Reprogramming of bone marrow myeloid progenitor cells in patients with severe coronary artery disease
- Department of Internal Medicine and Radboud Institute for Molecular Life Science (RIMLS), Radboud University Medical Center, Netherlands
- Department of Cardiology, Canisius Wilhelmina Hospital, Netherlands
- Quantitative Systems Biology, Life & Medical Sciences Institute, University of Bonn, Single Cell Genomics and Epigenomics Unit at the German Center for Neurodegenerative Diseases and the University of Bonn, Germany
- Department of Cardiology, Radboud University Medical Center, Netherlands
- Department of Laboratory Medicine – Laboratory for Haematology, Radboud University Medical Center, Netherlands
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Netherlands
- Department of Computational Biology for Individualised Infection Medicine, Centre for Individualised Infection Medicine (CiiM) & TWINCORE, joint ventures between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Germany
- Department of Haematology, Radboud University Medical Center, Netherlands
- Department of Medical Genetics, Iuliu Hatieganu University of Medicine and Pharmacy, Romania
- Department for Genomics & Immunoregulation, Life and Medical Sciences Institute (LIMES), University of Bonn, Germany
Figures
Figure 1
Cytokine production capacity of circulating PBMCs.
(A) Cytokine production capacity of circulating PBMCs after LPS stimulation in control individuals (white bars, n = 13) and individuals with CAD (gray bars, n = 13). Geometric mean with 95% CI. (B) Table of cytokine/chemokine production (x-axis) after stimulation with LPS or P3C (y-axis) of PBMCs showing statistical differences between groups. The p-values are corrected for age and BMI with ANCOVA. Outliers were removed with an SD of >2.5 of Z-scores. * indicates p<0.05, **: p<0.01.
Figure 2 with 1 supplement
Progenitor cell populations in the bone marrow compartment (A–G) and in the circulation (H and I).
Control individuals (white bars, n = 13) and individuals with CAD (gray bars, n = 13). HSC and MPP cell populations were combined as the CD90 expression marker was not available for n = 6 in each study group. Geometric mean with 95% CI. The p-values are corrected for age and BMI with ANCOVA. * indicates p<0.05, **: p<0.01. In top-down order: HSC indicates hematopoietic stem cell, MPP: multipotent progenitor, CLP: common lymphoid progenitor, CMP: common myeloid progenitor, GMP: granulocyte-macrophage progenitor, MEP: megakaryocyte erythrocyte progenitor.
Figure 2—figure supplement 1
Gating strategy of hematopoietic stem and progenitor cells in the bone marrow.
HSPCs were defined as CD45+CD34+CD38dim cells, after exclusion of dead cells and doublets. Next, the lymphoid lineage was excluded in CD19-CD117+ cells. In CD45RAdimCD38+ cells, CMP, GMP, MEP, and R1-3 progenitor populations were identified using CD123 and CD45RA expression, see Table for details. CD90 expression in CD38-CD45RA- cells determined MPP and HSC populations.
Figure 3
Cytokine production capacity of bone marrow MNCs.
(A) Cytokine production capacity of BM-MNCs after LPS stimulation in control individuals (white bars, n = 13) and individuals with CAD (gray bars, n = 13). Geometric mean with 95% CI. (B) Table of cytokine/chemokine production (x-axis) after stimulation with LPS or P3C (y-axis) of BM-MNCs showing statistical differences between groups. The p-values are corrected for age and BMI with ANCOVA. Outliers were removed with an SD of >2.5 of Z-scores. * indicates p<0.05, **: p<0.01.
Figure 4
Metabolism of BM-MNCs assessed with Seahorse respirometry in unstimulated condition and 2 hours after IFN-γ+LPS stimulation.
(A, B) Oxygen consumption and extracellular acidification rates over time using treatment with Oligomycin, FCCP, and Rotenone/Antimycin A. (C, D) Bar graphs of control individuals (white bars, n = 13) and individuals with CAD (gray bars, n = 13). Geometric mean with 95% CI. The p-values are corrected for age and BMI with ANCOVA. * indicates p<0.05, **: p<0.01. IFN-γ+LPS: 2 hr IFN-γ and LPS stimulation.
Figure 5
Proliferation capacity of bone marrow MNCs.
