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Updated: Jun 19, 2026

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma
Published on: December 28, 2015
Mathematical modeling of JAK2V617F clonal expansion in a general population cohort
Jordan Snyder1,2, Morten Andersen1, Johanne Gudmand-Høyer1
1Department of Science and Environment, Centre for Mathematical Modeling - Human Health and Disease, IMFUFA, Roskilde University, Roskilde 4000, Denmark.
Abstract:
The Philadelphia chromosome-negative myeloproliferative neoplasms (MPNs) are a group of blood cancers characterized by overproduction of one or more types of blood cells, which can lead to thrombosis and other complications. MPNs develop slowly and are driven by a relatively small set of mutations in the hematopoietic stem cells (HSCs). Their slow development (over the course of decades) affords a unique opportunity to study their onset, but until recently few data have been available from individuals not yet showing overt disease. Thanks to the ambitious Danish General Suburban Population Study conducted in suburban Zealand, Denmark, we have identified a ([Formula: see text]) cohort of individuals harboring the most common driver mutation in MPN (namely JAK2V617F) and have obtained follow-up measurements of their variant allele fraction (VAF) spanning over 10 y. We show that these data are consistent with a Moran model governing the competition between healthy and mutated HSCs, and estimate the selective advantage of the mutant clone for each individual. Notably, we find that for many individuals, the change in VAF over many years is statistically consistent with zero, or even negative, selective advantage. This is in contrast to prior studies that have focused on patients diagnosed with overt MPN disease, in whom the mutant cells are almost always found to outcompete the healthy cells. Our results have implications for our understanding of the very early phases of MPN disease, and may contribute to early detection and personalized prediction of disease progression.
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