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. Author manuscript; available in PMC: 2026 Jan 1.
Published in final edited form as: J Cardiovasc Nurs. 2024 Jul 10;40(4):E167–E173. doi: 10.1097/JCN.0000000000001110

Atrial Fibrillation and Older Age Predict Serum Brain-Derived Neurotrophic Factor (BDNF) Levels among Patients with Heart Failure

Susan J Pressler a, Miyeon Jung b, Susan G Dorsey c, Bruno Giordani d, Marita G Titler e, Kelly L Wierenga f, David G Clark g, Dean G Smith h, Asa B Smith i, Irmina Gradus-Pizlo j, Milton L Pressler k
PMCID: PMC11717985  NIHMSID: NIHMS1986913  PMID: 39007747

Abstract

Background:

Predictors have not been determined of serum brain-derived neurotrophic factor (BDNF) levels among patients with heart failure (HF).

Objective:

The primary purpose was to evaluate history of atrial fibrillation, age, gender, and LVEF as predictors of serum BDNF levels at baseline, 10 weeks, and 4 and 8 months after baseline among patients with HF.

Methods:

This study was a retrospective cohort analyses of 241 patients with heart failure (HF). Data were retrieved from patients’ health records (coded history of atrial fibrillation, left ventricular ejection fraction [LVEF]), self-report (age, gender), and serum (BDNF). Linear multiple regression analyses were conducted.

Results:

103 (42.7%) patients had a history of atrial fibrillation. History of atrial fibrillation was a significant predictor of serum BDNF levels at baseline (β = −.16, P = .016) and 4 (β = −.21, P = .005) and 8 months (β = −.19, P = .015). Older age was a significant predictor at 10 weeks (β = −.17, P = .017) and 4 months (β = −.15, P = .046).

Conclusions:

Prospective studies are needed to validate these results. Clinicians need to assess patients with HF for atrial fibrillation and include treatment of it in management plans.

Keywords: heart failure, congestive heart failure, atrial fibrillation, brain-derived neurotrophic factor, BDNF

Introduction

Heart failure (HF) is associated with high rates of mortality and morbidity affecting approximately 6.7 million people in the U.S.1 and 64.3 million people worldwide.2 Atrial fibrillation is a common comorbidity that occurs in approximately one-third of patients with HF.3 Patients with HF and atrial fibrillation are at increased risk of embolic stroke,4,5 dementia,6 and mortality.1,4,5 Cerebral microemboli7,8 that may result from atrial fibrillation4–6 are a potential etiology for cognitive dysfunction found among 23% to 50% of patients with HF.9,10 However, history of atrial fibrillation and its potential association with brain-derived neurotrophic factor (BDNF) were not investigated in past studies of cognitive dysfunction in HF.6,9–13

The neurotrophin BDNF has a role in neuronal development, neurogenesis, and neuroplasticity.14–16 It promotes growth and survival of neurons in the brain and regulates synaptic neuroplasticity, contributing to learning and memory.16 It has a neuroprotective effect in brain injury and disease (e.g., cerebral ischemia, neurotoxicity).15 Circulating blood levels of BDNF have been investigated to characterize phenotypes of cognitive dysfunction across populations. For example, persons with schizophrenia and Alzheimer disease had lower serum BDNF levels compared with healthy persons.17–19

The neurotrophin BDNF has a role in non-neuronal cells20–23 and independent and local effects on the cardiovascular system (e.g., angiogenesis, vasculogenesis, and cardiomyocyte contractility).20,21 In animal studies, BDNF deficiency was associated with murine endothelial cell apoptosis, missing intramyocardial blood vessels, thinning cardiac chambers, and depressed cardiac contractility during gestation.23 It may induce oxidative stress that is associated with atherosclerotic plaque instability.24 Lower levels of serum BDNF may be associated with death from cardiac related conditions.25 Bahls and colleagues26 evaluated associations between BDNF and left ventricular remodeling and N-terminal pro b-type natriuretic peptide (NTproBNP) among 2,976 adults (mean age 48; patients excluded if left ventricular ejection fraction [LVEF] < 40%). Lower levels of BDNF were associated with significantly greater left ventricular mass and higher levels of NTproBNP after controlling for age, sex, lean and fat mass, smoking, systolic blood pressure, and depression. In a study to evaluate plasma BDNF levels among 242 patients with HF and 80 age- and education-matched healthy adults, Takashio and colleagues27 found that plasma BDNF levels were significantly lower among the patients with HF and with worse NYHA functional class. Log BDNF levels were inversely correlated with log B-type natriuretic peptide (BNP) among the patients with HF.27 Overall, BDNF appears to be associated with cardiovascular function among adults with HF, but the specific mechanisms and directions of association are undetermined.21

