DNA methylation markers of Multimorbidity in Aging Humans and Mice

多发性疾病(MM)，传统上定义为两种或两种以上的慢性病，是一个公共卫生问题 在老年人身上。MM患者因多药、残疾和早产而发生医源性疾病的风险很高。 死亡，给照顾者带来了挑战，给社会带来了代价。多发性骨髓瘤的病理生理学研究 单一的生物标志物或途径取得的成功有限。此外，还没有全面的生物标志物。 为评估和预测MM而开发的。以前的经验和初步数据证实了这一假设 是否存在与MM相关的潜在DNA甲基化(DNaM)生物标记物 人口水平。此外，在人类组织水平上对多发性骨髓瘤发病机制的研究也很有限。 由于道德和后勤方面的复杂性。被忽视但无可争议的关键，识别dNaM标记 对于发展我们预测多发性骨髓瘤和多发性骨髓瘤的能力是至关重要的。 更多地揭示了其潜在的机制。 这项建议的首要目标是在人群中识别MM的dNaM标记，并 老鼠模型开发了一套全面的工具来识别高危个体。由此产生的 标志将适用于男性和女性个人。使用四个种群队列，我将测试使用 来预测谁有可能患多发性骨髓瘤。我将测量细胞特异性dNaM和基因 表达(RNA-seq)在基线和非MM个体之间既相关又不同 我将使用MM的动物模型，使用组织病理学 器官研究，以定义和测量dNaM和同源转录组学(rna-seq)。结果是 本研究可以更好地识别和理解MM的共享性机制(S)。 总而言之，识别“人类和小鼠衰老时多病的DNA甲基化标记”应该允许 老年病医生预测老年人的多发病，并帮助研究人员进一步了解 多发性疾病的潜在机制。该项目的结果，在未来可以应用于测试 针对这些预防和治疗机制的干预措施，如二甲双胍的有效性 嗯。

Multimorbidity (MM), conventionally defined as two or more chronic diseases, is a public health problem in older adults. MM patients are at high risk of iatrogenesis from polypharmacy, disability, and premature death, with challenges to caregivers and cost to society. The study of the pathophysiology of MM based on single biomarkers or pathways has had limited success. Moreover, there are no comprehensive biomarkers developed to evaluate and predict MM. Previous experience and preliminary data corroborate the hypothesis of the existence of potential DNA methylation (DNAm) biomarkers that are associated with MM at the population level. Additionally, the study of mechanisms of MM at the tissue level in humans have been limited due to ethical and logistical complications. Neglected yet unarguably pivotal, identifying DNAm markers associated with MM mouse models is of paramount importance to develop our capabilities to predict MM and shed more light on its underlying mechanisms. The overarching goal of this proposal is to identify DNAm markers of MM in human populations and mouse models to develop a set of comprehensive tools for the identification of at-risk individuals. The resulting markers will be applicable to both male and female individuals. Using four population cohorts, I will test the use of DNAm markers to predict who is likely develop MM. I will measure how cell specific DNAm and gene expression (RNA-seq) are related and different between individuals who are free of MM at baseline and developed MM and those who remained free of MM. I will use an animal model of MM using histopathology studies of organs to define mm and measure DNAm and cognate transcriptomics (RNA-seq). The results of this study can be used to better identify and understand the shared mechanism(s) that causes MM. Collectively, identifying “DNA methylation markers of multimorbidity in aging humans and mice” should allow geriatricians to predict multimorbidity in older adults and help researchers to further understand the mechanisms underlying multimorbidity. The results of this project, in the future, can be applied to test the effectiveness of interventions such as metformin that target these mechanisms for prevention and treatment of MM.