Approved Research

Methods development and methodological extensions to jointly analyze multifaceted biobank-scale data and outcomes

Lay summary

We will investigate and develop new approaches that allow us to scale and analyze the full complexity available in a biobank. We will build our methods and models on the UK Biobank, but we hope that our methods can be built to be flexibly used in other biobanks as well. We'll also extend existing approaches that use genome-wide association study summary statistics, to consider more sophisticated models that capture a broader range of possible effects across correlated outcomes, and we'll combine these summary statistics along with other data types, including imaging data, health linkage data, biomarker data, activity data, and the rich questionnaire data that has become a hallmark of the incredible UK Biobank dataset.

This work is in line with the UK Biobank's aim of enabling research to improve "prevention, diagnosis and treatment of illness and the promotion of health throughout society". It will not focus on one particular outcome, but instead apply these methods to learn about a wide range of traits through hypothesis-free approaches and methods development. We are hopeful that our approach will not only be useful to health researchers who wish to understand how to jointly utilize the richness of biobank-scale data, but will also play a major role in driving a more sophisticated public health understanding of the multifaceted and highly correlated nature of human health. We expect the first goals of our project to take 3 years, and so we are requested to be reviewed using the 3-year rolling period.