405030 Molecular Epidemiology (S) (SoSe 2022)

Molecular epidemiology is an interdisciplinary research strategy that utilizes advanced laboratory methods into epidemiology to assess disease association thus facilitating causal inference. It is increasingly being used to understand interactions between external 'environmental' exposures and genetic and other susceptibility factors, and to identify individuals who are at higher risk. This course will cover role of molecular epidemiology in environmental factors of health including the application of biomarkers to the study of disease association, risk assessment, and prevention. The course covers principles in the selection and validation of biomarkers, study design and statistical methods in data analysis including gene-environment interactions, biological sample collection, storage, and biobanking, and current laboratory methods for biomarker analysis. Examples from current molecular epidemiologic research in cancer, CVD, other metabolic outcomes, risk assessment, and disease prevention will be used to demonstrate these ideas. Students will develop expertise and experience in critically analyzing major articles in molecular epidemiology research.
Course content/Lehrinhalte
In this course students will gain knowledge on different study designs, laboratory and statistical methods in molecular epidemiology to assess the environmental exposures in disease risk

- Study designs in molecular epidemiology
- Classes of biomarkers (Exposure, Disease and Susceptibility)
- Gene-environment interactions
- Current laboratory methods for biomarker analysis
- Genome wide association study
- Basic quality control in genetic association studies: Data structure
- Statistical analysis in molecular/genetic epidemiology
- Interpretation of scientific articles on molecular and genetic epidemiology

On successful completion of the course students will be able to:
- Demonstrate an understanding of the role of molecular epidemiology with respect to environmental risk factors.
- Develop expertise in study designs and exposure assessment to characterize the distribution and burden of health outcomes.
- Prepare simple statistical program for gene-environment interactions and interpret its results
- Critically evaluate research article via journal club presentations