Counted colonies per 103 cultured BM-MNCs of control individuals (white bars, n = 13) and individuals with CAD (gray bars, n = 13). Geometric mean with 95% CI. The p-values are corrected for age and BMI with ANCOVA. BFU-E indicates erythroid progenitor population, CFU-GEMM: myeloid progenitor population, CFU-GM: granulocyte-macrophage progenitor population.
Figure 6 with 3 supplements
Transcriptome analyses of HSC, MPP, and GMP populations.
Control individuals (n = 10) versus individuals with CAD (n = 10) for each cell population. (A) Principle component analysis (PCA) based on differentially expressed (DE) genes of the HSC population; (B) Volcano plot showing differential expressed genes between patients with CAD and individuals without atherosclerosis, controlled for age, in a combined analysis of HSC, MPP, and GMP population. Genes with an FDR <0.1 are named; (C) Gene ontology enrichment analysis of DE genes from HSCs, MPPs, and GMPs, depicting the FDR and enrichment ratio.
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Figure 6—source data 1
Contains source data for Figure 6B, and Figure 6—figure supplements 1B, 2, 3.
Table of differential expressed genes between patients with CAD and individualswithout atherosclerosis, controlled for age, in a combined/separated analysis of HSCs, MPPs, and GMPs population.
- https://cdn.elifesciences.org/articles/60939/elife-60939-fig6-data1-v2.xlsx
-
Figure 6—source data 2
Contains source data for Figure 6C.
Table of enrichment analysis of gene ontology terms and involved DE genes of HSCs, MPPs, and GMPs population.
- https://cdn.elifesciences.org/articles/60939/elife-60939-fig6-data2-v2.xlsx
Figure 6—figure supplement 1
Transcriptome of HSC, MPP, and GMP populations.
(A) PCA analysis based on DE genes of the GMP and MPP cell population; (B) Volcano plot showing differential expressed genes between CAD patients and controls, controlled for age, in the HSC, MPP, and GMP cell populations. Genes with an FDR <0.1 are called out.
Figure 6—figure supplement 2
Combined heatmap showing the top 50 DE genes for the HSC, MPP, and GMP cell populations in the patients and the control subjects.
Genes with an FDR <0.1 are colored in red and blue for up- and down-regulated, respectively.
Figure 6—figure supplement 3
Separated heatmap showing the top 50 DE genes for each of the HSC, MPP, and GMP cell populations in the patients and the control subjects.
Genes with an FDR <0.1 are colored in red and blue for up- and down-regulated, respectively.
Figure 7 with 1 supplement
Vascular wall inflammation and hematopoietic tissue activation on [18F]FDG PET/CT scan.
Standard uptake value of each region in control individuals (white bars, n = 13) and individuals with CAD (gray bars, n = 13). Geometric mean with 95% CI. The p-values are corrected for age and BMI with ANCOVA.* indicates p<0.05, **: p<0.01. TBR: target SUV/mean blood pool SUV or mean liver SUV as background.
Figure 7—figure supplement 1
Splenic activity correlates with progenitor cells and circulating immune cells.
Linear regression with 95% CI (n = 26). Spearman correlation coefficient (rs). * indicates p<0.05, **: p<0.01. HSPCs: hematopoietic stem and progenitor cells, GMP: granulocyte macrophage progenitor cells, WBC: white blood cells.
Author response image 1
Tables
Table 1
Group characteristics.
