TECHNIQUES FOR QUANTITATION OF mRNA

Northern blotting has been the standard for detection and quantitation of mRNA levels. The technique is ideal for determining transcript size and for identifying alternatively spliced transcripts; however, two drawbacks of the procedure are that it is laborious and time-consuming. This is primarily due to the amount of time that is necessary for blotting the RNA on a nylon filter and for hybridizing a specific probe to the RNA fixed on the filter. Since Northern blotting is based on a non-amplifying way of mRNA quantification, the procedure has a low sensitivity. For this reason, the technique is suitable only for experiments in which the availability of tissue is not a limiting step, for example, in animal models or in vitro experiments. Another limitation of Northern blotting is the difficulty associated with analysis of multiple transcripts. The ribonuclease protection assay (RPA) is a good technique for simultaneously examining multiple mRNA transcripts (10 to 15) in one sample, and is more sensitive than Northern blotting. The basis of RPA is solution hybridization of an antisense probe to an RNA sample. RPA is even more time-consuming than Northern blotting, and its complex nature in practice limits the analysis to around 20 samples at one time. The technique of RNA in situ hybridization (RISH) is employed to localize specific mRNAs in cells or tissues. The advantage of RISH over other RNA detective techniques is that it provides information about the location of mRNA within the renal tissue. Unlike Northern blot analysis and RPA, RISH does not require the isolation or electrophoretic separation of RNA. However, it is generally accepted that this technique is not quantitative, and also is very time-consuming and laborious.

To test whether in humans the early mRNA elevation of ECM components predicts for the development of chronic renal disease has proven to be a difficult task. This is mainly due to the limited amount of biopsy tissue, the difficulties in isolating intact RNA from minor quantities of tissue, and the lack of both rapid and sensitive ways of quantitative mRNA measurement in small biopsy specimens. Since the amounts of mRNA obtained from minute quantities of renal tissue in clinical practice are below detection levels to be picked up by techniques such as Northern blotting and RPA, investigators have been making use of the reverse-transcriptase polymerase chain reaction (RT-PCR). Quantitative RT-PCR offers a good alternative to reproducibly quantitate mRNA levels^28,29,30. This technique of competitive PCR for measuring mRNA has been widely used in animal experiments and in isolated human glomeruli from native kidneys^31,32,33. The recent development of real-time PCR is a further major contribution to rapid and reliable mRNA measurement in small tissue specimens^34,35. In comparison with the more classical molecular-biological techniques summarized above, real-time PCR is an attractive method of choice in terms of high sample throughput. Despite this advantage, the number of transcripts for which mRNA expression can be measured in one sample by real-time PCR is still limited. For several years, scientists have been making use of techniques such as differential display and subtractive hybridization to screen RNA profiles between samples, and obtain differentially expressed genes. The even more recent arrival of microarray technology offers the possibility to simultaneously measure the RNA expression of thousands of genes in the kidney tissue, as if one obtains the results from thousands of Northern blot experiments at the same time. The potential and limitations of the microarray technique are elaborated upon later in this article. First, a brief outline of experiments shows the potency of levels of mRNA as prognostic tools, both in animal models in human kidney diseases.

ALTERATIONS IN mRNA LEVELS PRECEDE HISTOLOGICAL DAMAGE

Studies in murine chronic graft-versus-host (GvH) disease and chronic serum sickness (CSS) in the rat have particularly focused on the timing of up-regulation of mRNA levels for ECM components in relation to accumulation of the proteins and to the onset of histological damage.

During the course of the GvH disease in the mouse, renal mRNA levels for laminin, collagen 1(IV), and collagen 1(I) have been studied in whole cortex and in glomeruli. mRNA levels for these ECM components are already increased four weeks after the induction of the disease, and they remain elevated during the entire course Figure 1a³⁶. Furthermore, during the first weeks after induction of the disease alterations of the splicing pattern of the V-region of fibronectin occur at the mRNA level³⁷. Six weeks after the induction of the disease, the first signs of increased protein accumulation of the ECM components studied are observed³⁸. At this point, the mice also start developing proteinuria. At ten weeks, focal and segmental glomerulosclerosis is detected, with progression to global glomerulosclerosis between ten and twelve weeks. Further experiments showed that early treatment, coinciding with the time frame in which up-regulation of renal ECM mRNA levels was detected, proved beneficial and led to prevention of glomerulosclerosis³⁹. Administration of cyclosporine at week 6 suppresses the increase of cortical collagen IV and collagen I mRNA levels, and prevents glomerulonephritis and glomerulosclerosis, but only in animals that are not proteinuric at that time³⁹.

