Abstract
Clonal hematopoiesis (CH) is characterized by the acquisition of a somatic mutation in a hematopoietic stem cell that results in a clonal expansion. These driver mutations can be single nucleotide variants in cancer driver genes or larger structural rearrangements called mosaic chromosomal alterations (mCAs). The factors that influence the variations in mCA fitness and ultimately result in different clonal expansion rates are not well understood. We used the Passenger-Approximated Clonal Expansion Rate (PACER) method to estimate clonal expansion rate as PACER scores for 6,381 individuals in the NHLBI TOPMed cohort with gain, loss, and copy-neutral loss of heterozygosity mCAs. Our mCA fitness estimates, derived by aggregating per-individual PACER scores, were correlated (R2 = 0.49) with an alternative approach that estimated fitness of mCAs in the UK Biobank using population-level distributions of clonal fraction. Among individuals with JAK2 V617F clonal hematopoiesis of indeterminate potential or mCAs affecting the JAK2 gene on chromosome 9, PACER score was strongly correlated with erythrocyte count. In a cross-sectional analysis, genome-wide association study of estimates of mCA expansion rate identified a TCL1A locus variant associated with mCA clonal expansion rate, with suggestive variants in NRIP1 and TERT.
Original language | English |
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Article number | 3800 |
Journal | Nature Communications |
Volume | 15 |
Issue number | 1 |
DOIs | |
State | Published - Dec 2024 |
Bibliographical note
Publisher Copyright:© The Author(s) 2024.
Funding
We thank the studies and participants who provided biological samples and data for the NHLBI TOPMed Consortium. WGS for the Trans-Omics in Precision Medicine (TOPMed) program was supported by the National Heart, Lung, and Blood Institute (NHLBI). Centralized read mapping and genotype calling, along with variant quality metrics and filtering, were provided by the TOPMed Informatics Research Center (3R01HL-117626-02S1; contract HHSN268201800002I). Phenotype harmonization, data management, sample identity quality control, and general study coordination were provided by the TOPMed Data Coordinating Center (R01HL-120393; U01HL-120393; contract HHSN268201800001I). The full study-specific acknowledgments are included in the Supplementary Materials. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. We wish to acknowledge the contributions of the consortium working on the development of the NHLBI BioData Catalyst ecosystem. This work was supported by National Institutes of Health grant R01AG083736 (A.G.B., P.L.A., P.A.S.), National Institutes of Health grant R01HL117626, National Institutes of Health contract HHSN268201800002I, National Institutes of Health grant R01HL120393, National Institutes of Health grant U01HL120393, National Institutes of Health contract HHSN268201800001I, National Institutes of Health grant DP5OD029586 (A.G.B.), Burroughs Wellcome Foundation Career Award for Medical Scientists (A.G.B. and S.J.), NHLBI BioData Catalyst Fellowship (J.S.W.), and National Institutes of Health grant T32GM007347 (Y.P.).
Funders | Funder number |
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National Institutes of Health (NIH) | |
National Heart, Lung, and Blood Institute (NHLBI) | |
U.S. Department of Health and Human Services | U01HL-120393, R01AG083736, R01HL120393, DP5OD029586, R01HL117626 |
U.S. Department of Health and Human Services | |
TOPMed Informatics Research Center | HHSN268201800001I, HHSN268201800002I, 3R01HL-117626-02S1 |
Burroughs Wellcome Fund | T32GM007347 |
Burroughs Wellcome Fund |
ASJC Scopus subject areas
- General Chemistry
- General Biochemistry, Genetics and Molecular Biology
- General Physics and Astronomy