Exposome and gene-environment interaction

2019-2020

Course Objective

In this course students learn how to use large population-based
information databases (e.g. neighbourhood characteristics, electronic
patient files, cancer registration), in the study of human genetics.
Combining information available from publicly shared databases may
generate new testable hypotheses, but also presents computational
challenges (e.g. record linkage with careful attention to privacy / de-
identification steps). To enable the student to perfrom gene by
environment interaction analyses, we discuss what exactly the terms gene
and environment relate to in this context, the many pitfalls related to
gene by environment research, and state of the art methodology to detect
the presence of these interactions.

Course Content

Genetic influences were long thought to be largely independent of the
social world. This notion is now called into question as increasing
evidence underscores the interplay between the genome and the
environment. Within the field of behaviour and molecular genetics we are
facing the next level of understanding how genetic sources of individual
differences are amplified or dampened by environmental and social
factors and, conversely, how genetic pathways modulate environmental
effects and social interactions.
Essential to understand this multiple layer interplay is an as complete
as possible assessment of environmental and social exposure. Such a
collection of assessments (an exposome) was first proposed by Wild in
the field of cancer epidemiology and quickly expanded to other disease
fields In this course the concept of an exposome will be explained in
the context of complex traits. The study of gene by environment or gene
by exposure interactions and dependencies does make stringent
assumptions about the data used. These studies can also present ethical
dilemmas as healthy records, employment records and genetics data are
combined. Both the methodological aspects and ethical aspects will be
discussed in the course.

Teaching Methods

Tuition consists of lectures, homework assignments, and participation in
workgroups and hands-on activities in class.

Method of Assessment

A final grade based on the average grade of separate assessments.More
information on Cavnas

Entry Requirements

Successful completion of two of the following RM courses: Behaviour
Genetics, Gene finding: Genome-Wide Association Studies and beyond, or
Epigenomics and Sequencing in Behaviour and Health.

Literature

During the course, reading material based on the latest developments in
the field will be posted on Canvas or distributed in class.

General Information

Course Code P_MEXPGEI
Credits 6 EC
Period P1
Course Level 400
Language of Tuition English
Faculty Fac. of Behavioural and Movement Science
Course Coordinator prof. dr. M. Bartels
Examiner prof. dr. M. Bartels
Teaching Staff

Practical Information

You need to register for this course yourself

Teaching Methods Study Group, Lecture
Target audiences

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