Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Apr 15;15(1):12921.
doi: 10.1038/s41598-025-89800-9.

Biomarker and cognitive decline in atrial fibrillation: a prospective cohort study

Philipp Krisai  1 , Magdalena Eberl  2 , Michael Coslovsky  1 , Nicolas Rodondi  3 , Patricia Chocano-Bedoya  3 , Stefanie Aeschbacher  1 , Sujeena Balasundaram  1 , Vinzent Rolny  2 , Richard Kobza  4 , Giorgio Moschovitis  5 , Elia Rigamonti  5 , Jürg H Beer  6 , Andreas Müller  7 , Tobias Reichlin  8 , David Conen  9 , Stefan Osswald  1 , Leo H Bonati  10 , Michael Kühne  11 ; Swiss-AF investigators
Collaborators, Affiliations

Biomarker and cognitive decline in atrial fibrillation: a prospective cohort study

Philipp Krisai et al. Sci Rep. .

Abstract

We investigated associations of a broad biomarker panel with cognitive decline in atrial fibrillation (AF) patients to characterize possible mechanisms. We enrolled 1440 AF patients with available baseline biomarkers and cognitive testing by the Montreal Cognitive assessment (MoCA) score at inclusion and at ≥ 2 yearly follow-ups. We investigated the associations of biomarkers with cognitive decline in univariate logistic regression models, LASSO regression analysis and built a combined model. Mean age was 72 years, 75% male, 47% paroxysmal AF. Over 4 years, 93 patients (6.5%) had cognitive decline. These patients had more often permanent AF (32.3 vs 21.5%, p = 0.007) and more often a history stroke (23.7 vs 11.2%, p < 0.001), but similar baseline MoCA scores (24.9 vs 25.3 points, p = 0.22) and anticoagulation rates (93.5 vs 89.5%, p = 0.29). The three biomarkers with the highest univariate AUC for cognitive decline were GDF-15 (0.67 [0.62-0.72]), Cystatin C (0.67 [0.61-0.72]) and high-sensitivity Troponin T (hs-TnT) (0.65 [0.60-0.70]). In LASSO regression analysis, the best cross validation included GDF-15, GFAP, ESM-1, NfL and ALAT. The combined prediction model with the highest AUC of 0.73 (0.68-0.78) included IGFBP-7, GDF-15, Cystatin C, hsCRP, ALAT, GFAP, ESM-1 and FGF23. Over 4 years, 6.5% of AF patients had cognitive decline despite a high rate of anticoagulation. Inflammation, neuronal damage, and increased amyloid-beta might be important non-ischemic mechanisms of cognitive decline in AF patients.

Keywords: Atrial fibrillation; Biomarker; Cognitive decline.

