A Neutrophil Phenotype Model for Extracorporeal Treatment of Sepsis.
A Neutrophil Phenotype Model for Extracorporeal Treatment of Sepsis.
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DOI：
10.1371/journal.pcbi.1004314
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发表时间：
2015-10
影响因子：
4.3
通讯作者：
Clermont G
中科院分区：
文献类型：
--
作者：
Malkin AD;Sheehan RP;Mathew S;Federspiel WJ;Redl H;Clermont G
中性粒细胞在消除细菌病原体方面发挥着核心作用，但也可能导致脓毒症的终末器官损伤。白介素 8 (IL-8) 是中性粒细胞功能的关键调节剂，通过中性粒细胞特异性表面受体 CXCR-1 和 CXCR-2 发出信号。在这项研究中，使用机械计算模型来评估和部署调节 CXCR-1/2 水平的体外败血症治疗。首先，开发了 IL-8 介导的 CXCR-1/2 受体激活的简化机械计算模型，包含 16 个 ODE 和 43 个参数。受体水平动态和全身参数与多种中性粒细胞表型相结合，产生动态的活化中性粒细胞群体，减少病原体负荷，和/或启动中性粒细胞，当误导时引起不利的组织损伤。该数学模型使用狒狒注射大肠杆菌两小时后的实验数据进行校准，并跟踪最多 28 天。使用贝叶斯并行回火方法生成参数集合，以生成可以重现实验结果的模型拟合。逐步逻辑回归确定了七个模型参数作为死亡率的关键决定因素。敏感性分析表明，控制杀伤细胞中性粒细胞水平的参数会影响个体的整体系统损伤。为了评估救援策略并提供其对死亡率、发病时间、持续时间和调节中性粒细胞表型的体外装置捕获功效的影响的概率预测。我们的研究结果表明，旨在调节表型组成的干预措施具有时间敏感性。当感染持续 3-6 小时并持续 72 小时时，幸存者数量从 31% 增加到 40-80%。如果不在感染后 15 小时内采取治疗，治疗效果会迅速减弱。治疗持续时间为 5-24 小时可能会造成严重伤害，这可能会将生存率降低至 13%。对于严重脓毒症，调节 CXCR-1/2 水平的体外治疗具有治疗潜力，但也有潜在危害。计算模型的进一步开发将有助于指导最佳设备开发并确定治疗的目标患者群体。当患者因感染而产生全身免疫反应时，就会发生败血症。在这种情况下，称为中性粒细胞的白细胞处于活跃状态循环，寻找并消除入侵的细菌。然而，当中性粒细胞被激活时，健康组织会无意中成为目标，导致器官损伤并可能导致死亡。尽管脓毒症在全世界造成数百万人死亡，但美国仍然没有批准特定的治疗方法。这可能是由于人体免疫反应的复杂性和多样性，可以使用计算模型很好地管理。我们开发了一种计算模型来预测不同水平的中性粒细胞激活如何影响过度活跃的炎症条件下的生存。该模型用于评估模拟实验性脓毒症治疗的有效性，该治疗可调节中性粒细胞数量和活性。该评估确定治疗时机在治疗效果中起着至关重要的作用。如果使用得当，这种治疗方法可以大大提高生存率，但如果在错误的时间进行治疗，也存在对患者造成伤害的风险。我们希望这个计算模型能够支持和指导脓毒症治疗的进一步发展，并帮助将这些初步结果从实验室转化为临床。
Neutrophils play a central role in eliminating bacterial pathogens, but may also contribute to end-organ damage in sepsis. Interleukin-8 (IL-8), a key modulator of neutrophil function, signals through neutrophil specific surface receptors CXCR-1 and CXCR-2. In this study a mechanistic computational model was used to evaluate and deploy an extracorporeal sepsis treatment which modulates CXCR-1/2 levels. First, a simplified mechanistic computational model of IL-8 mediated activation of CXCR-1/2 receptors was developed, containing 16 ODEs and 43 parameters. Receptor level dynamics and systemic parameters were coupled with multiple neutrophil phenotypes to generate dynamic populations of activated neutrophils which reduce pathogen load, and/or primed neutrophils which cause adverse tissue damage when misdirected. The mathematical model was calibrated using experimental data from baboons administered a two-hour infusion of E coli and followed for a maximum of 28 days. Ensembles of parameters were generated using a Bayesian parallel tempering approach to produce model fits that could recreate experimental outcomes. Stepwise logistic regression identified seven model parameters as key determinants of mortality. Sensitivity analysis showed that parameters controlling the level of killer cell neutrophils affected the overall systemic damage of individuals. To evaluate rescue strategies and provide probabilistic predictions of their impact on mortality, time of onset, duration, and capture efficacy of an extracorporeal device that modulated neutrophil phenotype were explored. Our findings suggest that interventions aiming to modulate phenotypic composition are time sensitive. When introduced between 3–6 hours of infection for a 72 hour duration, the survivor population increased from 31% to 40–80%. Treatment efficacy quickly diminishes if not introduced within 15 hours of infection. Significant harm is possible with treatment durations ranging from 5–24 hours, which may reduce survival to 13%. In severe sepsis, an extracorporeal treatment which modulates CXCR-1/2 levels has therapeutic potential, but also potential for harm. Further development of the computational model will help guide optimal device development and determine which patient populations should be targeted by treatment. Sepsis occurs when a patient develops a whole body immune response due to infection. In this condition, white blood cells called neutrophils circulate in an active state, seeking and eliminating invading bacteria. However, when neutrophils are activated, healthy tissue is inadvertently targeted, leading to organ damage and potentially death. Even though sepsis kills millions worldwide, there are still no specific treatments approved in the United States. This may be due to the complexity and diversity of the body’s immune response, which can be managed well using computational modeling. We have developed a computational model to predict how different levels of neutrophil activation impact survival in an overactive inflammatory conditions. The model was utilized to assess the effectiveness of a simulated experimental sepsis treatment which modulates neutrophil populations and activity. This evaluation determined that treatment timing plays a critical role in therapeutic effectiveness. When utilized properly the treatment drastically improves survival, but there is also risk of causing patient harm when introduced at the wrong time. We intend for this computational model to support and guide further development of sepsis treatments and help translate these preliminary results from bench to bedside.