An angiopoietin 2, FGF23, and BMP10 biomarker signature differentiates atrial fibrillation from other concomitant cardiovascular conditions
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An angiopoietin 2, FGF23, and BMP10 biomarker signature differentiates atrial fibrillation from other concomitant cardiovascular conditions. / Chua, Winnie; Cardoso, Victor R; Guasch, Eduard; Sinner, Moritz F; Al-Taie, Christoph; Brady, Paul; Casadei, Barbara; Crijns, Harry J G M; Dudink, Elton A M P; Hatem, Stéphane N; Kääb, Stefan; Kastner, Peter; Mont, Lluis; Nehaj, Frantisek; Purmah, Yanish; Reyat, Jasmeet S; Schotten, Ulrich; Sommerfeld, Laura C; Zeemering, Stef; Ziegler, André; Gkoutos, Georgios V; Kirchhof, Paulus; Fabritz, Larissa.
In: SCI REP-UK, Vol. 13, No. 1, 05.10.2023, p. 16743.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - An angiopoietin 2, FGF23, and BMP10 biomarker signature differentiates atrial fibrillation from other concomitant cardiovascular conditions
AU - Chua, Winnie
AU - Cardoso, Victor R
AU - Guasch, Eduard
AU - Sinner, Moritz F
AU - Al-Taie, Christoph
AU - Brady, Paul
AU - Casadei, Barbara
AU - Crijns, Harry J G M
AU - Dudink, Elton A M P
AU - Hatem, Stéphane N
AU - Kääb, Stefan
AU - Kastner, Peter
AU - Mont, Lluis
AU - Nehaj, Frantisek
AU - Purmah, Yanish
AU - Reyat, Jasmeet S
AU - Schotten, Ulrich
AU - Sommerfeld, Laura C
AU - Zeemering, Stef
AU - Ziegler, André
AU - Gkoutos, Georgios V
AU - Kirchhof, Paulus
AU - Fabritz, Larissa
N1 - © 2023. Springer Nature Limited.
PY - 2023/10/5
Y1 - 2023/10/5
N2 - 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.
AB - 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.
KW - Humans
KW - Male
KW - Aged
KW - Female
KW - Atrial Fibrillation
KW - Angiopoietin-2
KW - Cross-Sectional Studies
KW - Biomarkers
KW - Stroke/complications
KW - Risk Factors
KW - Bone Morphogenetic Proteins/therapeutic use
U2 - 10.1038/s41598-023-42331-7
DO - 10.1038/s41598-023-42331-7
M3 - SCORING: Journal article
C2 - 37798357
VL - 13
SP - 16743
JO - SCI REP-UK
JF - SCI REP-UK
SN - 2045-2322
IS - 1
ER -
