Aim
Diagnosing diseases in very early stages – when obvious symptoms of the disease are not yet apparent – would greatly reduce treatment costs and negative impacts of treatments to patient, and would promise increased sucess of treatments.
The aim is to take proteome data from serum samples, analyse them with advanced mass spectrometry technology, manage the output in structured, standardised databases using latest database technologies, and explore and implement advanced statistical analyses to detect patterns that indicate diseases even in its very early stages.
Mass spectrometry proteome screening is increasingly applied in order to search for disease-specific patterns. However, these data is blurred and noisy.
This project – through the standards and technologies it is developing – opens up the possibility of a worldwide repository of proteome and mass spectrometry data which will benefit all disease research.
This „clinical proteomics“ project is unique in a number of ways:

• The process of serum probing has been standardised and data from a large study of a homogeneous patient pool is available, both of which are the prerequisites for proper statistical analysis.
• The data is managed in structured databases (and analysed on parallel processed jobs) which allows for larger datasets and better performance while analysing these data amounts.
• The analysis goes beyond the search for singular biomarkers and is looking for complex profile patterns. Large-scale statistical analysis (novel on this kind of data) promises new results.

Collaborators:

• Freie Universitaet Berlin
• University Hospital Leipzig

Future perspectives:
Worldwide Proteomics centres providing access to curated data collections and analysis services.
Advanced intercation between mass spectrometry and protein databases (de-novo sequencing of proteins, identification of post-translational modifications).
Spatiotemporal patterns of protein occurrences.

Please see also the project web page at the European Science Initiative website.

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