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Methods for Estimating Personal Disease Risk and Phylogenetic Diversity of Hematopoietic Stem Cells.
Craig, Jack M; Gerhard, Glenn S; Sharma, Sudip; Yankovskiy, Anastasia; Miura, Sayaka; Kumar, Sudhir.
Afiliação
  • Craig JM; Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA.
  • Gerhard GS; Department of Biology, Temple University, Philadelphia, PA, USA.
  • Sharma S; Department of Medical Genetics and Molecular Biochemistry, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, USA.
  • Yankovskiy A; Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA.
  • Miura S; Department of Biology, Temple University, Philadelphia, PA, USA.
  • Kumar S; Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA.
Mol Biol Evol ; 41(1)2024 Jan 03.
Article em En | MEDLINE | ID: mdl-38124397
ABSTRACT
An individual's chronological age does not always correspond to the health of different tissues in their body, especially in cases of disease. Therefore, estimating and contrasting the physiological age of tissues with an individual's chronological age may be a useful tool to diagnose disease and its progression. In this study, we present novel metrics to quantify the loss of phylogenetic diversity in hematopoietic stem cells (HSCs), which are precursors to most blood cell types and are associated with many blood-related diseases. These metrics showed an excellent correspondence with an age-related increase in blood cancer incidence, enabling a model to estimate the phylogeny-derived age (phyloAge) of HSCs present in an individual. The HSC phyloAge was generally older than the chronological age of patients suffering from myeloproliferative neoplasms (MPNs). We present a model that relates excess HSC aging with increased MPN risk. It predicted an over 200 times greater risk based on the HSC phylogenies of the youngest MPN patients analyzed. Our new metrics are designed to be robust to sampling biases and do not rely on prior knowledge of driver mutations or physiological assessments. Consequently, they complement conventional biomarker-based methods to estimate physiological age and disease risk.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Transtornos Mieloproliferativos / Neoplasias Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Transtornos Mieloproliferativos / Neoplasias Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article