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Integrated Omics Analysis of Pain: Omics Data Generation Center

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:
10611195
负责人:
TIMOTHY D HOWARD
金额:
$50.0万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-01 至 2023-07-31

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中文摘要
翻译
总结 WF ODGC的目标是生成从以下人群收集的血浆样本的代谢组学和脂质组学数据: A2 CPS联盟的参与者,并发现新的代谢组学和/或脂质组学特征, 与从急性疼痛转变为慢性疼痛相关。我们使用高分辨率HILIC-MS/MS和高分辨率 用于代谢物表征的分离度GC-MS和带电表面混合液相色谱- 在正负电喷雾模式下进行高分辨率精确质量MS/MS,以表征血浆脂质。 ODGC是维克森林大学学院精准医学中心与 医学和西海岸代谢组学中心在加州大学戴维斯分校。 由于病人招募工作出现意外延误,需要提出行政补充要求 在两个临床研究中心,MCC 1和MCC 2的入组,以及由此导致的样本分析延迟 ODGC。根据MCC的估计,预计代谢组学和脂质组学的所有样本 分析(共8400份样本)将于2025年8月底前收集,分析、数据和样本转移 将由ODGC在2026年5月底前完成。所要求的补充将确保成功 分析全部样品,表征和定量预选的次级 生物标志物,并将所得生物标志物数据与针对生物标志物收集的其他生物标志物信息整合。 财团
英文摘要
SUMMARY The goal of the WF ODGC is to generate metabolomics and lipidomics data on plasma samples collected from participants of the A2CPS Consortium, and to discover novel metabolomic and/or lipidomic signatures that are associated with the conversion from acute to chronic pain. We use high resolution HILIC-MS/MS and high resolution GC-MS for the characterization of metabolites, and charged surface hybrid liquid chromatography- high resolution accurate mass MS/MS in positive and negative electrospray mode to characterize plasma lipids. The ODGC is a collaboration between the Center for Precision Medicine at the Wake Forest University School of Medicine and the West Coast Metabolomics Center at the University of California at Davis. This request for an Administrative Supplement is necessitated by the unforeseen delay in patient recruitment and enrollment at the two Clinical sites, MCC1 and MCC2, and the resulting delay in sample analysis at the ODGC. Based on the estimates from the MCCs, it is anticipated that all samples for metabolomics and lipidomics analysis (8400 samples total) will be collected by the end of August 2025, and analysis, data and sample transfer will be completed by the ODGC by the end of May, 2026. The requested supplement will ensure the successful analysis of the entire complement of samples, characterization and quantification of preselected secondary biomarkers, and integration of the resulting biomarker data with other biomarker information collected for the Consortium.
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Integrated Omics Analysis of Pain: Omics Data Generation Center
Integrated Omics Analysis of Pain: Omics Data Generation Center
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