Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Apr 1;110(4):1010-1018.
doi: 10.3324/haematol.2024.286513. Epub 2024 Nov 14.

Germline genetics, disease, and exposure to medication influence longitudinal dynamics of clonal hematopoiesis

Taralynn Mack  1 , Yash Pershad  1 , Caitlyn Vlasschaert  2 , Cosmin A Bejan  3 , Jonathan Brett Heimlich  4 , Yajing Li  5 , Nicole A Mickels  1 , Joseph C Van Amburg  1 , Jessica Ulloa  1 , Alexander J Silver  6 , Leo Y Luo  7 , Angela Jones  1 , Paul Brent Ferrell  8 , Ashwin Kishtagari  9 , Yaomin Xu  5 , Michael R Savona  10 , Alexander G Bick  11
Affiliations

Germline genetics, disease, and exposure to medication influence longitudinal dynamics of clonal hematopoiesis

Taralynn Mack et al. Haematologica. .
No abstract available

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
Cohort characteristics and co-occurring clonal hematopoiesis of indeterminate potential mutations. (A) Our cohort consists of 892 clonal hematopoiesis of indeterminate potential (CHIP) mutations in 711 individuals. We calculated growth rate using a compound interest formula for sequencing at 2 blood draws. (B) Larger bar plot demonstrates the number of CHIP with a mutation in a driver gene. Smaller bar plot shows the number of individuals with 1, 2, 3, and 4 CHIP mutations. (C) Box plot of growth rate, calculated with a compound interest formula, for each CHIP mutation by driver gene with number of individuals with mutations in the driver gene shown below the gene name. Red diamond represents the mean growth rate. Box represents the interquartile range of the growth rate. Middle line in the box represents the median of the growth rate. (D) Theoretical example of possible trajectories for individuals with two CHIP mutations. The mutations can either be in distinct cell populations or the same cell population. Variant allele fraction (VAF) trajectories for each of these scenarios should follow similar trends to this example. Each mutation is represented by color, and the line represents change in VAF between first and second blood draws. (E) Box plot showing the difference in average growth rate of the fastest growing mutations for the 116 individuals grouped into the distinct versus sub-clone categories. The red diamond represents the average of the growth rate. Box represents the interquartile range of the growth rate. Middle line in the box represents the median of the growth rate. The x-axis is the growth rate while the y-axis is the category. (F) Upset plot showing the different combinations of driver genes represented within the group of 116 individuals with multiple CHIP mutations. Above the upset plot is a bar plot showing the distribution between distinct versus sub-clone trajectories for each of the driver gene combinations, with driver gene on the x-axis and count on the y-axis. (G) Heat map showing the deviation from random for the co-occurrence of each driver gene pair for the 116 individuals with 2 CHIP mutations. Each gene pair was tested with a Fisher’s exact test to identify deviation from expected occurrence via random chance. The x- and y-axes represent each gene in a pair, the color of the box represents the direction of the deviation from random, and the darkness of the hue represents the magnitude of the deviation. For gene combinations with a P value >0.05, the odds ratio is displayed, and the box is marked with “*” and for gene combinations that passed multiple-hypothesis correction with a P value of <0.001, the odds ratio is displayed and the box is marked with “**”.
Figure 2.
Figure 2.
Determinants of clonal hematopoiesis of indeterminate potential growth rate. (A) Forest plot of change in annual growth rate (%/yr) with each additional copy of the alternate allele (alt) for select germline single nucleotide polymorphisms (SNP) detectable with the targeted sequencing assay among individuals with clonal hematopoiesis of indeterminate potential (CHIP) mutations. Effect estimate represents the coefficient of a linear regression of growth rate and number of alternate alleles modeled additively as 0, 1, or 2, adjusting for age, sex, race, and variant allele fraction (VAF) at first sequencing. We computed the 95% confidence interval (95% CI) as the effect estimate +/- 1.96 standard error. The P value tests the null hypothesis of the effect estimate being 0. (B) Violin plot of %/yr for 0 versus >1 G allele for germline variant chr11:108272729:C:G in ATM. When modeled additively, each additional G allele is associated with greater %/yr in multiple linear regression by 0.46% per year (95% CI: 0.23-0.67, P<0.001). There were 619 CHIP mutations in individuals with 0 G alleles, 26 in individuals with 1 G allele, and 2 in individuals with 2 G alleles. (C) Violin plot of %/yr for 0, 1, and 2 T alleles for germline variant chr14:95714358:G:T in TCL1A for DNMT3A CHIP (left) and TET2 CHIP (right). When modeled additively, each additional T allele is associated with greater %/yr for TET2 CHIP mutations (P=0.03), but not for DNMT3A CHIP mutations (P=0.49). There were 132 TET2 mutations in individuals with 0 T alleles, 54 TET2 mutations in individuals with 1 T allele, and 6 TET2 mutations with 2 T alleles. There were 158 