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.

总结 急性疼痛通常由组织损伤（如创伤或手术）引发，可导致长期持续性慢性疼痛。 疼痛，一种需要广泛治疗和疼痛管理的使人衰弱的状况。有趣的是， 这种从急性到慢性疼痛的转变的基础知之甚少，这种知识的缺乏阻碍了 为慢性疼痛患者制定更好的治疗策略。最近的几项研究已经开始 探索转化为慢性疼痛的潜在遗传和分子特征，但很明显， 需要努力更好地了解更广泛的机制和分子特征， 手术和创伤患者。 NIH急性至慢性疼痛特征（A2CPS）项目的目标是确定 使一些人易受慢性疼痛的影响，而另一些人则对慢性疼痛的发展有弹性。我们提出一个组学 A2CPS联盟的数据生成中心（ODGC）是三个学术机构的合作成果 具有互补性技术专长、大规模数据生成项目经验的机构，以及 已建立的合作和互动： ·维克森林大学健康科学（WFUHS）， ·加州大学戴维斯分校（UCD）， ·杜克大学医学院（杜克）。 ODGC将在三个临床研究中心为研究参与者采集的血液样本生成组学数据。 评估（手术或肌肉骨骼创伤后0、3和6个月）进行综合分析 识别生物标志物特征，预测从急性疼痛到慢性疼痛的转变，并帮助揭示 介导这种转变的潜在病理生理机制。 我们已经组建了一个科学家团队，他们将使用最先进的技术来实现高通量 分析1）蛋白质组学（WFUHS和杜克），2）代谢组学（WFUHS和UCD），3）脂质组学（UCD）， 4)细胞外RNA（WFUHS），和5）SNP基因分型（WFUHS）。此外，我们建议研究 表观遗传学（DNA甲基化）是从转化者和非转化者的子集收集的单核细胞的表观遗传学。 所产生的数据将与广泛的临床评估数据相结合，并与数据中心合作， 整合和资源中心以及A2CPS联盟的多中心临床中心。