The evolutionary dynamics and fitness landscape of clonal haematopoiesis

Abstract

Somatic mutations acquired in healthy tissues as we age are major determinants of cancer risk. Whether variants confer a fitness advantage or rise to detectable frequencies by chance, however, remains largely unknown. Here, by combining blood sequencing data from ∼50,000 individuals, we reveal how mutation, genetic drift and fitness differences combine to shape the genetic diversity of healthy blood ('clonal haematopoiesis'). By analysing the spectrum of variant allele frequencies we quantify fitness advantages for key pathogenic variants and genes and provide bounds on the number of haematopoietic stem cells. Positive selection, not drift, is the major force shaping clonal haematopoiesis. The remarkably wide variation in variant allele frequencies observed across individuals is driven by chance differences in the timing of mutation acquisition combined with differences in the cell-intrinsic fitness effect of variants. Contrary to the widely held view that clonal haematopoiesis is driven by ageing-related alterations in the stem cell niche, the data are consistent with the age dependence being driven simply by continuing risk of mutations and subsequent clonal expansions that lead to increased detectability at older ages. clonal haematopoiesis | haematopoietic stem cells | evolution | population genetics | DNMT3A | TET2 | spliceosome | TP53 | acute myeloid leukaemia Correspondence: cw672@cam.ac.uk & jrb75@cam.ac.uk ResultsThe VAF distribution from ∼50,000 individuals. We analysed VAF measurements for somatic variants in the blood from ∼50,000 blood-cancer-free individuals from nine publicly available blood sequencing datasets 7-15 (Supplementary Information 1). VAF measurements in bone marrow and peripheral blood show good concordance 30 and so Watson | bioRχiv |

Clonal hematopoiesis and non-hematologic disorders

“…We still have limited understanding of what causes a clone to grow in size in some, but remain stagnant in others. Mutation-specific effects are certain to have a role, 106 but what about cell-extrinsic factors? Finally, a greater understanding of the mechanisms by which these mutations alter immune responses to cause disease is needed in order to rationally identify therapies that can be used to prevent the negative consequences associated with CHIP.…”

Measuring the distribution of fitness effects in somatic evolution by combining clonal dynamics with dN/dS ratios

“…Most prominently is lineage tracing of mutations in mouse models 4,5 , but these methods are not sufficiently high-throughput to produce the DFE for all somatic mutations. Other studies have estimated the selective coefficient of somatic mutations by measuring the frequency of such mutations over time in the same individual using longitudinal sampling 6,7 however this method is broadly limited to somatic evolution in the blood (where it is feasible to take samples from healthy individuals over time) and in rare cases of patients under active surveillance.…”

Clonal hematopoiesis and therapy-related myeloid neoplasms following neuroblastoma treatment

“…Furthermore, all 3 patients with CH harbored at least 1 clone without a known driver mutation, which corroborates evidence that knowledge of the somatic events under selective pressure is incomplete and that driverless CH cannot be accounted for by neutral drift alone. 11,20,21 In the 2 patients with TMN, the preponderance of platinum signatures in nascent premalignant clones, high TMN mutation burdens, and 99% probability that the founding driver mutation in the tumor of patient 1 arose to therapy-related mutagenesis contrast sharply with findings in adult TMN. [2][3][4][5][6] Together, these results suggest that the role of therapy-related mutagenesis in pediatric TMN may extend beyond the rare generation of balanced translocations linked to topoisomerase II inhibitors.…”