Myocardial ultrastructure of human heart failure with preserved ejection fraction.
Mariam MeddebNavid KoleiniAleksandra BinekMohammad KeykhaeiReyhane DarehgazaniSeoyoung KwonCelia AboafKenneth B MarguliesKenneth C BediMohamed LeharKavita SharmaVirginia S HahnJennifer E Van EykCinthia B DrachenbergDavid A KassPublished in: Nature cardiovascular research (2024)
Over half of patients with heart failure have a preserved ejection fraction (>50%, called HFpEF), a syndrome with substantial morbidity/mortality and few effective therapies 1 . Its dominant comorbidity is now obesity, which worsens disease and prognosis 1-3 . Myocardial data from patients with morbid obesity and HFpEF show depressed myocyte calcium-stimulated tension 4 and disrupted gene expression of mitochondrial and lipid metabolic pathways 5,6 , 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.
Keyphrases
- weight loss
- metabolic syndrome
- type diabetes
- insulin resistance
- endothelial cells
- left ventricular
- electron microscopy
- gene expression
- ejection fraction
- fatty acid
- bariatric surgery
- high fat diet induced
- oxidative stress
- weight gain
- adipose tissue
- induced pluripotent stem cells
- single cell
- pluripotent stem cells
- cardiovascular disease
- obese patients
- aortic stenosis
- dna methylation
- risk factors
- mass spectrometry
- glycemic control
- cardiovascular events
- big data
- skeletal muscle
- deep learning
- hypertrophic cardiomyopathy
- machine learning
- case report
- coronary artery disease
- liquid chromatography
- ultrasound guided