Application of integrative omics to identify mechanistic pathways of adverse outcomes in children with chronic kidney disease

About This Grant

PROJECT SUMMARY Chronic kidney disease (CKD) in children is associated with high mortality rates and negatively impacts bone accrual and linear growth. Current treatments for pediatric CKD are limited, and many children progress to kidney failure. Our prior work leading the pediatric investigations in the NIDDK CKD Biomarkers consortium identified biomarkers of CKD progression in the Chronic Kidney Disease in Children (CKiD) cohort using targeted protein and untargeted metabolomic approaches. We identified metabolites, metabolomic signatures, and six targeted proteins which were each independently associated with CKD progression. Recent advances in proteomic technologies enable the measurement of thousands of proteins concurrently with high specificity and sensitivity. Integrating large-scale, proteomics, metabolomics, and genomics provides unprecedented opportunities to define the molecular basis of CKD etiology and generate novel insights into CKD-related outcomes. With proteomic and metabolomic measurements supported by this award, and existing genomic, metabolomic, and targeted biomarker measurements, we hypothesize that an unbiased examination of the plasma and urine proteome will identify proteins and pathways involved in CKD progression and complications, expanding on our prior research to understand underlying tubular injury and dysfunction, inflammation, and repair mechanisms. This retrospective cohort study will leverage stored samples and existing data from >1,100 children in CKiD and the Cardiovascular Comorbidity in Children with CKD (4C) study, the two largest prospective cohort studies of pediatric CKD worldwide. Proteomic analysis will be performed on paired baseline plasma and urine samples. Untargeted metabolomic profiling of baseline 4C samples will be performed on the same platform used previously in CKiD. In Aim 1, we will: identify plasma and urine proteins that are biomarkers of CKD progression (50% decline in eGFR or kidney replacement therapy) and determine whether these protein markers differ by CKD etiology; identify novel biological pathways involved in CKD progression; and develop a multi-protein prognostic model that is highly predictive for CKD progression. In Aim 2, we will utilize the newly generated proteomic data to identify plasma and urine proteins and novel biological pathways associated with linear growth failure and mineral bone disease. Statistical analyses for Aims 1 and 2 will include Cox regression analysis, high dimensional regularization Cox regression with elastic net penalty, and consensus clustering analysis. In Aim 3, we will combine existing genomic and metabolomic data with newly generated proteomic and metabolomic data to apply novel integrative approaches to analyze multi-omic data. This is the first pediatric CKD study to couple high-throughput proteomic measurements with multi-omic data integration. The completion of these aims will: provide new insights into mechanisms of CKD progression and CKD-associated mineral bone disease and linear growth failure; contribute to the identification of non-invasive biomarkers; and generate a large repository of multi-omic data that can be leveraged to expand the project’s impact in future pediatric CKD research.