News | 2011

Proteomics Clin. Appl. 2011
Diagnosis of subclinical and clinical acute T-cell-mediated rejection in renal transplant patients by urinary proteome analysis
Metzger J, Chatzikyrkou C, Broecker V, Schiffer E, Jaensch L, Iphoefer A, Mengel M, Mullen W, Mischak H, Haller H, Gwinner W

Purpose: Noninvasive diagnosis of acute renal allograft rejection may be advantageous compared with the allograft biopsy. Experimental design: In this study, a multi-marker classification model for rejection was defined on a training set of 39 allograft patients by statistical comparison of capillary electrophoresis mass spectrometry (CE-MS) peptide spectra in urine samples from 16 cases with subclinical acute T-cell-mediated tubulointerstitial rejection and 23 nonrejection controls. Results: Application of the rejection model to a blinded validation set (n=64) resulted in an AUC value of 0.91 (95% CI: 0.82-0.97, p=0.0001). In total, 16 out of 18 subclinical and 10 out of 10 clinical rejections (BANFF grades Ia/Ib), and 28 out of 36 controls without rejection were correctly classified. Acute tubular injury in the biopsies or concomitant urinary tract infection did not interfere with CE-MS-based diagnosis. Sequence information of identified altered collagen α(I) and α (III) chain fragments in rejection samples suggested an involvement of matrix metalloproteinase-8 (MMP-8). Biopsy stainings revealed matrix metalloproteinase-8 exclusively in neutrophils located within peritubular capillaries and sparsely, in the tubulointerstitium during rejection. Conclusions and clinical relevance: The established marker set contains peptides related to tubulointerstitial infiltration seen in acute rejection. The set of urinary peptide markers will be used for early diagnosis of acute kidney allograft rejection marker in a multicenter phase III prospective study.
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PLoS ONE 2010 Oct; 5(10): e13421
Multicentric Validation of Proteomic Biomarkers in Urine Specific for Diabetic Nephropathy
Alkhalaf A, Zuerbig P, Bakker SJL, Bilo HJG, Cerna M, Fischer C, Fuchs S, Janssen B, Medek K, Mischak H, Roob JM, Rossing K, Rossing P, Rychlík I, Sourij H, Tiran B, Winklhofer-Roob BM, Navis GJ


Urine proteome analysis is rapidly emerging as a tool for diagnosis and prognosis in disease states. For diagnosis of diabetic nephropathy (DN), urinary proteome analysis was successfully applied in a pilot study. The validity of the previously established proteomic biomarkers with respect to the diagnostic and prognostic potential was assessed on a separate set of patients recruited at three different European centers. In this case-control study of 148 Caucasian patients with diabetes mellitus type 2 and duration ≥5 years, cases of DN were defined as albuminuria >300 mg/d and diabetic retinopathy (n = 66). Controls were matched for gender and diabetes duration (n = 82).


Proteome analysis was performed blinded using high-resolution capillary electrophoresis coupled with mass spectrometry (CE-MS). Data were evaluated employing the previously developed model for DN. Upon unblinding, the model for DN showed 93.8% sensitivity and 91.4% specificity, with an AUC of 0.948 (95% CI 0.898-0.978). Of 65 previously identified peptides, 60 were significantly different between cases and controls of this study. In <10% of cases and controls classification by proteome analysis not entirely resulted in the expected clinical outcome. Analysis of patient's subsequent clinical course revealed later progression to DN in some of the false positive classified DN control patients.


These data provide the first independent confirmation that profiling of the urinary proteome by CE-MS can adequately identify subjects with DN, supporting the generalizability of this approach. The data further establish urinary collagen fragments as biomarkers for diabetes-induced renal damage that may serve as earlier and more specific biomarkers than the currently used urinary albumin.
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BMC Nephrology 2010, 11:29
Urinary proteome analysis enables assessment of renoprotective treatment in type 2 diabetic patients with microalbuminuria
Andersen S, Mischak H, Zuerbig P, Parving HH, Rossing P


Previously the angiotensin II receptor blocker Irbesartan has been demonstrated to reduce the risk for progression from microalbuminuria to macroalbuminuria in type 2 diabetic patients. The purpose of this study was to evaluate the effect of treatment with Irbesartan in type 2 diabetic patients with microalbuminuria on the urinary proteome.


High-resolution capillary-electrophoresis coupled to mass-spectrometry (CE-MS) was used to profile the low-molecular-weight proteome in urine of a subgroup of patients from a two year randomized irbesartan versus placebo therapy trial, which included hypertensive type 2 diabetic patients with microalbuminuria on ongoing antihypertensive medication (IRMA2-substudy).


We demonstrate that the therapy with 300 mg Irbesartan daily over a period of two years results in significant changes of the urinary proteome. Both, a classifier developed previously that consists of urinary peptides indicative of chronic kidney disease, as well as several individual peptides changed significantly after treatment. These changes were not observed in the placebo-treated individuals. Most prominent are changes of urinary collagen fragments associated with progression of diabetic nephropathy, indicating normalization in urinary peptides.


CE-MS analysis of urine enabled identification of peptides as potential surrogate markers for renoprotection in microalbuminuric type 2 diabetic patients, which show persistent improvement after longterm treatment with Irbesartan. The results suggest that a major benefit of treatment by Irbesartan may be improvement of collagen turnover, reduction of fibrosis. They further suggest that urinary proteome analysis could be utilized to assess potential benefit of therapeutic intervention, providing statistically significant results even on a small population.
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Hypertension. 2011 Mar;57(3):561-9
Urinary Proteomics for Prediction of Preeclampsia.
Carty DM, Siwy J, Brennand JE, Zürbig P, Mullen W, Franke J, McCulloch JW, North RA, Chappell LC, Mischak H, Poston L, Dominiczak AF, Delles C.

