Clonal dynamics of haematopoiesis across the human lifespan

Abstract

Age-related change in human haematopoiesis causes reduced regenerative capacity1, cytopenias2, immune dysfunction3 and increased risk of blood cancer4–6, but the reason for such abrupt functional decline after 70 years of age remains unclear. Here we sequenced 3,579 genomes from single cell-derived colonies of haematopoietic cells across 10 human subjects from 0 to 81 years of age. Haematopoietic stem cells or multipotent progenitors (HSC/MPPs) accumulated a mean of 17 mutations per year after birth and lost 30 base pairs per year of telomere length. Haematopoiesis in adults less than 65 years of age was massively polyclonal, with high clonal diversity and a stable population of 20,000–200,000 HSC/MPPs contributing evenly to blood production. By contrast, haematopoiesis in individuals aged over 75 showed profoundly decreased clonal diversity. In each of the older subjects, 30–60% of haematopoiesis was accounted for by 12–18 independent clones, each contributing 1–34% of blood production. Most clones had begun their expansion before the subject was 40 years old, but only 22% had known driver mutations. Genome-wide selection analysis estimated that between 1 in 34 and 1 in 12 non-synonymous mutations were drivers, accruing at constant rates throughout life, affecting more genes than identified in blood cancers. Loss of the Y chromosome conferred selective benefits in males. Simulations of haematopoiesis, with constant stem cell population size and constant acquisition of driver mutations conferring moderate fitness benefits, entirely explained the abrupt change in clonal structure in the elderly. Rapidly decreasing clonal diversity is a universal feature of haematopoiesis in aged humans, underpinned by pervasive positive selection acting on many more genes than currently identified.

Mutation rates and fitness consequences of mosaic chromosomal alterations in blood

“…Genes recurrently mutated in clonal haematopoiesis or haematological malignancies which may be putative target genes for loss, gain or CN-LOH events are labelled in blue, red and orange respectively. (8) in whom an mCA had to be observed in order to calculate the mCA's fitness effect and mutation rate. The majority of mCAs were most commonly seen in individuals as single events ('most common total number of mCAs: 1').…”

“…1) across the distribution of ages in UK Biobank (23.8% aged 40-49, 33.6% aged 50-59, 42.6% aged 60-69). A maximum likelihood approach was used for parameter estimation, minimising the L2 norm between the cumulative log rescaled densities and the cumulative predicted densities, for all datapoints, in order to optimise N τ µ and s. The mCA-specific mutation rate (µ) was estimated by dividing the maximum-likelihood inferred N τ µ by N τ of ∼100,000 (5,8,19) (Tables S1-S3, Figures ??-S13).…”

“…Mutations in haematopoietic stem and progenitor cells (HSPCs) which confer a 'Darwinian' fitness advantage can clonally expand to detectable levels in blood -a phenomenon known as clonal haematopoiesis (CH) (1)(2)(3)(4). Previous studies have developed population genetic frameworks for estimating the mutation rates and associated fitness effects of these mutations (5,6) and these estimates have been validated in subsequent studies leveraging serial sampling (7) and single-cell derived phylogenies (8). These previous analyses have largely focused on the fitness effects and mutation rates of single nucleotide variants (SNVs) in cancer-associated genes.…”

“…These previous analyses have largely focused on the fitness effects and mutation rates of single nucleotide variants (SNVs) in cancer-associated genes. However, recent studies have estimated that between 60%-80% of clonal expansions in healthy blood are driven by mutations outside of cancer-associated genes ( 6, 8 ), raising the prospect of large numbers of highly fit mutations beyond SNVs, which could have implications for cancer risk.…”

“…c. CN-LOH mCAs. The dashed vertical line indicates the minimum number of people(8) in whom an mCA had to be observed in order to calculate…”