Pontillo C.,Mosaiques Diagnostics |
Mischak H.,Mosaiques Diagnostics |
Mischak H.,University of Glasgow
Clinical Kidney Journal | Year: 2017
Capillary electrophoresis coupled with mass spectrometry (CE-MS) has been used as a platform for discovery and validation of urinary peptides associated with chronic kidney disease (CKD). CKD affects ∼ 10% of the population, with high associated costs for treatments. A urinary proteome-based classifier (CKD273) has been discovered and validated in cross-sectional and longitudinal studies to assess and predict the progression of CKD. It has been implemented in studies employing cohorts of > 1000 patients. CKD273 is commercially available as an in vitro diagnostic test for early detection of CKD and is currently being used for patient stratification in a multicentre randomized clinical trial (PRIORITY). The validity of the CKD273 classifier has recently been evaluated applying the Oxford Evidence-Based Medicine and Southampton Oxford Retrieval Team guidelines and a letter of support for CKD273 was issued by the US Food and Drug Administration. In this article we review the current evidence published on CKD273 and the challenges associated with implementation. Definition of a possible surrogate early endpoint combined with CKD273 as a biomarker for patient stratification currently appears as the most promising strategy to enable the development of effective drugs to be used at an early time point when intervention can still be effective. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA.
PubMed | University of Southern Denmark, Mosaiques Diagnostics, University of Groningen, Steno Diabetes Center and University of Aarhus
Type: | Journal: Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association | Year: 2017
The mineralocorticoid receptor antagonist spironolactone significantly reduces albuminuria in patients with diabetes. Prior studies have shown large between-patient variability in albuminuria treatment response. We previously developed and validated a urinary proteomic classifier that predicts onset and progression of chronic kidney disease. Here, we tested whether the proteomic classifier based on 273 urinary peptides (CKD273) predicts albuminuria response to spironolactone treatment.We performed a post hoc analysis in a double-blind randomized clinical trial with allocation to either spironolactone 12.5-50mg/day (n=57) or placebo (n=54) for 16 weeks. Patients were diagnosed with type 2 diabetes and resistant hypertension. Treatment was an adjunct to renin-angiotensin system inhibition. Primary endpoint was the percentage change in urine albumin to creatinine ratio (UACR). Capillary electrophoresis mass spectrometry was used to quantify urinary peptides at baseline. The previously validated combination of 273 known urinary peptides was used as proteomic classifier.Spironolactone reduced UACR relative to placebo by 50%, although with a large between-patient variability in UACR response (5th to 95th percentile, 7 to 312%). An interaction was detected between CKD273 and treatment assignment (=-1.09, P=0.026). Higher values of CKD273 at baseline were associated with a larger reduction in UACR in the spironolactone group (=-0.70, P=0.049), but not in the placebo group (=0.39, P=0.25). Stratified in tertiles of baseline CKD273, reduction in UACR was greater in the highest tertile, 63% (95% confidence interval: 35-79%), as compared with the two other tertiles combined, 16% (-17 to 40%) (P=0.011).A urinary proteomics classifier can be used to identify individuals with type 2 diabetes who are more likely to show an albuminuria-lowering response to spironolactone treatment. These results suggest that urinary proteomics may be a valuable tool to tailor therapy, but confirmation in a larger clinical trial is required.
PubMed | Martin Luther University of Halle Wittenberg, University of Macedonia, Steno Diabetes Center, Novo Nordisk AS and 8 more.
