.1093/infdis/jix086.
It is important to identify vaccine-induced immune responses that predict the preventative efficacy of a human immunodeficiency virus (HIV)-1 vaccine. We assessed T-cell response markers as correlates of risk in the HIV Vaccine Trials Network (HVTN) 505 HIV-1 vaccine efficacy trial.
2504 participants were randomized to DNA/rAd5 vaccine or placebo, administered at weeks 0, 4, 8, and 24. Peripheral blood mononuclear cells were obtained at week 26 from all 25 primary endpoint vaccine cases and 125 matched vaccine controls, and stimulated with vaccine-insert-matched peptides. Primary variables were total HIV-1-specific CD4+ T-cell magnitude and Env-specific CD4+ polyfunctionality. Four secondary variables were also assessed. Immune responses were evaluated as predictors of HIV-1 infection among vaccinees using Cox proportional hazards models. Machine learning analyses identified immune response combinations best predicting HIV-1 infection.
We observed an unexpectedly strong inverse correlation between Env-specific CD8+ immune response magnitude and HIV-1 infection risk (hazard ratio [HR] = 0.18 per SD increment; P = .04) and between Env-specific CD8+ polyfunctionality and infection risk (HR = 0.34 per SD increment; P < .01).
Further research is needed to determine if these immune responses are predictors of vaccine efficacy or markers of natural resistance to HIV-1 infection.
识别能够预测人类免疫缺陷病毒（HIV）-1疫苗预防效果的疫苗诱导免疫反应至关重要。我们在HIV疫苗试验网络（HVTN）505 HIV-1疫苗疗效试验中评估了T细胞反应标志物作为风险的相关因素。
2504名参与者被随机分为DNA/rAd5疫苗组或安慰剂组，分别在第0、4、8和24周给药。在第26周从所有25例主要终点疫苗病例和125例匹配的疫苗对照中获取外周血单核细胞，并用与疫苗插入片段匹配的肽进行刺激。主要变量为HIV-1特异性CD4+ T细胞总数和Env特异性CD4+多功能性。还评估了四个次要变量。使用Cox比例风险模型评估免疫反应作为疫苗接种者中HIV-1感染预测指标的情况。机器学习分析确定了最能预测HIV-1感染的免疫反应组合。
我们观察到Env特异性CD8+免疫反应强度与HIV-1感染风险之间存在出乎意料的强负相关（每标准差增加的风险比[HR]=0.18；P=0.04），以及Env特异性CD8+多功能性与感染风险之间存在负相关（每标准差增加的HR=0.34；P<0.01）。
需要进一步研究以确定这些免疫反应是疫苗疗效的预测指标还是对HIV-1感染天然抗性的标志物。
