Assessment and Risk Prediction of Chronic Kidney Disease and Kidney Fibrosis Using Non-Invasive Biomarkers.

Effective management of chronic kidney disease (CKD), a major health problem worldwide, requires accurate and timely diagnosis, prognosis of progression, assessment of therapeutic efficacy, and, ideally, prediction of drug response. Multiple biomarkers and algorithms for evaluating specific aspects of CKD have been proposed in the literature, many of which are based on a small number of samples. Based on the evidence presented in relevant studies, a comprehensive overview of the different biomarkers applicable for clinical implementation is lacking. This review aims to compile information on the non-invasive diagnostic, prognostic, and predictive biomarkers currently available for the management of CKD and provide guidance on the application of these biomarkers. We specifically focus on biomarkers that have demonstrated added value in prospective studies or those based on prospectively collected samples including at least 100 subjects. Published data demonstrate that several valid non-invasive biomarkers of potential value in the management of CKD are currently available.

Non-Invasive Biomarkers for Diagnosis, Risk Prediction, and Therapy Guidance of Glomerular Kidney Diseases: A Comprehensive Review.

Effective management of glomerular kidney disease, one of the main categories of chronic kidney disease (CKD), requires accurate diagnosis, prognosis of progression, assessment of therapeutic efficacy, and, ideally, prediction of drug response. Multiple biomarkers and algorithms for the assessment of specific aspects of glomerular diseases have been reported in the literature. Though, the vast majority of these have not been implemented in clinical practice or are not available on a global scale due to limited access, missing medical infrastructure, or economical as well as political reasons. The aim of this review is to compile all currently available information on the diagnostic, prognostic, and predictive biomarkers currently available for the management of glomerular diseases, and provide guidance on the application of these biomarkers. As a result of the compiled evidence for the different biomarkers available, we present a decision tree for a non-invasive, biomarker-guided diagnostic path. The data currently available demonstrate that for the large majority of patients with glomerular diseases, valid biomarkers are available. However, despite the obvious disadvantages of kidney biopsy, being invasive and not applicable for monitoring, especially in the context of rare CKD etiologies, kidney biopsy still cannot be replaced by non-invasive strategies.

Differentiating primary and secondary FSGS using non-invasive urine biomarkers.

Background: Focal segmental glomerulosclerosis (FSGS) is divided into genetic, primary (p), uncertain cause, and secondary (s) forms. The subclasses differ in management and prognosis with differentiation often being challenging. We aimed to identify specific urine proteins/peptides discriminating between clinical and biopsy-proven pFSGS and sFSGS. Methods: Sixty-three urine samples were collected in two different centers (19 pFSGS and 44 sFSGS) prior to biopsy. Samples were analysed using capillary electrophoresis-coupled mass spectrometry. For biomarker definition, datasets of age-/sex-matched normal controls (NC, n = 98) and patients with other chronic kidney diseases (CKDs, n = 100) were extracted from the urinary proteome database. Independent specificity assessment was performed in additional data of NC (n = 110) and CKD (n = 170). Results: Proteomics data from patients with pFSGS were first compared to NC (n = 98). This resulted in 1179 biomarker (P < 0.05) candidates. Then, the pFSGS group was compared to sFSGS, and in a third step, pFSGS data were compared to data from different CKD etiologies (n = 100). Finally, 93 biomarkers were identified and combined in a classifier, pFSGS93. Total cross-validation of this classifier resulted in an area under the receiving operating curve of 0.95. The specificity investigated in an independent set of NC and CKD of other etiologies was 99.1% for NC and 94.7% for CKD, respectively. The defined biomarkers are largely fragments of different collagens (49%). Conclusion: A urine peptide-based classifier that selectively detects pFSGS could be developed. Specificity of 95%-99% could be assessed in independent samples. Sensitivity must be confirmed in independent cohorts before routine clinical application.

Urinary peptidomic liquid biopsy for non-invasive differential diagnosis of chronic kidney disease.