PubMed Disclaimer

Conflict of interest statement

Declarations. Competing interests: Andreas S. Müller received fellowship and training support from Biotronik, Boston Scientific, Medtronic, Abbott/St. Jude Medical, and Biosense Webster. Speaker honoraria from Biosense Webster, Medtronic, Abbott/St. Jude Medical, AstraZeneca, Daiichi Sankyo, Biotronik, MicroPort, Novartis. Consultant for Biosense Webster, Medtronic, Abbott/St. Jude Medcal, and Biotronik (all outside of the current work). David Conen received consulting fees from Roche Diagnostics, and speaker fees from Servier and BMS/Pfizer, all outside of the current work. Giorgio Moschovitis received advisory board or speaker’s fees from Astra Zeneca, Bayer, Boehringer Ingelheim, Daiichi Sankyo, Gebro Pharma, Novartis and Vifor, all outside of the submitted work. Jürg H. Beer reports grant support from the Swiss National Foundation of Science, The Swiss Heart Foundation and the Stiftung Kardio; grant support, speakers- and consultation fees to the institution from Bayer, Sanofi and Daichii Sankyo. Leo H. Bonati reports personal fees and nonfinancial support from Amgen, grants from AstraZeneca, personal fees and nonfinancial support from Bayer, personal fees from Bristol-Myers Squibb, personal fees from Claret Medical, grants from Swiss National Science Foundation, grants from University of Basel, grants from Swiss Heart Foundation, outside the submitted work. Michael Kühne reports grants from Bayer, grants from BMS, grants from Boston Scientific, grants from Daiichi Sankyo, grants from Pfizer, personal fees from Abbott, personal fees from Boston Scientific, personal fees from Daiichi Sankyo. Philipp Krisai reports speaker fees from BMS/Pfizer and research grants from the Swiss National Science Foundation, Swiss Heart Foundation, Foundation for Cardiovascular Research Basel, Machaon Foundation. Richard Kobza receives institutional grants from Abbott, Biosense-Webster, Boston-Scientific, Biotronik, Medtronic and Sis-Medical. Stefan Osswald Research grant from Swiss National Science Foundation (SNSF) for Swiss AF Cohort study (33CS30_18474/1&2). Research grant from Swiss National Science Foundation (SNSF) for Swiss AF Control study (324730_192394/1). Research grants from Swiss Heart Foundation (SHS). Research grants from Foundation for CardioVascular Research Basel (SKFB). Research grants from Roche. Educational and Speaker Office grants from Roche, Bayer, Novartis, Sanofi AstraZeneca, Daiichi-Sankyo, Pfizer. Tobias Reichlin has received research grants from the Swiss National Science Foundation, the Swiss Heart Foundation, the European Union [Eurostars 9799 – ALVALE), and the Cardiovascular Research Foundation Basel, all for work outside the submitted study. He has received speaker/consulting honoraria or travel support from Abbott/SJM, Astra Zeneca, Brahms, Bayer, Biosense-Webster, Biotronik, Boston-Scientific, Daiichi Sankyo, Medtronic, Pfizer-BMS, and Roche, all for work outside the submitted study. He has received support for his institution’s fellowship program from Abbott/SJM, Biosense-Webster, Biotronik, Boston-Scientific, and Medtronic, for work outside the submitted study. Stefanie Aeschbacher received speaker fee from Roche Diagnostics.

Figures

Fig. 1
Fig. 1
Examples of patients without (blue) and with (red) cognitive decline in their 3-year and overall slopes. Each point represents a yearly cognitive assessment.
Fig. 2
Fig. 2
Univariate performance with AUC and 95% confidence intervals of age and individual biomarkers for cognitive decline.
Fig. 3
Fig. 3
LASSO (Least Absolute Shrinkage and Selection Operator) regression analysis for biomarkers and cognitive decline. The lambdas (x axis) and the corresponding coefficients (y axis) for the different variables are plotted. The curves represent the change of the coefficient for each lambda and decrease with the increase of the penalty term (lambda). The first line is the minimal value of lambda that results in the best cross validation result. The second line is the largest lambda within 1 standard error of the minimal lambda. This lambda corresponds to a higher penalized model.
Fig. 4
Fig. 4
Multivariate regression model by stepwise selection (left) and AUC for the selected model (right) for cognitive decline. Estimates show the change in the risk of cognitive decline per 1-unit change of the natural logarithm of the respective biomarker.
See this image and copyright information in PMC

References

    1. Kalantarian, S., Stern, T. A., Mansour, M. & Ruskin, J. N. Cognitive impairment associated with atrial fibrillation: A meta-analysis. Ann. Intern. Med.158, 338–346 (2013). - PMC - PubMed
    1. Chen, L. Y. et al. Persistent but not paroxysmal atrial fibrillation is independently associated with lower cognitive function: ARIC study. J. Am. Coll. Cardiol.67, 1379–1380 (2016). - PMC - PubMed
    1. Krijthe, B. P. et al. Projections on the number of individuals with atrial fibrillation in the European Union, from 2000 to 2060. Eur. Heart J.34, 2746–2751 (2013). - PMC - PubMed
    1. Chugh, S. S. et al. Worldwide epidemiology of atrial fibrillation: A Global Burden of Disease 2010 Study. Circulation129, 837–847 (2014). - PMC - PubMed
    1. Conen, D. et al. Relationships of overt and silent brain lesions with cognitive function in patients with atrial fibrillation. J. Am. Coll. Cardiol.73, 989–999 (2019). - PubMed