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Approved research

Identifying genetic and environmental factors underpinning complex trait variation in humans

Principal Investigator: Professor Jian Yang
Approved Research ID: 54336
Approval date: September 25th 2019

Lay summary

Most human traits (including common diseases) are affected by many genetic and environmental factors. Results from GWAS have been proven valuable for identifying genetic factors responsible for the phenotypic differences between individuals and are potentially useful for predicting an individual's risk of developing a disease. Besides the genetic factors, an increasing number of lifestyle and environmental factors that can trigger and exacerbate a condition have been documented. Thus, it is essential to collect phenotypic and genotypic data from a very large cohort (e.g., hundreds of thousands to millions of individuals) to identify the genetic and environmental factors and to yield clinically actionable predictors. With the advances in sequencing technologies and the cooperative research effort, UKB has provided a comprehensive resource of genetic and non-genetic data on an immense scale. In this project, we aim to decipher the genetic and environmental factors underpinning complex trait variation in humans by developing sophisticated statistical models and applying them to the analyses of the genomic data on approximately 500,000 individuals with more than 3,000 traits in the UKB sample. For all the traits available in the UKB, we will estimate the proportion of the phenotypic variation explained by all common and rare variants and the distribution of the effects of those variants. We will also identify lifestyle factors that are causally linked to diseases and will predict disease risks of healthy individuals by integrative analysis of both genetic and lifestyle factors. This is crucial to the understanding of the disease etiology and prevention, of great importance for public health, and also in concordance with the UKB's stated purpose. Through the development of robust and powerful statistical methods, together with a large sample from the UKB, we will uncover additional sources of the 'missing heritability', identify new environmental/lifestyle risk factors, and improve the prediction accuracy for diseases. Genomics is a fast-moving field and creating a widening knowledge gap between cutting-edge genomics research and current clinical practices. The combination of new data and new methods will take us into an era of personalized and precision treatments based on individual's gene, environment, and lifestyle, which has the potential to have a significant impact on health care.