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Epigenetic and proteomic signatures associate with clonal hematopoiesis expansion rate

Abstract

Clonal hematopoiesis of indeterminate potential (CHIP), whereby somatic mutations in hematopoietic stem cells confer a selective advantage and drive clonal expansion, not only correlates with age but also confers increased risk of morbidity and mortality. Here, we leverage genetically predicted traits to identify factors that determine CHIP clonal expansion rate. We used the passenger-approximated clonal expansion rate method to quantify the clonal expansion rate for 4,370 individuals in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) cohort and calculated polygenic risk scores for DNA methylation aging, inflammation-related measures and circulating protein levels. Clonal expansion rate was significantly associated with both genetically predicted and measured epigenetic clocks. No associations were identified with inflammation-related lab values or diseases and CHIP expansion rate overall. A proteome-wide search identified predicted circulating levels of myeloid zinc finger 1 and anti-Müllerian hormone as associated with an increased CHIP clonal expansion rate and tissue inhibitor of metalloproteinase 1 and glycine N-methyltransferase as associated with decreased CHIP clonal expansion rate. Together, our findings identify epigenetic and proteomic patterns associated with the rate of hematopoietic clonal expansion.

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Fig. 1: A schematic representation of the study design.
Fig. 2: Linear regression analyses of clonal expansion rate with DNA methylation aging measures.
Fig. 3: Linear regressions of clonal expansion rate with inflammation.
Fig. 4: Linear regressions of clonal expansion rate with predicted protein levels.

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Data availability

WGS data for individuals in the TOPMed cohort and the CHIP variant call sets are available through restricted access from the dbGaP TOPMed Exchange Area available to TOPMed investigators to protect patient privacy. Individuals who want to apply for access to TOPMed data should follow the steps listed online (https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/about.html#request-controlled). Summary statistics for the measures of DNA methylation aging are available at https://datashare.ed.ac.uk/handle/10283/3645 and summary statistics for the four significant proteins are available at www.omicspred.org. All other data supporting the findings of the study are available from the authors upon request.

Code availability

Code developed to call passenger mutations using the Mutect2 WDL pipeline is available at https://dockstore.org/workflows/github.com/broadinstitute/gatk/mutect2:4.1.8.1?tab=info. Code on passenger variant filtering and quality control is available at https://github.com/weinstockj/passenger_count_variant_calling. Code to calculate PRSs is available for PRScs at https://github.com/getian107/PRScs and PRScsx at https://github.com/getian107/PRScsx.

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Acknowledgements

WGS for the TOPMed program was supported by the 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). We thank the study participants who provided biological samples and data for TOPMed. The full study-specific acknowledgments are included in the Supplementary Acknowledgements. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the NHLBI, the National Institutes of Health or the US Department of Health and Human Services. S.J. is supported by the Burroughs Wellcome Foundation Career Award for Medical Scientists, Foundation Leducq (TNE-18CVD04), the Ludwig Center for Cancer Stem Cell Research, the American Society of Hematology Scholar Award, the NIH Director’s New Innovator Award (DP2-HL157540) and a Leukemia and Lymphoma Society Discovery Grant. A.G.B. is supported by a Burroughs Wellcome Foundation Career Award for Medical Scientists, the NIH Director’s Early Independence Award (DP5-OD029586) and the Pew-Stewart Scholar for Cancer Research award, supported by the Pew Charitable Trusts and the Alexander and Margaret Stewart Trust.

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Authors and Affiliations

Authors

Contributions

T.M.M. and M.A.R. conceptualized and designed the study, performed the analyses and wrote the manuscript. Y.P. performed analyses. A.G.B., J.S.W. and S.J. conceptualized PACER and contributed to the study design. J.S.W. performed somatic variant calling. A.G.B. supervised the work and contributed to the drafting of the manuscript. D.C.N., K.D.T., X.G., A.R.S., J.R.O., E.E.K., R.J.F.L., S.R., B.E.C., B.M.P., J.C.B., J.A.B., E.K.S., J.H.Y., M.H.C., D.L.D., D.L., A.D.J., R.A.M., L.R.Y., S.R.H., N.L.S., K.L.W., L.M.R., A.P.C., J.I.R., S.S.R., A.W.M., C.C.G., Y.I.C., W.L., M.B.S., D.R., C.K., P.L.A., P.D., T.W.B., A.V.S., A.P.R. and the NHLBI TOPMed Consortium contributed to sequencing and phenotyping of the included NHLBI TOPMed cohorts. All authors read, revised and approved the manuscript.

Corresponding author

Correspondence to Alexander G. Bick.