Preeclampsia is a major determinant of fetal and maternal morbidity and mortality. We used a proteomic strategy to identify urinary biomarkers that predict preeclampsia before the onset of disease. We prospectively collected urine samples from women throughout pregnancy. Samples from gestational weeks 12 to 16 (n=45), 20 (n=50), and 28 (n=18) from women who subsequently had preeclampsia develop were matched to controls (n=86, n=49, and n=17, respectively). We performed capillary electrophoresis online coupled to micro-time-of-flight mass spectrometry. Disease-specific peptide patterns were generated using support vector machine-based software. Candidate biomarkers were sequenced by liquid chromatography-tandem mass spectrometry. From comparison with nonpregnant controls, we defined a panel of 284 pregnancy-specific proteomic biomarkers. Subsequently, we developed a model of 50 biomarkers from specimens obtained at week 28 that was associated with future preeclampsia (classification factor in cases, 1.032 ± 0.411 vs controls, -1.038 ± 0.432; P<0.001). Classification factor increased markedly from week 12 to 16 to 28 in women who subsequently had preeclampsia develop (n=16; from -0.392 ± 0.383 to 1.070 ± 0.383; P<0.001) and decreased slightly in controls (n=16; from -0.647 ± 0.437 to -1.024 ± 0.433; P=0.043). Among the biomarkers are fibrinogen alpha chain, collagen alpha chain, and uromodulin fragments. The markers appear to predict preeclampsia at gestational week 28 with good confidence but not reliably at earlier time points (weeks 12-16 and 20). After prospective validation in other cohorts, these markers may contribute to better prediction, monitoring, and accurate diagnosis of preeclampsia.
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Proteomics Clinical Applications 2011
Effect of fenofibrate treatment on the low molecular weight urinary proteome of healthy volunteers
Foucher C, Schiffer E, Mischak H, Ansquer JC, Wilbraham D


Urinary peptidome changes and discrimination for potential renal glomerular and tubular damage after 6 wk of fenofibrate treatment were evaluated in 26 healthy subjects.


Peptide profiling was performed in urine samples before and after treatment using high-resolution capillary electrophoresis coupled with electrospray ionization mass spectrometry.


A panel of 88 fenofibrate-sensitive peptides was detected with a frequency of ≥50% before and after treatment. This was reduced to 36 peptides by repeating the comparison ten times by randomly excluding samples at each time-point. Nineteen peptides were consistent and reliable biomarkers after an additional comparison with an age and sex-matched subject control group. Levels of peptides identified as fragments of Collagen α-1 (I), Collagen α-1 (XVII), Collagen α-2 (VIII) or sodium/potassium-transporting ATPase subunit gamma were reduced after fenofibrate treatment. Classification scores for renal tubular and glomerular damages determined by support vector machine based biomarker models increased after treatment but remained below pathological score cutoff values.


Fenofibrate treatment led to minor modifications of the urinary proteomic profile in a way that does not create safety issues affecting glomerular and tubular functions. Urinary peptide profiling proved to be appropriate to monitor drug pharmacological effects in a clinical setting.

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Hepatology. 2011 Mar;53(3):875-884. doi: 10.1002/hep.24103
Bile proteomic profiles differentiates cholangiocarcinoma from primary sclerosing cholangitis and choledocholithiasis
Lankisch TO, Metzger J, Negm AA, Voßkuhl K, Schiffer E, Siwy J, Weismüller TJ, Andrea S. Schneider AS, Thedieck K, Baumeister R, Zuerbig P, Weissinger EM, Manns MP, Mischak H, Wedemeyer J

Early detection of malignant biliary tract diseases, especially cholangiocarcinoma (CC) in patients with primary sclerosing cholangitis (PSC), is very difficult and often comes too late to give the patient a therapeutic benefit. We hypothesize that bile proteomic analysis distinguishes CC from nonmalignant lesions. We used capillary electrophoresis mass spectrometry (CE-MS) to identify disease-specific peptide patterns in patients with choledocholithiasis (n = 16), PSC (n = 18), and CC (n = 16) in a training set. A model for differentiation of choledocholithiasis from PSC and CC (PSC/CC model) and another model distinguishing CC from PSC (CC model) were subsequently validated in independent cohorts (choledocholithiasis [n = 14], PSC [n = 18] and CC [n = 25]). Peptides were characterized by sequencing. Application of the PSC/CC model in the independent test cohort resulted in correct exclusion of 12/14 bile samples from patients with choledocholithiasis and identification of 40/43 patients with PSC or CC (86% specificity, 93% sensitivity). The corresponding receiver operating characteristic (ROC) analysis revealed an area under the curve (AUC) of 0.93 (95% confidence interval [CI]: 0.82-0.98, P = 0.0001). The CC model succeeded in an accurate detection of 14/18 bile samples from patients with PSC and 21/25 samples with CC (78% specificity, 84% sensitivity) in the independent cohort, resulting in an AUC value of 0.87 (95% CI: 0.73-0.95, P = 0.0001) in ROC analysis. Eight out of 10 samples of patients with CC complicating PSC were identified. CONCLUSION: Bile proteomic analysis discriminates benign conditions from CC accurately. This method may become a diagnostic tool in future as it offers a new possibility to diagnose malignant bile duct disease and thus enables efficient therapy particularly in patients with PSC.
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