Health

Blood Test Could Predict Risk of Leukemia Years in Advance

Leukemia Blood Test

According to a new study, a blood test could predict the risk of developing leukemia years in advance.

By identifying changes in blood cell production, a blood test could predict the risk of developing leukemia in the elderly population years in advance, according to new research.

Experts say that identifying those most at risk should make it possible to provide preventive or early treatment in the future to improve patient outcomes.

Leukemia is often caused by the disruption of the delicate balance in blood cell production where new cells are manufactured and old blood cells die.

Mutations in blood stem cells as we age can mean that the altered cells can have a growth benefit over other blood cells and outnumber them in what is referred to as fitness advantage.

Scientists from the Universities of Edinburgh and Glasgow investigated how changes in fitness advantage that occur in blood production might provide clues to the risk of developing leukemia depending on the type of mutation that occurs.

”We measured changes in the blood samples of 83 older individuals of the Lothian Birth Cohorts, taken every three years over a 12-year period. Using the combined knowledge of mathematicians, biologists, and genome scientists, we set out to understand what these changes mean for our risk of developing leukemia as we grow older,” said Dr. Tamir Chandra, a chancellor’s fellow at the MRC Human Genetics Unit in Edinburgh.

The Lothian Birth Cohorts 1921 and 1936 are longitudinal studies of brain, cognitive and general aging which have followed up individuals every 3 years between the ages of 70 and 82 for the 1921 cohort and the ages of 79 to 92 for 1936.

The research team then combined these complex genomic data with a machine-learning algorithm to link different mutations with different growth speeds of blood stem cells carrying these mutations.

They discovered that specific mutations give distinct fitness advantages to stem cells measured in people without leukemia, which can then be used to forecast how quickly the mutated cells will grow, and therefore determine leukemia risk.

According to the scientists, further research is needed to validate these results in a larger population due to the limited sample size in the current study.

Dr. Kristina Kirschner, co-lead author and Senior Lecturer at the University of Glasgow’s Institute of Cancer Sciences, said: “In knowing an individual patient’s risk of developing leukemia, clinicians can schedule shorter gaps between appointments in those most likely to develop the disease and provide early treatment, which is more likely to be successful.”

Dr. Linus Schumacher, co-lead author and Chancellor’s Fellow at the Centre for Regenerative Medicine of the University of Edinburgh, said: “To understand leukemia risk, we need to consider the balance between the different cells involved in blood cell production and how this balance changes as we grow older. By linking genomic data with machine learning we have been able to predict the future behavior of blood cells based on the mutations they develop.”

Reference: “Longitudinal dynamics of clonal hematopoiesis identifies gene-specific fitness effects” by Neil A. Robertson, Eric Latorre-Crespo, Maria Terradas-Terradas, Jorge Lemos-Portela, Alison C. Purcell, Benjamin J. Livesey, Robert F. Hillary, Lee Murphy, Angie Fawkes, Louise MacGillivray, Mhairi Copland, Riccardo E. Marioni, Joseph A. Marsh, Sarah E. Harris, Simon R. Cox, Ian J. Deary, Linus J. Schumacher, Kristina Kirschner and Tamir Chandra, 4 July 2022, Nature Medicine.
DOI: 10.1038/s41591-022-01883-3

These findings have been published in the journal Nature Medicine. This research was funded by the Medical Research Council, Leukemia UK, and Cancer Research UK.

The Lothian Birth Cohort receives funding from Biotechnology and Biological Sciences Research Council, the Economic and Social Research Council, Age UK, Wellcome, the Royal Society, the Medical Research Council and the University of Edinburgh.

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University of Glasgow

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