Approved Research

Investigating the roles of genetic architecture, socioeconomic factors, and environmental characteristics in chronic disease

Lay summary

This study will focus on how environmental factors influence disease outcome when paired with genetic variations. These types of studies are called gene-environment analyses and require many more participants than do standard genome-wide studies, which test whether only genetics influence disease. The UKB data provides us with the ideal population to continue our research in gene-environment interactions.

Our first goal is to examine gene-environment interactions of rare and common variants in a number of mental health disorders, including post-traumatic stress disorder, bipolar disorder, and schizophrenia, as well as diseases such as obesity and heart disease. In other words, we will examine if a specific genetic variation, when paired with either a socio-demographic characteristic or a specific environmental factor (such as pollution, income level, or a traumatic childhood event) influence the outcome of disease to any extent. Environmental variables in this investigation include traumatic childhood events, alcohol intake, gambling status, educational and income level.

Our second aim is to identify and validate rare variants associated with obesity, heart disease, and schizophrenia. As these are rare variations in the genome, a large number of participants are required to generate robust results. Again, the UKB provides us with the ideal population to a) identify rare variants associated with disease and b) validate the rare variants we have previously identified.

The UK Biobank with its genetic data and detailed participant questionnaires will provide a rich analytical basis with which to discover and validate predictive models of health and wellness traits. This research will provide a better framework for understanding the specific causes of several disorders, whether genetic or environmental, and improve our ability to predict outcomes and target interventions. Moreover, it will enable actionable and individualized results, which we predict will increase the popularity, diversity, and impact of personal genomics.