Course details
Faculty | Health Sciences | ||
Department | Medicine | ||
Education level | Postgraduate / Master of Science | ||
Course code | B4 | Semester | 2 |
Course title | Special Topics in Data Analytics II | ||
Independent teaching activities | Hours per week | ECTS | |
Lectures | 2 | ||
Practice | 6 | ||
Total | 8 | 7,5 | |
Coursetype | General setting course, skills development | ||
Prerequisite courses | None | ||
Teaching and assessment language | English |
Learning outcomes
Objective
The aim of this module is to provide students with a fundamental understanding of the core concepts of molecular and genetic epidemiology and the application of relevant findings to public health and translational medicine. The module will encompass the appropriate study design for molecular and genetic epidemiologic investigations, biomarker development and the integration of biomarkers into epidemiologic studies, and the application of new and emerging molecular technologies in epidemiologic research.
Knowledge
Upon completion of the course, graduate students will be familiar with:
- The basic principles of molecular epidemiology
- Study designs in molecular epidemiology
- Biomarkers: Exposure and Effect/ Validity and Confirmation of Association
- Emerging Technologies in Molecular Epidemiology
- The basic principles of genetic epidemiology
- Study designs in genetic epidemiology
- Genome-Wide Association Studies (GWAS)
- Mendelian Randomisation
Capacities
The course participants upon completion will be able to:
- Describe the main types of study designs used in molecular and genetic epidemiologic investigations and identify potential sources of bias and the methods used to limit bias;
- Describe the main categories of biomarkers, explain how they are discovered
- and how they are integrated into epidemiologic study designs;
- Explain how new and emerging technologies such as ‘omics’ technologies can be applied to molecular epidemiologic study designs;
- Describe the basic principles of population genetics (e.g. mutation, recombination, population structure), the different types of genetic polymorphisms that are potentially relevant to disease, and recognise the current technological possibilities for measuring those polymorphisms;
- Demonstrate how to conduct a genome wide association study;
- Identify the aim, challenges and promises of Mendelian Randomisation.
Course contents
During the course, students will work on their own research question, and will experience the process of review at all stages. So they will learn how to:
- Introduction to Molecular Epidemiology
- Study Designs in Molecular Epidemiology
- Biomarkers: Exposure and Effect / Validation and Confirmation of Association
- Emerging Technologies I
- Emerging Technologies II
- Introduction to Genetic Epidemiology
- Study Designs in Genetic Epidemiology
- Genome-Wide Association Studies I
- Genome-Wide Association Studies II
- Mendelian Randomization I
- Mendelian Randomization II
Teaching methods | Face to face Distance learning | |
Use of information and communication technologies (ICT) | Use of ICT in Teaching- Moodle Virtual learning environment (VLE) (asynchronous learning, wikis, Online Discussion Fora, Educational Portfolio, assignment submission, assessment process) | |
Use of ICT in Communication with students (email, instant messaging via Moodle) | ||
Module structure | Work Hours per Semester | Activity |
Lectures | 55 | |
Exercises (Quiz) | 10 | |
Exercises (Wikis) | 10 | |
Exercises (Online discussion fora) | 20 | |
Exercises (Study relevant papers) | 20 | |
Essay background work | 40 | |
Essay writing | 45 | |
Overall work for the course | 200 | |
Assessment Methods | Written assignment, in English, approximately 2,500 words long, to be submitted by each student at the end of the course | |
Assessment of knowledge at the beginning and the end of the course with short-answer questions and essays development | ||
Weekly quizes, with multiple choice questions | ||
Assessment based on comments submitted by each student in online discussion fora |
Recommended bibliography
- Palmer LJ, Burton P, Davey Smith G. An Introduction to Genetic Epidemiology. Health & Society Series, 2011.
- F Perera and B Weinstein. Molecular Epidemiology: recent advances and future directions Carcinogenesis 2000; 21 (3):517-524
- M Spitz and M Bondy. The evolving discipline of molecular epidemiology of cancer. Carcinogenesis 2010; 3(1): 127-134
- A Rundle, P Vineis and H Ahsan. Design options for molecular epidemiology research within cohort studies. Cancer Epidemiology Biomarkers and Prevention. 2005 14; 1899-1904.
- N Caporaso. Integrative study designs-next step in the evolution of molecular epidemiology? Cancer Epidemiology Biomarkers and Prevention. 2007 16; 365
- N Holland, L Pfleger, E Berger, A Ho and M Bastaki. Molecular epidemiology biomarkers-sample collection and processing considerations. Toxicology and Applied Pharmacology. 2005; 261-268. P Vineis, F Perera. Molecular epidemiology and biomarkers in etiologic cancer research: the new in light of the old. Cancer Epidemiology Biomarkers and Prevention. 2007;16(10):1954-1965.
- N Rothman, W Stewart, P Schulte. Incorporating biomarkers into cancer epidemiology: a matrix of biomarker and study design categories. Cancer Epidemiology Biomarkers and Prevention. 1995;4:301–11.
- S Wacholder, S Chanock, M Garcia-Closas, L Elghormli, N Rothman Assessing the probability that a positive report is false: An approach for molecular epidemiology studies. J Natl Cancer Inst 2004 96: 434–442.
- J Ioannidis Microarrays and molecular research: Noise discovery? Lancet 2005 365: 454–455.
- J Vandenbroucke When are observational studies as credible as randomised trials? Lancet 2004 363: 1728–1731.
- D Thomas. High-volume “-omics” technologies and the future of molecular epidemiology. Epidemiology 2006 17(5):490-1.
- D Hunter. The future of molecular epidemiology. Int J Epidemiol. 1999 28(5): S1012-4.
- C Wild, G Law and E Roman. Molecular epidemiology and cancer: promising areas of future research in the post-genomic era. Mutation Research 2002 499(1): 3-12.
- Tzoulaki et al. Design and analysis of metabolomics studies in epidemiologic research: a primer on -omic technologies. Am J Epidemiol. 2014 Jul 15;180(2):129-39.
- Key concepts in genetic epidemiology. In: Palmer LJ, Burton P, Davey Smith G. An Introduction to Genetic Epidemiology. Health & Society Series, 2011. pp. 5-39.
- Genetic linkage studies. In: Palmer LJ, Burton P, Davey Smith G. An Introduction to Genetic Epidemiology. Health & Society Series, 2011. pp. 39-61.
- Genetic association studies. In: Palmer LJ, Burton P, Davey Smith G. An Introduction to Genetic Epidemiology. Health & Society Series, 2011. pp. 61-91.