398: Modeling JAK2V617F Clonal Expansion in the General Population

398: Modeling JAK2V617F Clonal Expansion in the General Population

Snyder J et al., Proceedings of the National Academy of Sciences (PNAS) - Longitudinal VAF measurements from 67 JAK2V617F-positive participants in the Danish GESUS study were analyzed with a Moran-process stem cell model and ABC-SMC to infer per-individual self-renewal advantages and assess prognostic value for MPN progression. Key terms: JAK2V617F, clonal hematopoiesis, Moran model, myeloproliferative neoplasms, mathematical modeling.

Study Highlights:
The study follows 67 individuals from the GESUS cohort with >1% JAK2V617F VAF and multiple follow-up measurements over >10 years. A Moran-process model at the HSC level fitted by ABC-SMC reproduced longitudinal VAF trajectories for 66 of 67 subjects and yielded per-individual estimates of the mutant self-renewal advantage s. Results show heterogeneity: ~70% of subjects had a statistically positive s, ~18% had a negative s, and ~12% were neutral, indicating many carriers show no expansion or even contraction. The fitted model can predict future VAF evolution for most subjects but s alone is not a perfect predictor of MPN diagnosis.

Conclusion:
A stem-cell Moran-process model explains longitudinal JAK2V617F VAF dynamics in most GESUS participants; inferred selective advantage varies widely, correlates with—but does not fully predict—MPN diagnosis, supporting individualized monitoring and further study of non-VAF risk factors.

Music:
Enjoy the music based on this article at the end of the episode.

Article title:
Mathematical modeling of JAK2V617F clonal expansion in a general population cohort

First author:
Snyder J

Journal:
Proceedings of the National Academy of Sciences (PNAS)

DOI:
10.1073/pnas.2507773123

Reference:
Snyder J, Andersen M, Gudmand-Høyer J, et al. Mathematical modeling of JAK2V617F clonal expansion in a general population cohort. Proc Natl Acad Sci U.S.A. 2026;123:e2507773123. doi:10.1073/pnas.2507773123

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

Support:
Base by Base – Stripe donations: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00

Official website https://basebybase.com

On PaperCast Base by Base you'll discover the latest in genomics, functional genomics, structural genomics, and proteomics.

Episode link: https://basebybase.com/episodes/base398-jak2v617f-moran

QC:
This episode was checked against the original article PDF and publication metadata for the episode release published on 2026-06-21.

QC Scope:
- article metadata and core scientific claims from the narration
- excludes analogies, intro/outro, and music
- transcript coverage: Substantively audited sections include background on JAK2V617F and MPN, Moran process model with carrying capacity and generation time, ABC-SMC inference of per-subject s, results breakdown (positive/neutral/negative s and 66/67 fit), link between s and MPN progression, inflammation/CRP and statin discussion, and limit
- transcript topics: JAK2V617F mutation and myeloproliferative neoplasms biology; Moran process model and stem cell carrying capacity; Inference of per-individual selective advantage (s) via ABC-SMC; VAF trajectories across individuals and fit to the model; Association between s and progression to MPN; imperfect prediction; Inflammation (CRP) and statins as modifiers of clonal dynamics

QC Summary:
- factual score: 10/10
- metadata score: 10/10
- supported core claims: 8
- claims flagged for review: 0
- metadata checks passed: 4
- metadata issues found: 0

Metadata Audited:
- article_doi
- article_title
- article_journal
- license

Factual Items Audited:
- 67 individuals with >1% JAK2V617F VAF in...

Chapters
  • (00:00:00) - Can Your Body Naturally Suppress a Cancer Mutation?
  • (00:05:30) - The genetics of JAK2 cancer
  • (00:10:47) - The Stochastic Selection of MPN
  • (00:16:05) - JAK2 mutation and the immune system

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