Greifswald Approach to Individualized Medicine (GANI_MED) – Rationale and Design

Background: Individualized Medicine has the aim to optimize prevention and treatment by extracting prognostic factors from a comprehensive set of information. Current concepts in this field mainly focus on genetic factors that are used as supplementary data to routine clinical characteristics. Major drawbacks of current concepts arise from less standardized information from patient cohorts and limited consideration of non-genetic factors. Aims: The project „Greifswald Approach to Individualized Medicine (GANI_MED)“ aims at identifying individual genetic and non-genetic factors, which predict outcomes in defined common diseases. Design: The major focus of GANI_MED is on patient cohorts recruited from hospitals. For this, clinical routine data from patient interviews, simple medical examinations including blood pressure and somatometric measurements as well as demanding imaging techniques are standardized in compliance with guidelines and recommendations to good epidemiological practice and using procedures established for the population-based Study of Health in Pomerania (SHIP). As a first step, we recruit patients with selected common diseases including heart failure, metabolic syndrome, stroke, renal and liver diseases. In the long run, all patients admitted to the University Hospital Greifswald will be offered to take part in GANI_MED. To facilitate research with biomaterials, the existing SHIP biobank is extended and automatized. Laboratory work is not only limited to standard laboratory markers but also include determination of hormonal factors as well as OMICs technologies (genomics, epigenomics, proteomics and metabolomics). Patient cohorts will be followed up for incident morbidities and mortality. Clinical-epidemiological and bioinformatics research is complemented with economic evaluation of individualized prevention and treatment concepts and research on ethical issues. Conclusion: GANI_MED extends current research concepts of individualized medicine by in-depth standardisation of clinical routine data and comprehensive inclusion of both genetic and non-genetic data. This broad approach has a high potential to establish and validate effective individualized prevention and treatment strategies in large patient cohorts.