Multivariate Biomarker Study for Sarcopenia in Heart Failure

N/AActive Not RecruitingNCT06217640

University of Liverpool80 enrolled

Overview

In the United Kingdom, heart failure (HF) affects about 900,000 people with 60,000 new cases annually. Up to 60% of people living with HF also experience sarcopenia, known as loss of muscle mass and strength. Sarcopenia contributes significantly to low physical capacity and exercise intolerance and worsens the prognosis of the disease and quality of life. In comparison to primary sarcopenia (age-related sarcopenia), secondary sarcopenia occurs if other factors, including malignancy or organ failure, are evident in addition to aging. Secondary sarcopenia is highly common in patients with heart failure (Sarc-HF) (prevalence is 35%-69%), and has a significantly negative impact on exercise capacity, weight-adjusted peak maximal oxygen consumption, left ventricular function, and re-hospitalization rates and mortality. In this integrated study of NHS patients with HF, the investigators aim is to identify the underlying mechanisms of muscle weakness in HF utilizing including body composition, circulating metabolites (metabolic profile), and functional tests for (1) early detection of otherwise subclinical HF, (2) diagnostic assessment of clinically manifest HF-sarcopenia, (3) the risk stratification of subjects with a suspected or confirmed diagnosis, and (4) selection of an appropriate therapeutic intervention.

Investigators aim to understanding the underlying physiological links for secondary sarcopenia in older age and particularly those with heart failure. This links partly can be explained by impaired energy metabolism of amino acids and fatty acid oxidation. This can lead to lower ATP production and deprivation of both skeletal muscle and heart from energy sources, which worsens the sarcopenia in HF. RESEARCH QUESTION/AIM(S) * Faecal and plasma metabolite content will be correlated with matrix of global muscle function to assess if there are differences according to sarcopenia status in heart failure. * Utilizing metabolomic data to disclose dysregulation of pathways linked to energy production (Krebs cycle, Warburg effect), amino acid catabolism and free fatty acids and Bile acids. I will investigate these relationships with gut microbiome composition. Outcomes Descriptive and bioinformatic analysis on associations of multivariate biomarkers including muscle mass and muscle strength from lower and upper body and functional tests, and plasma metabolome and proteome items according to cardiac function and HF status.

Study Type

OBSERVATIONAL

Enrollment

Eligibility

Sex: ALLMin age: 50 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion criteria for HF: 1. Clinically diagnosed HF regardless of ejection fraction rate (both HFrEF and HFpEF). 2. Age 50 years and older. 3. BMI more than 18 and less than 30 kg/m\^2. 4. Must be on optimal medical treatment for three months prior to inclusion. 5. Do not have contraindications to providing a blood sample. 6. Sufficient mental capacity to consent as determined by the researchers. 7. Able to walk with or without a walker for at least 16 m. 8. No objection to the researchers contacting their general practitioner and neurologist. Exclusion criteria for HF: 1. Receiving treatment with antibiotics, probiotics, or fish oil during the last 3 months prior to inclusion. 2. Major comorbidities (i.e., cancer, Alzheimer's, type 2 diabetes, chronic kidney disease). 3. Treatment with immunosuppressive drugs. 4. Concurrent infections, or bowel disease. 5. Patients who had received cardiac resynchronization therapy during the past 6 months will not be included. 6. Participants must also not be on any other clinical trial during the study. Inclusion criteria for Healthy controls: 1. No history of chronic disease and will be screened for hypertension. 2. BMI more than 18 and less than 30 kg/m\^2. 3. Although other cardiovascular conditions will be exclusionary, treated hypercholesterolemia and controlled hypertension will be allowed in the healthy group to allow the representation of elderly subjects within this cohort.

Outcomes

Primary Outcomes

Appendicular Lean Mass (kg)

Appendicular lean mass refers to the skeletal muscle mass in the limbs, including the arms and legs. It is a specific component of body composition that is often assessed in research and clinical settings. The term "appendicular" refers to the appendages or limbs of the body. This will be measured via dual x-ray absorptiometry (GE Lunar iDXA).

Time frame: Baseline

Gait Speed (m/s)

Gait speed test (10-meter walking); a physical function test for which the participants' walking speed is measured.

