Journal article icon

Journal article

An angiopoietin 2, FGF23, and BMP10 biomarker signature differentiates atrial fibrillation from other concomitant cardiovascular conditions

Abstract:
Abstract Early detection of atrial fibrillation (AF) enables initiation of anticoagulation and early rhythm control therapy to reduce stroke, cardiovascular death, and heart failure. In a cross-sectional, observational study, we aimed to identify a combination of circulating biomolecules reflecting different biological processes to detect prevalent AF in patients with cardiovascular conditions presenting to hospital. Twelve biomarkers identified by reviewing literature and patents were quantified on a high-precision, high-throughput platform in 1485 consecutive patients with cardiovascular conditions (median age 69 years [Q1, Q3 60, 78]; 60% male). Patients had either known AF (45%) or AF ruled out by 7-day ECG-monitoring. Logistic regression with backward elimination and a neural network approach considering 7 key clinical characteristics and 12 biomarker concentrations were applied to a randomly sampled discovery cohort (n = 933) and validated in the remaining patients (n = 552). In addition to age, sex, and body mass index (BMI), BMP10, ANGPT2, and FGF23 identified patients with prevalent AF (AUC 0.743 [95% CI 0.712, 0.775]). These circulating biomolecules represent distinct pathways associated with atrial cardiomyopathy and AF. Neural networks identified the same variables as the regression-based approach. The validation using regression yielded an AUC of 0.719 (95% CI 0.677, 0.762), corroborated using deep neural networks (AUC 0.784 [95% CI 0.745, 0.822]). Age, sex, BMI and three circulating biomolecules (BMP10, ANGPT2, FGF23) are associated with prevalent AF in unselected patients presenting to hospital. Findings should be externally validated. Results suggest that age and different disease processes approximated by these three biomolecules contribute to AF in patients. Our findings have the potential to improve screening programs for AF after external validation
Publication status:
Published
Peer review status:
Peer reviewed

Actions

Access Document

Files:
Publisher copy:
10.1038/s41598-023-42331-7
Publication website:
http://pure-oai.bham.ac.uk/ws/files/208278521/41598_2023_Article_42331.pdf

Authors

More by this author
Role:
Author
ORCID:
0000-0002-6747-8813
More by this author
Role:
Author
ORCID:
0000-0002-9588-6304
More by this author
Role:
Author
ORCID:
0000-0003-4238-5319
More by this author
Role:
Author
ORCID:
0000-0002-6660-796X
More by this author
Role:
Author
ORCID:
0000-0001-7088-3943


Publisher:
Nature Research
Journal:
Scientific Reports More from this journal
Volume:
13
Issue:
1
Pages:
16743-16743
Article number:
16743
Publication date:
2023-10-05
DOI:
EISSN:
2045-2322
ISSN:
2045-2322


Language:
English
Keywords:
Pubs id:
1546142
Local pid:
pubs:1546142
Source identifiers:
W4387373964
Deposit date:
2026-05-17
ARK identifier:
This ORA record was generated from metadata provided by an external service. It has not been edited by the ORA Team.

Terms of use


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP