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Disruption of the Uty epigenetic regulator locus in hematopoietic cells phenocopies the profibrotic attributes of Y chromosome loss in heart failure

Nature Cardiovascular Research volume 3, pages 343–355 (2024)Cite this article

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Abstract

Heart failure affects millions of people worldwide, with men exhibiting a higher incidence than women. Our previous work has shown that mosaic loss of the Y chromosome (LOY) in leukocytes is causally associated with an increased risk for heart failure. Here, we show that LOY macrophages from the failing hearts of humans with dilated cardiomyopathy exhibit widespread changes in gene expression that correlate with cardiac fibroblast activation. Moreover, we identify the ubiquitously transcribed tetratricopeptide Y-linked (Uty) gene in leukocytes as a causal locus for an accelerated progression of heart failure in male mice with LOY. We demonstrate that Uty disruption leads to epigenetic alterations in both monocytes and macrophages, increasing the propensity of differentiation into profibrotic macrophages. Treatment with a transforming growth factor-β-neutralizing antibody prevented the cardiac pathology associated with Uty deficiency in leukocytes. These findings shed light on the mechanisms that contribute to the higher incidence of heart failure in men.

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Fig. 1: Hematopoietic LOY in human DCM scRNA-Seq datasets.
Fig. 2: Deficiency of Y chromosome genes in hematopoietic cells exacerbates cardiac dysfunction in response to pressure overload.
Fig. 3: Hematopoietic Uty is a potential gene candidate that contributes to LOY-mediated deterioration of cardiac function.
Fig. 4: Uty disruption in hematopoietic cells accelerates cardiac dysfunction in response to pressure overload.
Fig. 5: Multimodal single-cell analysis reveals the profibrotic chromatin accessibility signatures of recruited UtyGT cardiac monocytes and macrophages.
Fig. 6: Inhibition of TGFβ reverses cardiac dysfunction after TAC in mice with hematopoietic Uty deficiency.

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Data availability

All data supporting the findings in this study are included in the main article and associated files. Single-cell multiomics raw sequencing data and processed data files used to generate and perform analyses of control and UtyGT cardiac leukocytes are available in the NCBI GEO repository under accession no. GSE241486. Additional analyses used datasets available in the NCBI GEO repository under accession nos. GSE183852 and GSE145154 and the Broad Institute Single Cell Portal under accession no. SCP1303. Source data are provided with this paper.

Code availability

Code used to analyze datasets was generated from available vignettes and tutorials. This code is available at https://github.com/nicholaschavkin/UTY_HF.

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Acknowledgements

This work was supported by National Institutes of Health (NIH) grants AG073249 and HL142650 and National Aeronautics and Space Administration grant 80NSSC21K0549 to K.W.; NIH grant HL152174 to S.S. and K.W.; the University of Virginia Medical Scientist Training Program (T32GM007267) to J.D.C.; American Heart Association grant 23CDA1054358 to N.W.C.; Grant-in-Aid for Research Activity Start-up (21K20879) to S.S.; Grant-in-Aid for Scientific Research (22K08162) to S.S.; Grant for Basic Research of the Japanese Heart Failure Society to S.S.; Grant for Basic Research of the Japanese Circulation Society to S.S.; Research Grant of the Japan Cardiovascular Research Foundation to S.S.; Research Grant of the SENSHIN Medical Research Foundation to S.S.; Research Grant of the MSD Life Science Foundation to S.S.; Novartis research grant to S.S.; Research Grant of the Kondou Kinen Medical Foundation to S.S.; and the Bayer Scholarship for Cardiovascular Research to S.S. We would like to thank X. Chen and H. Hrncir (Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, USA) for technical assistance. We acknowledge the use of Servier Medical Art, as Fig. 5a was partially generated using Servier Medical Art, provided by Servier, licensed under a Creative Commons Attribution 3.0 unported license. Some illustrations (Fig. 3a and Supplementary Fig. 1) were created with BioRender.com. This research was made possible by the University of Virginia Flow Cytometry Core (RRID: SCR_017829) and Genome Analysis and Technology Core (RRID: SCR_018883).

