PROJECT SUMMARY
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.