BACKGROUND AND HYPOTHESIS: Specific urinary peptides hold information on disease pathophysiology, which, in combination with artificial intelligence, could enable non-invasive assessment of chronic kidney disease (CKD) aetiology. Existing approaches are generally specific for the diagnosis of single aetiologies. We present the development of models able to simultaneously distinguish and spatially visualize multiple CKD aetiologies. METHODS: The urinary peptide data of 1850 healthy control (HC) and CKD [diabetic kidney disease (DKD), immunoglobulin A nephropathy (IgAN) and vasculitis] participants were extracted from the Human Urinary Proteome Database. Uniform manifold approximation and projection (UMAP) coupled to a support vector machine algorithm was used to generate multi-peptide models to perform binary (DKD, HC) and multiclass (DKD, HC, IgAN, vasculitis) classifications. This pipeline was compared with the current state-of-the-art single-aetiology CKD urinary peptide models. RESULTS: In an independent test set, the developed models achieved 90.35% and 70.13% overall predictive accuracies, respectively, for the binary and the multiclass classifications. Omitting the UMAP step led to improved predictive accuracies (96.14% and 85.06%, respectively). As expected, the HC class was distinguished with the highest accuracy. The different classes displayed a tendency to form distinct clusters in the 3D space based on their disease state. CONCLUSION: Urinary peptide data present an effective basis for CKD aetiology differentiation using machine learning models. Although adding the UMAP step to the models did not improve prediction accuracy, it may provide a unique visualization advantage. Additional studies are warranted to further validate the pipeline's clinical potential as well as to expand it to other CKD aetiologies and also other diseases.

Microangiopathy in multiple myeloma: a case of carfilzomib-induced secondary thrombotic microangiopathy successfully treated with plasma exchange and complement inhibition.

BACKGROUND: Thrombotic microangiopathy (TMA) is a potentially organ and life-threatening condition affecting patients with multiple myeloma (MM). Cases of proteasome inhibitor-induced TMA and specifically carfilzomib-induced TMA have been rarely reported and standards for diagnostic workup and treatment are not available. CASE PRESENTATION: We describe a case of a male MM patient under salvage therapy including proteasome inhibitor carfilzomib following chemotherapy and autologous stem cell transplantation. The patient then developed acute kidney injury with clinical and laboratory signs of TMA. Hemodialysis became necessary and treatment with plasma exchange was initiated followed by therapy with C5 complement inhibitor eculizumab which led to amelioration of kidney function and hemolysis parameters. CONCLUSION: We report a patient with suspected proteasome inhibitor-induced secondary thrombotic microangiopathy that has been successfully treated with plasma exchange and eculizumab, a monoclonal antibody targeting complement factor C5.

Recent Advances in Urinary Peptide and Proteomic Biomarkers in Chronic Kidney Disease: A Systematic Review.

Biomarker development, improvement, and clinical implementation in the context of kidney disease have been a central focus of biomedical research for decades. To this point, only serum creatinine and urinary albumin excretion are well-accepted biomarkers in kidney disease. With their known blind spot in the early stages of kidney impairment and their diagnostic limitations, there is a need for better and more specific biomarkers. With the rise in large-scale analyses of the thousands of peptides in serum or urine samples using mass spectrometry techniques, hopes for biomarker development are high. Advances in proteomic research have led to the discovery of an increasing amount of potential proteomic biomarkers and the identification of candidate biomarkers for clinical implementation in the context of kidney disease management. In this review that strictly follows the PRISMA guidelines, we focus on urinary peptide and especially peptidomic biomarkers emerging from recent research and underline the role of those with the highest potential for clinical implementation. The Web of Science database (all databases) was searched on 17 October 2022, using the search terms "marker *" OR biomarker * AND "renal disease" OR "kidney disease" AND "proteome *" OR "peptid *" AND "urin *". English, full-text, original articles on humans published within the last 5 years were included, which had been cited at least five times per year. Studies based on animal models, renal transplant studies, metabolite studies, studies on miRNA, and studies on exosomal vesicles were excluded, focusing on urinary peptide biomarkers. The described search led to the identification of 3668 articles and the application of inclusion and exclusion criteria, as well as abstract and consecutive full-text analyses of three independent authors to reach a final number of 62 studies for this manuscript. The 62 manuscripts encompassed eight established single peptide biomarkers and several proteomic classifiers, including CKD273 and IgAN237. This review provides a summary of the recent evidence on single peptide urinary biomarkers in CKD, while emphasizing the increasing role of proteomic biomarker research with new research on established and new proteomic biomarkers. Lessons learned from the last 5 years in this review might encourage future studies, hopefully resulting in the routine clinical applicability of new biomarkers.

Predictive performance and clinical application of COV50, a urinary proteomic biomarker in early COVID-19 infection: a prospective multicentre cohort study.

