Common diseases like allergy, obesity and cancer are complex. Each of these diseases is caused by altered interactions between multiple genes. These alterations may differ between different individuals although they appear to have the same disease. A clinical consequence is that a medication that works for one patient does not work for another. In some individuals the medication may even cause severe side-effects and deterioration of the disease.
Ideally, physicians should be able to personalize medication based on simple tests that measure a few proteins in saliva or blood.
The aim of ComplexDis is to identify such proteins using high-throughput technology, high-performance computing and systems biology.
Common hay fever is used as a model of complex disease. This is because we have a well-defined disease model that can be studied with out risk or discomfort in a large number of patients.
White blood cells are challenged with allergen in vitro and mRNA expression of all human genes examined with DNA microarrays. Network-based analysis is performed to find transcriptomal sub-networks that are specific for different disease sub-types (transcriptome=all mRNAs that are expressed in a cell or a tissue).
The sub-networks are dissected to find pathways and regulatory genes. These genes are examined for disease-associated polymorphisms and if their corresponding proteins can be used as diagnostic markers.
Another aim is the development of standardized analytical procedures for studies of complex diseases that will be made freely available for the research community. In this way, the project may facilitate similar studies of other complex diseases.
The project is co-ordinated from Göteborg University and based on a collaboration between seven European and one American group.