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首页> 外文期刊>PLoS Computational Biology >Quantifying the Impact of Human Immunodeficiency Virus-1 Escape From Cytotoxic T-Lymphocytes
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Quantifying the Impact of Human Immunodeficiency Virus-1 Escape From Cytotoxic T-Lymphocytes

机译:量化人类免疫缺陷病毒1从细胞毒性T淋巴细胞逃逸的影响

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HIV-1 escape from the cytotoxic T-lymphocyte (CTL) response leads to a weakening of viral control and is likely to be detrimental to the patient. To date, the impact of escape on viral load and CD4+ T cell count has not been quantified, primarily because of sparse longitudinal data and the difficulty of separating cause and effect in cross-sectional studies. We use two independent methods to quantify the impact of HIV-1 escape from CTLs in chronic infection: mathematical modelling of escape and statistical analysis of a cross-sectional cohort. Mathematical modelling revealed a modest increase in log viral load of 0.051 copies ml鈭? per escape event. Analysis of the cross-sectional cohort revealed a significant positive association between viral load and the number of 鈥渆scape events鈥? after correcting for length of infection and rate of replication. We estimate that a single CTL escape event leads to a viral load increase of 0.11 log copies ml鈭? (95% confidence interval: 0.040鈥?.18), consistent with the predictions from the mathematical modelling. Overall, the number of escape events could only account for approximately 6% of the viral load variation in the cohort. Our findings indicate that although the loss of the CTL response for a single epitope results in a highly statistically significant increase in viral load, the biological impact is modest. We suggest that this small increase in viral load is explained by the small growth advantage of the variant relative to the wildtype virus. Escape from CTLs had a measurable, but unexpectedly low, impact on viral load in chronic infection.
机译:HIV-1从细胞毒性T淋巴细胞(CTL)反应中逃逸会导致病毒控制能力减弱,并且可能对患者有害。迄今为止,逃逸对病毒载量和CD4 + T细胞计数的影响尚未被量化,这主要是因为在横断面研究中纵向数据稀疏并且难以将因果关系分开。我们使用两种独立的方法来量化HIV-1在慢性感染中从CTL中逃逸的影响:逃生的数学建模和横断面队列的统计分析。数学模型显示对数病毒载量温和增加0.051个拷贝/ ml。每个逃生事件。对横断面队列的分析表明,病毒载量与“逸出事件”的数量之间存在显着的正相关。在校正感染时间和复制率之后。我们估计单个CTL逃逸事件会导致病毒载量增加0.11个日志拷贝ml鈭? (95%置信区间:0.040-0.18),与数学建模的预测一致。总体而言,逃逸事件的数量仅占该群体病毒载量变化的大约6%。我们的发现表明,尽管单个表位的CTL反应丧失会导致病毒载量的统计学显着增加,但生物学影响却不大。我们建议,病毒载量的这种小幅增长可以通过该变体相对于野生型病毒的小增长优势来解释。逃离CTL对慢性感染中的病毒载量有可测量但出乎意料的低影响。

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