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Member Profile

Marcus Pezzolesi

Personal Information
Title Assistant Professor
Expertise Nephropathy
Institution University of Utah
Data Summary
TypeCount
Grants/SubContracts 2
Progress Reports 1
Publications 2
Protocols 0
Committees 2
Experiments 0
Strains 0
Models 0

SubContract(s)


An Integrated, 'Big-Data' Approach to Accelerate Gene Discovery in Diabetic Kidney Disease
Diabetic kidney disease (DKD) is a complex, heterogeneous complication of diabetes. Genetic factors are known to contribute to DKD susceptibility, however, despite intense effort, the identification of variants that underlie its risk has been challenging. Taking advantage of insights from previous studies, as well as epidemiologic studies on the natural history of DKD, we propose a novel, highly innovative ‘big-data’ approach to accelerate gene discovery in DKD that integrates data from the Utah Population Database (UPDB), a unique population-based genealogy resource containing family histories and demographic data for 14 million individuals, electronic health records for 2.1 million individuals in the UPDB, and high throughput next-generation sequencing technology. The goal of this Pilot and Feasibility project is to apply this approach to i) identify high-risk DKD families that are enriched for rapid progression of renal function decline, the predominant clinical feature of DKD (Specific Aim 1), and ii) to initiate whole-genome sequencing (WGS) in these families to begin determining the contribution of variation across the entire genome on renal function decline in DKD (Specific Aim 2). Using more than 200,000 diabetic patients in the UPDB, we will establish estimated glomerular filtration rate (eGFR) trajectories using longitudinal measures of eGFR obtained from electronic health records from the University of Utah Health Sciences Center Hospital and Clinics (UUHSC) and Intermountain Healthcare (IHC) Enterprise Data Warehouses, our electronic health record repositories, determine the familiality of rapid renal function decline among these diabetic patients, and identify high-risk families enriched for rapid renal function decline. After identifying and prioritizing these families, we will identify select individuals to optimize WGS-based gene discovery power using innovative tools developed at the University of Utah and perform WGS-based gene discovery in these individuals to identify genes for rapid renal function decline. After completing this Pilot and Feasibility project, we anticipate that we will have identified as many as 50 to 100 (or more) large, multi-generational pedigrees that are enriched for progression of rapid renal function decline. As part of this project, we will perform WGS-based gene discovery in a subset of these families as proof-of-concept of our integrative ‘bigdata’ approach. The data generated through these efforts will be a springboard for further WGS-based gene discovery studies in the remaining families and future studies on the mechanisms of progressive function renal decline in diabetes.

Establishing miRNome Expression Profiles of Renal Function Decline in T1D
Diabetic nephropathy (DN) is the major complication of Type 1 diabetes (T1D). This multiple stage disease first manifests as microalbuminuria and, over time, some patients progress to proteinuria. For a subset of these individuals, renal function continues to deteriorate until end-stage renal disease (ESRD) is reached. Recent studies have begun to investigate the role of microRNAs (miRNAs) in the pathogenesis of DN. These studies, however, have primarily involved mouse models or in vitro studies. Whether this class of molecules is associated with either the risk of or protection against rapid renal function decline has not yet been investigated. Because miRNAs are expressed and stable in a variety of biofluids, these molecules have potential utility as novel biomarkers of the risk of progression to ESRD in DN. The goal of this pilot project is to begin to fill this knowledge gap by comprehensively analyzing the miRNA genome (miRNome) in a well-characterized cohort of T1D patients who progressed rapidly to ESRD (i.e., rapid progressors) and those who did not, despite persistent proteinuria (i.e., non-progressors). The proposed project will take advantage of biological specimens from patients from these phenotypic extremes that have been collected as part of a longitudinal investigation of the natural history of DN in T1D to determine the role of plasma and urinary miRNAs in renal function decline and progression to ESRD in patients with T1D. To accomplish this, we propose a cost-effective, two-stage approach to identify miRNAs that are robustly associated with these phenotypes (Specific Aim 1). In Stage 1, we will establish miRNome profiles of 1,066 miRNAs in pooled RNA samples obtained from rapid progressors and non-progressors. In Stage 2, the most differentially expressed miRNAs from Stage 1 will be measured and analyzed in individual specimens obtained from these 2 study groups as well as a reference panel of T1D patients with normoalbuminuria. In both stages, plasma and urinary miRNAs will be analyzed using specimens collected at baseline and after several years of follow-up. Differentially expressed miRNAs identified through these experiments will be used to determine the role of miRNAs in renal function decline and progression to ESRD in T1D (Specific Aim 2).


Progress Reports

Annual Reports

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