Author information

Author notes

  1. Keita Horitani

    Present address: Department of Medicine II, Kansai Medical University, Osaka, Japan

  2. Ying Wang

    Present address: Department of Cardiology, Second Affiliated Hospital of Army Medical University, Chongqing, China

  3. Hayato Ogawa & Yoshimitsu Yura

    Present address: Department of Cardiology, Nagoya University Graduate School of Medicine, Nagoya, Japan

  4. Emiri Miura-Yura

    Present address: Division of Diabetes, Department of Internal Medicine, Aichi Medical University School of Medicine, Nagakute, Japan

  5. These authors contributed equally: Keita Horitani, Nicholas W. Chavkin, Soichi Sano.

Authors and Affiliations

  1. Hematovascular Biology Center, Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, VA, USA

    Keita Horitani, Nicholas W. Chavkin, Yohei Arai, Ying Wang, Hayato Ogawa, Yoshimitsu Yura, Megan A. Evans, Jesse D. Cochran, Mark C. Thel, Ariel H. Polizio, Miho Sano, Emiri Miura-Yura, Yuka Arai, Heather Doviak, Soichi Sano & Kenneth Walsh

  2. Department of Cell Biology, University of Virginia School of Medicine, Charlottesville, VA, USA

    Nicholas W. Chavkin & Karen K. Hirschi

  3. Medical Scientist Training Program, University of Virginia School of Medicine, Charlottesville, VA, USA

    Jesse D. Cochran

  4. Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, USA

    Arthur P. Arnold

  5. Ophthalmology, Biomedical Engineering, Center for Advanced Vision Science (CAVS), University of Virginia School of Medicine, Charlottesville, VA, USA

    Bradley D. Gelfand

  6. Laboratory of Cardiovascular Mosaicism, National Cerebral and Cardiovascular Center, Osaka, Japan

    Soichi Sano

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  1. Keita Horitani
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Contributions

S.S. and K.W. designed the experiments. K.H., N.W.C., Yohei A., Y.W., H.O., Y.Y., M.A.E., J.D.C., M.C.T., M.S., E.M.-Y., Yuka A., H.D., A.H.P. and S.S. performed the experiments. Y.W. performed statistical analyses. A.P.A., B.D.G. and K.K.H. provided scientific advice. S.S., N.W.C. and K.W. wrote the paper. All authors approved the final version of the paper.

Corresponding authors

Correspondence to Soichi Sano or Kenneth Walsh.

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Nature Cardiovascular Research thanks Tim Stuart, Alan Tall and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Hematopoietic LOY in human dilated cardiomyopathy scRNA-Seq datasets.

a. UMAP dimensionality reduction of annotated cardiac cells from integrated scRNA-Seq datasets (Koenig NCVR 2022, Rao BRC 2021, Chaffin Nature 2022). b. Expression of cell type-specific genes used for annotation. c. UMAP of annotated cardiac leukocytes. d. Expression of cell type-specific genes used for annotation. e. Total number of control and LOY leukocytes within each leukocyte subtype (gray = control, red = LOY). f. UMAP of annotated cardiac fibroblasts with expression of cell type-specific genes used for myofibroblast annotation. g. Linear correlation of myofibroblast percentage within each patient and LOY percentage within each patient, presented by disease.

Source data

Extended Data Fig. 2 Hematopoietic cells with Y chromosome gene deficiency do not display fitness advantage in vivo.

Mice underwent partial (50%) bone marrow reconstitution with XY* and XY*X cells following lethal irradiation. After 4 weeks and 8 weeks of recovery, flow cytometric analysis of peripheral blood was performed. (XY* n = 7, XY*X n = 7). Data are presented as mean values +/- SEM. WBC; white blood cells.

Source data

Extended Data Fig. 3 Hematopoietic LOY in human healthy cardiac scRNA-Seq datasets.

a. UMAP dimensionality reduction of annotated cardiac cells from integrated scRNA-Seq datasets of healthy male patients. b-c. Expression of markers for immune cells (PTPRC), monocytes/macrophages (CD68, CD14), and Y chromosome genes (UTY, DDX3Y, KDM5D), visualized on (B) UMAP dimensionality reduction plots, and (C) relative expression between cell types.