Figure 1.

Early elevation of extracellular membrane (ECM) mRNA levels precedes accumulation of ECM protein and the onset of glomerulosclerosis. Symbols are: () collagen a1(IV); () collagen a1(I); () laminin b2. Two animal models were employed: (A) graft versus host (GvH) disease in mice and (B) chronic serum sickness (CSS) in rats. During the course of the diseases, renal RNA levels for several ECM components were measured by Northern blot analysis. These mRNA levels are already increased one month after initiation of the disease. The first signs of accumulation of ECM protein and of histological damage are detected at later stages of the disease. Data are adapted from^36,40,41.

Full figure and legend (28K)

In chronic serum sickness in the rat, glomerular mRNA levels for laminin, collagen 1(IV), collagen 2(IV), and fibronectin peak at five weeks after induction of the disease, but mostly return to normal by week 20 Figure 1b^40,41. Splicing at the V-region of fibronectin is observed in an early phase of the disease³⁷. Only at twenty weeks after induction of the disease, the first signs of ECM accumulation are detected⁴⁰. Between weeks 30 and 35, the kidneys show focal and segmental glomerulosclerosis. In conclusion, the results from these two animal models suggest that mRNA levels for ECM molecules may serve as prognostic tools in a way that changes in mRNA levels detected early in the course of the disease herald alterations at the protein level and histological changes occurring in later stages.

LEVELS OF mRNA AS PREDICTORS FOR RENAL OUTCOME

Molecular-biological research in an animal model for anti-glomerular basement membrane (anti-GBM) disease and in transgenic animals has shown that early levels of mRNA correlate with renal outcome in a later phase of the disease.

Already at day 4 after initiation of anti-GBM disease in rabbits, mRNA levels of collagen 1(I), collagen 1(IV), and TGF- are increased^42,43. Further study in this model showed that levels of collagen 1(I) mRNA measured at day 7 predict for the extent of fibrosis at day 30. The early mRNA levels also predict for the percentage of fibrous crescents at day 30. Most importantly, the predictive power of these mRNA levels is higher than that of serum creatinine levels, urine protein, the extent of glomerular damage, and the extent of interstitial damage, all measured at day 7³³.

Mice transgenic for the bovine growth hormone gene (bGH-tg) show rapidly progressive glomerulosclerosis, whereas mice transgenic for a mutated bGH gene (bGH-m11-tg) show slowly progressive glomerulosclerosis⁴⁴. Between two and three months of age, the increase in glomerular mRNA levels of various cytokines and ECM molecules in bGH-tg mice is approximately twice as high as that in bGH-m11-tg mice. Additional results from experiments in normal mice³¹, non-obese diabetic mice⁴⁵, and bGH-tg mice suggest that the levels of ECM mRNA predict the slope of progression of renal function loss. This slope parallels the increase of ECM mRNA^46,47,48.

Based on the findings in animal models, the hypothesis was put forward that mRNA levels of ECM components might serve as prognostic tools in patients with chronic renal diseases. Three important features, found in animal models, served as the basis for this hypothesis: (1) alterations of mRNA levels for ECM components and ECM-regulating cytokines are detected before a change in ECM protein composition takes place, and before the onset of sclerotic lesions; (2) ECM mRNA levels correlate with the rate of renal disease progression; and (3) early levels of ECM mRNA correlate with the extent of kidney damage in a later phase of the disease.

EVALUATION OF THE PROGNOSTIC VALUE OF RENAL mRNA LEVELS IN HUMANS

A considerable number of studies have made use of quantitative RT-PCR for measuring mRNA levels in glomerular tissue from patients in relation to diagnosis^{49,50,51,52,53}. However, none of these studies have involved the tubulointerstitial compartment in their analyses, or have looked at the potential prognostic value of the mRNA levels.

