Classification of patients with sepsis according to blood genomic endotype: a prospective cohort study
Classification of patients with sepsis according to blood genomic endotype: a prospective cohort study
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DOI：
10.1016/s2213-2600(17)30294-1
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发表时间：
2017-10-01
影响因子：
76.2
通讯作者：
van der Poll, Tom
中科院分区：
文献类型：
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作者：
Scicluna, Brendon P.;van Vught, Lonneke A.;van der Poll, Tom
背景脓毒症期间的宿主反应是高度异质性的，这阻碍了高死亡风险患者的识别和靶向治疗的选择。在这项研究中，我们的目的是确定生物学相关的分子endotypes在患者sepsis.Methods这是一个前瞻性的观察性队列研究，包括连续的患者承认脓毒症的两个重症监护病房（ICU）在荷兰之间的2011年1月1日和7月20日，2012年（发现和第一个验证队列）和因社区获得性肺炎而入院的脓毒症患者（第二个验证队列）。我们从入院样本中生成了全基因组血液基因表达谱，并通过无监督共识聚类和机器学习对其进行了分析。本研究的主要目的是建立败血症患者的内型，并评估这些内型与临床特征和生存结局的相关性。我们还建立了候选生物标志物的内型，以允许识别患者的内型在clinical practice.Findings发现队列有306例患者，第一个验证队列有216，第二个验证队列有265例患者。在发现队列中确定了4种脓毒症分子内源型，命名为Mars 1 -4，与28天死亡率相关（对数秩p=0.022）。在发现队列中，最坏的结果是被归类为具有Mars 1内型的患者，在28天，90名具有Mars 1内型的患者中有35人（39（风险比[HR] vs所有其他内型1.86 [95%CI 1.21-2.86]; p=0.0045），相比之下，105名Mars 2内型患者中有23名（22%）（HR 0.64 [0.40-1.04]; p=0.061），71名患者中有16名（23%）具有Mars 3内型（HR 0.71 [0.41-1.22]; p=0.19），40名患者中有13名（33%）具有Mars 4内型（HR 1.13 [0.63-2.04]; p=0.69）。使用联合临床和内源性模型对净重新分类改善进行分析，将风险预测值显著提高至0.33（0.09-0.58; p=0.008）。在第一和第二验证队列中，140个基因表达特征可靠地将脓毒症患者分层为四种内型。只有Mars 1与所有队列的28天死亡率始终显著相关。为了方便可能的临床应用，生物标志物是来自每个endotype; BPGM和TAP 2可靠地确定与Mars 1 endotype.Interpretation患者本研究提供了一种方法，重症监护病房入院后，脓毒症患者的分子分类到四个不同的endotypes。败血症内源型的检测可能有助于提供个性化的患者管理和试验的选择。
Background Host responses during sepsis are highly heterogeneous, which hampers the identification of patients at high risk of mortality and their selection for targeted therapies. In this study, we aimed to identify biologically relevant molecular endotypes in patients with sepsis.Methods This was a prospective observational cohort study that included consecutive patients admitted for sepsis to two intensive care units (ICUs) in the Netherlands between Jan 1, 2011, and July 20, 2012 (discovery and first validation cohorts) and patients admitted with sepsis due to community-acquired pneumonia to 29 ICUs in the UK (second validation cohort). We generated genome-wide blood gene expression profiles from admission samples and analysed them by unsupervised consensus clustering and machine learning. The primary objective of this study was to establish endotypes for patients with sepsis, and assess the association of these endotypes with clinical traits and survival outcomes. We also established candidate biomarkers for the endotypes to allow identification of patient endotypes in clinical practice.Findings The discovery cohort had 306 patients, the first validation cohort had 216, and the second validation cohort had 265 patients. Four molecular endotypes for sepsis, designated Mars1-4, were identified in the discovery cohort, and were associated with 28-day mortality (log-rank p=0.022). In the discovery cohort, the worst outcome was found for patients classified as having a Mars1 endotype, and at 28 days, 35 (39%) of 90 people with a Mars1 endotype had died (hazard ratio [HR] vs all other endotypes 1.86 [95% CI 1.21-2.86]; p=0.0045), compared with 23 (22%) of 105 people with a Mars2 endotype (HR 0.64 [0.40-1.04]; p=0.061), 16 (23%) of 71 people with a Mars3 endotype (HR 0.71 [0.41-1.22]; p=0.19), and 13 (33%) of 40 patients with a Mars4 endotype (HR 1.13 [0.63-2.04]; p=0.69). Analysis of the net reclassification improvement using a combined clinical and endotype model significantly improved risk prediction to 0.33 (0.09-0.58; p=0.008). A 140-gene expression signature reliably stratified patients with sepsis to the four endotypes in both the first and second validation cohorts. Only Mars1 was consistently significantly associated with 28-day mortality across the cohorts. To facilitate possible clinical use, a biomarker was derived for each endotype; BPGM and TAP2 reliably identified patients with a Mars1 endotype.Interpretation This study provides a method for the molecular classification of patients with sepsis to four different endotypes upon ICU admission. Detection of sepsis endotypes might assist in providing personalised patient management and in selection for trials.