Analysis of Longitudinal High Dimensional Data for Burn and Trauma Studies
Analysis of Longitudinal High Dimensional Data for Burn and Trauma Studies
批准号:
7231912
负责人:
DIANNE M FINKELSTEIN
金额:
$8.75万
依托单位国家:
美国
项目类别:
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-04-25 至 2009-03-31
关键词:
AcuteAnusBiometryBloodBurn TraumaBurn injuryCessation of lifeChildhoodClinicalComplexComputersDataData SetEventFatty acid glycerol estersFundingGene ExpressionGene FamilyGenesGeneticGenomicsGluesGoalsGrantGrowthHospitalizationHospitalsImmune responseImmunologicsInflammationInjuryInternetKnowledgeLettersLongitudinal StudiesMedicalMetabolic MarkerMetabolismMethodologyMethodsModelingMolecular ProfilingMorbidity - disease rateMuscleOutcomePatientsPatternPhenotypePhysiologicalPopulationProteinsProteomicsRecoveryScientistScoreSkinStandards of Weights and MeasuresStatistical Data InterpretationStatistical MethodsTestingTimeTissuesTraumaUnited States National Institutes of HealthWorkWound Healingbiological adaptation to stressbone losscarbohydrate metabolismcomputer programfollow-upimprovedmortalityresponseresponse to injurywasting
中文摘要
描述(由申请方提供):重度烧伤的特征是高代谢应激反应,导致体重减轻和肌肉萎缩、免疫功能受损、伤口愈合缓慢和相关骨丢失,所有这些都导致发病率、死亡率增加和损伤恢复时间延长。事实上,小儿烧伤患者在急性住院治疗后严重虚弱,并且通常在受伤后一年内不会生长。美国国立卫生研究院正在资助一项炎症和宿主对损伤的反应研究(也称为胶水资助,因为它是临床和基础科学家的联盟),以更深入地了解导致身体免疫反应的复杂事件。Glue基金在烧伤人群中的一个目的是将烧伤患者代谢中明确定义的表型变化与从血液、脂肪、肌肉和皮肤中分析的遗传和蛋白质组表达谱相关联,目的是鉴定在烧伤后组织生理反应之前的时间过程中被调节的基因家族。本提案的主要目的是开发计算上易于处理的统计分析方法,用于识别在烧伤患者表型变化之前随时间推移遵循不同模式的基因阵列,如代谢标志物和生长恢复到正常水平所示。这些数据的统计分析无法使用标准的可用方法进行:事实上,由于数据的高维性,基因微阵列的分析提出了独特的统计挑战。当微阵列数据随时间连续收集时,该问题进一步复杂化。此外,当表型是事件时间时,方法学会因以下事实而进一步复杂化:对于某些患者,事件可能在随访结束或死亡时被删失。我们建议调整方法,分析时间事件数据的纵向收集的微阵列数据的设置。我们将开发一种评分测试,该测试对哪些基因在恢复的患者中差异表达敏感。我们将扩展这些方法来处理死亡率,并开发可以利用纵向微阵列来预测哪些患者将从严重创伤或烧伤中恢复的模型。我们将应用本基金开发的方法研究纵向基因组与Glue研究中儿科烧伤患者数据中各种临床结局的相关性。该提案的目的是开发统计方法,用于识别随时间推移的基因表达模式,预测与代谢标志物和生长恢复到正常水平相关的烧伤患者的变化。这些方法将应用于NIH资助的炎症和宿主对损伤的反应(胶水)项目中的儿科烧伤患者的数据。这将提供一个更好的了解复杂的事件,最终在身体的免疫反应烧伤,有助于增加发病率和死亡率在这些患者。这些知识可用于改善严重烧伤患者的治疗,从而使其更快、更完全地康复。
英文摘要
DESCRIPTION (provided by applicant): Severe burns are characterized by a hypermetabolic stress response which causes a loss of body mass and muscle wasting, immunologic compromise, slowed wound healing, and related bone loss, all of which contribute to increased morbidity, mortality, and prolonged recovery from injury. In fact, pediatric burn victims, after their acute hospitalization, are severely weakened, and often do not grow for a year post injury. The NIH is funding an Inflammation and the Host Response to Injury study (also known as the Glue grant because it is a consortium of clinical and basic scientists) to more deeply understand the complex set of events that culminate in the body's immune response to the injury of burn and trauma. One aim of the Glue grant in the burn population is to correlate the well defined phenotypic changes in metabolism in patients with burns with genetic and proteomic expression profiles analyzed from blood, fat, muscle and skin with the goal of identifying families of genes that are modulated in a time course prior to a physiologic response of tissues after a burn. The primary objective of this proposal is to develop computationally tractable methods of statistical analysis for identifying gene arrays that follow a distinct pattern over the time prior to a phenotypic change in burn patients, as indicated by the return of metabolic markers and growth to normal levels. The statistical analysis of these data cannot be performed using standard available methods: in fact, the analysis of gene microarrays presents unique statistical challenges because of the high- dimensionality of the data. This issue is further complicated when microarray data are collected serially over time. Additionally, when the phenotype is an event time, the methodology is further complicated by the fact that for some patients the event may be censored by the end of follow-up or death. We propose to adapt methods for analyzing time to event data to the setting of longitudinally collected microarray data. We will develop a score test that is sensitive to which genes are expressed differentially in patients who recover. We will extend these methods to handle mortality and to develop models that can utilize longitudinal microarrays to predict which patient will recover from severe trauma or burn. We will apply the methods developed in this grant to study the longitudinal genomic correlates to various clinical outcomes in data from pediatric burn patients in the Glue study. The objective of this proposal is to develop statistical methods for identifying gene expression patterns over time that would predict changes in burn patients that are associated with the return of metabolic markers and growth to normal levels. These methods will be applied to data from pediatric burn patients in the NIH-funded Inflammation and the Host Response to Injury (Glue) project. This will provide a better understanding of the complex set of events that culminate in the body's immune response to burn injuries that contributes to increased morbidity and mortality in these patients. This knowledge can be used to improve the treatment of severely burned patients resulting in more rapid and complete recovery.
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