In recent years, we and others have been trying to find an answer to the question whether mRNA levels of ECM components and TGF- in biopsy tissue have a prognostic value in patients with renal diseases or renal allografts. For this purpose, first the RNA isolation method from minute quantities of microdissected glomerular and tubulointerstitial tissue was improved (abstract; Baelde HJ, J Am Soc Nephrol 12:809A, 2001)^54,55. It was shown that mRNA quantitation is feasible in whole cortex obtained from frozen archival biopsy specimens⁵⁴. This finding corroborates frozen, archival renal tissue as an important source for obtaining proper RNA in future kidney research. In subsequent studies, mRNA levels for collagen IV and collagen I proved to be age-dependent in kidneys without any signs of renal disease⁵⁶. In addition, mRNA levels in a renal biopsy specimen turned out to be representative of those in the entire kidney⁵⁶. These observations are to be taken into account when ECM mRNA levels are used for diagnostic purposes. In a recent study, the RNA isolation technique and real-time PCR method were used to measure mRNA levels of TGF-, collagen IV, collagen I, and decorin in archival tissue from 28 patients with a renal transplant [abstract; Eikmans M et al, J Am Soc Mephrol (in press)]. Eighteen patients retained stable graft function for at least five years (non-progressors), whereas 10 patients lost their grafts to chronic rejection within this period of time (progressors). The main question was whether the mRNA levels measured during early acute rejection within the first six months after transplantation predict for the occurrence of chronic rejection in a later phase after transplantation. The results from this study showed that during the acute rejection episodes the mean mRNA levels for all molecules studied, but in particular those for TGF-Figure 2, were higher in the non-progressors than in the progressors. In conclusion, high mRNA levels for TGF- and ECM molecules during acute rejection are associated with absence of late chronic rejection⁵⁷.

Figure 2.

High transforming growth factor- (TGF-) mRNA levels during early acute rejection are associated with absence of chronic rejection. Cortical TGF- mRNA levels were measured by real-time PCR in biopsies taken during acute rejection episodes within the first six months after transplantation. The "progressors" group (N = 10) shows progressive deterioration of graft function beyond six months, and develops chronic rejection. The "non-progressors" group (N = 18) retains a stable graft function beyond six months for at least five years. mRNA levels are shown relative to the mean mRNA level in the progressor group, which has been set to 1. Data are expressed as means of duplicate measurements (P < 0.05). (Reproduced with permission from Transplantation 73:573–579, 2002.)

Full figure and legend (11K)

Over the last four years we have been collecting fresh biopsy tissue from renal patients who are under clinical surveillance in our hospital center or in surrounding hospitals. Each biopsy was microdissected under stereomicroscopy to separate glomeruli and tubulointerstitium. RNA was isolated from both compartments. Real-time PCR was applied on microdissected biopsy tissue from 52 patients with various renal diseases for the measurement of mRNA levels for TGF-, collagen IV, collagen I, and fibronectin. The glomerular filtration rate (GFR) was determined at the time of biopsy and was followed for one year. The goal was to determine the predictive value of the mRNA levels for the rate of change in renal function of the patients after biopsy (abstract; Eikmans M, J Am Soc Nephrol 12:70A, 2001). The predictive power of the mRNA levels was compared to that of functional parameters and the extent of histological damage at time of biopsy. The findings show that tubulointerstitial TGF- mRNA levels and glomerular fibronectin mRNA levels correlate with the rate of change in renal function between time of biopsy and one month, and between three months and 12 months, respectively [abstract; Eikmans M et al, J Am Soc Nephrol (in press)]. Thus, relatively high mRNA levels for TGF- and fibronectin are associated with a relatively favorable prognosis.

THE ROLE OF TGF-

An interesting, but controversial, result obtained from the studies described above is that relatively high mRNA levels for TGF- and ECM components are associated with a relatively favorable prognosis with respect to renal function of native kidneys and transplanted kidneys. The controversial aspect in this finding lies in the fact that in the literature primarily the role of TGF- in renal scarring has been emphasized. It has been postulated that overproduction or persistent production of TGF- leads to excessive deposition of ECM components, and eventually to scarring of renal tissue^16,17,58,59.

