Literature DB >> 25810360

4D MRI of polycystic kidneys from rapamycin-treated Glis3-deficient mice.

Luke Xie1, Yi Qi, Ergys Subashi, Grace Liao, Laura Miller-DeGraff, Anton M Jetten, G Allan Johnson.   

Abstract

Polycystic kidney disease (PKD) is a life-threatening disease that leads to a grotesque enlargement of the kidney and significant loss of function. Several imaging studies with MRI have demonstrated that cyst size in polycystic kidneys can determine disease severity and progression. In the present study, we found that, although kidney volume and cyst volume decreased with drug treatment, renal function did not improve with treatment. Here, we applied dynamic contrast-enhanced MRI to study PKD in a Glis3 (GLI-similar 3)-deficient mouse model. Cysts from this model have a wide range of sizes and develop at an early age. To capture this crucial stage and assess cysts in detail, we imaged during early development (3-17 weeks) and applied high spatiotemporal resolution MRI (125 × 125 × 125 cubic microns every 7.7 s). A drug treatment with rapamycin (also known as sirolimus) was applied to determine whether disease progression could be halted. The effect and synergy (interaction) of aging and treatment were evaluated using an analysis of variance (ANOVA). Structural measurements, including kidney volume, cyst volume and cyst-to-kidney volume ratio, changed significantly with age. Drug treatment significantly decreased these metrics. Functional measurements of time-to-peak (TTP) mean and TTP variance were determined. TTP mean did not change with age, whereas TTP variance increased with age. Treatment with rapamycin generally did not affect these functional metrics. Synergistic effects of treatment and age were not found for any measurements. Together, the size and volume ratio of cysts decreased with drug treatment, whereas renal function remained the same. The quantification of renal structure and function with MRI can comprehensively assess the pathophysiology of PKD and response to treatment.
Copyright © 2015 John Wiley & Sons, Ltd.

Entities:  

Keywords:  Glis3 protein; MR microscopy; MRI; polycystic kidney disease; small animal preclinical imaging; three-dimensional dynamic contrast-enhanced

Mesh:

Substances:

Year:  2015        PMID: 25810360      PMCID: PMC4400264          DOI: 10.1002/nbm.3281

Source DB:  PubMed          Journal:  NMR Biomed        ISSN: 0952-3480            Impact factor:   4.044


  43 in total

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4.  Four-dimensional MRI of renal function in the developing mouse.

Authors:  Luke Xie; Ergys Subashi; Yi Qi; Mark A Knepper; G Allan Johnson
Journal:  NMR Biomed       Date:  2014-07-26       Impact factor: 4.044

5.  Live nephron imaging by MRI.

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Review 9.  Clinical and laboratory markers of autosomal dominant polycystic kidney disease (ADPKD) progression: an overview.

Authors:  V Corradi; F Gastaldon; G M Virzì; C Caprara; F Martino; C Ronco
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  4 in total

1.  Dynamic contrast-enhanced MRI promotes early detection of toxin-induced acute kidney injury.

Authors:  Jamie R Privratsky; Nian Wang; Yi Qi; Jiafa Ren; Benjamin T Morris; John C Hunting; G Allan Johnson; Steven D Crowley
Journal:  Am J Physiol Renal Physiol       Date:  2018-12-05

2.  High-resolution MRI of kidney microstructures at 7.05 T with an endo-colonic Wireless Amplified NMR detector.

Authors:  Xianchun Zeng; Shuangtao Ma; John M Kruger; Rongpin Wang; Xiaobo Tan; Chunqi Qian
Journal:  J Magn Reson       Date:  2019-04-25       Impact factor: 2.229

Review 3.  GLIS1-3 transcription factors: critical roles in the regulation of multiple physiological processes and diseases.

Authors:  Anton M Jetten
Journal:  Cell Mol Life Sci       Date:  2018-05-19       Impact factor: 9.261

4.  Phenotyping by magnetic resonance imaging nondestructively measures glomerular number and volume distribution in mice with and without nephron reduction.

Authors:  Edwin J Baldelomar; Jennifer R Charlton; Scott C Beeman; Bradley D Hann; Luise Cullen-McEwen; Valeria M Pearl; John F Bertram; Teresa Wu; Min Zhang; Kevin M Bennett
Journal:  Kidney Int       Date:  2016-02       Impact factor: 10.612

  4 in total

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