Network Medicine Approaches to Classify Heart Failure With PReserved Ejection Fraction by Signatures of DNA Methylation and Point-of-carE Risk calculaTors (PRESMET)
- Conditions
- Heart Failure, SystolicHeart Failure, DiastolicAtrial FibrillationPulmonary Hypertension
- Interventions
- Other: RRBS
- Registration Number
- NCT05475028
- Lead Sponsor
- University of Campania "Luigi Vanvitelli"
- Brief Summary
Heart failure (HF) is a syndrome, resulting from structural or functional impairment of ventricular filling or ejection of blood. Effective HF management depends on accurate and rapid diagnosis requiring assessment of symptoms and physical signs in combination with advanced and expensive imaging tools. However, several challenges arise from the traditional symptom-based diagnosis because co-morbidities of HF have similar presentations. This implies the need for a deeper knowledge of mechanistic links among genetic and epigenetic events governing the pathophysiology of HF leading to a novel molecular-based system to differentiate HF phenotypes. Now, it is emerging that the pathophysiology of HFpEF and HFrEF is different, it provides an opportunity to identify biomarker candidates that could aid in HF diagnosis and stratification between these two forms of the disease. The aim of PRESMET project is to perform liquid biopsy strategies to identify novel putative non-invasive epigenetic-sensitive biomarkers that could be used either alone or in combination with established diagnostic tests, such as natriuretic peptide, to help differentiate HFpEF from HFrEF. The Investigators will perform DNA methylation analysis on CD4+ T cells isolated from patients versus controls. Remarkably, big data generated from NGS tools will be analyzed by advanced network-oriented algorithms. Our results may provide a useful clinical roadmap in order to improve precision medicine and personalized therapy of HF.
- Detailed Description
The Investigators will perform the first Network Medicine approach to integrate the DNA methylome of circulating CD4+T cells and clinical parameters in patients with HFpEF and HFrEF.
Liquid biopsy strategies will be performed to isolate PBMCs and purificate CD4+ T cells. Successivelly, genomic DNA will be extracted on columns and will be send out for RRBS.
Network-oriented algorithms will be used to analyze DNA methylation signatures and to identify specific epigenetic changes in relation to left ventricle ejection fraction.
Network-oriented DNA methylation signatures will be integrated to the H2FPEF point-of-care calculator and, then, will be validated by the use of q-RT-PCR, WB, and ELISA.
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 60
- HFrEF (LVEF < 40%)
- HFpEF (LVEF > 50%)
- Patients with HF with a history of a reduced LVEF ≤ 40% (HFrEF) who recover LV function (LVEF ≥ 50%)
- Chronic inflammatory diseases
- Cancer
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description HFrEF RRBS We will recruit HFrEF (LVEF \< 40%) HFpEF RRBS We will recruit HFpEF (LVEF \> 50%) Healthy controls RRBS We will recruit volunteer blood donors
- Primary Outcome Measures
Name Time Method Levels of differentially expressed genes in CD4+ T cells 1 month The Investigators will measure the levels of gene expression of selected genes (qRT-PCR) in HFpEF vs. HFrEF, HFpEF vs. healthy controls, and HFrEF vs. healthy controls.
Percentage of differentially methylated regions (DMRs) in CD4+ T cells 3 months The Investigators will identify the panel of DMRs able to distinguish HFpEF vs. HFrEF, HFpEF vs. healthy controls, and HFrEF vs. healthy controls.
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
University of Campania Luigi Vanvitelli
🇮🇹Naples, Italy