Atrial Fibrillation Fingerprinting

Atrial fibrillation (AF) is the most common age-related cardiac rhythm disorder accounting for about one-third of rhythm abnormalities related hospitalizations with annual costs in the European Union of 13 billion euro. Early recognition of AF is essential for prevention of disease progression from recurrent intermittent episodes to finally permanent AF. This progression is accompanied by a gradual increase in therapy failure and can in the end-stage even with extensive therapy not be treated. Persistence of AF is rooted in the presence of electropathology, which is defined as complex electrical conduction disorders caused by structural damage of atrial tissue. Therefore, early recognition of AF susceptibility in patients is of prime importance to halt electropathology and hence disease onset and progression. At present, AF can only be diagnosed with a surface electrocardiogram when a patient already suffers from AF. In addition, this rhythm registration cannot assess the degree of electropathology and thus the stage of AF which is essential for selection of the appropriate therapy. Hence, early recognition of AF and the start of effective treatment is seriously hampered. By exploiting electropathology, we are able to develop a novel diagnostic instrument to predict AF onset and early progression. We hypothesize that every patient has a unique biological and electrical signal profile that is influenced by age, gender and heart disease. This bio-electrical profile is deduced from the ratio abnormal/normal electrical signals in the atria and determination of specific biomarkers levels in tissue or blood samples related to structural damage. These outcomes are summarized in an AF Fingerprint. The primary objective of this project is to design a patient-specific invasive and non-invasive AF Fingerprint, which reveals the degree of electropathology and can be used to early recognize AF onset or progression in daily clinical practice. Hereto we utilize a bottom-up study design consisting of 3 different phases; AF Fingerprinting during longstanding persistent AF, progression from recurrent intermittent to persistent AF and early recognition of AF onset in a broad population. In order to achieve this we aim to 1) develop signal processing algorithms for automatic assessment of electrical profiles by quantifying signal features, 2) establish the effects of patient characteristics, different stages of AF on invasive electrical signal profiles by utilizing a unique high density atrial mapping approach (golden standard measurements) during cardiac surgery and non-invasive electrical signal profiles consisting of whole-heart body surface electrocardiograms, 3) construct AF Fingerprints, by correlating electrical signal profiles with levels of specific biomarkers related to structural damage in atrial tissue (invasive AF Fingerprint) and blood-based biomarkers (non-invasive AF Fingerprint) 4) design a mapping device for signal acquisition, compatible with the developed algorithmic software, for general use in clinical practice, replacing current available prototypes restricted by a limited number of electrode positions. At the end of this project, AF Fingerprinting can be used in daily clinical practice for early recognition or progression of AF by determination of stage of electropathology. As such, AF Fingerprinting enables early and optimal patient tailored AF treatment, thereby improving patient's outcome.

1. http://publications.europa.eu/resource/authority/data-theme/HEAL

1. http://id.loc.gov/vocabulary/iso639-1/en

1. http://data.europa.eu/eli/reg/2025/327/oj

collection type: Cohort,Disease specific,Hospital,Non-Human,Sample collection | disease: Other conduction disorders | data categories: Biological samples,Imaging data,Medical records,Physiological/Biochemical measurements,Other | materials: cDNA / mRNA,Cell lines,DNA,Serum,Tissue, cryo preserved | omics: Proteomics | imaging: N | sex: Female,Male