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

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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.