Integrated Omics Analysis of Pain: Omics Data Generation Center

疼痛的综合组学分析：组学数据生成中心

• 批准号: 10001491
• 负责人: TIMOTHY D HOWARD
• 金额: $ 152.28万
• 依托单位: WAKE FOREST UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10001491
• 关键词: Acute; Acute Pain; Biological; Biological Markers; Blood specimen; California; Clinical assessments; Collaborations; DNA Methylation; Data; Data Set; Development; Epigenetic Process; Generations; Goals; Health Sciences; Institution; Knowledge; Lead; Mediating; Methods; Molecular; Molecular Profiling; Musculoskeletal; Operative Surgical Procedures; Pain; Pain management; Participant; Proteomics; RNA; Research Personnel; Resources; SNP genotyping; Scientist; Shipping; Technical Expertise; Technology; Trauma; Trauma patient; United States National Institutes of Health; Universities; chronic pain; chronic pain patient; clinical center; cohort; data exchange; data integration; data resource; experience; extracellular; forest; genetic signature; genetic variant; high throughput analysis; large scale data; medical schools; metabolomics; monocyte; predictive signature; programs; sample collection; tissue injury; treatment strategy

SUMMARY Acute pain, usually triggered by tissue injury, such as trauma or surgery, can lead to long-­term persistent chronic pain, a debilitating condition that requires extensive treatment and pain management. Interestingly, the molecular basis of this transition from acute to chronic pain is poorly understood, and this lack of knowledge impedes the development of better treatment strategies for patients with chronic pain. Several recent studies have begun to explore underlying genetic and molecular signatures of the conversion to chronic pain, but clearly, additional efforts are needed to better understand the mechanisms and molecular signatures in a wider range of surgery and trauma patients. The goal of the NIH Acute to Chronic Pain Signatures (A2CPS) program is to determine the mechanisms that make some people susceptible and others resilient to the development of chronic pain. We propose an Omics Data Generation Center (ODGC) for the A2CPS Consortium as a collaborative effort of three academic institutions with complementary technical expertise, experience in large-­scale data generation projects, and established collaborations and interactions: · Wake Forest University Health Sciences (WFUHS), · The University of California at Davis (UCD), and · Duke University School of Medicine (Duke). The ODGC will generate omics data for blood samples collected from study participants at three clinical assessments (0, 3, and 6 months after a surgical procedure or musculoskeletal trauma) for an integrated analysis to identify biomarker signatures that are predictive of the transition from acute to chronic pain, and help reveal the underlying pathophysiological mechanisms mediating this transition. We have assembled a team of scientists that will use cutting-­edge technologies to perform high-­throughput analyses in 1) proteomics (WFUHS and Duke), 2) metabolomics (WFUHS and UCD), 3) lipidomics (UCD), 4) extracellular RNA (WFUHS), and 5) SNP genotyping (WFUHS). In addition, we propose to examine the epigenetics (DNA methylation) of monocytes collected from a subset of converters and non-­converters. The resulting data will be integrated with extensive clinical assessment data, in collaboration with the Data Integration and Resource Center and the Multisite Clinical Centers of the A2CPS Consortium.

概括 通常是由组织损伤引发的急性疼痛，例如创伤或手术，会导致长期持续性慢性 疼痛，一种令人衰弱的状况，需要广泛的治疗和疼痛管理。有趣的是，分子 这种从急性到慢性疼痛的过渡的基础知之甚少，缺乏知识阻碍了 为患有慢性疼痛的患者开发更好的治疗策略。最近的一些研究已经开始 探索转化为慢性疼痛的基本遗传和分子特征，但显然，额外 需要努力以更好地了解更广泛的机制和分子特征 手术和创伤患者。 NIH急性对慢性疼痛特征（A2CPS）程序的目的是确定机制 使某些人容易受到敏感，而另一些人则有弹性的慢性疼痛发展。我们提出了一个OMICS A2CPS联盟的数据生成中心（ODGC）作为三个学术的协作工作 具有完善技术专长的机构，大规模数据生成项目的经验以及 建立的合作和互动： 威克森林大学健康科学（WFUHS）， ·加利福尼亚大学戴维斯分校（UCD）和 ·杜克大学医学院（杜克大学）。 ODGC将在三个临床上从研究参与者那里收集的血液样本生成OMICS数据 评估（手术程序或肌肉骨骼创伤后的0、3和6个月）进行综合分析 确定可预测从急性到慢性疼痛过渡的生物标志物特征，并有助于揭示 介导这种过渡的基本病理生理机制。 我们组建了一个科学家团队，这些科学家将使用尖端技术执行高通量 1）蛋白质组学（WFUHS和DUKE）的分析，2）代谢组学（WFUHS和UCD），3）脂肪组学（UCD）， 4）细胞外RNA（WFUHS）和5）SNP基因分型（WFUHS）。此外，我们建议检查 从转化器和非转换器的子集收集的单核细胞的表观遗传学（DNA甲基化）。 由此产生的数据将与大量的临床评估数据集成在一起，并与数据合作 集成和资源中心以及A2CPS联盟的多站点临床中心。