Type: Journal Article | Journal: BMJ open | Year: 2016
Diabetes mellitus affects 9% of the European population and accounts for 15% of healthcare expenditure, in particular, due to excess costs related to complications. Clinical trials aiming for earlier prevention of diabetic nephropathy by renin angiotensin system blocking treatment in normoalbumuric patients have given mixed results. This might reflect that the large fraction of normoalbuminuric patients are not at risk of progression, thereby reducing power in previous studies. A specific risk classifier based on urinary proteomics (chronic kidney disease (CKD)273) has been shown to identify normoalbuminuric diabetic patients who later progressed to overt kidney disease, and may hold the potential for selection of high-risk patients for early intervention. Combining the ability of CKD273 to identify patients at highest risk of progression with prescription of preventive aldosterone blockade only to this high-risk population will increase power. We aim to confirm performance of CKD273 in a prospective multicentre clinical trial and test the ability of spironolactone to delay progression of early diabetic nephropathy.Investigator-initiated, prospective multicentre clinical trial, with randomised double-masked placebo-controlled intervention and a prospective observational study. We aim to include 3280 type 2 diabetic participants with normoalbuminuria. The CKD273 classifier will be assessed in all participants. Participants with high-risk pattern are randomised to treatment with spironolactone 25 mg once daily, or placebo, whereas, those with low-risk pattern will be observed without intervention other than standard of care. Treatment or observational period is 3 years.The primary endpoint is development of confirmed microalbuminuria in 2 of 3 first morning voids urine samples.The study will be conducted under International Conference on Harmonisation - Good clinical practice (ICH-GCP) requirements, ethical principles of Declaration of Helsinki and national laws. This first new biomarker-directed intervention trial aiming at primary prevention of diabetic nephropathy may pave the way for personalised medicine approaches in treatment of diabetes complications.NCT02040441; Pre-results.
Lankisch T.O.,Hannover Medical School |
Metzger J.,Mosaiques diagnostics |
Negm A.A.,Hannover Medical School |
Vokuhl K.,Hannover Medical School |
And 12 more authors.
Hepatology | Year: 2011
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. © 2011 American Association for the Study of Liver Diseases.
Klein J.,University of Manchester |
Eales J.,University of Manchester |
Zurbig P.,Mosaiques Diagnostics |
Vlahou A.,Academy of Athens |
And 3 more authors.
Proteomics | Year: 2013
In this study, we have developed Proteasix, an open-source peptide-centric tool that can be used to predict in silico the proteases involved in naturally occurring peptide generation. We developed a curated cleavage site (CS) database, containing 3500 entries about human protease/CS combinations. On top of this database, we built a tool, Proteasix, which allows CS retrieval and protease associations from a list of peptides. To establish the proof of concept of the approach, we used a list of 1388 peptides identified from human urine samples, and compared the prediction to the analysis of 1003 randomly generated amino acid sequences. Metalloprotease activity was predominantly involved in urinary peptide generation, and more particularly to peptides associated with extracellular matrix remodelling, compared to proteins from other origins. In comparison, random sequences returned almost no results, highlighting the specificity of the prediction. This study provides a tool that can facilitate linking of identified protein fragments to predicted protease activity, and therefore into presumed mechanisms of disease. Experiments are needed to confirm the in silico hypotheses; nevertheless, this approach may be of great help to better understand molecular mechanisms of disease, and define new biomarkers, and therapeutic targets. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Siwy J.,Mosaiques Diagnostics |
Siwy J.,Charité - Medical University of Berlin |
Zoja C.,Mario Negri Institute for Pharmacological Research |
Klein J.,University of Manchester |
And 11 more authors.
PLoS ONE | Year: 2012
Representative animal models for diabetes-associated vascular complications are extremely relevant in assessing potential therapeutic drugs. While several rodent models for type 2 diabetes (T2D) are available, their relevance in recapitulating renal and cardiovascular features of diabetes in man is not entirely clear. Here we evaluate at the molecular level the similarity between Zucker diabetic fatty (ZDF) rats, as a model of T2D-associated vascular complications, and human disease by urinary proteome analysis. Urine analysis of ZDF rats at early and late stages of disease compared to age- matched LEAN rats identified 180 peptides as potentially associated with diabetes complications. Overlaps with human chronic kidney disease (CKD) and cardiovascular disease (CVD) biomarkers were observed, corresponding to proteins marking kidney damage (eg albumin, alpha-1 antitrypsin) or related to disease development (collagen). Concordance in regulation of these peptides in rats versus humans was more pronounced in the CVD compared to the CKD panels. In addition, disease-associated predicted protease activities in ZDF rats showed higher similarities to the predicted activities in human CVD. Based on urinary peptidomic analysis, the ZDF rat model displays similarity to human CVD but might not be the most appropriate model to display human CKD on a molecular level. © 2012 Siwy et al.
PubMed | Hannover Medical School, Medical University of Graz, Northumbria University, Mosaiques Diagnostics and 2 more.
