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linusschumacher.bsky.social
@linusschumacher.bsky.social
Cobbling together data and models at the Centre for Regenerative Medicine in Edinburgh. Interested in the collective behaviour of cells in development and regeneration, and better ways of sciencing.
Congratulations Matt!
April 8, 2025 at 9:01 AM
Reposted
Our framework enables more accurate prediction of CH's clinical impact, moving us closer to personalized risk assessment and potential intervention strategies.
March 7, 2025 at 1:10 PM
Reposted
MACS120 outperformed traditional measurements (like variant allele frequency) in predicting mortality risk and showed increased correlations with the speed of change in blood markers like lymphocyte and albumin levels.
March 7, 2025 at 1:10 PM
Reposted
Considering these factors, we developed MACS120 - a novel metric that combines mutation fitness and acquisition timing to predict maximum clone size a mutation will reach over a lifetime.
March 7, 2025 at 1:10 PM
Reposted
Third, we discovered a strong correlation between mutation timing, or age at time of mutation acquisition (ATMA), and fitness. Higher fitness mutations tend to appear later in life - possibly due to declining quality control mechanisms with age.
March 7, 2025 at 1:10 PM
Reposted
Similarly, mutations can have different fitness effects depending on what other mutations are present in the same clone. For example, ASXL1 mutations have higher fitness when co-occurring with SRSF2 than with TET2.
March 7, 2025 at 1:10 PM
Reposted
Second, we found that clonal coexistence matters! Mutations don't grow in isolation - when multiple clones are present in the same person, they alter each other's overall contribution to the production of blood cells.
March 7, 2025 at 1:10 PM
Reposted
First, we confirmed gene-specific fitness differences: RNA splicing mutations (like U2AF1, U2AF2) show higher fitness than epigenetic regulator mutations (like DNMT3A, TET2).
March 7, 2025 at 1:10 PM
Reposted
Our key insight: Three factors, mutation fitness (growth advantage), mutation timing, and clonal structure (which mutations occur together) are needed to understand the progression and clinical impact of CH.
March 7, 2025 at 1:10 PM
Reposted
We integrated data from 713 individuals across 3 longitudinal aging cohorts (2,341 observations total) and developed models to understand the dynamics of CH mutations over time. #CancerResearch #ClonalHematopoiesis
March 7, 2025 at 1:10 PM
Reposted
Clonal hematopoiesis (CH) is common in aging populations and associated with increased risk of blood cancers and other diseases. But what determines which CH mutations will progress to disease?
March 7, 2025 at 1:10 PM
Reminds me of my PhD work modelling neural crest migration (+ earlier work by Louise Dyson). Great to see your thorough exploration of this in other biological systems as well
journals.biologists.com/dev/article/...
www.sciencedirect.com/science/arti...
www.sciencedirect.com/science/arti...
Neural crest migration is driven by a few trailblazer cells with a unique molecular signature narrowly confined to the invasive front
Summary: Single cell mRNA profiling defines a group of leading cells in migratory neural crest. Key factors expressed in these cells regulate the behaviour of the migrating neural crest population.
journals.biologists.com
January 9, 2025 at 11:00 AM
You should chat to incoming Collaboratorium fellow Eric Latorre-Crespo about clonal haematopoeisis and ageing.
November 19, 2024 at 1:22 PM