Center for the Study of Symptom Science, Metabolomics and Multiple Chronic Conditions

美国超过25%的成年人口患有多种慢性病(MCC)， 这一数字在上升，特别是在黑人男性和女性中，他们的MCC发病率最高。那些 患有MCC的患者经常出现症状或症状群，这些症状或症状群破坏了他们的生活质量和 自我管理。重要的是，即使是相同的MCC患者的症状严重程度也不同，这表明 在MCC中驱动症状的机制并不是固定的，而是以不同的方式使它们服从于 有针对性的干预--护理学的本质。该中心的总体目标是 《症状科学、代谢组学与多种慢性病的研究》旨在增强老年人的能力 不同的护士科学家使用尖端代谢组学进行创新的翻译研究 和微生物组技术，以减轻MCC患者的症状。该中心的研究目标是 应用下一代代谢组学技术和数据分析策略来刺激发现 MCC患者体内存在的代谢物和代谢途径，主要集中在代谢物和 代谢途径在各种情况下协同作用，并与严重的疲劳症状相关联， 抑郁或焦虑及其聚集性，但在患有MCC的患者中较少出现，他们的症状最少 或者没有症状。与症状相关的代谢物和途径将根据协变量进行评估 例如，性别作为生物变量、年龄、压力和歧视、饮食和药物。探索性目标 将调查肠道微生物群的组成，作为这些症状的潜在协变量。这一目标 利用我校在微生物组研究和将微生物组与这些微生物组联系起来的证据方面的优势 症状。飞行员1-3将检查循环代谢物和与 MCC患者的疲劳、抑郁和焦虑症状的严重程度，并根据协变量， 并检查每个时间点的关联，而Pilot 4将应用数据分析技术来建模 MCC中与症状严重性、协同性、聚集性和健康质量结果相关的复杂途径。 飞行员5将测试飞行员4模型，以证明飞行员1-3中确定的代谢物和协变量的概念 确实与症状严重程度相关，并且是有效的干预目标。与以下物质有关的代谢产物 MCC的症状，包括那些协同作用、有助于聚集的症状，或与微生物组相关的症状， 都尚未被描述。在26名中心工作人员中，有18名是中心教职员工和成员。我们的研究基地 在MCC，自我管理、代谢组学和微生物组很强大，每年的直接成本为4.7美元 百万美元。数据科学中心每年得到50万美元的支持，并将提供基础设施 数据科学核心。我们将利用埃默里代谢组学和集成基因组学的资源 核心。使初级教员具备思考复杂理论和使用尖端技术的能力，同时 专注于翻译，为未来的护士科学家做好准备，以解决对患者和家属重要的问题。

Over 25% of the adult population in the United States suffers from multiple chronic conditions (MCC), with numbers rising, especially among Black men and women who experience the highest MCC morbidity. Those with MCC often experience symptoms or symptom clusters that undermine their quality of life and ability to self-manage. Importantly, symptom severity in those with even the same MCC varies, suggesting that the mechanisms driving symptoms in MCC are not fixed but vary in ways that may make them amenable to targeted interventions – the very essence of nursing science. The over-arching goal of the “Center for the Study of Symptom Science, Metabolomics and Multiple Chronic Conditions” is to strengthen the capacities of a diverse faculty of nurse scientists to conduct innovative translational research using cutting-edge metabolomics and microbiomic technologies to reduce symptoms in individuals with MCC. The Center’s research aim is to apply next-generation metabolomics technology and data analytic strategies to stimulate discovery of the metabolites and metabolic pathways that are present in individuals with MCC, focusing on the metabolites and metabolic pathways that synergize across conditions and associate with severe symptoms of fatigue, depression, or anxiety and their cluster, but are less represented in individuals with MCC who have minimal or no symptoms. Metabolites and pathways associated with symptoms will be evaluated in light of covariates such as sex as a biological variable, age, stress and discrimination, diet and medications. An exploratory aim will investigate the composition of the gut microbiome as a potential covariate to these symptoms. This aim takes advantage of our School’s strength in microbiome research and evidence linking the microbiome to these symptoms. Pilots 1-3 will examine the circulating metabolites and metabolic profiles that associate with the severity of the symptoms of fatigue, depression, and anxiety in individuals with MCC and in light of covariates, and examine the associations at each time point, while pilot 4 will apply data analytic techniques to model the complex pathways associated with symptom severity, synergy, cluster, and health quality outcomes in MCC. Pilot 5 will test the Pilot 4 model for proof of concept that the metabolites and covariates identified in Pilots 1-3 do associate with symptom severity and are valid targets for intervention. Metabolites associated with symptoms in MCC, including those that synergize, that contribute to clustering, or are microbiome-associated, have yet to be described. Of the 26 Center Personnel, 18 are Center Faculty and Members. Our research base in MCC, self-management, metabolomics, and the microbiome is strong with annual direct costs of $4.7 million. The Center for Data Science is supported with ½ million dollars annually, and will provide infrastructure to the Data Science Core. We will leverage resources of the Emory Metabolomics and Integrated Genomic Cores. Equipping junior faculty to consider complex theories and employ cutting-edge technology, while focused on translation, prepares future nurse scientists to address issues that matter to patients and families.