Integrated Omics Analysis of Pain: Omics Data Generation Center

摘要 急性疼痛通常由组织损伤引发，如创伤或手术，可导致长期持续的慢性疼痛 疼痛，一种需要广泛治疗和疼痛管理的虚弱状况。有趣的是，分子 从急性疼痛到慢性疼痛的这种转变的基础尚不清楚，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，但显然， 需要努力在更广泛的范围内更好地理解机制和分子签名 外科手术和创伤病人。 美国国立卫生研究院急性到慢性疼痛信号(A2CPS)计划的目标是确定 让一些人对慢性疼痛的发展变得敏感，而另一些人则变得灵活。我们提出了一个OMICS A2CPS联盟的数据生成中心(ODGC)是三家学术机构共同努力的成果 具有互补的技术专长、大型数据生成项目经验的机构，以及 已建立的协作和互动： ·维克森林大学健康科学(WFUHS)， ·加州大学戴维斯分校(UCD)，以及 ·杜克大学医学院。 ODGC将为从三个临床研究参与者那里收集的血液样本生成组学数据 综合分析评估(手术或肌肉骨骼创伤后0、3和6个月) 识别可预测从急性疼痛向慢性疼痛过渡的生物标志物信号，并帮助揭示 调节这一转变的潜在病理生理机制。 我们已经组建了一支科学家团队，他们将使用尖端技术来实现高吞吐量 分析1)蛋白质组学(WFUHS和Duke)，2)代谢组学(WFUHS和UCD)，3)脂质组学(UCD)， 4)细胞外RNA(WFUHS)；5)SNP基因分型(WFUHS)。此外，我们建议研究 从转化子和非转化子子集收集的单核细胞的表观遗传学(DNA甲基化)。 所产生的数据将与广泛的临床评估数据结合在一起，并与数据协作 A2CPS联盟的整合和资源中心和多站点临床中心。

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.