Biomarker analysis
Biomarker analysis
Frustrated by the lack of reliable biomarkers?
Try clinical proteomics!
Mosaiques offers the medical research community the world's leading urinary proteome analysis platform for the definition of molecular disease processes based on proteins and peptides contained in one urine sample!
Some diseases, especially chronic diseases and several types of cancers, have already been defined on the basis of the urine proteome. However, thousands of additional applications still need to be explored. A company cannot do this alone.
Benefits of urine samples:
- Non-invasive (painless and without risk) sampling
- Available in bulk
- Stable at -20°C for over 10 years (no loss of information)
Our Service
Mosaiques makes its unique proteome analysis technology available as a service provider for researchers and clinicians. Interested in collaboration with Mosaiques?
Contact us at proteomestudies@mosaiques.de to discuss how we can assist you.
Here's what we can do for you:
Proteomics Analysis: Our core technique to comprehensively assess the proteome is capillary electrophoresis coupled with mass spectrometry. This technology allows for the detection and quantification of peptides and proteins present in the urine samples. Specialized software and bioinformatics tools are used to process and analyze the data.
Identification of non-invasive biomarkers: The analysis of proteomics data follows a rigorous statistical approach, aiming to identify specific peptides/proteins and their patterns that are linked to certain clinical conditions or disease states. Moreover, we strive to establish potential connections between the identified biomarkers and the underlying disease pathophysiology. Once potential biomarkers are identified, they need to be validated in larger and independent cohorts of patients. The extensive Urinary Proteome Database is a valuable resource for conducting this validation process. Through this robust methodology, we are committed to advancing the field of clinical proteomics and unlocking new possibilities for personalized medicine and improved patient care.
AI-driven approach: We recognize the superior performance of biomarker panels over single biomarkers in clinical applications. Thus, we employ advanced AI and machine learning algorithms to integrate individual biomarkers into panels that offer enhanced diagnostic accuracy and predictive capabilities.
Reporting and Interpretation: The results of the proteomics analysis and biomarker discovery are compiled into a comprehensive report. This report presents detailed information about the identified biomarkers, including their sequence, performance within the biomarker panel, and their relevance to the studied clinical condition. Our team of experts ensures that the report is comprehensive and easily understandable.
Expert Consultation: Our team of scientists will provide expert consultation, guiding you through the research process to ensure precision and success.
Sample requirements
To ensure the success of your project and provide you with the best results, we have outlined the sample requirements necessary for the biomarker development process:
Sample Type: For optimal results, we recommend collecting the second morning mid-stream urine. Under no circumstances should additives (e.g., protease inhibitors, chelating agents, etc.) be added. Please refer to our SOPs for detailed sample collection, storage, and shipment instructions available here.
Sample Metadata: Supply essential metadata associated with each sample. If specific treatments, medications, or interventions are involved, provide detailed information about the conditions under which the samples were collected. All data are managed in full compliance with the European General Data Protection Regulation (GDPR).
Ethical Considerations: Comply with all ethical guidelines and obtain necessary approvals (e.g., Institutional Review Board approval) for sample collection and usage. Ensure that all samples are collected ethically and with informed consent.
Biomarker analysis - an example
Case-study: Biomarker discovery during Covid-19 pandemic
In the summer of 2020, the search for suitable biomarkers to predict severe Covid-19 started and was prioritized using one of the most powerful proteomic databases.
The identification of 50 biomarkers, their integration in biomarker panel (termed COV50), and the successful completion of a clinical trial (German Register for Clinical Studies, ID: DRKS00022495) including >1000 subjects within half a year is the result of systematic work. As demonstrated in this project, diseases can be predicted at an early stage and the economic costs for the healthcare system can be reduced.
COV50 is registered in Germany and available for clinical use in the EU.
The future of personalized medicine, in which diagnosis and therapy form a symbiosis and go hand in hand, is already the reality.
Reference
Staessen, J. A., Wendt, R., Yu, Y. L., Kalbitz, S., Thijs, L., Siwy, J., Raad, J., Metzger, J., Neuhaus, B., Papkalla, A., von der Leyen, H., Mebazaa, A., Dudoignon, E., Spasovski, G., Milenkova, M., Canevska-Taneska, A., Salgueira Lazo, M., Psichogiou, M., Rajzer, M. W., Fuławka, Ł., … CRIT-CoV-U investigators (2022). Predictive performance and clinical application of COV50, a urinary proteomic biomarker in early COVID-19 infection: a prospective multicentre cohort study. The Lancet. Digital health, 4(10), e727–e737. doi.org/10.1016/S2589-7500(22)00150-9
Further reading
Latosinska, A., Frantzi, M., & Siwy, J. (2023). Peptides as "better biomarkers"? Value, challenges, and potential solutions to facilitate implementation. Mass spectrometry reviews, 10.1002/mas.21854. doi.org/10.1002/mas.21854
Tofte, N., Lindhardt, M., Adamova, K., Bakker, S. J. L., Beige, J., Beulens, J. W. J., Birkenfeld, A. L., Currie, G., Delles, C., Dimos, I., Francová, L., Frimodt-Møller, M., Girman, P., Göke, R., Havrdova, T., Heerspink, H. J. L., Kooy, A., Laverman, G. D., Mischak, H., Navis, G., … PRIORITY investigators (2020). Early detection of diabetic kidney disease by urinary proteomics and subsequent intervention with spironolactone to delay progression (PRIORITY): a prospective observational study and embedded randomised placebo-controlled trial. The lancet. Diabetes & endocrinology, 8(4), 301–312. doi.org/10.1016/S2213-8587(20)30026-7
Mischak, H., Allmaier, G., Apweiler, R., Attwood, T., Baumann, M., Benigni, A., Bennett, S. E., Bischoff, R., Bongcam-Rudloff, E., Capasso, G., Coon, J. J., D'Haese, P., Dominiczak, A. F., Dakna, M., Dihazi, H., Ehrich, J. H., Fernandez-Llama, P., Fliser, D., Frokiaer, J., Garin, J., … Vlahou, A. (2010). Recommendations for biomarker identification and qualification in clinical proteomics. Science translational medicine, 2(46), 46ps42. doi.org/10.1126/scitranslmed.3001249
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