Chronic kidney disease (CKD) affects 500 million people worldwide, with the greatest burden among older adults. People with CKD are at elevated risk for not only end-stage kidney disease, but also cardiovascular disease, heart failure, and death. Existing treatment for CKD is inadequate, and there is vast, poorly understood heterogeneity in disease progression. While genome-wide association studies have identified genetic variants that modulate CKD-associated risk, much of the hereditability of CKD, as well as the molecular basis for how identified variants regulate disease, remains unexplained. Our overarching hypothesis is that an integrated approach combining genetics, epigenetics, proteomics, and metabolomics can yield novel insights into the pathogenesis and prognosis of CKD. Variability in disease may be due in part to variability in DNA methylation, which changes with age and the metabolic milieu and can modify gene expression. Advances in high-throughput technology have revolutionized the breadth and precision of metabolomic and proteomic profiling, enabling unprecedented windows into trans-omic networks. The objective of this study is to use a systems biology approach to integrate genetic sequence variation with DNA methylation patterns, proteomics, and metabolomics in order to advance our understanding and treatment of CKD risk. The proposed grant will pursue biological pathways that affect CKD risk in the ongoing Atherosclerosis Risk Communities (ARIC) study, a contemporary, community-based cohort of white and black adults now aged 70 years and older, with plan for replication in two CKD cohorts and further extension to kidney tissue. The combination of rich phenotyping, comprehensive adjudicated outcomes, and genetic, epigenomic (funded by this grant), proteomic, and metabolomic data provides a unique opportunity to generate insights into the molecular basis of CKD, improve CKD risk prediction, and identify a series of candidate pathways and genes whose products may serve as targets for drug development. With the long-term goal of improving care in patients with CKD, we aim to discover associations between kidney function and metabolites, proteins, and related pathways (Aim 1), identifying specific pathways that provide insight into CKD-associated outcomes, including CKD progression, heart failure, cardiovascular disease, and mortality (Aim 2), and elucidate genetic and epigenetic variation underlying these candidate pathways (Aim 3). The study will use a combination of innovative methods and omics data to identify pathways and genetic variation that are clinical relevant and thus useful in informing the risk prediction and potentially treatment of patients with CKD.
There are 500 million people worldwide with chronic kidney disease, and it disproportionately affects older adults. Our goal is to integrate multi-omics data to elucidate biological pathways underlying chronic kidney disease risk with the purpose of improving risk prediction, prevention, and prognosis.
