Jun Zhang1, Mohammad Kazem Fallahzadeh2, Peter A McCullough3. 1. Baylor Heart and Vascular Institute, Dallas, Tex., USA. 2. Department of Internal Medicine, Baylor University Medical Center, Dallas, Tex., USA. 3. Baylor Heart and Vascular Institute, Dallas, Tex., USA; Department of Internal Medicine, Baylor University Medical Center, Dallas, Tex., USA; Baylor Jack and Jane Hamilton Heart and Vascular Hospital, Dallas, Tex, Tex., USA; The Heart Hospital Baylor Plano, Plano, Tex., USA.
Abstract
BACKGROUND: Although there are some animal models for biomarkers of contrast-induced acute kidney injury (CI-AKI), for cardiorenal syndrome (CRS) and for acute renal failure, the interplay between CI-AKI and CRS has yet to be evaluated. Insight into the pathogenesis of CRS is urgently needed from animal models in order to foster the discovery and implementation of novel biomarkers for this disease. Specially designed animal models for type 1 and 3 CRS, particularly CI-AKI, have not yet emerged. SUMMARY: We hypothesize that the aging male spontaneously hypertensive rat (SHR) is likely to be a suitable model. The SHR model is able to mimic risk factors for preclinical CRS that appears in the clinical setting, specifically hypertension, age, preexisting damage and dysfunction of the heart and kidney, endothelial dysfunction, increased level of reactive oxygen species, decreased level and bioavailability of nitric oxide (NO), impairment of the L-arginine-NO pathway, and insulin resistance. In the SHR, CI-AKI results in a different profile of AKI biomarkers than is seen with preexisting chronic kidney injury. KEY MESSAGES: The SHR model can be used to evaluate the interaction between CI-AKI and CRS type 1 and 3 and to verify neutrophil gelatinase-associated lipocalin (NGAL) as a reliable CI-AKI biomarker for clinical application. Further research is warranted with a large number of aging male SHRs to prove NGAL as a sensitive, specific, highly predictive, early biomarker for CI-AKI.
BACKGROUND: Although there are some animal models for biomarkers of contrast-induced acute kidney injury (CI-AKI), for cardiorenal syndrome (CRS) and for acute renal failure, the interplay between CI-AKI and CRS has yet to be evaluated. Insight into the pathogenesis of CRS is urgently needed from animal models in order to foster the discovery and implementation of novel biomarkers for this disease. Specially designed animal models for type 1 and 3 CRS, particularly CI-AKI, have not yet emerged. SUMMARY: We hypothesize that the aging male spontaneously hypertensive rat (SHR) is likely to be a suitable model. The SHR model is able to mimic risk factors for preclinical CRS that appears in the clinical setting, specifically hypertension, age, preexisting damage and dysfunction of the heart and kidney, endothelial dysfunction, increased level of reactive oxygen species, decreased level and bioavailability of nitric oxide (NO), impairment of the L-arginine-NO pathway, and insulin resistance. In the SHR, CI-AKI results in a different profile of AKI biomarkers than is seen with preexisting chronic kidney injury. KEY MESSAGES: The SHR model can be used to evaluate the interaction between CI-AKI and CRS type 1 and 3 and to verify neutrophil gelatinase-associated lipocalin (NGAL) as a reliable CI-AKI biomarker for clinical application. Further research is warranted with a large number of aging male SHRs to prove NGAL as a sensitive, specific, highly predictive, early biomarker for CI-AKI.
Authors: Lennart G Bongartz; Branko Braam; Carlo A Gaillard; Maarten J Cramer; Roel Goldschmeding; Marianne C Verhaar; Pieter A Doevendans; Jaap A Joles Journal: Am J Physiol Renal Physiol Date: 2012-08-22
Authors: Iveta Bernatova; M Victoria Conde; Jana Kopincova; M Carmen González; Angelika Puzserova; Silvia M Arribas Journal: J Hypertens Suppl Date: 2009-08
Authors: Mariusz K Szymanski; Rudolf A de Boer; Gerjan J Navis; Wiek H van Gilst; Hans L Hillege Journal: Heart Fail Rev Date: 2012-05 Impact factor: 4.214
Authors: Onju Ham; William Jin; Lei Lei; Hui Hui Huang; Kenji Tsuji; Ming Huang; Jason Roh; Anthony Rosenzweig; Hua A Jenny Lu Journal: Sci Rep Date: 2018-10-31 Impact factor: 4.379