At the same time, it has been recognized that TGF- can exert anti-inflammatory effects and plays an important role in regulation of tissue repair and regeneration after tissue injury. We hypothesize that the beneficial actions of TGF- such as its anti-inflammatory actions or its role in tissue repair explain our findings. Firstly, TGF- has been shown by several investigators to exert anti-inflammatory effects^60,61, and more specifically it has been shown to inhibit B cells, T helper cells, cytotoxic T cells, and macrophages^62,63. Secondly, TGF- regulates ECM expression in relation to tissue repair and remodeling⁶⁴.

Some additional comments on potential pitfalls in the studies described above have to be made. The mRNA levels determined in the biopsies are likely under the influence of many variables, including the type and dose of medication, the time of biopsy, and in the case of the transplantation study, the severity of the acute rejection. Therefore, valuable information would be gained if all biopsies taken within the first six months after transplantation, and the pre-transplant biopsy from each patient were studied. This would establish in a single patient the amount of variation in mRNA levels between different acute rejection episodes. To test the hypothesis that TGF- acts as an immunosuppressant during acute rejection, an analysis of the composition of cellular infiltrates in biopsies in relation to TGF- expression levels would be clarifying. In addition, analysis of TGF- and the ECM components at the protein level by immunohistochemistry would certainly be informative. Finally, the possibility should be taken into account that the presence of high TGF- mRNA levels reflects a higher responsiveness to therapy, and thus a better prognosis in the long term.

OPTIMAL EXPLOITATION OF mRNA LEVELS AS PROGNOSTIC TOOLS

There are some drawbacks in the light of efforts to use tissue mRNA levels as prognostic tools. First, a kidney biopsy is generally taken because of renal dysfunction. Most often, renal biopsies obtained from patients with renal diseases already contain histological abnormalities to such an extent that, even if mRNA levels should be of any prognostic value, therapeutic intervention is only expected to be partially effective at best. In contrast, research in animal models theoretically allows analysis of mRNA levels over the entire period of disease progression. In this case, the detection of early alterations at the mRNA level allows the prevention of sclerosis by therapeutic intervention in an early phase of the disease³⁹. Our study mentioned earlier performed in 52 patients with diverse renal diseases included almost exclusively patients who had been suffering from clinical symptoms already for some time. To render mRNA analysis even more effective as a prognostic tool, it would be ideal to measure mRNA levels in biopsies with normal histology, or at least without chronic lesions.

Secondly, the patients in our studies already received appropriate medication according to standard protocols [abstract; Eikmans M, J Am Soc Nephrol 2000 (in press)]⁵⁷. If accurate, the prediction of who eventually will progress toward chronic damage and who will not by means of mRNA detection would allow for more intensive follow-up of patients at risk for progression, and the use of more aggressive medication during the pre-sclerotic stage to prevent the development of sclerosis and fibrosis. The application of TGF- inhibitors as a molecular approach to intervene early in the development of renal disease, as it was successfully used for attenuation of glomerulonephritis in rats⁶⁵, at the moment seems to be questionable in human renal disease. The studies in patients with renal transplants raise the question whether it would be beneficial, in any stage of acute allograft rejection, to inhibit the actions of TGF-⁵⁷.

Using mRNA levels as prognostic tools would require a baseline measurement in biopsies taken before the onset of any renal scarring whatsoever. A way to tackle this issue would be to perform mRNA measurements in protocolized biopsies, for example in patients with a renal allograft at times of stable renal function, or in patients with systemic diseases [for example, diabetes, systemic lupus erythematosus (SLE), vasculitis] in early stages or remission. To predict the development of diabetic nephropathy, one could consider performing mRNA measurements in biopsies from individuals with diabetes mellitus, having only microscopic albuminuria. At this stage, the biopsy is not expected to show histological abnormalities, and the mRNA levels measured in the tissue may be used to identify the individuals at risk of developing diabetic nephropathy. In this respect, a recent study by Adler and colleagues of mRNA quantitation in biopsy specimens from patients with type I diabetes is worth mentioning⁶⁶. Whereas glomerular mRNA levels of collagen IV and CTGF are twofold higher in microalbuminuric patients compared to normoalbuminuric patients, the degree of glomerular mesangial expansion between the two patient groups did not significantly differ. It would be interesting to see if the levels of mRNA within the microalbuminuric group are associated with the rate of change in renal function or proteinuria after biopsy.

