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The Endocrinology & Metabolic Diseases cluster, integral to the Clinical Chemistry sector of the Department of Laboratory Medicine, is comprised of three interrelated specialty laboratories: the Laboratory of Binding Analysis, the Laboratory of Special Chemistry, and the Laboratory of Metabolic Diseases.

This cluster is dedicated to advancing both translational and fundamental research in the realms of neuroendocrinology, oncology, genetic and acquired metabolic disorders, and inflammation. Emphasizing laboratory innovation, biomarker discovery, and the development of new assays, it leverages cutting-edge techniques such as chromatography, mass spectrometry, metabolomics, electrophoresis, ligand-binding assays and machine learning to push the boundaries of scientific inquiry and clinical application.

We not only support research connected to clinical trials both internally and externally but also play a pivotal role in developing and implementing analyses while providing guidance to researchers on various critical aspects. These aspects include preanalytical conditions, the selection of sample types, the configuration of assays, identification of biomarkers, and the choice of analytical methods. The scope of analyses spans from those conducted as part of routine patient care, which are accredited under the ISO 15189 certification, to assays exclusively designed for research purposes, such as the evaluation of experimental biomarkers.

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Our research primarily targets the advancement and innovation of laboratory diagnostics, encompassing the discovery and measurement of biomarkers within endocrinology, immunology and metabolic diseases. Key areas include:

  • Implementing continuous serial sampling techniques.
  • Utilizing laboratory analyses for lifestyle monitoring.
  • Creating bioinformatic pipelines and employing machine learning to enhance data-driven patient care.
  • Investigating newborn screening methodologies.
  • Developing both targeted and untargeted metabolomics for clinical and research applications.
  • Developing novel near patient testing applications
Relevance

Societal relevance

  • Diagnostic Precision: Advances in diagnostics and biomarker discovery enable early and accurate disease detection, improving treatment outcomes.
  • Proactive Health Management: Techniques like continuous sampling and lifestyle marker analysis allow for early intervention, preventing chronic diseases.
  • Newborn Health: Improved screening techniques can detect metabolic and other disorders early, offering life-changing interventions.
  • Molecular Insights: Metabolomics advancements provide deeper disease understanding, paving the way for new treatments.
  • Technology in Medicine: Utilizing AI and bioinformatics in studying metabolic diseases speeds up research, enhancing diagnostics and therapies.
  • Economic Efficiency: Innovations lead to healthcare savings by improving disease management.
  • Near-Patient Testing: Making diagnostic tests available closer to the patient, or even at home, speeds up decision-making and treatment initiation, greatly enhancing patient convenience and access to care.

Contact

For general inquiries or more information about our research programs, please don't hesitate to get in touch. You can reach us via email (see “Meet our Experts).

If you're interested in discussing project collaborations, method development, or have specific questions related to our ongoing research projects, please direct your questions or proposals to our specialized contacts:

Metabolic disease research and metabolomics:
E-mail: [email protected]

Mass spectrometric analysis in the field of (neuro)endocrine and oncology:
E-mail: [email protected]

Ligand binding analysis in the field of endocrinology, oncology and inflammation:
E-mail: [email protected]

We welcome your questions, proposals for collaboration, and interest in our work. Our team is committed to responding promptly and assisting you with your needs.

Visiting address
University Medical Center Groningen
Laboratory Medicine
Hanzeplein 1
9713 GZ Groningen