| Application: | 55154, Identifying gene-by-environment interplay in, and the genetic architecture of, health and human capital outcomes. |
| Title: | Reweighting the UK Biobank to reflect its underlying sampling population substantially reduces pervasive selection bias due to volunteering |
| Size: | 7.1 MB |
| Archived: | 5 Dec 2023 |
| Stability: | Complete |
| Personal: | Contains individual-level data |
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Notes
This file contains inverse probability weights based on UK census microdata for UKB respondents.Application 55154
Identifying gene-by-environment interplay in, and the genetic architecture of, health and human capital outcomes.
We aim to gain insight into socioeconomic inequality and its effects on an individual's health and capabilities. Using the UKB data, we will focus on several outcomes related to health (e.g., smoking, drinking, obesity), human capital (e.g., education, personality traits, employment), and behaviour (e.g., risk taking), to increase knowledge of the biology underlying these traits, and the relationships among them. Further, we seek to quantify how several risk factors (e.g., lifestyle, environment, genetics), both separately, and in combination, influence human capabilities and health. The duration of the entire project will be around 3 to 5 years. The project will be divided in various sub-projects, each answering specific research questions, resulting in multiple independent publications. The impact on public health of this project is at least three-fold: - First, a better understanding of the genetic architecture of, and the interdependency among, complex traits, is expected to provide new knowledge about shared biology and point to avenues for future research investigating these complex traits. Besides being of value in advancing basic research, this may help identify and / or improve existing treatment and prevention options relating to health and human-capital outcomes. - Second, GxE interplay research may point to modifiable characteristics of socioeconomic and policy environments, identify critical periods of life and subpopulations at greater risk (not necessarily identified by their genetic information [but, e.g., by associated behaviour]), and through causal analyses point to mechanisms. Such information is useful to health professionals and policy makers, pointing to means of medical and policy intervention. - Third, this research may aid individuals by allowing them to use personal genetic information preventively by avoiding environments that may harm them.
| Lead investigator: | Dr Titus Galama |
| Lead institution: | VU University Amsterdam |
Enabling scientific discoveries that improve human health