BACKGROUND: The SARS-CoV-2 pandemic is a worldwide challenge. The CRIT-CoV-U pilot study generated a urinary proteomic biomarker consisting of 50 peptides (COV50), which predicted death and disease progression from SARS-CoV-2. After the interim analysis presented for the German Government, here, we aimed to analyse the full dataset to consolidate the findings and propose potential clinical applications of this biomarker. METHODS: CRIT-CoV-U was a prospective multicentre cohort study. In eight European countries (Austria, France, Germany, Greece, North Macedonia, Poland, Spain, and Sweden), 1012 adults with PCR-confirmed COVID-19 were followed up for death and progression along the 8-point WHO scale. Capillary electrophoresis coupled with mass spectrometry was used for urinary proteomic profiling. Statistical methods included logistic regression and receiver operating characteristic curve analysis with a comparison of the area under curve (AUC) between nested models. Hospitalisation costs were derived from the care facility corresponding with the Markov chain probability of reaching WHO scores ranging from 3 to 8 and flat-rate hospitalisation costs adjusted for the gross per capita domestic product of each country. FINDINGS: From June 30 to Nov 19, 2020, 228 participants were recruited, and from April 30, 2020, to April 14, 2021, 784 participants were recruited, resulting in a total of 1012 participants. The entry WHO scores were 1-3 in 445 (44%) participants, 4-5 in 529 (52%) participants, and 6 in 38 (4%) participants; and of all participants, 119 died and 271 had disease progression. The odds ratio (OR) associated with COV50 in all 1012 participants for death was 2·44 (95% CI 2·05-2·92) unadjusted and 1·67 (1·34-2·07) when adjusted for sex, age, BMI, comorbidities, and baseline WHO score; and for disease progression, the OR was 1·79 (1·60-2·01) when unadjusted and 1·63 (1·41-1·91) when adjusted (p<0·0001 for all). The predictive accuracy of the optimised COV50 thresholds was 74·4% (71·6-77·1%) for mortality (threshold 0·47) and 67·4% (64·4-70·3%) for disease progression (threshold 0·04). When adjusted for covariables and the baseline WHO score, these thresholds improved AUCs from 0·835 to 0·853 (p=0·033) for death and from 0·697 to 0·730 (p=0·0008) for progression. Of 196 participants who received ambulatory care, 194 (99%) did not reach the 0·04 threshold. The cost reductions associated with 1 day less hospitalisation per 1000 participants were million Euro (M€) 0·887 (5-95% percentile interval 0·730-1·039) in participants at a low risk (COV50 <0·04) and M€2·098 (1·839-2·365) in participants at a high risk (COV50 ≥0·04). INTERPRETATION: The urinary proteomic COV50 marker might be predictive of adverse COVID-19 outcomes. Even in people with mild-to-moderate PCR-confirmed infections (WHO scores 1-4), the 0·04 COV50 threshold justifies earlier drug treatment, thereby potentially reducing the number of days in hospital and associated costs. FUNDING: German Federal Ministry of Health.

Molecular Mapping of Urinary Complement Peptides in Kidney Diseases.

Defective complement activation has been associated with various types of kidney disease. This led to the hypothesis that specific urine complement fragments may be associated with kidney disease etiologies, and disease progression may be reflected by changes in these complement fragments. We investigated the occurrence of complement fragments in urine, their association with kidney function and disease etiology in 16,027 subjects, using mass spectrometry based peptidomics data from the Human Urinary Proteome/Peptidome Database. Twenty-three different urinary peptides originating from complement proteins C3, C4 and factor B (CFB) could be identified. Most C3-derived peptides showed inverse association with estimated glomerular filtration rate (eGFR), while the majority of peptides derived from CFB demonstrated positive association with eGFR. Several peptides derived from the complement proteins C3, C4 and CFB were found significantly associated with specific kidney disease etiologies. These peptides may depict disease-specific complement activation and could serve as non-invasive biomarkers to support development of complement interventions through assessing complement activity for patients' stratification and monitoring of drug impact. Further investigation of these complement peptides may provide additional insight into disease pathophysiology and could possibly guide therapeutic decisions, especially when targeting complement factors.

[KDIGO 2021 guideline glomerulonephritis - focus on ANCA-associated vasculitides and anti-glomerular basement membrane glomerulonephritis]. / KDIGO-Leitlinien 2021 zur Glomerulonephritis ­ Focus ANCA-assoziierte Vaskulitiden und antiglomeruläre Basalmembran-Nephritis.

