DNMT3A and TET2 dominate clonal hematopoiesis and demonstrate benign phenotypes and different genetic predispositions
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had no impact on blood counts or indices. Mutational burden of both genes correlated with X-inactivation skewing but no significant association with age-adjusted telomere length reduction was documented. The discordance between the high prevalence of mutations in these 2 genes and their limited biological impact raise the question of the potential role of dysregulated epigenetic modifiers in normal aging hematopoiesis, which may include support to failing hematopoiesis.
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CH is associated with chronic obstructive pulmonary disease and other pulmonary disease.
“Various other systemic effects have been described in association with CH, including chronic obstructive pulmonary disease and other pulmonary disease [16,33,34]”
From Clonal hematopoiesis and inflammation – the perpetual cycle (2023) · cites this paper as [33]
In “Risk factors for acquiring mutations,” the paper reports a significant association between TET2 mutations and a self-reported COPD-asthma category. It does not establish separate associations for COPD and other pulmonary diseases, or for clonal hematopoiesis regardless of mutation. (LLM, conf=0.85)
Experimental — accuracy not yet measuredLoss-of-function heterozygous mutations in TET2 account for about 10% to 30% of mutations found in CHIP carriers.
“Loss-of-function heterozygous mutations in epigenetic regulators DNMT3A (cytosine methyltransferase) and TET2 (methylcytosine dioxygenase) are the most frequently detected mutations in CHIP, accounting for about 50% to 60% and 10% to 30% of mutations found in CHIP carriers, respectively.1, 2, 3,7,8”
From Aging drives <i>Tet2</i> <i>+/−</i> clonal hematopoiesis via IL-1 signaling (2023) · cites this paper as [7]
The Prevalence of mutations section identifies TET2 as one of the most frequently affected genes, but reports 33.3% (134/402) of documented mutations, above the claimed 10%–30% range. The Type of mutations section lists truncating and other TET2 variants, but does not establish that heterozygous loss-of-function TET2 mutations account for the claimed proportion. Page numbers are unavailable in our copy. (LLM, conf=0.86)
Experimental — accuracy not yet measuredIn CHIP, TET2 mutations show highest clonal expansion rates over time, with an estimated 10% annual growth rate compared with 5% for DNMT3A mutations.
“In the context of CHIP, TET2 mutations show highest clonal expansion rates over time (with an estimated 10% annual growth rate compared with 5% of DNMT3A mutations7,8,10).”
From Aging drives <i>Tet2</i> <i>+/−</i> clonal hematopoiesis via IL-1 signaling (2023) · cites this paper as [7]
The 'Effect of DNMT3A and TET2 somatic mutations on clonal expansion' section reports an estimated 9.98% yearly increase in mean variant allele frequency (VAF) for TET2, compared with 3.95% for DNMT3A—not 5%. The Discussion explains that these estimates use age at sampling as a surrogate for growth because the cohort was not resampled over time. The paper suggests TET2 may expand faster than DNMT3A, but does not establish that it has the highest rate among all CHIP mutations. (LLM, conf=0.88)
Experimental — accuracy not yet measuredLoss-of-function heterozygous mutations in DNMT3A account for about 50% to 60% of mutations found in CHIP carriers.
“Loss-of-function heterozygous mutations in epigenetic regulators DNMT3A (cytosine methyltransferase) and TET2 (methylcytosine dioxygenase) are the most frequently detected mutations in CHIP, accounting for about 50% to 60% and 10% to 30% of mutations found in CHIP carriers, respectively.1, 2, 3,7,8”
From Aging drives <i>Tet2</i> <i>+/−</i> clonal hematopoiesis via IL-1 signaling (2023) · cites this paper as [7]
The ‘Prevalence of mutations’ section reports that DNMT3A accounts for 57.2% (230/402) of documented somatic mutations, supporting the approximate 50%–60% figure. But the ‘Type of mutations’ section includes 142 missense mutations among those 230; the paper does not establish that all mutations counted in the 57.2% are loss-of-function or heterozygous. Page numbers were not available in our copy. (LLM, conf=0.88)
Experimental — accuracy not yet measuredTET2 heterozygous loss-of-function mutations are predicted to have high expansion rates (10% increase in mean VAF per year).
