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Longitudinal dynamics of clonal hematopoiesis identifies gene-specific fitness effects

Clonal hematopoiesis of indeterminate potential (CHIP) increases rapidly in prevalence beyond age 60 and has been associated with increased risk for malignancy, heart disease and ischemic stroke. CHIP is driven by somatic mutations in hematopoietic stem and progenitor cells (HSPCs). Because mutation...

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Detalles Bibliográficos
Autores principales: Robertson, Neil A., Latorre-Crespo, Eric, Terradas-Terradas, Maria, Lemos-Portela, Jorge, Purcell, Alison C., Livesey, Benjamin J., Hillary, Robert F., Murphy, Lee, Fawkes, Angie, MacGillivray, Louise, Copland, Mhairi, Marioni, Riccardo E., Marsh, Joseph A., Harris, Sarah E., Cox, Simon R., Deary, Ian J., Schumacher, Linus J., Kirschner, Kristina, Chandra, Tamir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9307482/
https://www.ncbi.nlm.nih.gov/pubmed/35788175
http://dx.doi.org/10.1038/s41591-022-01883-3
Descripción
Sumario:Clonal hematopoiesis of indeterminate potential (CHIP) increases rapidly in prevalence beyond age 60 and has been associated with increased risk for malignancy, heart disease and ischemic stroke. CHIP is driven by somatic mutations in hematopoietic stem and progenitor cells (HSPCs). Because mutations in HSPCs often drive leukemia, we hypothesized that HSPC fitness substantially contributes to transformation from CHIP to leukemia. HSPC fitness is defined as the proliferative advantage over cells carrying no or only neutral mutations. If mutations in different genes lead to distinct fitness advantages, this could enable patient stratification. We quantified the fitness effects of mutations over 12 years in older age using longitudinal sequencing and developed a filtering method that considers individual mutational context alongside mutation co-occurrence to quantify the growth potential of variants within individuals. We found that gene-specific fitness differences can outweigh inter-individual variation and, therefore, could form the basis for personalized clinical management.