The evolutionary dynamics and fitness landscape of clonal haematopoiesis

Publication type

Journal Article

Published in

bioRxiv

Authors

Caroline J. Watson, Alana Papula, Yeuk P.G. Poon, Wing H. Wong, Andrew L. Young, Todd E. Druley, Daniel S. Fisher and Jamie R. Blundell

Publication date

Summary

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.

DOI

https://doi.org/10.1101/569566

Subjects

Older People, Health, Life Course Analysis, Biology and Genetics

Notes

The copyright holder for this preprint (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.; Studies included in analysis - ECS: Error-corrected sequencing, HPFS: Health Professionals Follow-Up Study, MSKCC: Memorial Sloan Kettering Cancer Center, NBS: Nijmegen Biomedical Study, NHS: Nurses Health Study, smMIPs: Single Molecule Molecular Inversion Probes, T2DM: Type 2 Diabetes Mellitus, UKHLS: UK Household Longitudinal Study, WES: Whole Exome Sequencing, WGS: Whole Genome Sequencing, WHI: Women’s Health Initiative, WTCCC: Wellcome Trust Case Control Consortium