In 2021 new KDIGO (Kidney Disease: Improving Global Outcomes) guidelines for the management of glomerular diseases were published.For ANCA-associated glomerulonephritis the new recommendations comprise a more rapid steroid taper during induction treatment with cyclophosphamide or rituximab, the advice against routine use of plasma exchange, the choice of drug for and duration of maintenance treatment in accordance with predictors of relapse. A kidney transplant should be performed after at least 6 months of remission irrespective of the ANCA titer in ANCA-associated disease, and 6 months after absence of anti-GBM-antibodies in anti-GBM-disease.

A Novel Urinary Proteomics Classifier for Non-Invasive Evaluation of Interstitial Fibrosis and Tubular Atrophy in Chronic Kidney Disease.

Non-invasive urinary peptide biomarkers are able to detect and predict chronic kidney disease (CKD). Moreover, specific urinary peptides enable discrimination of different CKD etiologies and offer an interesting alternative to invasive kidney biopsy, which cannot always be performed. The aim of this study was to define a urinary peptide classifier using mass spectrometry technology to predict the degree of renal interstitial fibrosis and tubular atrophy (IFTA) in CKD patients. The urinary peptide profiles of 435 patients enrolled in this study were analyzed using capillary electrophoresis coupled with mass spectrometry (CE-MS). Urine samples were collected on the day of the diagnostic kidney biopsy. The proteomics data were divided into a training (n = 200) and a test (n = 235) cohort. The fibrosis group was defined as IFTA ≥ 15% and no fibrosis as IFTA < 10%. Statistical comparison of the mass spectrometry data enabled identification of 29 urinary peptides with differential occurrence in samples with and without fibrosis. Several collagen fragments and peptide fragments of fetuin-A and others were combined into a peptidomic classifier. The classifier separated fibrosis from non-fibrosis patients in an independent test set (n = 186) with area under the curve (AUC) of 0.84 (95% CI: 0.779 to 0.889). A significant correlation of IFTA and FPP_BH29 scores could be observed Rho = 0.5, p < 0.0001. We identified a peptidomic classifier for renal fibrosis containing 29 peptide fragments corresponding to 13 different proteins. Urinary proteomics analysis can serve as a non-invasive tool to evaluate the degree of renal fibrosis, in contrast to kidney biopsy, which allows repeated measurements during the disease course.

Adverse Drug Events in Patients with Chronic Kidney Disease Associated with Multiple Drug Interactions and Polypharmacy.

BACKGROUND AND PURPOSE: Chronic kidney disease (CKD) is associated with adverse drug events due to medication errors and the risks of polypharmacy. The aim of this study was to investigate whether multiple pharmacodynamic interactions are a significant problem in CKD patients to improve medication safety. METHODS: The discharge medication of 200 elderly patients with stage 3, 4 and 5/5D CKD was analysed in a retrospective observational study with respect to kidney-related medication errors and multiple pharmacodynamic interactions. The clinical relevance of the most common and hazardous multiple interactions was assessed by evaluating adverse events at the primary or the subsequent hospital stay. RESULTS: Findings showed that 29.5% of the study cohort were at risk of QTc-interval prolongation in association with their medication combinations and half of them exhibited QTc-interval prolongation. The QTc interval was extended among all patients receiving a combination of two or more drugs with 'known' risk of Torsades de pointes. Amiodarone, citalopram and ciprofloxacin turned out to be the most hazardous drugs in this context. Eight percent of the patient population received a regimen of 4-6 potassium-enhancing drugs during their hospital stay, which was not de-escalated in 75.0% in the ambulatory setting. Despite close monitoring in the clinical setting, 37.5% of these patients developed hyperkalaemic episodes during their primary stay and 66.7% during rehospitalization. Of the study cohort, 8.5% received a combination of three drugs with antithrombotic or antiplatelet effects. Of these, 64.7% developed haemorrhagic events with two of them proving fatal. CONCLUSION: Multiple pharmacodynamic interactions related to QTc prolongation, hyperkalaemia and haemorrhage are frequently associated with a negative outcome in older adults with CKD and often require recurrent medical treatment or rehospitalization.

Noninvasive diagnosis of chronic kidney diseases using urinary proteome analysis.

