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Immune cell gene expression and predictive models in CFS

Immune cell gene expression and predictive models in CFS
CFS 中的免疫细胞基因表达和预测模型
批准号:
9266829
负责人:
Olivier Elemento
金额:
$52.21万
依托单位国家:
美国
项目类别:
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-05-15 至 2020-04-30

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中文摘要
翻译
描述(申请人提供):慢性疲劳综合症目前是通过一系列症状来诊断的,这限制了它的识别,直到疾病发作后至少6个月。此外,缺乏客观的分子或生化测试,可以由不熟悉这种疾病的医务人员进行,往往会导致更多的延误和对其他疲劳性疾病的误诊。治疗选择有限。新疗法的开发受到几个障碍的阻碍:(1)缺乏简单的客观监测工具来确定疗法是否有效;(2)难以区分可能的患者亚群;(3)缺乏关于疾病病理生理学的信息,可以建议开发新的药物。这些问题将通过使用最先进的深度测序方法和生物信息学分析来识别CFS患者和健康对照组之间的基因表达差异来解决。过去的研究表明,感染因素、自身免疫或免疫系统紊乱会影响循环中白细胞的活动。全血中的信使RNA和microRNAs以及通过流式细胞术纯化的B、T和NK细胞将通过Illumina条形码cDNA文库的测序进行鉴定。将在蛋白质水平上分析候选失控的mRNA编码基因的子集的表达。标记物将在独立于发现标记物的队列中得到确认。将开发和验证多变量生物标记物模型,以预测诊断和疾病严重程度。免疫细胞基因表达的综合分析将有助于我们进一步了解CFS的发病机制。
英文摘要
DESCRIPTION (provided by applicant): Chronic fatigue syndrome is presently diagnosed by a constellation of symptoms, which limit its identification until a minimum of 6 months after disease onset. Furthermore, the lack of an objective molecular or biochemical test that can be ordered by medical personnel unfamiliar with the illness often results in even further delay and misdiagnosis with other fatiguing illnesses. Treatment options are limited. Development of new therapies is hindered by several obstacles: (1) the absence of simple objective monitoring tools to determine whether a therapy is efficacious (2) difficulty in distinguishing possible sub-groups of patients and (3) lack of information about the pathophysiology of the disease that could suggest development of novel medications. These problems will be attacked through identification of gene expression differences between CFS patients and healthy controls using state-of-the-art deep sequencing methods and bioinformatic analysis. Past studies implicate infectious agents, autoimmunity, or immune system disturbances that affect the activity of circulating leukocytes. Messenger RNAs and microRNAs from whole blood and B, T, and NK cells purified by flow cytometry will be characterized through Illumina sequencing of barcoded cDNA libraries. The expression of a subset of candidate dysregulated mRNA-encoding genes will be assayed at the protein level. Markers will be confirmed in cohorts independent of those where they have been discovered. Multivariate biomarker models will be developed and validated in order to predict diagnosis as well as disease severity. Integrative analyses of immune cell gene expression will be carried out to help further our understanding of CFS pathogenesis.
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Data Management and Analysis Core
Data Management and Analysis Core
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