Type: | Journal: Leukemia | Year: 2016
Allogeneic hematopoietic stem cell transplantation (allo-HSCT) may be curative, but is associated with significant morbidity and mortality. Chronic graft-versus-host disease (cGvHD), characterized by inflammation and fibrosis of multiple target organs, considerably contributes to the morbidity and mortality even years after allo-HSCT. Diagnosis of cGvHD is based on clinical features and histology of biopsies. Here, we report the generation of a urinary cGvHD-specific proteome-pattern (cGvHD_MS14) established by capillary electrophoresis-mass spectrometry to predict onset and severity of cGvHD as an unbiased laboratory test. cGvHD_MS14 was evaluated on samples from 412 patients collected prospectively in four transplant centers. Sensitivity and specificity was 84 and 76% by cGvHD_MS14 classification. Sensitivity further increased to 93% by combination of cGvHD_MS14 with relevant clinical variables to a logistic regression model. cGvHD was predicted up to 55 days prior to clinical diagnosis. Acute GvHD is not recognized by cGvHD_MS14. cGvHD_MS14 consists of 14 differentially excreted peptides, six of those have been sequenced to date and are fragments from thymosin -4, eukaryotic translation initiation factor 42, fibrinogen -chain or collagens. In conclusion, the cGvHD_MS14-pattern allows early, highly sensitive and specific prediction of cGvHD as an independent diagnostic criterion of clinical diagnosis potentially allowing early therapeutic intervention.Leukemia advance online publication, 4 November 2016; doi:10.1038/leu.2016.259.
Klein J.,Mosaiques Diagnostics |
Papadopoulos T.,Academy of Athens |
Mischak H.,Mosaiques Diagnostics |
Mischak H.,University of Glasgow |
Mullen W.,University of Glasgow
Electrophoresis | Year: 2014
Clinical proteomics has led to the identification of biomarkers specifically associated with a clinical condition that can serve for diagnostic or prognostic purposes. Learning more about the origin of these protein fragments would lead to a better insight in the pathology, and this requires improved identification of the peptide sequences. The aim of this study is to assess the complementarity of LC-MS/MS and CE-MS/MS as techniques in peptide sequence identification of the urinary low-molecular weight proteome. A male standard human urine sample was analyzed using LC- and CE-MS/MS (n = 10 per technique), identifying 905 unique peptide sequences with high confidence, 50% of those were identified only with LC, 20% only with CE and 30% with both techniques. Higher LC coverage might be due in part to the higher amount of sample that can be loaded onto an LC column. Peptides uniquely identified in CE are generally small and highly charged, likely unable to bind to the LC column In conclusion, we showed that LC-MS/MS and CE-MS/MS are highly complementary in identifying peptide sequences. The combination of both technologies results in significantly increased sequence coverage. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Mermelekas G.,Academy of Athens |
Makridakis M.,Academy of Athens |
Koeck T.,Mosaiques Diagnostics |
Vlahou A.,Academy of Athens
Expert Review of Proteomics | Year: 2013
Quantitative determination of reactive oxygen species and reactive nitrogen species in body fluids, tissues or cells has always been problematic due to their high chemical reactivity and the resulting short half-life. This high reactivity may involve reversible and/or irreversible protein modifications, in particular the covalent oxidative modification of specific amino acid residues. Thus, the occurrence of reactive oxygen species and reactive nitrogen species can be monitored indirectly from the identification of specific protein-chemical footprints. In combination with classical gel-based proteomics or liquid chromatography labeling or label-free techniques, mass spectrometry has emerged as a powerful tool to identify these protein modifications in biological samples. In this review, we present the main methodological approaches for gel-based proteomics and quantitative mass spectrometry applied to oxidative protein modifications, mainly Cys. Representative examples from their application in identifying respective biomarkers in diseases related to oxidative stress are also presented. © 2013 Informa UK, Ltd.
PubMed | Mosaiques Diagnostics and French Institute of Health and Medical Research
Type: Journal Article | Journal: Bioanalysis | Year: 2016
The recent advancements in clinical proteomics enabled identification of biomarker panels for a large range of diseases. A number of CE-MS-identified biomarker panels were verified and implemented in clinical studies. Despite multiple challenges, accumulating evidence supports the value and the need for proteome-based biomarker panels. In this perspective, we provide an overview of clinical studies indicating the added value of CE-MS biomarker panels over traditional diagnostics and monitoring methods. We outline apparent advantages of applying novel proteomic biomarker panels for disease diagnosis, prognosis, staging, drug development and patient management. Facing the plethora of benefits associated with the use of CE-MS biomarker panels, we envision their implementation into the medical practice in the near future.