A third drawback when attempting to use tissue mRNA levels as prognostic tools is that taking a renal biopsy is an invasive procedure that is uncomfortable for the patient and occasionally results in a life-threatening complication. Implementation of protocolized biopsies in clinical practice therefore brings along an additional risk for the patient, and it also may result in ethical and, possibly, economic objections. This is the major reason why several research groups investigate the potential diagnostic and prognostic value of mRNA levels determined using noninvasive tests, for example, by performing measurements of mRNA in the urine or in the circulation^67,68. However, there is some skepticism concerning such applications. In particular, the question remains whether these non-invasive tests are as reliable as measurements in a renal biopsy in terms of specificity in relation to the renal disease.

APPLICATION OF MICROARRAY TECHNIQUES FOR RNA PROFILING

The simultaneous RNA expression analysis of a large number of genes is a logical step in elucidating the molecular mechanism that underlies disease initiation and progression. After all, it has been shown in animal models that quantitative changes at the RNA level precede and predict changes at the protein level. The identification of specific genes involved in the onset and progression of renal disease may in the end reveal the most appropriate molecular target for drug intervention.

To study RNA expression profiles in renal cells or tissue at a large scale, investigators have made use of techniques such as cDNA subtractive hybridization, mRNA differential display, and high-density cDNA filter array. Extensive research has focused on the mapping of RNA expression profiles with regard to the development of diabetic nephropathy, in order to find genes that potentially are involved in this process^69,70,71. In these studies, experimental models for diabetes and cell cultures stimulated with high glucose concentrations were used. With similar molecular techniques, gene expression profiles have been obtained in normal human renal cortex⁷², in patients with IgA nephropathy⁷³, and in glomeruli from patients with congenital nephrotic syndrome⁷⁴. Much has been speculated about the recent development of the microarray technique that allows screening of the complete human genome at the mRNA level in one single experiment^75,76,77. This includes the use of customized or commercially produced cDNA microarray chips. The former allows the analysis of smaller subsets of genes within certain fields of research. This was recently described in studies that used arrays containing 250 toxicity-related genes⁷⁸, and cDNA microarray for expression profiling of inflammation-associated genes⁷⁹. With commercially produced microarray chips, approximately 22,000 sets of cDNA molecules, each encoding for a different gene, are printed on an array the size of a thumbnail. The RNA is extracted from the kidney tissue, labeled with a fluorescent dye, and allowed to hybridize with the cDNA printed on the array. Thus, the amount of RNA hybridized to the array can be used as a measure for the amount of mRNA of singular transcripts present in the RNA sample. Analysis and management of microarray data are currently difficulties in application of the technology. This includes gene clustering and prediction of gene function^80,81.

More recently, microarray technology was used to identify specific gene expression patterns in various types of tissues other than renal cortex as well. Classification of subsets of tumors on the basis of RNA expression profiles might have major implications for assessing prognosis and establish medication tuned to the individual patient. For example, large-scale gene expression profiling has been used in diagnostic tumor specimens from patients with diffuse large B-cell lymphoma⁸². A small subset of genes was differentially-expressed between patients with a relatively favorable prognosis and those with a relatively unfavorable prognosis. These so-called marker genes predicted clinical outcome better than histological alterations in the tissue. Another example is the use of microarray in identifying high-risk breast cancer patients. In a large group of patients with a breast tumor, a subset of marker genes predicted a high risk of relapse of the disease and the occurrence of distant metastases⁸³.

SCREENING OF DNA MUTATIONS AND GENE POLYMORPHISMS

In a number of diseases including kidney disorders, mutations occurring in the DNA have important implications for prognosis and therapy. Techniques such as restriction fragment length polymorphism (RFLP) and single-strand conformation polymorphism (SSCP) have been used for detection of genetic alterations. The screening of all possible mutations in one gene using such approaches is mostly cumbersome. The use of microarray technology for large-scale screening of mutations and gene polymorphisms might be the solution, and this has already been initiated in cancer research. Mutations in the BRCA1 gene may place individuals at risk of developing breast and ovarian cancer. High-density arrays consisting of over 96,000 oligonucleotides were employed to screen for heterozygous mutations in BRCA1⁸⁴. Another example is the employment of microchip analysis for mutation screening in patient samples in the cystic fibrosis gene⁸⁵.

