Stratification of pediatric septic shock

描述(由申请人提供)：感染性休克是成人和儿童的主要公共卫生问题。感染性休克是一种异质性综合征，在特定的患者队列中有高度不同的表达。该领域的一个关键挑战是通过更有效地对患者进行分层来减少和管理这种异质性，以达到更合理和有效的临床研究和个性化临床管理的目的。在过去的7年里，我们已经建立了感染性休克儿童的基因组表达数据库。我们现在建议利用这个注释丰富的数据库，通过3个具体目标开发新的败血症休克分层工具，这些目标集中在基于基因表达的败血症休克亚类、败血症休克相关肾功能衰竭早期检测的生物标记物以及败血症生物学中一个新的候选基因的基因分型。在具体目标1中，我们将推出一种分类策略，根据100个基因表达特征将感染性休克患者分成不同的亚类。该分类策略将在现有的180名患者队列中进行，并将使用NanoStringnCounter平台进行基因表达测量。根据我们最近公布的数据，我们预计基于表达式的亚类将具有临床上重要的表型差异。定义子类的表达签名将使用基因表达动态检查器(GEDI)平台转换为视觉直观的“马赛克”。在生成定义亚类的嵌合体后，我们将使用200名患者的单独队列，前瞻性地验证这些嵌合体识别临床相关的、基于基因表达的感染性休克亚类的能力。在特定的目标2中，我们将建立一个预测和早期发现感染性休克相关肾功能衰竭(SSARF)的风险模型。我们已经客观地获得了一组7个基于血清的候选蛋白质生物标志物，用于SSARF的早期检测。我们将在180名患者的衍生队列中测量这些候选生物标记物，并开发一个基于多生物标记物的风险模型。该模型随后将在200名预期登记的患者队列中得到验证。在具体目标3中，我们将对整个基质金属肽酶-8(MMP8)基因区域进行测序，并测量序列变异与疾病严重程度之间的关系。我们还将测试基质金属蛋白酶-8序列变异和基质金属蛋白酶-8表达水平(mRNA、蛋白质和活性)之间的关系。这一应用程序的预期交付是临床上有用的SPIC休克分层的新工具。

DESCRIPTION (provided by applicant): Septic shock is a major public health problem in both adults and children. Septic shock is a heterogeneous syndrome having highly variable expression in a given patient cohort. A key challenge in the field is to reduce and manage this heterogeneity by more effectively stratifying patients for the purposes of more rational and effective clinical research and individualized clinical management. Over the last 7 years we have developed a genomic expression data base of children with septic shock. We are now proposing to leverage this richly annotated database to develop novel septic shock stratification tools via 3 Specific Aims focused on gene expression-based septic shock subclasses, biomarkers for early detection of septic shock associated renal failure, and genotyping of a novel candidate gene in sepsis biology. In Specific Aim 1 we will derive a classification strategy that groups septic shock patients into distinct subclasses based on a 100 gene expression signature. The classification strategy will be derived in an existing cohort of 180 patients and gene expression measurements will be conducted using the NanoString nCounter platform. Based on our recently published data, we expect that the expression-based subclasses will have clinically important phenotypic differences. The subclass-defining expression signatures will be converted to visually intuitive "mosaics" using the Gene Expression Dynamic Inspector (GEDI) platform. After generating the subclass- defining mosaics, we will prospectively validate the ability of these mosaics to identify clinically relevant, gene expression-based septic shock subclasses using a separate cohort of 200 patients. In Specific Aim 2 we will derive a risk model for the prediction and early detection of septic shock associated renal failure (SSARF). We have objectively derived a panel of 7, serum-based, candidate protein biomarkers for the early detection of SSARF. We will measure these candidate biomarkers in a derivation cohort of 180 patients and develop a multi-biomarker based risk model. The model will be subsequently validated in a prospectively enrolled cohort of 200 patients. In Specific Aim 3 we will sequence the entire matrix metallopeptidase-8 (MMP-8) gene region and measure associations between sequence variations and illness severity. We will also test associations between MMP-8 sequence variations and expression levels of MMP-8 (mRNA, protein, and activity). The expected deliverables of this application are novel tools for clinically useful stratification of sptic shock.