Determinants of Uremic Symptoms in CKD and Associations to Clinical Outcomes

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Uremic symptoms, including fatigue, nausea, anorexia, pruritus, decreased mental acuity, poor sleep, and paresthesia, represent a significant burden on the quality of life for millions of US adults living with chronic kidney disease (CKD). The observation that many uremic symptoms improve following kidney transplantation suggests that retained solutes play a causal role in their pathogenesis. However, cross-sectional studies do not show a consistent association between kidney function and uremic symptoms, suggesting that other determinants must also be present. In order to guide management strategies, research is needed to evaluate the association between kidney function and uremic symptoms and identify any modifiable factors that additionally influence this relationship. Furthermore, the distinct disrupted metabolic pathways that contribute to the development of uremic symptoms are unknown. Metabolomics technology, which involves the comprehensive analysis of metabolites in a biological specimen, has the potential to rapidly accelerate the identification of uremic retention solutes that drive symptoms, leading to novel therapeutic strategies. The Chronic Renal Insufficiency Cohort (CRIC), an NIDDK-sponsored study of 3,939 individuals with CKD that has over 14 years of longitudinal assessments of kidney function and uremic symptoms, creates the ideal opportunity to complete our overall objective: to identify determinants of and outcomes associated with longitudinal trends in uremic symptoms and gain insight into their metabolic causes. Our central hypothesis is that beyond metrics of kidney function (e.g. estimated glomerular filtration rate [eGFR]), novel modifiable factors, both clinical and metabolite, will be associated with uremic symptoms, and that symptom trends over time can identify patients at increased risk of adverse outcomes. In Aim 1 of the study, we will quantify the association between changes in eGFR and changes in uremic symptoms and the association of uremic symptoms with dialysis initiation. In Aim 2 we will utilize the available plasma metabolomics data for a subset of CRIC participants (N=1,800) to identify metabolites associated with uremic symptoms and will evaluate whether metabolite markers of symptoms are also associated with the risk of dialysis initiation. These studies will result in a comprehensive picture of the prognosis for patients with uremic symptoms and provide insight into associations between disrupted metabolic pathways and symptom development. Such information stands to influence clinical practice as well as lead to novel therapeutics aimed at directly improving the quality of life for this patient population. The research aims are integrated into a comprehensive training plan that includes practical mentored experiences and a Master’s Degree in Public Health and will provide Dr. Wulczyn the opportunity to 1) learn advanced principals of biostatistical and epidemiological methods, including mixed effects modelling and survival analysis, 2) apply machine learning algorithms to predictive modelling, and 3) advance towards independence as a clinical investigator.