Individual profiling of DNA patterns also might be an approach to the identification of individuals at risk for developing progressive renal disease. It is generally believed that a genetic component is involved in the development of many renal diseases. Several examples in which mutations in a single gene or a chromosome region lead to renal dysfunction have appeared recently in the literature. For instance, mutations in the NPHS1 gene are the cause of the congenital nephrotic syndrome⁸⁶. This autosomal recessive disorder is accompanied by the absence of nephrin from the slit pore diaphragm of the kidney⁸⁷, and, consequently, by the presence of heavy proteinuria. Both for IgA nephropathy and diabetes mellitus, the most common causes worldwide of progressive renal failure leading to ESRD, a genetic component has been described. Familial IgA nephropathy was linked to chromosome 6⁸⁸. Two chromosome regions show association with, and linkage to type I diabetes: the HLA region and the insulin region⁸⁹. The application of microarray technology, especially in individuals from families in which renal diseases occur frequently, could be useful in the detection of specific gene mutations that may lead to progressive renal disease.

In the past years, investigation of single nucleotide polymorphisms (SNPs) in relation to disease occurrence and susceptibility has gained considerable attention. One can think of the occurrence of gene polymorphisms in the DNA leading to alterations of amino acids, and thereby in altered functionality of the gene protein product. In addition, polymorphisms in the promoter region of a gene might have influence on the rate of mRNA transcription of this gene. In renal allografts, gene polymorphism in the proinflammatory cytokines TNF- and IL-10 has been associated with the occurrence of acute rejection⁹⁰. Similarly, genotypic variations in the TGF- gene have been described in relation to the occurrence of renal failure^91,92,93. Polymorphisms in the angiotensin I gene and angiotensin-converting enzyme gene have been characterized in relation to progression of renal disease^94,95,96,97. Microarray techniques might be suitable for large-scale screening of SNPs in candidate genes analyzed in DNA extracted from blood samples of patients with renal diseases. SNP analysis could be performed with the aid of probes hybridizing to relatively short oligonucleotides printed on the arrays. The fact that such analyses can be done in blood samples is to the advantage of studies in renal biopsy tissue in terms of restriction of inconvenience for the patient and timing of sampling.

FUTURE UTILITIES OF MICROARRAY TECHNOLOGY IN NEPHROLOGY: TOWARD NEPHROGENOMICS

In kidney research, microarray gene profiling might be used in similar ways as currently performed in cancer research. Simultaneous RNA expression profiling of thousands of genes in biopsy tissue from patients with kidney diseases might identify shared gene expression patterns involved in development and progression of renal disorders. This eventually opens the way to aimed therapy for the individual patient. Currently a limitation of the microarray technique is that still relatively large amounts of RNA, in general at least 10 g, are needed for hybridization. In cancer research, the tumor samples from patients are often large enough for obtaining individual expression profiles by array analysis. However, the yield of RNA from renal specimens is considerably lower than the amount of RNA needed for hybridization on current arrays. At the moment, this excludes the possibility of application of microarray in individual renal patients. Recent breakthroughs in nanotechnological research may enable the use of even smaller array chips in the near future, which need far less RNA for proper hybridization than the current microarray chips^98,99.

One solution to the problem that a singular biopsy specimen contains too little RNA for a microarray experiment would be pooling the RNA from multiple biopsies. Currently, experiments are on the way using the microarray technique on RNA obtained from diseased native and transplanted kidneys. As an example, Figure 3 shows the hybridization signals of two patient groups having a renal transplant. RNA was obtained from renal allograft biopsies from patients with acute rejection within six months after transplantation. Part of the patients progressed to chronic rejection within a few years (progressors), whereas the other patients retained a stable graft function during the same time period (non-progressors). To identify differentially expressed genes between progressors and non-progressors, microarray analysis was performed on pooled RNA samples from the two patient groups Figure 3. The red and blue dots that lie the furthest from their corresponding cluster represent RNA encoding for molecules that are differentially expressed between the two samples. These molecules are of particular interest, since they might play a role in progression of allograft damage. The results of this study will be described in detail in a forthcoming paper (Eikmans et al, manuscript in preparation).

