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Myocardial ultrastructure of human heart failure with preserved ejection fraction

Nature Cardiovascular Research volume 3, pages 907–914 (2024)Cite this article

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Abstract

Over half of patients with heart failure have a preserved ejection fraction (>50%, called HFpEF), a syndrome with substantial morbidity/mortality and few effective therapies1. Its dominant comorbidity is now obesity, which worsens disease and prognosis1,2,3. Myocardial data from patients with morbid obesity and HFpEF show depressed myocyte calcium-stimulated tension4 and disrupted gene expression of mitochondrial and lipid metabolic pathways5,6, abnormalities shared by human HF with a reduced EF but less so in HFpEF without severe obesity. The impact of severe obesity on human HFpEF myocardial ultrastructure remains unexplored. Here we assessed the myocardial ultrastructure in septal biopsies from patients with HFpEF using transmission electron microscopy. We observed sarcomere disruption and sarcolysis, mitochondrial swelling with cristae separation and dissolution and lipid droplet accumulation that was more prominent in the most obese patients with HFpEF and not dependent on comorbid diabetes. Myocardial proteomics revealed associated reduction in fatty acid uptake, processing and oxidation and mitochondrial respiration proteins, particularly in very obese patients with HFpEF.

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Fig. 1: Representative myocardial electron micrographs for each HFpEF subgroup and non-failing controls with or without DM.
Fig. 2: Analysis of group myocardial ultrastructural features and for proteomics of selected metabolic pathways in human HFpEF compared to controls.

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Data availability

The human HFpEF and control RNA sequencing databases are publicly available at https://doi.org/10.5281/zenodo.4287234 (ref. 43), and the proteomic database is publicly available at https://www.ebi.ac.uk/pride/archive/projects/PXD045677. The micrographs are also available at https://doi.org/10.5281/zenodo.12191847 (ref. 44). Source data are provided with this paper. Any additional data requests can be addressed to the corresponding author D.A.K.

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Acknowledgements

This work was funded by National Heart, Lung, and Blood Institute (NHLBI) R35HL135827, R35HL166565, American Heart Association 20SRG35490443, 16SFRN28620000 (D.A.K.), NHLBI T32:HL007227 (M.M.), American Heart Association Fellowship 23POST1026402 (N.K.), American Heart Association 16SFRN28620000 (K.S.), NHLBI K23HL166770, Sarnoff Scholar Award 138828 (V.S.H.), 1R01HL149891 (K.B.M.), NHLBI HL155346 and American Heart Association 20SRG35490443 (J.V.E.). We thank I. Aslam, Duke University, for patient database assistance and D. E. Hicks and E. Roberts of the Johns Hopkins Electron Microscopy Core and R. Grebe from the Microscopy Core at the Wilmer Eye Institute, Johns Hopkins School of Medicine, for their technical assistance with this project. We would like to thank the Gift of Life Donor Program of Philadelphia for enabling the procurement of human hearts from deceased organ donors.

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Authors and Affiliations

  1. Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA

    Mariam Meddeb, Navid Koleini, Mohammad Keykhaei, Seoyoung Kwon, Celia Aboaf, Kavita Sharma, Virginia S. Hahn & David A. Kass

  2. Advanced Clinical Biosystems Research Institute, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA

    Aleksandra Binek & Jennifer E. Van Eyk

  3. Department of Biological Sciences, University of Maryland, Baltimore, MD, USA

    Reyhane Darehgazani

  4. Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Kenneth B. Margulies & Ken C. Bedi Jr

  5. Department of Anesthesia, Johns Hopkins University, Baltimore, MD, USA

    Mohamed Lehar

  6. Department of Pathology, University of Maryland, Baltimore, MD, USA

    Cinthia I. Drachenberg

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  1. Mariam Meddeb
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Contributions

Study conception and design: D.A.K., K.S., C.I.D., M.M., N.K. and V.S.H. Tissue collection and processing: K.S., K.B.M., K.C.B.J. and M.L. Data collection: M.M., N.K., M.K., R.D., S.K. and C.A. Proteomics analysis: A.B., J.V.E. and V.S.H. Analysis and interpretation of the results: M.M., N.K., R.D., C.A., V.S.H., C.I.D. and D.A.K. Paper drafting and editing: M.M. and D.A.K. All authors reviewed the results and approved the final version of the paper.

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Correspondence to Cinthia I. Drachenberg or David A. Kass.

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Nature Cardiovascular Research thanks Christoph Maack 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 Distribution of comorbidities in the Johns Hopkins HFpEF cohort.

The figures show distributions for systolic blood pressure (SBP), left ventricular mass index (LV Mass I), and body mass index (BMI) from a myocardial biopsy cohort of 111 HFpEF patients. For each, low-to-high quartiles were assigned a rank of 0 to 3, and a hemodynamic versus metabolic score was determined for each patient. The ratio of one to the other (corrected for the theoretical maximal sum) was determined, and the upper and lower quintile of this ratio was used as the source of patients in the H/H versus Obese groups. The mixed group had the elevated rank scores for both sets of variables. Blue lines show 25th and 75th percentiles, red bar shows median. For BMI data, patients with a history of diabetes (all Type 2) are shown by the dark color, those without by the light color. They were distributed throughout each quartile of BMI.

