Literature DB >> 12234282

RNA expression profiling as prognostic tool in renal patients: toward nephrogenomics.

Michael Eikmans1, Hans J Baelde, Emile de Heer, Jan A Bruijn.   

Abstract

Damage to the kidney generally elicits tissue repair mechanisms, but these processes themselves conversely may result in the progression of chronic renal disease. In a majority of patients chronic renal insufficiency progresses to a common histological end point, marked by the presence of a vast amount of scar tissue, that is, glomerulosclerosis and interstitial fibrosis. These lesions are the result of an excessive production of extracellular matrix (ECM) components. Studies on RNA expression in experimental kidney disease have shown that renal mRNA levels for ECM components and cytokines can function as prognostic tools. This suggests that mRNA levels potentially predict outcome and reaction to therapy in patients with renal diseases. Timely detection of molecular alterations could allow early therapeutic intervention that slows down or even prevents the development of sclerotic and fibrotic lesions. This review first provides a short introduction on mechanisms of initiation and progression of renal disease. Molecular techniques are available to identify renal RNA sequences potentially involved in disease progression. We discuss several molecular techniques that are being used in kidney research for quantitation and detection of mRNA. This is followed by a brief overview of investigation in experimental renal diseases, which reveal that alterations in tissue ECM mRNA levels precede histological damage and can function as predictors of clinical outcome. In particular, studies in human kidney biopsies that evaluate the prognostic value of mRNA levels with respect to renal function are examined, paying special attention to the pitfalls that potentially are encountered when interpreting the results of such studies. Then, we elaborate on ways of optimal exploitation of mRNA quantification as a prognostic tool. The potential and limitations of microarray technology in the search for genes specifically involved in progression of renal disease are reviewed, including RNA expression profiling and large-scale DNA mutation screening. Finally, the future utilities of microarray in nephrology and renal pathology are discussed.

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Year:  2002        PMID: 12234282     DOI: 10.1111/j.1523-1755.2002.kid566.x

Source DB:  PubMed          Journal:  Kidney Int        ISSN: 0085-2538            Impact factor:   10.612


  6 in total

1.  Global gene expression profiling of renal scarring in a rat model of pyelonephritis.

Authors:  Manabu Ichino; Terumi Mori; Mamoru Kusaka; Yoko Kuroyanagi; Kiyohito Ishikawa; Ryoichi Shiroki; Hiroe Kowa; Hiroki Kurahashi; Kiyotaka Hoshinaga
Journal:  Pediatr Nephrol       Date:  2008-01-23       Impact factor: 3.714

2.  Analysis of the gene expression profile of curcumin-treated kidney on endotoxin-induced renal inflammation.

Authors:  Fang Zhong; Hui Chen; Yuanmeng Jin; Shanmai Guo; Weiming Wang; Nan Chen
Journal:  Inflammation       Date:  2013-02       Impact factor: 4.092

3.  Urinary expression of kidney injury markers in renal transplant recipients.

Authors:  Cheuk-Chun Szeto; Bonnie Ching-Ha Kwan; Ka-Bik Lai; Fernand Mac-Moune Lai; Kai-Ming Chow; Gang Wang; Cathy Choi-Wan Luk; Philip Kam-Tao Li
Journal:  Clin J Am Soc Nephrol       Date:  2010-07-29       Impact factor: 8.237

Review 4.  Gene expression in diabetic nephropathy.

Authors:  Daniela Hohenadel; Fokko J van der Woude
Journal:  Curr Diab Rep       Date:  2004-12       Impact factor: 4.810

5.  Current awareness on comparative and functional genomics.

Authors: 
Journal:  Comp Funct Genomics       Date:  2003

6.  Markers of disease and steroid responsiveness in paediatric idiopathic nephrotic syndrome: Whole-transcriptome sequencing of peripheral blood mononuclear cells.

Authors:  Hee Gyung Kang; Heewon Seo; Jae Hyun Lim; Jong Il Kim; Kyoung Hee Han; Hye Won Park; Ja Wook Koo; Kee Hyuck Kim; Ju Han Kim; Hae Il Cheong; Il-Soo Ha
Journal:  J Int Med Res       Date:  2017-01-01       Impact factor: 1.671

  6 in total

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