Time frame: Baseline

Handgrip Strength (kg)

A surrogate marker of upper-body strength for which a hand dynamometer (Jamar Hydraulic Hand Dynamometer) will be used for its assessment in both arms.

Time frame: Baseline

Secondary Outcomes

Metabolomics

Metabolomics is a branch of omics sciences that involves the comprehensive study of small molecules, known as metabolites, within a biological system. As part of this study blood samples will be analysed using Chromatography Mass Spectrometry (LC/MS).

Time frame: Baseline

Hospital admission due to cardiac event

Number of hospital admissions due to cardiac event for each participant

Time frame: up to 3 years

Short-chain fatty acid count

Faecal concentration of short-chain fatty acids will be assessed via Gas Chromatography Mass Spectrometry (GC/MS); a powerful analytical technique used to analyze and quantify the concentration of various compounds, including Short-chain fatty acid, in biological samples.

Time frame: Baseline

Gut microbiota count

For the assessment of gut microbiota through faecal samples, 16S rRNA-based sequencing will be employed. 16S rRNA-based sequencing is a molecular biology technique used for the analysis of microbial communities, particularly bacteria.

Time frame: Baseline

Dietary Intake (kcal and grams/day)

Food Frequency Questionnaire (FFQ- EPIC-Norfolk) will be used to evaluate the daily energy and macro/micronutrient intake of each participant. Data from FFQ will be analysed FETA, which is an open source, cross-platform tool that processes dietary data from the food frequency questionnaire used by the European Prospective Investigation into Cancer and Nutrition Norfolk (EPIC-Norfolk) and automatically generates a spreadsheet containing energy, nutrient and food group intakes.

Time frame: Baseline

Quality of Life (score)

The SarQoL questionnaire is a patient-reported outcome measure specific to sarcopenia in aged people. The SarQoL® questionnaire consists of 22 questions incorporating 55 items that fall into seven domains of health-related quality of life (HRQoL). These domains are "Physical and Mental Health," "Locomotion," "Body Composition," "Functionality," "Activities of Daily Living," "Leisure activities," and "Fears," and it takes 10 min to complete. Each domain is scored from 0 to 100, and an overall score is calculated obtained the official scoring algorithm from the developers of the SarQoL® questionnaire.

Time frame: Baseline

Physical Activity level

International Physical Activity Questionnaire (IPAQ) (physical activity levels of each participant)

Time frame: Baseline

Insomnia (score)

Responses can range from 0 to 4, where higher scores indicate more acute symptoms of insomnia. Scores are tallied and can be compared both to scores obtained at a different phase of treatment and to the scores of other individuals. A total score of 0-7 indicates "no clinically significant insomnia," 8-14 means "sub-threshold insomnia," 15-21 is "clinical insomnia (moderate severity)," and 22-28 means "clinical insomnia (severe).

Time frame: Baseline

Malnutrition (score)

Mini Nutritional Assessment (malnutrition status of each participant). Individuals will be divided in 3 groups using threshold values of \<17 for 'malnourished', 17-23.5 for 'at risk of malnutrition' and ≥ 24 for 'normal nutritional status', with a maximum total score of 30 point.

Time frame: Baseline

Sleep Quality (score)

Pittsburgh Sleep Quality Index (PSQI) (sleep quality status of each participant). The 19 items are grouped into 7 components, including (1) sleep duration, (2) sleep disturbance, (3) sleep latency, (4) daytime dysfunction due to sleepiness, (5) sleep efficiency, (6) overall sleep quality, and (7) sleep medication use. The global PSQI score is then calculated by totaling the seven component scores, providing an overall score ranging from 0 to 21, where lower scores denote a healthier sleep quality.

Time frame: Baseline

SARC-F (score)

SARC-F scale scores range from 0 to 10 (i.e. 0-2 points for each component; 0 = best to 10 = worst) and were dichotomised to represent symptomatic (4+) vs. healthy (0-3) status.

Time frame: Baseline

Multivariate Biomarker Study for Sarcopenia in Heart Failure

Overview

Conditions

Interventions

Eligibility

Locations (1)

Outcomes

Primary Outcomes

Secondary Outcomes