This introductory course explores the complex interplay between genes and the environment in shaping human phenotypes. Participants will gain knowledge of cohort datasets, environmental readouts, and computational resources to investigate gene-environment interactions. Ethical and legal frameworks related to data privacy and consent will be discussed. The course also covers computational modelling techniques for integrating genotype and environmental effects. By the end, attendees will be equipped to analyse cohort datasets, make use of computational resources, and interpret the results.

Who is this course for?

This introductory course is aimed at MRes/PhD students, researchers, clinicians, and other professionals working in the fields of genomics, exposomics, epidemiology, or toxicology with an interest in understanding how interactions between genes and the environment underlie human phenotypes. The course will cover the underlying concepts, computational resources, and computational modelling methods available to investigate interactions between genes and the environment (including social, biological, and physical exposures).

Learning outcomes

After the course, you should be able to:

-Discuss the types, limitations, and advantages of human cohort datasets.
-Discuss the types, limitations, and advantages of different environmental readouts, including proxies for exposures in human cohorts.
-Explain the ethical and legal frameworks governing human data reuse and request access to datasets of interest in compliance with legal and ethical standards.
-Use and explain the need for Federated/Trusted Research Environments.
-Employ relevant computational methods and resources to investigate gene and environment interactions and interpret the results.
-Understand how to apply techniques (GWAS, Mendelian Randomisation, predictive modelling) to analyse cohort datasets and how to interpret these results.

Course content

- How to predict gene and environment interactions in human cohort datasets: study design, analysis techniques and interpretation.
- Tools and services available for investigating gene and environment interaction (e.g. GWAS catalogue, EGA)
- Computational Modeling strategies to integrate Genotype * Environmental effects.
- Ethical and legal frameworks relating to human cohorts considering: privacy and data security, informed consent, issues related to genetic discrimination, ethical issues related to new technologies