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Clonal haematopoiesis is thought to be a rare condition that increases in frequency with age and predisposes individuals to haematological malignancy. Recent studies, utilizing next-generation sequencing (NGS), observed haematopoietic clones in 10% of 70-year olds and rarely in younger individuals. However, these studies could only detect common haematopoietic clones—>0.02 variant allele fraction (VAF)—due to the error rate of NGS. To identify and characterize clonal mutations below this threshold, here we develop methods for targeted error-corrected sequencing, which enable the accurate detection of clonal mutations as rare as 0.0003 VAF. We apply these methods to study serially banked peripheral blood samples from healthy 50–60-year-old participants in the Nurses' Health Study. We observe clonal haematopoiesis, frequently harbouring mutations in DNMT3A and TET2, in 95% of individuals studied. These clonal mutations are often stable longitudinally and present in multiple haematopoietic compartments, suggesting a long-lived haematopoietic stem and progenitor cell of origin.

Acquired mutations are pervasive across normal tissues. However, our understanding of the processes that drive transformation of certain clones to cancer is limited. Here we study this phenomenon in the context of clonal hematopoiesis (CH) and the development of therapy-related myeloid neoplasms (tMN). We find mutations are selected differentially based on exposures. Mutations in ASXL1 are enriched in current or former smokers, whereas cancer therapy with radiation, platinum and topoisomerase II inhibitors preferentially selects for mutations in DNA damage response (DDR) genes ( TP53, PPM1D, CHEK2 ). Sequential sampling provides definitive evidence that DDR clones outcompete other clones when exposed to certain therapies. Among cases where CH was previously detected, the CH mutation was present at tMN diagnosis. We identify the molecular characteristics of CH that increase risk of tMN. The increasing implementation of clinical sequencing at diagnosis provides an opportunity to identify patients at risk of tMN for prevention strategies.

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 remains largely unknown. Blood sequencing data from ~50,000 individuals reveal how mutation, genetic drift, and fitness shape the genetic diversity of healthy blood (clonal hematopoiesis). We show that positive selection, not drift, is the major force shaping clonal hematopoiesis, provide bounds on the number of hematopoietic stem cells, and quantify the fitness advantages of key pathogenic variants, at single-nucleotide resolution, as well as the distribution of fitness effects (fitness landscape) within commonly mutated driver genes. These data are consistent with clonal hematopoiesis being driven by a continuing risk of mutations and clonal expansions that become increasingly detectable with age.

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