Genetic of Kidney Disease and Hypertension in MVP II

Veterans Health Administration, Decatur PA

Investigators

Linked publications, trials & patents

Abstract

Chronic Kidney Disease (CKD) is a global public health issue, affecting 1 in 7 adults in the United States and 850 million people worldwide. In addition to the risk of progressing to end-stage renal disease (ESRD), a life- threatening condition with a devastating impact on quality of life, CKD is associated with a high-cost burden to the healthcare system and high mortality. However, therapies to slow progression remain scarce. A major barrier for discovery of disease mechanisms and therapeutic targets in CKD is the heterogeneity of disease progression and outcomes, even within specific etiologies such as diabetic kidney disease (DKD), arterionephrosclerosis, or glomerular diseases. While the genetic contribution to kidney disease has been characterized in cross-sectional designs and mostly using estimated glomerular filtration rate (eGFR), there remains a significant gap in knowledge of the genetic contributors to disease progression and for some CKD subtypes. In this application, we propose to address these limitations by creating a comprehensive model of CKD progression centered on genetics that integrates kidney biopsy data, highly curated clinical phenotypes, and state-of-the-art omics methodologies, including genomics, methylation, proteomics, and gene expression. This will provide deeper understanding of mechanisms of CKD, while overcoming the phenotypic heterogeneity traditionally seen in CKD and the limitation of using cross-sectional designs of eGFR. This, in turn, will foster the discovery of disease mechanisms, identify therapeutic targets so desperately needed, and inform risk prediction. Additionally, we will continue researching second hits for APOL1-mediated kidney disease (AMKD). Diet has been considered potentially a second hit for AMKD and APOL1 effect on blood pressure. Diet is a critical and modifiable determinant of CKD progression. To this end, we will study gene*diet interactions as a modifiable determinant of CKD progression, hypertension. We will accomplish these goals through the following aims: 1) To curate the “VA e-Kidney biopsy repository” by defining kidney phenotypes using kidney biopsy data nationally and in MVP. We will generate an algorithm for kidney biopsy results based on structured data and automated information extraction using natural language processing from the report or clinical notes. We will integrate urinary biomarkers: proteinuria, albuminuria, hematuria, specific gravity, 24-hour urine collection. We will collaborate with VHA Program for Kidney Medicine. 2) To perform GWASs and whole genome analysis of CKD progression in non-diabetic CKD and incident DKD by ancestry in MVP. Disease progression outcomes will include a) eGFR slope, b) a composite of 40% decline in eGFR or ESRD15, and c) rapid decline >3 ml/min per 1.73m2 per year, in MVP. We will also study CKD subtypes with histological diagnosis and imaging when possible. Risk factors for CKD will be explored using Mendelian randomization analyses for causal inference (mineral metabolism, etc). Polygenic risk scores will be used for prediction models of progression. Gene expression analyses will prioritize identified variants relevant to CKD. 3) To study gene*nutrient interactions (micro- and macro- nutrients: salt, potassium, oxalate, plant vs. non-plant protein, etc), derived from the MVP lifestyle survey. 3.a) Gene*nutrient interactions are studied as important determinants of CKD progression, kidney stones, and blood pressure. 3.b.) APOL1 mechanism-driven interactions influence pathways related to kidney health, e.g., APOL1*salt intake, blood pressure, and CKD. Sub-aim 3.b will help to inform further the value of APOL1 testing and dietary recommendations for CKD care. Identifying additional ancestry-specific variants and interactions remains essential to continue progressing toward diminishing long-standing inequities in CKD. Our project will provide a step forward in understanding the pathophysiology of CKD through genetics, inform new drug targets, and improve risk prediction and will offer several avenues of applying genomics into medicine to improve the care we provide for patients with CKD. Replications will be pursued in BioVU, All of Us, UKBB, and eMERGE.