Identification of the Metabolic Signature of Atrial Fibrillation for Personalized Prevention (IMAGE-AF)

Atrial fibrillation (AF) is a major public health problem. The efficacy of the existing techniques is limited in the more aggressive forms. It is therefore necessary to develop approaches, in particular the identification of relevant biomarkers, to prevent the onset, recurrence or progression of AF in at-risk patients. The objective of this study is to describe the longitudinal metabolic and biomolecular signature of AF in patients eligible for cardiac ablation.

Study Overview

• Status: Recruiting
• Conditions: Atrial Fibrillation (AF)
• Intervention / Treatment: Procedure: FA ablation; Biological: Lab test

Detailed Description

Atrial fibrillation (AF) is a major public health problem. Its prevalence exceeds 2%. The main aim of drug treatment is to prevent the onset of stroke and heart failure, but side effects often require discontinuation, and contraindications limit their use. Rhythm control strategies based on catheter ablation have led to significant progress in incident AF, improving quality of life. Nevertheless, the efficacy of these techniques is limited in the more aggressive forms. Significant recurrence rates are reported one year after ablation, and access to them is often reserved for symptomatic patients due to their invasive and costly nature.

It is therefore necessary to develop approaches to prevent the onset, recurrence or progression of AF in at-risk patients. While the pathophysiology of AF involves metabolic remodelling that can be observed in animal and human models, no clinically relevant metabolites have been identified as biomarkers of the risk of AF onset or progression, with a view to preventive and personalized management.

In response to this unmet need, this project aims to develop a method for assessing the risk of AF recurrence, combining the identification of a metabolic signature of the arrhythmia and the patient, with a machine learning approach to aggregate conventional risk factors and metabolic biomarkers. A longitudinal clinical study will be conducted on patients scheduled for AF ablation, to monitor changes in their metabolic signature over 12 months, in parallel with arrhythmia progression. Using machine learning, the study team will establish and validate a classifier retrospectively stratifying patients with or without recurrent AF, and compare this method with canonical risk stratification. This will enable to consider personalized management of patients at risk of recurrence, with the aim of reducing human and economic costs.

• Study Type: Interventional
• Enrollment (Estimated): 400
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Guido CALUORI; Phone Number: +33 5 35 38 19 58; Email: guido.caluori@ihu-liryc.fr
• Study Contact Backup: Name: Lorena SANCHEZ BLANCO; Phone Number: +33 5 57 62 30 91; Email: lorena.sanchez-blanco@chu-bordeaux.fr

Study Locations

• France
  • Pessac, France, 33604
    • Recruiting
    • University Hospital of Bordeaux
    • Contact: Lorena SANCHEZ BLANCO; Phone Number: +33 5 57 62 30 91; Email: lorena.sanchez-blanco@chu-bordeaux.fr
    • Contact: Nicolas DERVAL; Phone Number: +33 5 56 79 56 79; Email: nicolas.derval@chu-bordeaux.fr
    • Principal Investigator: Nicolas DERVAL

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• Age ≥ 18 years, all genders, and ethnic origins
• Free, informed, and written consent signed
• Person affiliated to or benefiting from a social security scheme

Exclusion Criteria:

• Age < 18 years
• Lack of informed consent
• Gestating women (pregnancy test carried out as part of care for FA patients, contraception, or menopause for women in control groups)
• Persons under administrative or judicial protection
• Endocarditis or pericarditis in progress or within the 3 last months
• Active tumor pathology (benign or malignant)
• Chronic inflammation or autoimmune disease
• Chronic liver disease
• Myocardial infarction within the last 8 weeks

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Prevention
• Allocation: Non-Randomized
• Interventional Model: Sequential Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Other: Patients with FA; Patient with a documented Fibrillation Atrial within the last 18 months	Procedure: FA ablation; Ablation of the FA; Biological: Lab test; Blood collection
Other: Patients without FA; Patient without Fibrillation Atrial	Biological: Lab test; Blood collection

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Biomarkers T1	The individuation of biomarkers uniquely present in AF patients - compared to control groups.	Day 0
Biomarkers T2	The individuation of biomarkers uniquely present in AF patients - compared to control groups.	Day 1
Biomarkers 2	The identification of biomarkers predictive of the risk of AF recurrence	12 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Algorithm	Identification of the machine learning algorithm with the best predictive performance for AF recurrence	Month 12
Atrial electroanatomy and apneas	Existence of correlation between atrial electroanatomy and apneas accompanied by desaturation	Immediately after the procedure

Collaborators and Investigators

• Sponsor: University Hospital, Bordeaux
• Investigators: Principal Investigator: Nicolas DERVAL, University Hospital, Bordeaux

Study record dates

Study Major Dates

• Study Start (Actual): March 10, 2025
• Primary Completion (Estimated): October 1, 2029
• Study Completion (Estimated): October 1, 2029

Study Registration Dates

• First Submitted: November 21, 2024
• First Submitted That Met QC Criteria: December 10, 2024
• First Posted (Actual): December 16, 2024

Study Record Updates

• Last Update Posted (Actual): June 9, 2026
• Last Update Submitted That Met QC Criteria: June 4, 2026
• Last Verified: May 1, 2026

More Information

Terms related to this study

• Keywords: biomarkers; atrial fibrillation; prevention; cardiac metabolism
• Additional Relevant MeSH Terms: Cardiovascular Diseases; Pathologic Processes; Heart Diseases; Arrhythmias, Cardiac; Pathological Conditions, Signs and Symptoms; Atrial Fibrillation
• Other Study ID Numbers: CHUBX 2024/01; 2024-A00416-41 (Registry Identifier: ANSM)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No