Logo BMBF
 
Logo NGFN
Home
_
Genetic epidemiological methods - GEMs

Coordinator: Prof. Dr. Max Baur

Summary:

Genetic Epidemiology is concerned with the etiology, distribution, and control of human diseases in groups of relatives, and with the inherited predisposition to diseases in populations. Over the last 20 years, the genetic basis of many single-gene disorders has been elucidated following the positional cloning paradigm. In the future, however, the major challenge to genetic epidemiology will undoubtedly be posed by so-called “complex” diseases which comprise conditions such as disorders of the CNS, cardio vascular diseases, cancer, infection and inflammation, environmentally affected diseases.

It became evident in the field of genetically complex diseases, that only cooperative efforts of scientists from fields of differing competence had any chance of success at all. The original cooperative model proposed by the GEM platform joins the three major competence components - genetics (human genetics, molecular genetics, genotyping), clinic (patients, recruiting, diagnosis, phenotyping), and epidemiology (genetic epidemiology, genetic biometry, bioinformatics, study design, information logistics, analysis) - in an integrated structure for the interdependent components of any disease driven project in complex diseases. The basic idea of this structure has been widely adopted by the whole NGFN in the way of disease-oriented networks cooperating with the high throughput genotyping platform and the platform of the GEMs (centers of excellence for Genetic Epidemiological Methods). This cooperative research structure received an extremely positive response from the international review board of the NGFN.

The fields of competence can be listed as follows:

  • Study design (including power analysis)
  • Definition of data formats and design of case report forms
  • Database planning and implementation
  • Recruitment monitoring
  • Data management and quality control
  • Data integration (phenotypes, genotypes)
  • State of the art data analysis
  • Development and implementation of new analysis tools
 
Project List: