Studies in both community-based and high-risk populations show that chronic kidney disease (CKD) (defined as an estimated glomerular filtration rate (eGFR) <60 ml/min/m2 or albuminuria) confers at least a two-fold increase in cardiovascular risk. Approximately 10% of the $200 billion 2008 United States Medicare budget was devoted to managing patients with concomitant CKD and cardiovascular disease (CVD). Despite this enormous public health impact, we still know relatively little about the predictors and mediators of the association between CKD and CVD. Clinicians lack a viable cardiovascular risk prediction model for patients with CKD, and there are few effective cardiovascular therapies for this high-risk population. While traditional risk factors such as hypertension and diabetes predict adverse cardiovascular outcomes in these patients, non-traditional risk factors involved in inflammation and deranged bone/mineral metabolism are also thought to play an important role. However, these risk factors do not fully explain the excess risk of CVD among CKD patients, nor, when incorporated into risk prediction models, acceptably predict CVD risk in this population. Furthermore, many of these risk factors are not pharmacologically modifiable (e.g. age, sex, race). In this application, our overall goal is to accelerate the search for novel protei biomarkers of CVD in CKD. We hope to facilitate more accurate cardiovascular risk prediction and discover potentially modifiable protein mediators of CVD in CKD that may become targets for novel pharmacologic therapies. We will leverage large-scale proteomics with modified aptamers (SOMAscan, SomaLogic, Boulder CO), a transformative method in the field of proteomics, that allows for rapid quantification of over 1100 plasma proteins in a small blood sample, making proteomics feasible in large cohort studies. We will carry out our investigation in the Chronic Renal Insufficiency Cohort (CRIC), a multi-center cohort of 3939 racially and ethnically diverse individuals between the ages of 21 to 74 years with estimated glomerular filtration rate (eGFR) between 20 and 70 ml/min/1.73m2. Proteomic analyses will be carried out in 2571 CRIC participants without baseline CVD who will have 11 years of adjudicated atherosclerotic cardiovascular events, heart failure and cardiovascular mortality at the time of the proposed analyses. We will assay concentrations of 1130 plasma proteins in order to complete the following Specific Aims: 1a) to discover > 100 novel protein biomarkers associated with incident CVD and cardiovascular mortality in the CRIC cohort; 1b) to elucidate causal pathways of cardiovascular disease in CKD by applying pathway analysis to discovered proteins under 1a); 2) to devise a parsimonious cardiovascular risk prediction model utilizing proteins that are associated with cardiovascular risk; and 3) to compare the proteomic cardiovascular risk model to traditional, Framingham factor-based clinical risk models in the CRIC cohort.
There are over 20 million patients with chronic kidney disease in the United States, many of whom have over twice the risk of cardiovascular disease compared to individuals with normal kidney function. We currently do not know why these patients are at such high cardiovascular risk, and we have few effective therapies to prevent or treat cardiovascular disease in this population. We intend to apply a novel method that measures over 1130 proteins in one drop of blood to the study of cardiovascular disease in the Chronic Renal Insufficiency Cohort (CRIC) in order to discover new, potentially modifiable proteins that could help us predict cardiovascular risk and eventually lead to new therapies for this high risk population.
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