Source data

Extended Data Fig. 4 CRISPR/Cas9-mediated gene disruption of Y chromosome genes in bone marrow lineage-negative cells.

a. Gating strategy used for the Fluorescence-Activated Cell Sorting (FACS) of peripheral blood cells. Cells transduced with lentivirus transduced cells are designed to express turbo red fluorescent protein (tRFP). b-e. The results of Tracking of Indels by Decomposition (TIDE) analysis of sorted cells revealed the presence of multiple insertions and deletions in Ddx3y (b), Uty (c), Kdm5d (d), Eif2s3y (e) genes. f. Percentage of tRFP-positive cells in blood following BMT in the different gene-editing screens (n = 10 for all conditions, statistical analysis by Student’s t test). Data are presented as mean values +/- SEM.

Source data

Extended Data Fig. 5 Hematopoietic parameters remain unaffected by CRISPR/Cas9-mediated disruption of hematopoietic Y chromosome genes (Ddx3y, Kdm5d, Uty, Eif2s3y).

White blood cell count, hemoglobin concentration, and platelet count were assessed at 4 months (a, b, d) and 1 month (c) post-bone marrow transplant (n = 10 for all conditions). Data are presented as mean values +/- SEM. WBC; white blood cell, HGB; hemoglobin, PLT; platelet.

Source data

Extended Data Fig. 6 CRISPR/Cas9-mediated disruption of hematopoietic Eif2s3y, Ddx3y, or Kdm5d genes do not promote cardiac dysfunction after TAC.

a, c and e. Sequential echocardiographic analysis of KO mice and control mice after TAC at the indicated time points (a: control, n = 6; Eif2s3y-KO, n = 6, c: control n = 10, Ddx3y-KO n = 8, e: control n = 25, Kdm5d-KO n = 23). b, d and f. Heart weight (HW) and lung weight (LW) relative to tibia length (TL) at 28 days after TAC procedure (b-HW/TL; control, n = 5; Eif2s3y-KO, n = 6, b-LW/TL; control, n = 5; Eif2s3y-KO, n = 6, d-HW/TL: control n = 9, Ddx3y-KO n = 8, d-LW/TL: control n = 8, Ddx3y-KO n = 8, f-HW/TL: control n = 24, Kdm5d-KO n = 21, f-LW/TL: control n = 7, Kdm5d-KO n = 7). Data are presented as mean values +/- SEM.

Source data

Extended Data Fig. 7 Uty expression and X chromosome paralogs in hematopoietic cells of UtyGT mice.

a. Transcript levels of Uty in total bone marrow cells (BM, wild-type n = 3, UtyGT n = 3, Student’s t test) and whole peripheral blood cells (PB, wild-type n = 5, UtyGT n = 5, Student’s t test). b. Transcript levels of Utx, Ddx3x, Eif2s3x, and Kdm5c in BM cells (n = 3 for all conditions). After TAC, lung weight, body weight and blood cell counts in wild-type mice and UtyGT mice were determined. c. Lung weight relative to tibial length at 0 and 28 days after TAC procedure. (Day 0: wild-type n = 5, UtyGT n = 5, Day 28: wild-type n = 10, UtyGT n = 10). d. Body weight over the time course after TAC (wild-type n = 10, UtyGT n = 10). LW; lung weight, TL: tibial length, BW; body weight. e. Flow cytometry was performed at baseline and 1 month post-TAC to determine cell counts in peripheral blood (Pre: Control n = 9, UtyGT n = 9, 1 M after TAC: Control n = 8, UtyGT n = 6, statistical analysis by two-way ANOVA post hoc Tukey). Data are presented as mean values +/- SEM, p-values: N.S.=not significant, *<0.05, **<0.01. BM; bone marrow, PB; peripheral blood; WBC; white blood cells.

