Approved research

Statistical methods for understanding genetic basis of complex diseases/traits

Lay summary

While Genome-wide association studies (GWAS) have successfully identified thousands of genetic variants with hundreds of complex traits, genetic variability is still not fully explained and disease mechanism between genetic variants and traits is not well understood. Large-scale analysis and new statistical or state-of-art computing methods are needed to identify and characterize the novel susceptibility genetic variations. We aim to use UK biobank to discover the novel associations and their associated risk factors, and to validate the findings obtained in other consortium. We will apply the existing methods and also develop the novel statistical approaches to perform analyses of multiple diseases/traits. Our diseases/traits of interest include: cancers, aging traits, neurological disorders, cardiovascular diseases and their associated risk factors. The accomplishment of this project can lead to a better understanding of genetic architecture of our studied diseases.