DNMT3A mutations in individuals with 0 T alleles, 95 DNMT3A mutations in individuals with 1 T allele, and 28 DNMT3A mutations in individuals with 2 T alleles. (D) Forest plot of change in annual growth rate (%/yr) with each additional prescription month of 4 selected drugs with suggestive associations: colchicine, denosumab, methylprednisolone, and hydroxychloroquine. Black effect estimate represents the coefficient of a linear regression of growth rate and number of months exposed to the drug adjusting for age, sex, race, and VAF at first sequencing with all data. Gray effect estimate represents the coefficient of a linear regression of growth rate and number of months exposed to the drug for 3:1 matched non-drug-exposed controls to drug-exposed cases (matched by age, sex, CHIP driver gene, VAF at first sequencing). We computed the 95% CI as the effect estimate +/- 1.96 standard error. The P value tests the null hypothesis of the effect estimate being 0. N represents the number of individuals prescribed the drug for at least 1 month. (E) Forest plot of change in %/yr among individuals with select pre-existing diagnoses based on phecodes. Individuals had to have their first diagnosis of the phecode before their second blood draw. Estimate represents the coefficient of a linear regression of growth rate and presence of diagnosis as a binary variable adjusting for age, sex, race, and VAF at first sequencing. We computed the 95% CI as the effect estimate +/- 1.96 standard error. The P value tests the null hypothesis of the effect estimate being 0. N represents the number of individuals with the diagnosis in each regression.
Figure 3.
Figure 3.
Phenotypic consequences of growth rate. (A) On the left, Kaplan-Meier curve of time to low myeloid counts - defined as thrombocytopenia (platelet count <169.06x109 cells/L), anemia (red blood cell count <3.96x1012 cells/L) or neutropenia (neutrophil count <1.47x109 cells/L) for individuals with a CHIP growth rate >16% annually (red) and <16% annually (gray). A Cox proportional hazard model of time to low myeloid counts and rank-inverse normalized growth rate, when adjusting for age, variant allele fraction (VAF) at the first blood draw, and sex was significant (hazard ratio [HR]=1.20, 95% confidence interval [CI]: 1.05-1.36, P<0.001). On the right, Kaplan-Meier curve of time to high myeloid counts - defined as thrombocytosis (platelet count >397.1x109 cells/L), polycythemia (red blood cell count >5.5x1012 cells/L), or elevated neutrophil count (neutrophil count >7.06x109 cells/L) for individuals with a clonal hematopoiesis of indeterminate potential (CHIP) growth rate >16% annually (red) and <16% annually (gray). A Cox proportional hazard model of time to high myeloid counts and rank-inverse normalized growth rate, when adjusting for age, VAF at the first blood draw, and sex was significant (HR=1.14, 95% CI: 1.02-1.27, P=0.003). (B) Forest plot showing the association between growth rate and time to event for the listed phenotypes. Out of the 711 individuals in the study, individuals who had a phenotype for the first time after the second blood draw are included, with each phenotype sample size listed in the figure. (C) Heatmap showing Clonal Hematopoiesis Risk Score (CHRS) category at the first blood draw (TP1) versus risk at second blood draw (TP2) for N=134 individuals with data available to compute a CHRS (blood counts, mean corpuscular volume, and red cell distribution width). As per Weeks et al.43, low risk was defined as CHRS ≤9.5, intermediate risk as 10< CHRS <12, and high risk as CHRS ≥12.5. Darker hues represent higher numbers of individuals, and exact counts are displayed for each category. (D) Heatmap showing the change in each of the CHRS criteria for the N=30 individuals that shifted into a different risk category between first and second blood draw. The x-axis represents each individual and the y-axis represents the CHRS components, which are faceted based on what clinical test would need to be performed to ascertain that information (i.e., none, blood panel, and sequencing). The color of the box represents the direction of the change (red is positive and blue is negative) and the darkness of the hue represents the magnitude of the change.
See this image and copyright information in PMC

References

    1. Bick AG, Weinstock JS, Nandakumar SK, et al. . Inherited causes of clonal haematopoiesis in 97,691 whole genomes. Nature. 2020;586(7831):763-768. - PMC - PubMed
    1. Jaiswal S, Natarajan P, Silver AJ, et al. . Clonal hematopoiesis and risk of atherosclerotic cardiovascular disease. N Engl J Med. 2017;377(2):111-121. - PMC - PubMed
    1. Jaiswal S, Fontanillas P, Flannick J, et al. . Age-related clonal hematopoiesis associated with adverse outcomes. N Engl J Med. 2014;371(26):2488-2498. - PMC - PubMed
    1. Vlasschaert C, Mack T, Heimlich JB, et al. . A practical approach to curate clonal hematopoiesis of indeterminate potential in human genetic data sets. Blood. 2023;141(18):2214-2223. - PMC - PubMed
    1. Fabre MA, de Almeida JG, Fiorillo E, et al. . The longitudinal dynamics and natural history of clonal haematopoiesis. Nature. 2022;606(7913):335-342. - PMC - PubMed

LinkOut - more resources