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305 Leveraging multi-timepoint blood samples to characterize cancer-associated mutations in the blood over time
OBJECTIVES/GOALS: Clonal hematopoiesis of indeterminate potential (CHIP) is a common age-related condition that confers an increased risk of blood cancer, cardiovascular disease, and overall mortality. Larger proportions of blood cells with the CHIP mutation (clones) lead to worse outcomes. The goal...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10129680/ http://dx.doi.org/10.1017/cts.2023.358 |
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author | Mack, Taralynn Von Beck, Kelly Silver, Alexander Savona, Michael Vanderbilt, Alexander Bick |
author_facet | Mack, Taralynn Von Beck, Kelly Silver, Alexander Savona, Michael Vanderbilt, Alexander Bick |
author_sort | Mack, Taralynn |
collection | PubMed |
description | OBJECTIVES/GOALS: Clonal hematopoiesis of indeterminate potential (CHIP) is a common age-related condition that confers an increased risk of blood cancer, cardiovascular disease, and overall mortality. Larger proportions of blood cells with the CHIP mutation (clones) lead to worse outcomes. The goal of this study was to characterize CHIP clonal behavior over time. METHODS/STUDY POPULATION: While DNA biobanks have the ability to identify large cohorts of individuals with CHIP, they typically only contain blood from a single timepoint, limiting the ability to infer how CHIP clones change over time. In this preliminary study, we utilized multi-timepoint blood samples from 101 individuals with CHIP in Vanderbilt’s biobank (BioVU) to characterize clonal behavior over time. Using a CHIP gene-specific sequencing pipeline, we were able to characterize each individual’s CHIP mutation(s) and how the fraction of cells with the CHIP mutation expanded/reduced over time. By Spring 2023, we will also include ~300 additional individuals with CHIP in this study. RESULTS/ANTICIPATED RESULTS: CHIP mutations occurred 48% of the time in DNMT3A and 23% of the time in TET2, consistent with previous studies. 21% of individuals had more than one CHIP mutation. The mean difference in time between the two timepoints was 5.2 years (SD=2.9). Surprisingly, we observed both clonal expansion and clonal reduction across timepoints with 30% of DNMT3A, 0.6% of TET2, and 46% of JAK2 clones shrinking over time. The fastest average expansion was seen in TET2 clones (2% growth/year) and the slowest in DNMT3A clones (0.4% growth/year), but there was a significant amount of variation between individuals. In DNMT3A clones, there were no differences observed between loss of function mutations, missense mutations or DNMT3A R882 hotspot mutations. Clonal competition was observed in individuals with multiple driver mutations. DISCUSSION/SIGNIFICANCE: We used multi-timepoint blood samples to quantify the change in CHIP cell fraction over time on a per individual basis and observed novel clonal behavior and competition. Understanding the factors that influence the rate of CHIP progression can lead to personalized disease risk assessment for individuals with CHIP. |
format | Online Article Text |
id | pubmed-10129680 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-101296802023-04-26 305 Leveraging multi-timepoint blood samples to characterize cancer-associated mutations in the blood over time Mack, Taralynn Von Beck, Kelly Silver, Alexander Savona, Michael Vanderbilt, Alexander Bick J Clin Transl Sci Precision Medicine/Health OBJECTIVES/GOALS: Clonal hematopoiesis of indeterminate potential (CHIP) is a common age-related condition that confers an increased risk of blood cancer, cardiovascular disease, and overall mortality. Larger proportions of blood cells with the CHIP mutation (clones) lead to worse outcomes. The goal of this study was to characterize CHIP clonal behavior over time. METHODS/STUDY POPULATION: While DNA biobanks have the ability to identify large cohorts of individuals with CHIP, they typically only contain blood from a single timepoint, limiting the ability to infer how CHIP clones change over time. In this preliminary study, we utilized multi-timepoint blood samples from 101 individuals with CHIP in Vanderbilt’s biobank (BioVU) to characterize clonal behavior over time. Using a CHIP gene-specific sequencing pipeline, we were able to characterize each individual’s CHIP mutation(s) and how the fraction of cells with the CHIP mutation expanded/reduced over time. By Spring 2023, we will also include ~300 additional individuals with CHIP in this study. RESULTS/ANTICIPATED RESULTS: CHIP mutations occurred 48% of the time in DNMT3A and 23% of the time in TET2, consistent with previous studies. 21% of individuals had more than one CHIP mutation. The mean difference in time between the two timepoints was 5.2 years (SD=2.9). Surprisingly, we observed both clonal expansion and clonal reduction across timepoints with 30% of DNMT3A, 0.6% of TET2, and 46% of JAK2 clones shrinking over time. The fastest average expansion was seen in TET2 clones (2% growth/year) and the slowest in DNMT3A clones (0.4% growth/year), but there was a significant amount of variation between individuals. In DNMT3A clones, there were no differences observed between loss of function mutations, missense mutations or DNMT3A R882 hotspot mutations. Clonal competition was observed in individuals with multiple driver mutations. DISCUSSION/SIGNIFICANCE: We used multi-timepoint blood samples to quantify the change in CHIP cell fraction over time on a per individual basis and observed novel clonal behavior and competition. Understanding the factors that influence the rate of CHIP progression can lead to personalized disease risk assessment for individuals with CHIP. Cambridge University Press 2023-04-24 /pmc/articles/PMC10129680/ http://dx.doi.org/10.1017/cts.2023.358 Text en © The Association for Clinical and Translational Science 2023 https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work. |
spellingShingle | Precision Medicine/Health Mack, Taralynn Von Beck, Kelly Silver, Alexander Savona, Michael Vanderbilt, Alexander Bick 305 Leveraging multi-timepoint blood samples to characterize cancer-associated mutations in the blood over time |
title | 305 Leveraging multi-timepoint blood samples to characterize cancer-associated mutations in the blood over time |
title_full | 305 Leveraging multi-timepoint blood samples to characterize cancer-associated mutations in the blood over time |
title_fullStr | 305 Leveraging multi-timepoint blood samples to characterize cancer-associated mutations in the blood over time |
title_full_unstemmed | 305 Leveraging multi-timepoint blood samples to characterize cancer-associated mutations in the blood over time |
title_short | 305 Leveraging multi-timepoint blood samples to characterize cancer-associated mutations in the blood over time |
title_sort | 305 leveraging multi-timepoint blood samples to characterize cancer-associated mutations in the blood over time |
topic | Precision Medicine/Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10129680/ http://dx.doi.org/10.1017/cts.2023.358 |
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