Biomarkers for pressure injury risk following spinal cord injury: Development of a multi-scalar predictive model for personalized preventive health care

脊髓损伤后压力性损伤风险的生物标志物：开发用于个性化预防保健的多标量预测模型

• 批准号: 10261428
• 负责人: KATH BOGIE
• 金额: --
• 依托单位: LOUIS STOKES CLEVELAND VA MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-11-01 至 2023-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10261428
• 关键词: 3-Dimensional; Activities of Daily Living; Address; Adipose tissue; Affect; Anterior; Area; Automobile Driving; Biological Assay; Biological Markers; Blood; Blood Tests; Blood specimen; Candidate Disease Gene; Caregivers; Caring; Cessation of life; Classification; Clinical; Cohort Studies; Complication; DNA; Data; Deposition; Development; Diagnostic Reagent Kits; Dose; Drug or chemical Tissue Distribution; Early identification; Exclusion Criteria; Exhibits; Freezing; Genes; Genetic; Genetic Markers; Genetic Variation; Head; Health; Health Care Costs; Health Status; Health behavior; Hospitalization; Image; Incidence; Individual; Inferior; Inflammation; Institutes; Intramuscular; Investigation; Measures; Medical center; Metabolism; Modeling; Monitor; Muscle; Output; Participant; Pelvis; Performance; Persons; Phase; Prevention; Preventive healthcare; Procedures; Process; Protocols documentation; Quality Control; Quality of life; Questionnaires; Recording of previous events; Recurrence; Research; Research Design; Risk; Risk Assessment; Risk Factors; Sacral vertebra structure; Sacroiliac joint structure; Sampling; Scanning; Site; Skin; Slice; Spinal cord injury; Standardization; Supination; Surveys; Systemic disease; Telephone; Testing; Thinness; Time; Tissues; Underrepresented Populations; Update; Validation; Variant; Veterans; Whole Blood; X-Ray Computed Tomography; base; biomarker validation; clinically significant; cohort; cost; decubitus ulcer; early detection biomarkers; economic cost; genome analysis; improved; next generation sequencing; personalized care; predictive modeling; pressure; programs; reconstruction; recruit; tool

Pressure injures (PrI) are a major secondary complication for far too many people with spinal cord injury (SCI). Development and/or recurrence of a PrI limits activities of daily living, often leading to hospitalization and even death. In addition to the devastating impact on affected individuals and their caregivers, PrI management has a significant effect on Veterans Heath Administration healthcare costs, which provides lifetime care for our Veterans with SCI. The proposed study will address the conundrum of why some Veterans with SCI suffer from a continuous cycle of recurring PrI, while others remain PrI free. The research strategy will build on the model developed by the Bogie lab of Biomarkers for Early Identification of Pressure Injury Risk (BEIPIR) for persons with SCI. BEIPIR unifies hierarchical relationships between clinical factors, health behaviors and muscle composition. We have shown that intramuscular adipose tissue (IMAT) is a critical clinically significant risk factor for PrI development. IMAT levels and accumulation rates vary greatly in this cohort. Some people exhibit rapid IMAT accumulation following SCI, while others do not. It is important to explain what is driving these changes. Our preliminary findings provide the basis for the central hypothesis: DNA variants predispose some individuals to increased deposition of IMAT following SCI, and resultant increased PrI risk. The proposed study will update the BEIPIR model by examining IMAT in conjunction with investigation of DNA variants associated with accelerated and/or higher levels of IMAT deposition. The TruSight™ One Expanded Sequencing panel (Illumina, San Diego CA) will be applied for Next Generation Sequencing of 50 existing blood samples from 38 persons with complete or incomplete SCI (AIS A-D) for whom gluteal muscle composition over time has already been evaluated. Genetic profile information, specifically DNA variants which are differentially active between persons with and without a history of PrI at a statistically significant level of p<0.05, will be selected and incorporated into the multi-scalar BEIPIR model for early identification of PrI risk. The updated BEIPIR model will be internally and externally validated to establish predicative efficacy. Internal validation of the BEIPIR model will be provided by testing the model with the genetic biomarkers identified. Split bootstrap procedures will be employed in order to derive stable estimations with low bias. A four year repeated measures study will be carried out to externally validate the BEIPIR model. A stratified study design will be employed to achieve a study cohort of 100 Veterans with SCI (AIS A-D) including participants with and without a history of PrI. Study participants will be recruited from Louis Stokes Cleveland VA Medical Center and the James J. Peters VA Medical Center (Site PI: Dr. Galea). Whole blood will be collected from study participants and DNA extracted prior to processing using the TruSight™ One Expanded Sequencing panel. Very low dose transverse pelvic region CT scans with contrast will be carried out based on our established protocol. Muscle composition and cross-sectional area will be determined using our established Hounsfield Unit scale classification protocol to determine relative lean muscle and IMAT content. 3D reconstruction will be applied to show IMAT distribution throughout the muscle. Study participants will be surveyed monthly by phone using our standardized skin status questionnaire to determine tissue health status. Incidences of tissue compromise or breakdown will be monitored and data applied to refine the BEIPIR model. Blood draw and CT scans will be repeated annually or when a PrI occurs. Longitudinal repeated measures of the de novo study cohort will be used to evaluate BEIPIR model performance and provide external validation of the model. Update and validation of the BEIPIR model will provide a clinical tool to optimize personalized care, recognizing that every person with SCI is an individual. Our proposed study has great potential to improve PrI risk assessment, enhance health status and quality of life for Veterans with SCI and reduce VHA costs. In the longer term, the BEIPIR model may provide the basis for development of a blood test kit for PrI risk. This research will also expand the de-identified genetic data publicly available for this underrepresented population.