| Characteristics | Individuals with CAD (n = 13) | Individuals without atherosclerosis (n = 13) |
|---|---|---|
| Age (years) | 59.8 ± 9.7 | 52.2 ± 10.4 |
| Sex (% men, n) | 100 (13) | 100 (13) |
| BMI (kg/m2) | 27.8 ± 2.8 | 25.8 ± 2.5 |
| SBP (mm Hg) | 133 ± 15 | 126 ± 10 |
| DBP (mm Hg) | 90 ± 8* | 84 ± 6 |
| Hypertension (%, n) | 93 (12)** | 31 (4) |
| Current smoking (%, n) | 23 (3) | 31 (4) |
| Calcium score (HU) | 445 [213-781]** | 0 [0] |
| Total Plaque score (0–16)‡ | 14 [9-15]*** | 0 [0] |
| Lipid-lowering therapy (%, n) | 77 (10)*** | 8 (1) |
| Acetylsalicylic acid use (%, n) | 69 (9)*** | 0 (0) |
| ACE-inhibitor use (%, n) | 23 (3) | 8 (1) |
| β-blocker use (%, n) | 23 (3) | 8 (1) |
| Glucose (mmol/L) | 5.9 ± 0.8 | †5.7 ± 0.7 |
| Creatinine (µmol/L) | 89 ± 14 | 91 ± 16 |
| Tchol (mmol/L) | 4.51 ± 0.86** | 5.61 ± 0.61 |
| LDLc (mmol/L) | †2.52 ± 0.97** | 3.56 ± 0.64 |
| HDLc (mmol/L) | 1.25 ± 0.31 | 1.51 ± 0.34 |
| TG (mmol/L) | 1.98 ± 1.97 | 1.20 ± 0.38 |
| nHDLc (mmol/L) | 3.26 ± 1.06* | 4.11 ± 0.75 |
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Data are reported as mean ± SD, as mean (number of participants), or as median [interquartile range] and compared with the appropriate statistical tests. ‡ TPS was calculated for participants with a calcium score of <400 HU (n = 6). † Data is missing for one participant. * indicates p<0.05, **: p<0.01, ***: p<0.001.
Table 2
Circulating immune cells and inflammatory markers in patients and controls.
| Cell types | Individuals with CAD | Individuals without atherosclerosis |
|---|---|---|
| WBC (106/mL) | †5.5 [4.9–6.0] | 5.4 [4.8–6.7] |
| Neutrophils (106/mL) | †3.2 [2.5–3.6] | 3.0 [2.6–4.0] |
| Lymphocytes (106/mL) | 1.7 [1.3–1.9] | 1.8 [1.5–2.5] |
| Monocytes (106/mL) | 0.53 [0.42–0.67] | 0.55 [0.45–0.66] |
| Monocytes (%) | 9.8 [8.0–11.5] | 9.3 [7.7–11.1] |
| Classical monocytes (%gated) | 78.1 [72.8–80.3] | 72.8 [70.1–85.5] |
| Intermediate monocytes (%gated) | 9.8 [8.2–14.2] | 10.1 [7.6–13.7] |
| Nonclassical monocytes (%gated) | 12.2 [9.3–14.3] | 13.1 [6.3–18.2] |
| CCR2+ monocytes (%gated) | 80.5 [73.0–82.3] | †77.6 [71.4–86.3] |
| CD11b expression monocytes (MFI) | 10490 [7814–12025]^ | ††6978 [6512–10041] |
| CD41+ monocytes (%gated) | 7.8 [6.5–9.7] | 8.7 [7.6–8.9] |
| Inflammatory markers | ||
| IL-1β (pg/mL) | †0.12 [0.09–0.17] | 0.12 [0.06–0.15] |
| IL-1Ra (pg/mL) | 271 [197-338] | 212 [165-253] |
| IL-6 (pg/mL) | 2.31 [1.37–2.86] | †1.61 [1.23–2.19] |
| IL-18 (pg/mL) | 162 [127-227] | 195 [144-236] |
| hsCRP (pg/mL) | 1.66 [0.83–4.87] | 1.37 [0.53–3.84] |
| E-selectin (ng/mL) | †11.74 [7.65–15.10]* | 8.45 [4.52–14.06] |
| VCAM-1 (ng/mL) | 773 [711-859]^ | 769 [643-844] |
| MMP2 (ng/mL) | 354 [264-434] | 341 [250-427] |
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Circulating concentrations of cells and inflammatory markers in individuals with CAD (n = 13) compared to individuals without atherosclerosis (n = 13). Median with [IQR]. P-values are corrected for age and BMI with ANCOVA. Outliers were removed with an SD of >2.5 of Z-scores. † Data is missing for one participant. *p<0.05, **p<0.01. HSPCs: hematopoietic stem and progenitor cells.