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Competing interests

S.J. is on advisory boards for Novartis, AVRO Bio and Roche Genentech, reports speaking fees and honorarium from GSK and is on the scientific advisory board of Bitterroot Bio. P.N. reports grants support from Amgen, AstraZeneca, Apple, Novartis and Boston Scientific, is a paid consultant for Apple, AstraZeneca, Novartis, Genentech and Blackstone Life Sciences and has spousal employment at Vertex, all unrelated to the present work. S.J., A.G.B. and P.N. are paid consultants for Foresite Labs and cofounders, equity holders and scientific advisory board members of TenSixteen Bio. Stanford University has filed a patent application for the use of PACER to identify therapeutic targets, on which S.J., A.G.B. and J.S.W. are listed as inventors (US patent 63/141,333). The patent has been licensed to TenSixteen Bio. A.S. is an employee of Regeneron Pharmaceuticals. B.M.P. serves on the Steering Committee of the Yale Open Data Access Project funded by Johnson and Johnson. E.S. receives grant support from Bayer and GSK. J.Y. and D.D. receive grant support from Bayer. M.C. receives grant support from Bayer and GSK and consulting and speaking fees from Illumina and AstraZeneca. S.S.R. and L.M.R. are paid consultants for Westat, the Administrative Coordinating Center for the NHLBI TOPMed program. The remaining authors declare no competing interests.

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Nature Aging thanks Siddhartha Kar, Jennifer Kwan and Kristina Kirschner for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Description of CHIP cohort characteristics.

A density plot displaying the distribution of driver gene VAF across the cohort stratified by driver gene as well as the overall driver gene count across the cohort.

Extended Data Fig. 2 Epigenetic aging correlation measures.

Correlation in methylation measures. (a) Correlation matrix within measured epigenetic aging data. (b) Correlation matrix within predicted epigenetic aging data. (c) Box plot showing correlation between calculated PRS (n = 297 individuals) (grouped into quartiles) and z-scored measured methylation data. Color denotes a significant association between measured and PRS data. The center line is the median value, with the bounds of the box representing the first through third quartiles and the whiskers representing the minimum and maximum while any remaining points are outliers.

Extended Data Fig. 3 Full regression results for inflammation analyses.

Linear regressions of clonal expansion rate with inflammation (full results). (a) Heat map showing associations between clonal expansion rate and PRS for inflammation-related proteins from the Somalogic database stratified by CHIP gene. Significance and direction of effect are denoted by the color of the box. (b) Heat map showing associations between clonal growth and PRS for inflammation-related phenotypes. Significance and direction of effect are denoted by the color of the box.

Extended Data Fig. 4 Gene-specific circulating protein regression results.

Linear regressions of clonal expansion rate with predicted protein levels in CHIP gene-specific analyses. Volcano plots showing significantly associated protein PRS from the Somalogic database. Colored points are statistically significant. The color of the point shows the direction of the effect (blue = negative, red = positive). To account for multiple testing, we used a Bonferroni corrected p-value of 2.3 × 10−5. (a) DNMT3A-specific CHIP (b) TET2-specific CHIP (c) SRSF2/SF3B1/U2AF1-specific CHIP.

Extended Data Fig. 5 Sex-stratified circulating protein regression results.

Linear regression analyses of clonal expansion rate with Somalogic protein PRS stratified by biological sex (n = 4,370 individuals). To account for multiple testing, we used a Bonferroni corrected p-value of 0.01.

Extended Data Fig. 6 Full results of GSEA analyses.

Hallmark pathways in Gene Set Enrichment Analysis (GSEA). (a) Heat map showing the pathways most implicated in both overall CHIP and gene-specific CHIP. Color denotes the direction of the association. GSEA is a statistical functional enrichment analysis. (b) Protein PRSs contributing to the hallmark pathways most strongly associated with clonal expansion rate. Color denotes the direction of the association.

Extended Data Fig. 7 Gene-specific GSEA results.

Gene Set Enrichment Analysis (GSEA) results for CHIP gene-specific analyses. (a) Pathways implicated in the associations between clonal expansion rate and circulating protein PRS in DNMT3A-specific CHIP. (b) TET2-specific CHIP. (c) Pearson’s correlation test between pathways implicated in DNMT3A & TET2-specific CHIP. The translucent error bars around the linear regression line represent 95% confidence intervals.

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Mack, T.M., Raddatz, M.A., Pershad, Y. et al. Epigenetic and proteomic signatures associate with clonal hematopoiesis expansion rate. Nat Aging (2024). https://doi.org/10.1038/s43587-024-00647-7

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