压力损伤（PrI）是脊髓损伤（SCI）患者的主要继发性并发症。 PrI的发展和/或复发限制了日常生活活动，通常导致住院治疗，甚至 死亡除了对受影响的个人及其照顾者的破坏性影响外，PrI管理还具有 对退伍军人健康管理局的医疗保健费用产生重大影响，为我们的 退伍军人SCI这项拟议的研究将解决为什么一些SCI退伍军人会遭受创伤的难题。 持续循环的重复性PrI，而其他人保持PrI免费。研究战略将建立在该模型的基础上 由生物标志物的转向架实验室开发，用于早期识别压力损伤风险（BEIPIR）的人 关于SCI BEIPIR统一了临床因素、健康行为和肌肉之间的层次关系 混合物.我们已经证明，肌内脂肪组织（IMAT）是一个重要的临床显著的危险因素 为了PrI的发展。IMAT水平和积累率在这一群体中差异很大。有些人表现出快速 IMAT积累后SCI，而其他人没有。解释是什么推动了这些变化是很重要的。 我们的初步研究结果为核心假设提供了基础：DNA变异使某些个体易患 SCI后IMAT沉积增加，导致PrI风险增加。研究报告将更新 BEIPIR模型通过检查IMAT结合与以下相关的DNA变异的研究 加速和/或更高水平的IMAT沉积。TruSight™ One Expanded Sequencing panel（Illumina， San Diego CA）将应用于来自38人的50份现有血液样本的下一代测序 完全或不完全SCI（AIS A-D）患者，其臀肌成分随着时间的推移已经 评估。基因图谱信息，特别是人与人之间有差异的DNA变异 将选择有和没有PrI病史的患者，统计学显著性水平为p<0.05，并纳入 用于PrI风险早期识别的多标量BEIPIR模型。更新后的BEIPIR模型将在内部和 外部验证以确定预测性疗效。BEIPIR模型的内部验证将由 用鉴定的遗传生物标志物测试模型。将采用拆分引导程序，以便 得到具有低偏差的稳定估计。将进行为期四年的重复测量研究， 验证BEIPIR模型。将采用分层研究设计，以实现100名退伍军人的研究队列 SCI（AIS A-D）患者，包括有和无PrI病史的受试者。研究受试者将从 Louis Stokes Cleveland VA Medical Center和James J. Peters VA Medical Center（研究中心PI：Dr. Galea）。 在使用TruSight™处理之前，将从研究参与者采集全血并提取DNA 一个扩展测序面板。将进行极低剂量横向盆腔区域CT扫描，并使用对比剂 根据我们的既定协议。肌肉组成和横截面积将使用我们的 建立了Hounsfield单位量表分类方案，以确定相对瘦肌肉和IMAT含量。3D 将应用重建来显示整个肌肉的IMAT分布。研究参与者将 使用我们的标准化皮肤状况问卷每月进行电话调查，以确定组织健康状况。 将监测组织受损或破裂的发生率，并将数据用于完善BEIPIR模型。 每年或发生PrI时重复抽血和CT扫描。纵向重复测量 重新研究队列将用于评价BEIPIR模型性能，并提供 模型BEIPIR模型的更新和验证将为优化个性化护理提供临床工具， 认识到每一个SCI患者都是独立的个体。我们提出的研究有很大的潜力，以改善PrI 风险评估，提高SCI退伍军人的健康状况和生活质量，降低VHA成本。在 从长远来看，BEIPIR模型可能为开发PrI风险的血液检测试剂盒提供基础。这 研究还将扩大公开提供的这一代表性不足的人口的去身份化遗传数据。