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Aging Biomarkers: Integrating Omic Profiles with Mechanistic Measures

Aging Biomarkers: Integrating Omic Profiles with Mechanistic Measures
衰老生物标志物:将组学概况与机械测量相结合
批准号:
10445057
负责人:
JINGZHONG DING
金额:
$56.27万
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-30 至 2024-05-31

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中文摘要
翻译
本研究的目的是开发和验证反映生物衰老机制的生物标志物。 至少有五种药物化合物被批准用于人类,可延长啮齿动物的健康寿命和寿命 模型人类的平行方法需要持续40多年的研究,并且是不可行的。相反地, 该领域需要可靠的人类生物标志物, 衰老相关的途径在较短的时间内。表观基因组学和由此产生的转录组学变化可能 将动物研究中涉及的生物衰老机制结合起来,并解开新的途径。在基因组中- 对来自多种族研究的1,200人(年龄55-94岁)的单核细胞样本进行了广泛分析, 在动脉粥样硬化(梅萨)中,我们确定了1,794个年龄相关甲基化位点和2,704个年龄相关甲基化位点。 转录本,其中过度代表了几个网络,包括线粒体生物能量学和自噬。 我们进一步证明了这些基因网络与年龄无关的衰老相关疾病的关联。 除了组学特征之外,功能表型可以提供作为衰老的生物标志物的进一步优势。 过程例如,我们在老年人中的研究表明,外周血的生物能容量 单核细胞与身体功能测量正相关,即使在控制年龄时也是如此。我们 预测这些表观遗传学、转录组学和功能标记将与 与衰老相关的合并症,并对热量限制有反应。我们建议利用现有的纵向 评估单核细胞表观遗传/转录组学特征和年龄相关的健康结果, 中年和老年人(55-94岁)在梅萨研究。利用正在进行的随机临床试验 (VEGGIE)的热量限制在200名成人(40-70岁),我们还建议增加骨骼肌活检 (N=80)。具体目的是:1)确定是否与衰老相关的单核细胞转录组/表观基因组 单独或组合的途径预测8年随访期间衰老相关疾病的变化 (N= 1,800);和2)确定热量限制是否使衰老相关的单核细胞 转录组/表观基因组途径(N=200)和循环细胞和骨骼肌中的生物能量测量 肌肉(N=80)向年轻模式发展,以及这些变化单独或组合是否与 与衰老相关的代谢、身体和认知健康结果的变化。拟定的研究将 生成一组生物标志物,反映一系列全面的老化途径, 转录组学和表观基因组学概况与循环和骨骼肌中的生物能量学,从现有的 一项纵向队列研究和一项正在进行的热量限制临床试验, 通过多种趋同策略验证潜在的生物标志物。
英文摘要
The objective of this study is to develop and validate biomarkers that reflect mechanisms of biological aging. At least five pharmacologic compounds approved for human use extend health span and life span in rodent models. Parallel approaches in humans would require studies lasting 40+ years and are infeasible. Rather, the field needs reliable human biomarkers that indicate beneficial (or adverse) effects of an intervention on aging-related pathways over shorter time periods. Epigenomics and resultant transcriptomic changes may unite mechanisms of biological aging implicated in animal studies and unravel novel pathways. In a genome- wide analysis of monocyte samples in 1,200 persons (aged 55-94 years) from the Multi-Ethnic Study of Atherosclerosis (MESA), we identified 1,794 age-associated methylation sites and 2,704 age-associated transcripts, which over-represented several networks, including mitochondrial bioenergetics and autophagy. We further demonstrated associations of these gene networks with aging-related diseases independent of age. In addition to omic profiles, functional phenotyping may provide further advantages as biomarkers of the aging process. For example, our studies in older adults indicate the bioenergetic capacity of peripheral blood mononuclear cells is positively associated with physical function measures even when controlling for age. We predict that these epigenetic, transcriptomic, and functional markers will be associated with the development of aging-related comorbidities and are responsive to caloric restriction. We propose to utilize existing longitudinal assessments of monocyte epigenetic/transcriptomic profiles and age-related health outcomes from 1,800 middle-aged and older adults (55-94 years) in the MESA study. Leveraging an ongoing randomized clinical trial (VEGGIE) of caloric restriction in 200 adults (40-70 years), we also propose to add skeletal muscle biopsy (N=80). The specific aims are: 1) to determine whether aging-related monocyte transcriptomic/epigenomic pathways individually or in combination predict changes in aging-related diseases over an 8-year follow up (N=1,800); and 2) To determine whether caloric restriction shifts aging-related monocyte transcriptomic/epigenomic pathways (N=200) and bioenergetic measures in circulating cells and skeletal muscle (N=80) towards a younger pattern and whether these changes individually or in combination correlate with changes in aging-related metabolic, physical and cognitive health outcomes. The proposed study will generate a panel of biomarkers reflecting a comprehensive battery of aging pathways by integrating transcriptomic and epigenomic profiles with bioenergetics in circulation and skeletal muscle, from an existing longitudinal cohort study and an ongoing clinical trial of caloric restriction, to efficiently and cost-effectively validate potential biomarkers through multiple convergent strategies.
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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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