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T helper cells in development of chronic inflammation and multimorbidity

T helper cells in development of chronic inflammation and multimorbidity
T辅助细胞在慢性炎症和多发病发展中的作用
批准号:
10737051
负责人:
JINGZHONG DING
金额:
$66.18万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-08-15 至 2028-06-30

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中文摘要
翻译
多发性硬化症是两种或两种以上慢性疾病的共存,通常与衰老有关, 老年人慢性炎症与多发病和个体衰老相关疾病有关 包括心血管疾病、糖尿病、癌症、阿尔茨海默病和骨质疏松症。抗炎 靶向IL 1 β治疗可降低心血管疾病风险,但调节炎症的临床益处 仍然存在争议。动物研究表明,包括T辅助细胞在内的免疫细胞的浸润, 动脉壁、脂肪和其他组织可能是慢性炎症的中心机制 以及随后的疾病。然而,大多数人类研究依赖于炎症生物标志物,如IL 6和IL 8。 CRP,缺乏机制特异性。缺乏直接表征免疫细胞功能的人体研究, 在炎症过程中的作用是一个主要的差距,阻碍翻译的动物为基础的机械工作。我们 提出T辅助细胞是慢性炎症和随后疾病的重要贡献者 因为它们调节适应性和先天性免疫细胞的免疫应答,包括激活 单核细胞/巨噬细胞。这一观点得到了我们来自多民族研究的初步数据的支持。 动脉粥样硬化(梅萨),显示T辅助细胞的促炎特征与 多发性骨髓炎、慢性炎症和单核细胞的炎症反应。虽然这些微阵列数据 支持T辅助细胞在慢性炎症和多发性硬化中的作用,大型纵向研究 需要确定细胞特征是否先于疾病发展。拟议的研究将利用 梅萨中分离的人T辅助细胞的独特资源(N= 1,900)。我们假设细胞 在外周T辅助细胞中协调炎症反应的特征有助于随后的炎症反应。 慢性炎症、外周单核细胞中的炎性变化和多发性骨髓瘤。为了验证这一 假设,我们将研究以下具体目标:1)研究是否组学概况的T辅助细胞 预测1,900名梅萨参与者的11年多发病率变化,2)评估 T辅助细胞预测单核细胞和循环促炎细胞组学特征的6年变化 在1,900个个体中进行生物标志物的研究,以及3)为了测试从人的T辅助细胞的药理学调节的效果, 梅萨参与者的炎症反应。这项拟议的研究将首次调查 人类辅助性T细胞和多聚体的组学特征之间的纵向关系。结果 从拟议的研究将提高我们对人类炎症过程的理解,特别是他们的 细胞特征,并加速开发更精确的针对性抗炎干预措施, 防止多人死亡。
英文摘要
Multimorbidity, the coexistence of two or more chronic and often aging-related diseases, affects the majority of older adults. Chronic inflammation has been implicated in multimorbidity and individual aging-related diseases including cardiovascular disease, diabetes, cancer, Alzheimer’s disease, and osteoporosis. Anti-inflammatory therapy targeting IL1β reduces risk for cardiovascular disease, but clinical benefits of modulating inflammation remain controversial. Animal studies suggest that the infiltration of immune cells including T helper cells into the arterial wall, adipose, and other tissues may be the central mechanism underlying chronic inflammation and subsequent diseases. Most human studies, however, rely on inflammatory biomarkers such as IL6 and CRP, which lack mechanistic specificity. The paucity of human studies directly characterizing the immune cells’ role in the inflammatory process is a major gap retarding the translation of animal-based mechanistic work. We propose that T helper cells are an important contributor to both chronic inflammation and subsequent diseases because of their regulating immune response of both adaptive and innate immune cells including activation of monocytes/macrophages. This view is supported by our preliminary data from the Multi-Ethnic Study of Atherosclerosis (MESA) which shows the associations of pro-inflammatory signatures of T helper cells with multimorbidity, chronic inflammation, and inflammatory response of monocytes. While these microarray data support the role of T helper cells in chronic inflammation and multimorbidity, large longitudinal studies are needed to establish whether cellular features precede disease development. The proposed study will leverage the unique resource of isolated human T helper cells in MESA (N=1,900). We hypothesize that cellular features that coordinate the inflammatory response in peripheral T helper cells contribute to subsequent chronic inflammation, inflammatory changes in peripheral monocytes, and multimorbidity. To test this hypothesis, we will examine the following specific aims: 1) to examine whether omics profiles of T helper cells predict 11-year changes in multimorbidity in 1,900 MESA participants, 2) to evaluate whether omics profiles of T helper cells predict 6-year changes in omics profiles of monocytes and circulating pro-inflammatory biomarkers in 1,900 individuals, and 3) To test effects of pharmacological modulation of T helper cells from MESA participants on inflammatory responses. The proposed study will for the first time investigate the longitudinal relationship between omics profiles of T helper cells and multimorbidity in humans. The results from the proposed study will improve our understanding of inflammatory processes in humans, particularly their cellular features, and accelerate the development of more precisely targeted anti-inflammatory interventions for preventing multimorbidity.
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会议论文
Aging Biomarkers: Integrating Omic Profiles with Mechanistic Measures
Aging Biomarkers: Integrating Omic Profiles with Mechanistic Measures
Aging Biomarkers: Integrating Omic Profiles with Mechanistic Measures
Aging Biomarkers: Integrating Omic Profiles with Mechanistic Measures
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