Source data

Extended Data Fig. 8 Transgenic-mediated Ddx3y-KO of hematopoietic cells does not promote cardiac dysfunction after TAC.

a. Schematic of experimental procedure. b. Transcript levels of the Y chromosome genes (Eif2s3y, Ddx3y, Kdm5d, Uty) in bone marrow cells (wild-type n = 3, Ddx3y-KO n = 3). c. Transcript levels of the X chromosome gene homologues (Eif2s3x, Ddx3x, Kdm5c, Utx) in white blood cells isolated from bone marrow from either group of mice (wild-type n = 3, Ddx3y-KO n = 3). d. Sequential echocardiographic analysis of mice transplanted with wild-type or Ddx3y-KO cells. Repeated measurement was performed at the indicated time points after TAC operation (wild-type, n = 10; Ddx3y-KO, n = 8). e. Heart weight (HW) and lung weight (LW) relative to tibial length (TL) at 4 weeks after TAC procedure (HW/TL; control, n = 10; Ddx3y-KO, n = 8, LW/TL; wild-type, n = 10; Ddx3y-KO, n = 8). f. Transcript levels of heart failure markers in heart tissue at four weeks after TAC operation (wild-type, n = 10; Ddx3y-KO, n = 8). Statistical analyses were performed using 2-way ANOVA with Sidak’s multiple comparison tests d. and two-sided unpaired Student’s t test (b, c, e, f). TAC; transverse aortic constriction, FS; fractional shortening, LVPWTd; left ventricular posterior wall thickness at end-diastole, LVDs; left ventricular diameter at end-systole, LVDd; left ventricular diameter at end-diastole. Dots in all panels represent individual samples. Data are shown as mean ± SEM.

Source data

Extended Data Fig. 9 Multi-modal single-cell omics of recruited UtyGT cardiac leukocytes.

a. Quality control metrics for single cell muiltiomics dataset: RNA reads per cell (nCount_RNA), ATAC reads per cell (nCount_ATAC), quantified peaks per cell (nCount_peaks), enrichment of ATAC reads near transcriptional start sites (TSS Enrichment), nucleosome banding pattern (nucleosome_signal) (box plots: min 25%, max 75%, middle median, whiskers 5%-95%, Control n = 8156, UtyGT n = 9169). b. DNA accessibility coverage plot for the Uty locus in Control and UTYGT samples showing ATAC reads and calculated peaks. c. Expression of known genes that are enriched in specific leukocyte cell types used to annotate clusters of single cells within the single-cell multiomics dataset. d. UMAP dimensionality reduction of wild-type and UtyGT cardiac leukocytes based on differential chromatin availability around genes. e. Scoring of each cell on increased chromatin availability around genes associated with fibrotic macrophages (Fibrotic Score) or inflammatory macrophages (Inflammatory Score), plotted by UMAP position.

Source data

Extended Data Fig. 10 Abundance of monocytes and macrophages in the hearts from control and UtyGT mice after TAC.

a. Relative abundance of monocytes and macrophages in datasets from control and UtyGT hearts quantified by percentage of total cell number. b. Flow cytometric analysis of macrophage counts in heart tissue 28 days after TAC. The absolute numbers of cells were normalized by tissue weight (Sham: wild-type n = 5, UtyGT n = 5; TAC: wild-type n = 5, UtyGT n = 5, data are presented as mean values +/- SEM, two-way ANOVA post hoc Tukey, p-value: **<0.01, ***<0.001, ****<0.0001). c. Variation in expression of each gene between Control and UtyGT monocytes and macrophages plotted as -Log10(p-value) versus Log2(Fold Change) (Wilcoxon Rank Sum statistical test). d, e. Gene Ontology terms significantly enriched in significant differentially expressed genes monocytes and macrophages (d: enriched in UtyGT cells, e: enriched in Control cells).

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Horitani, K., Chavkin, N.W., Arai, Y. et al. Disruption of the Uty epigenetic regulator locus in hematopoietic cells phenocopies the profibrotic attributes of Y chromosome loss in heart failure. Nat Cardiovasc Res 3, 343–355 (2024). https://doi.org/10.1038/s44161-024-00441-z

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