Defining the normal ranges of blood count as a function of demographic variables and genetic analysis of blood count parameters
Principal Investigator: Dr William Astle
Approved Research ID: 13745
Approval date: June 1st 2013
Our groups investigate the genetics and epidemiology of blood counts with the aims of i) optimising blood donation policies and ii) understanding the molecular mechanisms of blood formation. Our ultimate goals are to develop personalized blood donation schedules and to improve diagnosis and therapies for blood diseases. We have completed genome wide association analyses involving 150,000 individuals and found 140 regions of the genome implicated in regulating the formation of red cells and platelets. We are currently sequencing these regions of the genome in 2000 individuals with extreme red cell volume or platelet count ascertained from the LifeLines cohort of 100,000 individuals, to discover rare variants that affect the formation of these cells. We seek access to the complete Biobank data to: 1) better define ranges of blood parameters in the UK population, and with unprecedented power, establish how demographic variables such as age and gender affect them. This will be of particular interest for our INTERVAL trial of 50,000 blood donors, which aims to optimise blood donation frequency, by allowing us to better interpret the effects of blood donation. 2) Assess the impact on blood parameters of other variables collected by Biobank, particularly laboratory and nutrition-related data. 3) Investigate blood parameters measured by Biobank that are not routinely measured clinically but that may be better reporters of blood formation such as immature reticulocyte fraction. 3) Study the relationship between blood indices, mortality and cancer. 4) Carry out genome wide association studies, once UKBiobank genotypes become available, of blood parameters to identify genetic determinants of blood formation. Because of the large number of parameters we wish to study we seek access to Biobank?s complete data on the full cohort but do not need samples. As they become available we also seek access to genotypes, mortality outcomes, repeat measurements and biochemistry results.