BACKGROUND: In spite of its invasive nature and risks, kidney biopsy is currently required for precise diagnosis of many chronic kidney diseases (CKDs). Here, we explored the hypothesis that analysis of the urinary proteome can discriminate different types of CKD irrespective of the underlying mechanism of disease. METHODS: We used data from the proteome analyses of 1180 urine samples from patients with different types of CKD, generated by capillary electrophoresis coupled to mass spectrometry. A set of 706 samples served as the discovery cohort, and 474 samples were used for independent validation. For each CKD type, peptide biomarkers were defined using statistical analysis adjusted for multiple testing. Potential biomarkers of statistical significance were combined in support vector machine (SVM)-based classifiers. RESULTS: For seven different types of CKD, several potential urinary biomarker peptides (ranging from 116 to 619 peptides) were defined and combined into SVM-based classifiers specific for each CKD. These classifiers were validated in an independent cohort and showed good to excellent accuracy for discrimination of one CKD type from the others (area under the receiver operating characteristic curve ranged from 0.77 to 0.95). Sequence analysis of the biomarkers provided further information that may clarify the underlying pathophysiology. CONCLUSIONS: Our data indicate that urinary proteome analysis has the potential to identify various types of CKD defined by pathological assessment of renal biopsies and current clinical practice in general. Moreover, these approaches may provide information to model molecular changes per CKD.

"Vodka energy": too much for the adolescent nephron?

We report here the case of a 17-year-old boy who suffered acute renal failure after consuming 3 L of energy drink (ED) in combination with 1 L of vodka amounting to 4600 mg of taurine and 780 mg of caffeine mixed with 380 g of alcohol. The consumption of this mixture is extremely popular in adolescents, because the joint effects of caffeine and taurine reduce the effect of alcohol. Although there have been case reports of deaths linked to the consumption of EDs with and without alcohol, awareness of the possible dangers is still low. The fact that athletes and major sports events are sponsored by ED manufacturers implies that they may even be healthy and performance-enhancing.

Naturally occurring human urinary peptides for use in diagnosis of chronic kidney disease.

Because of its availability, ease of collection, and correlation with physiology and pathology, urine is an attractive source for clinical proteomics/peptidomics. However, the lack of comparable data sets from large cohorts has greatly hindered the development of clinical proteomics. Here, we report the establishment of a reproducible, high resolution method for peptidome analysis of naturally occurring human urinary peptides and proteins, ranging from 800 to 17,000 Da, using samples from 3,600 individuals analyzed by capillary electrophoresis coupled to MS. All processed data were deposited in an Structured Query Language (SQL) database. This database currently contains 5,010 relevant unique urinary peptides that serve as a pool of potential classifiers for diagnosis and monitoring of various diseases. As an example, by using this source of information, we were able to define urinary peptide biomarkers for chronic kidney diseases, allowing diagnosis of these diseases with high accuracy. Application of the chronic kidney disease-specific biomarker set to an independent test cohort in the subsequent replication phase resulted in 85.5% sensitivity and 100% specificity. These results indicate the potential usefulness of capillary electrophoresis coupled to MS for clinical applications in the analysis of naturally occurring urinary peptides.

Identification and validation of urinary biomarkers for differential diagnosis and evaluation of therapeutic intervention in anti-neutrophil cytoplasmic antibody-associated vasculitis.

Renal activity and smoldering disease is difficult to assess in anti-neutrophil cytoplasmic antibody-associated vasculitis (AAV) because of renal scarring. Even repeated biopsies suffer from sampling errors in this focal disease especially in patients with chronic renal insufficiency. We applied capillary electrophoresis coupled to mass spectrometry toward urine samples from patients with active renal AAV to identify and validate urinary biomarkers that enable differential diagnosis of disease and assessment of disease activity. The data were compared with healthy individuals, patients with other renal and non-renal diseases, and patients with AAV in remission. 113 potential biomarkers were identified that differed significantly between active renal AAV and healthy individuals and patients with other chronic renal diseases. Of these, 58 could be sequenced. Sensitivity and specificity of models based on 18 sequenced biomarkers were validated using blinded urine samples of 40 patients with different renal diseases. Discrimination of AAV from other renal diseases in blinded samples was possible with 90% sensitivity and 86.7-90% specificity depending on the model. 10 patients with active AAV were followed for 6 months after initiation of treatment. Immunosuppressive therapy led to a change of the proteome toward "remission." 47 biomarkers could be sequenced that underwent significant changes during therapy together with regression of clinical symptoms, normalization of C-reactive protein, and improvement of renal function. Proteomics analysis with capillary electrophoresis-MS represents a promising tool for fast identification of patients with active AAV, indication of renal relapses, and monitoring for ongoing active renal disease and remission without renal biopsy.

Assessment of renal vasoconstriction in vivo after intra-arterial administration of the isosmotic contrast medium iodixanol compared to the low-osmotic contrast medium iopamidol.

