Clonal haematopoiesis (CH) -- the ubiquitous expansion of variants in blood with age -- is increasingly recognized to be a result of ongoing somatic evolution in normal human tissues. However, the details of the underlying evolutionary processes driving these clonal dynamics are not yet fully understood. In this ongoing project, we have analysed publicly available donor data describing time resolved trajectories of individual CH variants. We hypothesize that clonal competition explains much of the observed complex dynamics observed in these data. To test this, we developed a mathematical model of clonal interference that describes the continuous occurrence of numerous clones of differing fitness expanding and competing for dominance. This competition induces an emerging fitness landscape of haematopoietic stem cells (HSCs) that changes over time in a highly stochastic manner within and between individuals. Comparisons of stochastic simulations of the model to time resolved clone trajectories in 385 individuals, and to changes of the HSC site frequency spectrum from newborns to octogenarians converge to nearly identical estimates of the innate CH fitness distribution and the arrival rate of advantageous clones. A preprint of this work can be found here https://www.biorxiv.org/content/10.1101/2024.04.16.589764v1.
We wish to extend this work by testing the model inference on two-timepoint trajectories, such as those found in the requested dataset, as well as comparing our model predictions with prevalences of largely expanded mutant clones with age. We are interested in both the number of expanded clones observed in single individuals with age, as well as the size distribution of such observed variants. The requested dataset would be a great resource for this by providing variant allele frequency information in a large cohort of individuals. We believe testing our model predictions against these data could contribute to our collective understanding of clonal dynamics and the role of clonal competition in CH.