“are predicted to have high expansion rates (10% increase in mean VAF per year1, 2, 3,7)”
From Aging drives <i>Tet2</i> <i>+/−</i> clonal hematopoiesis via IL-1 signaling (2023) · cites this paper as [7]
The clonal-expansion section reports a 9.98% increase in estimated mean TET2 VAF per year of age, supporting the approximate 10% figure. But it estimates this relationship across TET2 mutations generally, without establishing that the rate applies specifically to heterozygous loss-of-function mutations; the study also lacked serial resampling. (LLM, conf=0.87)
Experimental — accuracy not yet measured
DNMT3A mutations confer little phenotype on steady state hematopoiesis.
“many have noted that DNMT3A mutations confer little phenotype on steady state hematopoiesis (Buscarlet et al., 2017)”
From Chronic infection drives Dnmt3a-loss-of-function clonal hematopoiesis via IFNγ signaling (2021) · cites this paper as Buscarlet et al., 2017
CHIP itself does not denote a malignancy, nor is it associated with clinically significant alterations in blood counts.
“CHIP itself does not denote a malignancy, nor is it associated with clinically significant alterations in blood counts 28,63.”
From Clonal hematopoiesis in human aging and disease (2019) · cites this paper as [63]
CHIP is linked to chronic obstructive pulmonary disease (COPD).
“Other studies have found links between CHIP and chronic obstructive pulmonary disease (COPD) 37,63.”
From Clonal hematopoiesis in human aging and disease (2019) · cites this paper as [63]
The link between CHIP and COPD could be confounded by smoking, because CHIP was also strongly linked to smoking in these studies.
“However, CHIP was also strongly linked to smoking in these studies, so the result could be confounded by this association.”
From Clonal hematopoiesis in human aging and disease (2019) · cites this paper as [63]
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- Authors
- Buscarlet, M., Provost, S., Zada, Y. F., Barhdadi, A., Bourgoin, V., Lépine, G., Mollica, L., Szuber, N., Dubé, M.-P., & Busque, L.
- Affiliations
- Hôpital Maisonneuve-Rosemont (CA)
- Montreal Heart Institute (CA)
- ORCID
- Venue
- Blood
- Publisher
- American Society of Hematology
- Published
- 2017-08-10
- Volume
- 130
- Issue
- 6
- Pages
- 753-762
- ISSN
- 0006-4971 (ISSN-L)
- 1528-0020
- OpenAlex
- W2728241634
- Cited by
- 383
- References
- 50
- Citations by year
- 2026: 22 · 2025: 34 · 2024: 37 · 2023: 47 · 2022: 59 · 2021: 55 · 2020: 46 · 2019: 40 · 2018: 34 · 2017: 6
- FWCI
- 26.24
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Blood (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Concordia University
- Canadian Institutes of Health Research
- Topics
- Health Sciences › Medicine › Hematology › Acute Myeloid Leukemia Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Keywords
- DNMT3A, TET2, clonal hematopoiesis, somatic mutations, X-inactivation skewing, telomere length, epigenetic regulators, genetic susceptibility, mutational burden
- MeSH terms
- DNA Methyltransferase 3A, Age Factors, Aged, Aged, 80 and over, Aging, Blood Cell Count, Clone Cells, DNA (Cytosine-5-)-Methyltransferases, DNA-Binding Proteins, Female, Hematopoiesis, Humans, Male, Middle Aged, Mutation, Proto-Oncogene Proteins, Cohort Studies, Hematologic Neoplasms, Genetic Predisposition to Disease, Dioxygenases, X Chromosome Inactivation, High-Throughput Nucleotide Sequencing, Telomere Homeostasis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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