Key resources table
| Reagent type (species) or resource | Designation | Source or reference | Identifiers | Additional information |
|---|---|---|---|---|
| Biological sample (Homo sapiens) | Peripheral blood | Through venous puncture | Freshly isolated from Homo sapiens, men, 18–75 years | |
| Biological sample (Homo sapiens) | Bone Marrow aspirate | From the posterior iliac crest according to standard practice | Freshly isolated from Homo sapiens | |
| Antibody | Mouse monoclonal CD45 KO | Beckman Coulter | Clone J33 Cat# B36294, RRID:AB_2833027 | (1:25) |
| Antibody | Mouse monoclonal HLA-DR PE | Beckman Coulter | Clone immu-357 Cat# IM1639U RRID:AB_2876782 | (1:10) |
| Antibody | Mouse monoclonal CD14 PECy7 | eBioscience | Clone 61D3 Cat# 25-0149-42 RRID:AB_1582276 | (1:25) |
| Antibody | Mouse monoclonal CD16 FITC | eBioscience | Clone CB16 Cat# 11-0168-42 RRID:AB_10805747 | (1:25) |
| Antibody | Mouse monoclonal CD3 APC-Alexa750 | Beckman Coulter | Clone UCTH1 Cat# A66329 RRID:AB_2876783 | (1:25) |
| Antibody | Mouse monoclonal CD56 APC | Beckman Coulter | Clone N901 Cat# IM2474U RRID:AB_2876784 | (1:25) |
| Antibody | Mouse monoclonal CD192 BV421 | BD Biosciences | Clone 48607 Cat# 564067, RRID:AB_2738573 | (1:50) |
| Antibody | Mouse monoclonal CD11b BV785 | Biolegend | Clone ICRF44 Cat# 301346, RRID:AB_2563794 | (1:50) |
| Antibody | Mouse monoclonal CD41 PerCP-Cy5.5 | Biolegend | Clone Hip8 Cat# 303719, RRID:AB_2561731 | (1:50) |
| Antibody | Mouse monoclonal CD90 FITC | Biolegend | Clone 5E10 Cat# 328107, RRID:AB_893438 | (1:50) |
| Antibody | Mouse monoclonal CD123 PE | BD Biosciences | Clone 9F5 Cat# 555644, RRID:AB_396001 | (1:40) |
| Antibody | Mouse monoclonal CD19 ECD | Beckman Coulter | Clone J4.119 Cat# IM2708U, RRID:AB_130854 | (1:20) |
| Antibody | Mouse monoclonal CD38 PC5.5 | Beckman Coulter | Clone LS198-4-3 Cat# IM2651U, RRID:AB_131166 | (1:20) |
| Antibody | Mouse monoclonal CD117 PEC7 | Beckman Coulter | Clone 104D2D1 Cat# IM3698, RRID:AB_131184 | (1:20) |
| Antibody | Mouse monoclonal CD45RA APC | Beckman Coulter | Clone 2H4LDH11LD89 (2H4) Cat# B14807 RRID:AB_2876787 | (1:20) |
| Antibody | Mouse monoclonal CD34-APC A750 | Beckman Coulter | Clone 581 Cat# A89309 RRID:AB_2876786 | (1:20) |
| Commercial assay or kit | DRAQ7 | Biostatus | Live/Dead stain | (1:500) |
| Commercial assay or kit | Human Cytokine Magnetic Magpix 25-plex panel | Invitrogen | MAGPIX platform | |
| Commercial assay or kit | SimplePlex cartridge | ProteinSimple | Ella platform | |
| Commercial assay or kit | Truseq small RNA primers | Illumina | ||
| Commercial assay or kit | hsCRP ELISA | R&D | DY1707 | |
| Commercial assay or kit | VCAM-1 ELISA | R&D | DY809 | |
| Commercial assay or kit | MMP2 ELISA | R&D | DY902 | |
| Commercial assay or kit | E-selectin ELISA | R&D | DY724 | |
| Chemical compound, drug | Pharm Lyse lysing buffer | BD Biosciences | ||
| Chemical compound, drug | Glutamine | Invitrogen | 2 mmol/L in RPMI | |
| Chemical compound, drug | Gentamycin | Centrafarm | 10 mg/mL in RPMI | |
| Chemical compound, drug | Pyruvate | Invitrogen | 1 mmol/L in RPMI | |
| Chemical compound, drug | Methocult GF | Stemcell Technologies | H84435 | |
| Sequence-based reagent | Hg19 human Refseq transcriptome | Li and Durbin, 2010 | To align RNAseq | |
| Peptide, recombinant protein | Lipopolysaccharide from Escherichia coli | Sigma-Aldrich | Serotype 055:B5, L2880 | 10 ng/mL |
| Peptide, recombinant protein | Pam3CysK4 | EMC Microcollections | L2000 | 10 ug/mL |
| Peptide, recombinant protein | Interferon gamma | Immukine, Boehringer Ingelheim BV | 50 ng/mL for Seahorse | |