Source data

Extended Data Fig. 2 Phenotypic differences in HFpEF subgroups.

Comparison of hemodynamics, body mass index (BMI), and estimated glomerular filtration rate (GFR) in the three HFpEF clinical subgroups. SBP: systolic blood pressure; LVMI, left ventricular mass index; PASP, pulmonary artery systolic pressure; PCWP, pulmonary capillary wedge pressure; CI, cardiac index. Statistical analysis for SBP, PASP, PCWP, CI, and BMI: 1-way ANOVA, Tukey multiple comparison; GFR – Kruskal-Wallis, Dunn’s multiple comparison, LVMI, Welch ANOVA, Dunnett’s multiple comparison.

Source data

Extended Data Fig. 3 Ultrastructure of HFpEF phenogroups reclassified without accounting for left ventricular hypertrophy.

A) Summary qualitative analysis of electron micrograph assessed fibrosis in the non-failing and the three HFpEF subgroups. Summary qualitative analysis of electron micrograph features for B) sarcomere disruption, lysosome/phagosome abundance, mitochondrial swelling and cristae disruption, C) mitochondrial number, size and area density; and D) Lipid droplet number per field from non-failing (NF) versus HFpEF myocardium. Fibrosis analysis in panel A is based on the primary subgroups presented in Figs. 1 and 2. For panels C-D, HFpEF groups were redefined excluding LV mass information and hence based on those with predominantly elevated systolic blood pressure and the least obesity/DM (Htn-HFpEF), the most prominent obesity/DM but lowest systolic blood pressures (Ob-HFpEF), and a mixed group with equally elevated levels as found in the other two groups (mixed HFpEF). N = 14 non failing, 9 Htn-HFpEF, 9 Ob-HFpEF and 7 mixed-HFpEF. Data shown as mean ± SEM. Statistical analysis: Kruskal-Wallis with Dunn’s multiple comparisons test.

Source data

Extended Data Fig. 4 Ultrastructure of HFpEF phenogroups does not differ based on diabetes status.

A) Summary qualitative analysis of electron micrograph assessed fibrosis, sarcomere disruption and lysosome/phagosome abundance and B) Mitochondrial swelling and cristae destruction in patients with HFpEF and no diabetes (HFpEF DM-, N = 8 patients) versus HFpEF and diabetes (HFpEF DM + , N = 17 patients). Statistical analysis using Fisher’s exact test C) Lipid droplet number per 12000x field in HFpEF DM- and HFpEF DM+ patients. N = 8 HFpEF DM- and 17 HFpEF DM + . Data shown as mean ± SEM. Statistical analysis: Mann-Whitney test. D) Heatmap showing changes in proteins involved in fatty acid (FA) transport, lipid droplet processing, FA oxidation, tricarboxylic acid cycle and electron transport chain in the 3 HFpEF phenogroups, normalized to mean of non-failing control hearts. Data obtained by proteomics from patients from the current study cohort (N = 9 H/H, 9 Ob and 6 mixed HFpEF heart tissue) are shown on the left-hand side, and data obtained from the larger source HFpEF population (N = 14 H/H, 13 Ob-DM and 16 mixed HFpEF heart tissue) are shown on the right-hand side. Statistical analysis: multiple Kruskal Wallis tests with 2 comparisons (non failing versus H/H and non failing vs combined ob and mixed groups).

Source data

Extended Data Fig. 5 HFpEF myocardium is not associated with overt activation of inflammatory signaling.

Heat map for relative gene expression of inflammation-related signaling. Data are first normalized to the median of the controls, and median levels for each HFpEF subgroup are displayed. Asterisks indicate transcripts with significant changes in HFpEF myocardium versus non failing controls based on Deseq P value < 0.05. N = 24 non failing controls, 9 H/H, 10 Ob and 16 mixed HFpEF heart tissue. Statistical analysis: Deseq comparing non failing versus all HFpEF patients combined.

Source data

Extended Data Table 1 Clinical characteristics of individual study participants
Full size table
Extended Data Table 2 Proteomics analysis of FA uptake and processing pathways
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Extended Data Table 3 Analysis of inflammation-related transcripts
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Supplementary information

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Table of contents and Supplementary Figs. 1–6.

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44161_2024_516_MOESM3_ESM.xlsx

Source data for all figures in the main text and extended data figures. Individual numbers used in all summary data figures are displayed in Fig. 2 of the paper and for each extended data figure. Each is identified by a separate tab in the Excel spreadsheet.

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Meddeb, M., Koleini, N., Binek, A. et al. Myocardial ultrastructure of human heart failure with preserved ejection fraction. Nat Cardiovasc Res 3, 907–914 (2024). https://doi.org/10.1038/s44161-024-00516-x

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