Validation of clonal haematopoiesis prediction model developed on data from the UK-Biobank

Somatic mutations in haematopoietic stem cells continually occur in all individuals throughout their lives. The presence of expanded clones of mutated cells (clonal haematopoiesis) is highly prevalent in older adults but is also a known precursor to haematological malignancies such as acute myeloid leukaemia. A better quantitative understanding of the dynamics of CH could therefore lead to a powerful tool for early cancer detection.
The primary focus of our project is to use the UK Biobank (single-timepoint data) to model healthy clonal dynamics on a population scale, in particular exploring factors such as how clonal dynamics change with age, diversity in growth rates between individuals and the effect of clonal competition within individuals. Solely using low-depth single timepoint data has limitations however, and we plan to use longitudinal data (such as Lifelines) to help validate the predictions from our models and inform further research. 
An accurate quantitative understanding of CH could be the basis for effective population-scale early detection of blood cancers, provide insights into healthy ageing, and would also enhance our ability to distinguish rare pathogenic germline variants in CH driver genes such as TP53.