| Peptide, recombinant protein | Oligomycin | Sigma-Aldrich | 75351 | 1 mM for Seahorse |
| Peptide, recombinant protein | FCCP | Sigma-Aldrich | C2920 | 1 mM for Seahorse |
| Peptide, recombinant protein | Rotenone | Sigma-Aldrich | R8875 | 1.25 mM |
| Peptide, recombinant protein | Antimycin A | Sigma-Aldrich | A8674 | 2.5 mM |
| Software, algorithm | Kaluza | Beckman Coulter | Version 2.1 RRID:SCR_016182 | Flow Cytometry analysis |
| Software, algorithm | MultiQC | Ewels et al., 2016 | RRID:SCR_014982 | Quality check RNAseq |
| Software, algorithm | DEseq2 v1.22.0 | Love et al., 2014 BioConductor | RRID:SCR_015687 | Differential gene expression RNAseq |
| Software, algorithm | clusterProfiler v3.10.1 | Yu et al., 2012 BioConductor | RRID:SCR_016884 | RNAseq |
| Software, algorithm | R 3.6.1 | https://www.r-project.org/ | RRID:SCR_001905 | |
| Software, algorithm | TrueX algorithm | EARL protocols | ||
| Software, algorithm | Inveon Research Workspace 4.2 | Preclinical Solutions, Siemens Medical Solutions | 3D Gaussian filter kernel, 3.0 mm | Postprocessing of FDG PET CT scanning |
| Software, algorithm | PyRadiomics toolbox | van Griethuysen et al., 2017 | Analysis FDG PET CT | |
| Software, algorithm | SPSS V25.0 | SPSS | RRID:SCR_002865 | Data analysis |
| Software, algorithm | Prism v6.0 | GraphPad software | RRID:SCR_002798 | Figures |
| Other | Sysmex-XN 450 hematology analyzer | Sysmex | For total blood counts | |
| Other | CytoFLEX flow cytometer | Beckman Coulter | 13 color on CytExpert RRID:SCR_017217 | Flow Cytometry Peripheral blood |
| Other | Navios flow cytometer | Beckman Coulter | RRID:SCR_014421 | Flow Cytometry Bone marrow Progenitors |
| Other | XFp Analyzer | Seahorse Bioscience | ||
| Other | BD FACSAria II SORP | Becton Dickinson | RRID:SCR_018091 | Flow cytometry sorting |
| Other | Illumina Nextseq500 platform | Illumina | RRID:SCR_014983 | RNAseq |
| Other | Biograph 40 mCT scanner | Siemens Healthineers | ~2.1 MGq/kg FDG i.v. | FDG PET CT |
Table 3
Cell composition of PBMC and BM-MNC fraction.
| Cell types in PBMC fraction | Controls | Patients |
|---|---|---|
| Lymphocytes (%) | 73 [68-79] | 65 [62-75]* |
| Monocytes (%) | 25 [19-31] | 32 [23-35] |
| Neutrophils (%) | 0.7 [0.6–1.1] | 1.2 [0.6–1.7] |
| Cell types in BM-MNC fraction | ||
| HSPCs (%) | 1.6 [1.2–2.0] | 1.4 [1.2–4.7] |
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Cellular composition after mononuclear cell enrichment of peripheral blood and bone marrow. Median with [IQR]. Mann-Whitney U test. *: p<0.05, **: p<0.01. HSPCs: hematopoietic stem and progenitor cells.
Additional files
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Supplementary file 1
Gating strategy of circulating immune cells (related to Table 2).
Monocytes were selected based on CD45+ HLA-DR+ and monocyte scatter properties, after exclusion of dead cells and doublets. Then CD3+ lymphocytes and CD56+ NK-cells were excluded, and monocyte subsets were identified in the CD14/CD16 plot as the percentage of gated. CD11b and CCR2 expression was determined on the monocyte population.
- https://cdn.elifesciences.org/articles/60939/elife-60939-supp1-v2.pdf
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Transparent reporting form
- https://cdn.elifesciences.org/articles/60939/elife-60939-transrepform-v2.docx
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Reprogramming of bone marrow myeloid progenitor cells in patients with severe coronary artery disease
eLife 9:e60939.
https://doi.org/10.7554/eLife.60939
