Discovery and replication of low-frequency variants involved in complex diseases
Principal Investigator: Dr David Torrents
Approved Research ID: 16803
Approval date: January 11th 2016
We have recently developed novel methodologies and approaches to re-analyze existing GWAS data through combined genotype imputation of several reference panels. We propose to use the UK Biobank as a replication dataset for the current findings. Our studies are focused on type 2 diabetes and related clinical variables such as glycemic traits. I would be also interested in obtaining primary care data and adjudicated diabetes when available. The discovery of variants associated to metabolic diseases are key to generate novel hypothesis for the diagnosis, treatment, prevention, and early detection of the disease. In that sense, the UK Biobank will help replicate, and enhance the power of our current studies. It therefore, clearly meets the UK Biobank stated purpose. We have identified a subset of genetic variants associated with type 2 diabetes (T2D). In order to confirm these findings, and also to strengthen the power, we will meta-analyze the results we obtained in our discovery sample with the results obtained in the UK Biobank We intend to use the full cohort, and compare all the individuals suffering the metabolic condition, i. e. type 2 diabetes, with the rest of individuals not suffering this disease.