Trauma in silico: Individual-specific mathematical models and virtual clinical populations
Trauma in silico: Individual-specific mathematical models and virtual clinical populations
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DOI：
10.1126/scitranslmed.aaa3636
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发表时间：
2015-04-29
影响因子：
17.1
通讯作者：
Vodovotz, Yoram
中科院分区：
文献类型：
--
作者：
Brown, David;Namas, Rami A.;Vodovotz, Yoram
创伤引起的危重疾病是由急性炎症引起的，创伤后全身白细胞介素 6 (IL-6) 升高是不良后果的生物标志物。我们构建了一个代表虚拟创伤患者的多室常微分方程模型。该模型的个体特异性变体再现了 33 名钝性创伤幸存者的全身炎症和结果，从中生成了 10,000 名虚拟创伤患者的队列。模型预测的重症监护病房住院时间、多器官功能障碍程度以及作为损伤严重程度函数的 IL-6 曲线下面积与 147 名钝性创伤患者的验证队列的结果一致。在 98 名创伤患者的亚队列中，具有高 IL-6 单核苷酸多态性 (SNP) 的患者比具有低 IL-6 SNP 的患者表现出更高的血浆 IL-6 水平，这与模型预测相符。尽管 IL-6 可能会导致个别虚拟患者的死亡率增加，但整个队列中的模拟结果与产生 IL-6 的倾向无关，这一预测在 98 名患者的子队列中得到了验证。计算机随机临床试验表明，IL-6 抑制的生存获益较小，IL-1b 抑制的获益较小，肿瘤坏死因子-a 抑制后生存较差。这项研究证明了从还原论机制推断个体和人群结果的局限性，并展示了机械模拟在复杂疾病中的应用。
Trauma-induced critical illness is driven by acute inflammation, and elevated systemic interleukin-6 (IL-6) after trauma is a biomarker of adverse outcomes. We constructed a multicompartment, ordinary differential equation model that represents a virtual trauma patient. Individual-specific variants of this model reproduced both systemic inflammation and outcomes of 33 blunt trauma survivors, from which a cohort of 10,000 virtual trauma patients was generated. Model-predicted length of stay in the intensive care unit, degree of multiple organ dysfunction, and IL-6 area under the curve as a function of injury severity were in concordance with the results from a validation cohort of 147 blunt trauma patients. In a subcohort of 98 trauma patients, those with high-IL-6 single-nucleotide polymorphisms (SNPs) exhibited higher plasma IL-6 levels than those with low IL-6 SNPs, matching model predictions. Although IL-6 could drive mortality in individual virtual patients, simulated outcomes in the overall cohort were independent of the propensity to produce IL-6, a prediction verified in the 98-patient subcohort. In silico randomized clinical trials suggested a small survival benefit of IL-6 inhibition, little benefit of IL-1b inhibition, and worse survival after tumor necrosis factor-a inhibition. This study demonstrates the limitations of extrapolating from reductionist mechanisms to outcomes in individuals and populations and demonstrates the use of mechanistic simulation in complex diseases.