Figure 3.

Microarray analysis of approximately 12,000 genes in renal transplant biopsies with acute rejection. RNA was pooled from biopsies obtained from two groups of at least ten patients One group of patients eventually develops chronic rejection within a few years (A; progressors). The other group retains a stable graft function for at least five years (B; non-progressors). A and B show part of the arrays after hybridization and scanning for both patient groups. (C) Each dot in the graph represents the hybridization signal of a single gene. The horizontal and vertical axes depict the intensity (logarithmic scale) of the genes in the progressor and non-progressor groups, respectively. Yellow dots: intensity is below threshold level in both groups. Blue dots: intensity is below threshold level in one of the groups. Red dots: high intensity in both groups.

Full figure and legend (79K)

We envision that the results from genetic linkage analyses in families with hereditary kidney disease, and from microarray application on bulk amounts of kidney tissue from single cases or on pooled samples from multiple cases will cut back the number of key genes involved in the development of kidney disease. This will eventually lead to the development of designer chips containing a limited set of kidney disease-specific candidate genes, which need further testing in large patient groups. At the same time, one could think of performing in DNA samples large-scale SNP analyses of candidate genes that previously have come up in the microarray analyses on the basis of their RNA expression. The very challenge at the moment in microarray application is not so much the practical procedure of the technique itself, but rather the interpretation and processing of the data. One needs to be cautious not to drown in the amount of data generated from experiments with microchips. It is tempting to interpret the microarray data within an established framework of current knowledge from nephrological research, focusing especially on genes that already have been described in literature to play a role in renal disease. Rather, of particular interest are those genes that appear at the top of the list, despite the fact that they at first seem inexplicable in relation to renal pathology. Such genes need to be further tested for their plausibility by measuring their expression in biopsy samples from large sets of patients with the aid of real-time PCR and immunohistochemistry. In the years ahead, data management and data processing will have to keep up with the continuous flow of microarray data that is being generated. In particular, the linkage of results from different public databases could identify specific molecular pathways involved in renal pathology, establishing specific molecular targets for drug intervention in kidney disease.

CONCLUSION

Progression of chronic renal disease is associated with a decrease in renal function and an accumulation of ECM components, directed by the actions of cytokines. Investigators have been making use of different molecular techniques to measure mRNA expression levels in renal tissue, each with their own advantages and limitations. Experiments in animal models show that mRNA levels for ECM components can be used to predict renal outcome. Correspondingly, evidence has been found that mRNA levels assessed in biopsy specimens can be used to predict patient prognosis with respect to renal function. Early findings show that increased levels of TGF- mRNA and ECM mRNA are associated with a favorable prognosis after kidney transplantation and in native kidneys. This suggests that the immunosuppressive and repairing actions of TGF- prevail over their profibrotic effects. Although the results concerning the evaluation of mRNA levels in renal biopsies as prognostic tools are promising, further studies in larger patient groups strengthening these findings are mandatory. The simultaneous profiling of thousands of mRNA transcripts in a sample could identify marker genes that discriminate progressors from non-progressors. In cancer research, microarray technology has already proved to be suitable for such applications. Microarray can be applied in renal pathology for similar purposes and opens up the way to a more efficient search for new diagnostic and prognostic markers in clinical nephrology. The use of microarray and nanoarray technology for RNA expression profiling and DNA mutation screening in patients with renal disease might identify subsets of key genes involved in disease progression. This could reveal new molecular targets and pathways for therapeutic intervention in future renal medicine. In the years to come, the utilization of new approaches and improvement of existing approaches to molecular analyses may contribute to the validation of the use of renal gene expression profiles as prognostic tools for the individual patient with a renal disorder.

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Acknowledgments

This work was supported by the Dutch 'Praeventiefonds'/Zorgonderzoek Nederland (Grant 28-2184-1). During the World Congress of Nephrology in 2001, Dr. M. Eikmans received the Young Investigator award from the Renal Pathology Society for parts of the studies described in this article. The authors thank Dr. I.M. Bajema for critically reading the manuscript.