BACKGROUND: Low-osmotic contrast media (LOCM) such as iopamidol are known to increase the renal resistance index (RRI). The aim of our study was to evaluate in vivo the different effects of intra-arterial administration of LOCM in comparison to isosmotic contrast medium (IOCM) such as iodixanol on the human RRI. METHODS: Twenty patients (16 males, 4 females; 66 years on average) with normal renal function (mean creatinine 1.0 mg/dl) had digital subtraction angiography (DSA) of the abdominal and lower-limb arteries. Ten patients received LOCM, and 10 patients IOCM (150 ml on average, 20 ml/s). The RRI was assessed by an experienced nephrologist with duplex ultrasound from 15 min before until 30 min after the first injection with delays of 1-5 min. The basic value of the RRI and differential RRI were calculated. RESULTS: The basic value of the RRI was 0.69 in the LOCM group and 0.71 in the IOCM group. After LOCM a significant increase of the RRI to 0.73 on average (P < or = 0.001) 2 min after the first injection was found, whereas IOCM did not result in a significant change of the RRI (RRI remained 0.71 on average, P > or = 0.1). In the LOCM group, the RRI returned to the basic value after 30 min (+/-2.3 min). CONCLUSIONS: Intra-arterial administration of IOCM had no influence on renal vascular resistance as expressed by the RRI, unlike LOCM, which induced a highly significant increase of the RRI for up to 30 min.

Angiopoietin 1 and 2 gene and protein expression is differentially regulated in acute anti-Thy1.1 glomerulonephritis.

Capillary neoformation is important in repair of glomerular injury of various origins. VEGF was shown to be crucial for glomerular capillary repair in glomerulonephritis (GN). We reasoned that other angiogenic factors are likewise involved in glomerular capillary remodeling and found angiopoietin 1 and -2 (ANG1 and ANG2) mRNA to be upregulated in cDNA microarrays of microdissected glomeruli of anti-Thy1.1 GN of the rat. We then studied glomerular in situ gene and protein expression of ANG1 and ANG2 and their receptor Tie-2 in the course of anti-Thy1.1 GN, which was induced by injection of OX-7 antibody. Animals were perfusion fixed at days 6 and 12 after GN induction and compared with nonnephritic controls receiving PBS. Capillary damage and repair were quantitatively analyzed using stereological techniques. Gene and protein expression of ANG1 and ANG2 and their receptor Tie-2 was analyzed using real-time quantitative PCR from microdissected glomeruli, nonradioactive in situ hybridization, double immunofluorescence, and Western blot analysis. Glomerular capillarization assessed as length density was significantly lower at day 6 of anti-Thy1.1 GN than in controls; it was back to normal values at day 12. ANG1 and ANG2 gene expression was markedly upregulated at day 6 of the disease compared with controls. Protein expression of ANG1 and ANG2 was confined to podocytes and that of Tie-2 to endothelial cells. At day 12 of anti-Thy1.1 GN when capillary restoration was nearly completed, ANG1 and ANG2 gene expression returned to basal levels, whereas Tie-2 expression was still high. With the use of a combined molecular and in situ approach, the spatial and temporal gene and protein expression of the angiopoietins and their receptor was analyzed in anti-Thy1.1 GN. The results indicate that glomerular expression of ANG1 and ANG2 and Tie-2 is differentially regulated and may contribute to healing and endothelial cell stabilization in experimental GN.

Nitric oxide modulates expression of extracellular matrix genes linked to fibrosis in kidney mesangial cells.

Mesangial cells are thought to be important mediators of glomerular inflammation and fibrosis. Studies have established a direct role for nitric oxide (NO) in the regulation of gene expression in mesangial cells. Representational difference analysis was used to investigate changes in gene expression elicited by the treatment of S-nitroso-L-glutathione in rat mesangial cells. Seven upregulated and 11 downregulated genes were identified. Four out of 11 downregulated genes (connective tissue growth factor, thrombospondin-1, collagen type I alpha1 and collagen type I alpha2) are known to be linked to inflammation and fibrosis. Results were verified across species in mesangial cells treated with a series of NO donors using Northern blot analysis, quantitative real-time PCR and protein analysis methods. Induction of endogenous NO production by cytokine stimulation also triggered regulation of the genes. One example gene, connective tissue growth factor, was studied at the promoter level. Promoter-reporter gene studies in mesangial cells demonstrated that NO acts at the transcriptional level to suppress gene expression. Our results reveal a complex role of NO in regulating gene expression in mesangial cells and suggest an antifibrotic potential for NO.