The mechanisms behind heart failure are largely unknown. Despite an increasing arsenal of pharmacological therapies, cardiovascular disease is still the most common cause of death in the western world, which demonstrates a pronounced need for more patient-related mechanistic research. Cachexia and limited exercise capacity are the symptoms that best match prediction of heart failure, both of which are symptoms involving a dysfunctional skeletal muscle. An increased understanding of the mechanisms and signaling pathways connects the failure heart with skeletal muscle dysfunction is likely to lead both to discoveries of prognostic factors and possible therapeutic options. The study is a prospective, non-blinded, study. The study will consist of the assignment of patients with heart failure, New York Heart Association (NYHA) III-IV, 60-80 years old. One hundred (100) patients will be enrolled in this study.
The primary objective is to investigate how changes in the skeletal muscle coincide with changes in physical performance, cardiac function, and prognosis in patients with heart failure, and changes over time. Therefore, the investigators will investigate patients with severe heart failure at 'baseline' and on a second follow-up occasion after 12-16 months. The secondary and tertiary objective is to investigate how changes in the metabolic signature of blood and satellite cells coincide with changes in physical performance, cardiac function, and prognosis in patients with heart failure, and changes over time. Patient recruitment is expected to occur over 36 months. The study will be conducted in Sweden at Karolinska University Hospital, Huddinge.
Study Type
OBSERVATIONAL
Enrollment
100
Karolinska University Hospital
Stockholm, Stockholm County, Sweden
RECRUITINGMetabolic signature of muscle, messenger RNA (mRNA) gene expression
Metabolomics profile using nuclear magnetic resonance (NMR)
Time frame: Change from baseline metabolic signature at 24 months
Metabolic signature of muscle, messenger RNA (mRNA) gene
Metabolomics profile using liquid chromatography-high-resolution mass spectrometry (LC-HRMS)
Time frame: Change from baseline metabolic signature at 24 months
Metabolic signature of blood, mRNA gene expression
Metabolomics profile using NMR
Time frame: Change from baseline metabolic signature at 24 months
Metabolic signature of blood, mRNA gene expression
Metabolomics profile using LC-HRMS
Time frame: Change from baseline metabolic signature at 24 months
Metabolic signature of satellite cells, mRNA gene expression
Metabolomics profile using NMR
Time frame: Change from baseline metabolic signature at 24 months
Metabolic signature of satellite cells, mRNA gene expression
Metabolomics profile using LC-HRMS
Time frame: Change from baseline metabolic signature at 24 months
Expression levels of targeted genes using transcriptomics
Choice of genes based on results obtained by metabolomics approaches
Time frame: Change from baseline metabolic signature at 24 months
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