Marcus Pezzolesi

Personal Information
Title Associate Professor
Expertise Nephropathy
Institution University of Utah
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Data Summary
Grants/SubContracts 3
Progress Reports 3
Publications 4
Protocols 0
Committees 2

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).
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.
Integrative ‘Omics’ Analysis of Progression of Renal Decline in Type 1 Diabetes
Diabetic kidney disease, also known as diabetic nephropathy (DN), is a complex, heterogeneous complication of diabetes. Genetic factors are known to contribute to DN susceptibility; however, despite intense effort, the identification of variants that underlie its risk has been challenging. As such, novel approaches are needed to advance our understanding of the heritable factors associated with DN. Despite this bottleneck, longitudinal studies conducted over the past 20 years have improved our understanding of the course of deteriorating renal function in diabetic patients with kidney disease, establishing progressive renal decline as the predominant clinical feature of DN. Here, we propose a novel study to examine the role of epigenetics in rapid renal decline in type 1 diabetes (T1D) participants of the Joslin Kidney Study (JKS). Specifically, we hypothesize that integrative analysis of co-measured DNAme (methylome), gene expression (transcriptome), and genetic variation (genome) taken during follow-up of JKS participants will aid in identifying DNAme changes that persist during renal function decline and the associated genes that drive progressive renal decline in DN. The goals of this Pilot and Feasibility project are i) to perform DNAme profiling in a subset of JKS participants in our preliminary studies, ii) to perform RNA-sequencing in co-ascertained whole-blood RNA specimens from these participants, and iii) to integrate these data with genetic data to identify ‘omics’ signatures of rapid renal decline. To accomplish these goals, we will i) establish persistent DNAme profiles and gene expression profiles in well-phenotyped participants of the JKS (Specific Aim 1) and ii) identify persistent DNAme signatures, methylation quantitative trait loci (mQTLs), and expression QTLs (eQTLs) associated with rapid renal decline (Specific Aim 2). We will perform DNAme profiling in follow-up whole-blood DNA specimens from 25 slow decliners and 25 rapid decliners with T1D from the JKS and conduct high-depth RNA-sequencing (RNA-Seq) on co-ascertained whole-blood RNA specimens from these 25 slow decliners and 25 rapid decliners from the JKS. We will then examine associations between persistent DNAme and gene expression in rapid renal function decline and map genetic regulators of DNAme (mQTLs) and gene expression (eQTLs) that are associated with rapid renal decline. Importantly, our proposed research is poised to generate critical new knowledge on the role of DNAme in the progression of renal decline in T1D. Our approach is highly innovative, leveraging a unique, well-characterized collection of patients and an integrative ‘omics’ approach, and involves a multidisciplinary team of investigators with expertise in all aspects of the proposed research. Our implementation of the proposed studies will define currently unknown factors in DN and serve as a springboard for future studies aimed at establishing the biological and mechanistic significance of the identified DNAme sites. Together, these efforts may lay the foundation for novel therapeutic strategies to prevent progression of renal decline in T1D.

Progress Reports

Annual Reports
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Year: 2022; Items: 1

A dominant negative ADIPOQ mutation in a diabetic family with renal disease, hypoadiponectinemia, and hyperceramidemia.
Simeone CA, Wilkerson JL, Poss AM, Banks JA, Varre JV, Guevara JL, Hernandez EJ, Gorsi B, Atkinson DL, Turapov T, Frodsham SG, Morales JCF, O'Neil K, Moore B, Yandell M, Summers SA, Krolewski AS, Holland WL, Pezzolesi MG
NPJ genomic medicine, 2022 (7), 43

Year: 2019; Items: 1

The Familiality of Rapid Renal Decline in Diabetes.
Frodsham SG, Yu Z, Lyons AM, Agarwal A, Pezzolesi MH, Dong L, Srinivas TR, Ying J, Greene T, Raphael KL, Smith KR, Pezzolesi MG
Diabetes, 2019 (68), 420 - 429

Year: 2015; Items: 2

SORBS1 gene, a new candidate for diabetic nephropathy: results from a multi-stage genome-wide association study in patients with type 1 diabetes.
Germain M, Pezzolesi MG, Sandholm N, McKnight AJ, Susztak K, Lajer M, Forsblom C, Marre M, Parving HH, Rossing P, Toppila I, Skupien J, Roussel R, Ko YA, Ledo N, Folkersen L, Civelek M, Maxwell AP, Tregouet DA, Groop PH, Tarnow L, Hadjadj S
Diabetologia, 2015 (58), 543 - 8
Circulating TGF-ß1-regulated miRNAs and the risk of rapid progression to ESRD in type 1 diabetes.
Pezzolesi MG, Satake E, McDonnell KP, Major M, Smiles AM, Krolewski AS
Diabetes, 2015
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