Atrial fibrillation is associated with cognitive dysfunction. Rivard and colleagues6 reviewed the literature and concluded that a relationship between atrial fibrillation and cognitive impairment and dementia may exist, but more rigorous prospective studies and randomized controlled trials are needed to confirm a causal association.6 These authors recommended that biomarkers be identified and validated to predict cognitive dysfunction among patients with HF.6 In a search of Medline (keywords: heart failure, congestive heart failure, atrial fibrillation, brain-derived neurotrophic factor, and BDNF; timing: inception - July 26, 2023), no studies were identified that addressed the relationship between atrial fibrillation and serum BDNF levels among patients with HF. Rahman and colleagues28 conducted a retrospective study of the association of serum BDNF with 10-year risk of incident atrial fibrillation using Framingham Heart Study data. Of the 3,457 community-dwelling participants in the study, 395 (11%) developed atrial fibrillation. Serum BDNF was significantly associated with atrial fibrillation incidence in the unadjusted Cox proportional hazards regression model, but the model became non-significant when adjusted for age and sex.28 In the study, the ability to detect an association was likely limited because participants did not have atrial fibrillation or serious cardiac conditions (i.e., myocardial infarction, 5%; HF, 1%) at study entry.

Serum BDNF levels may vary with age, sex, and measures of HF severity (e.g., LVEF; BNP). Lommatzsch and colleagues29 found that the concentration ranges of serum, plasma, and platelet BDNF levels varied widely and that plasma BDNF levels were negatively correlated with age and weight among 140 healthy adults ages 20 to 60 years. Naegelin30 found that serum BDNF levels were weakly correlated with age but not with sex among 259 healthy volunteers.

Circulating levels of BDNF in the blood may reflect local BDNF levels in selected structures and may be influenced by single-nucleotide polymorphisms (SNPs) in the BDNF locus on chromosome 11.31 The BDNF SNP rs6265 produces a valine(Val)-to-methionine (Met) substitution in the pro-BDNF protein at codon 66 (Val66Met) which inhibits production and release of BDNF. The Met allele is associated with learning and memory disorders in adults in the U.S. and Australia.16,32–34 The prevalence of people with the BDNF Met allele varies by population genetic structure, ranging from 0 to 72%.21,35 The prevalence of the BDNF Met allele (Val/Met or Met/Met genotype) is approximately 20% among Americans of European descent, 50% among persons of East Asian descent, and 5% among persons of African American descent.36

The primary purpose of the current study was to evaluate history of atrial fibrillation, age, gender, and LVEF as predictors of serum BDNF levels at baseline, 10 weeks, and 4 and 8 months after baseline among patients with HF in the Cognitive Intervention to Improve Memory in Heart Failure Patients (NR016116;NCT #03035565; Pressler MPI) (MEMOIR-HF) study.37,38 The hypotheses were that history of atrial fibrillation, age, gender, and LVEF predict serum BDNF levels measured over time among patients with HF in MEMOIR-HF. In secondary analyses, BDNF Val66Met and BNP were evaluated as predictors of serum BDNF levels. To our knowledge, this is one of the first studies to evaluate the association between atrial fibrillation and serum BDNF levels measured serially over 8 months among a sample of patients with HF.

Methods

Design and Procedures

This study was a retrospective cohort analyses39 of data obtained from MEMOIR-HF, a 3-arm randomized controlled trial conducted to evaluate the efficacy of a computerized cognitive training intervention compared with computerized puzzles active control intervention and usual care among 256 patients with HF.37 MEMOIR-HF was approved by the university institutional review board and patients provided written informed consent prior to data collection. The complete MEMOIR-HF procedures are described elsewhere.37,38 Briefly, in MEMOIR-HF, it was hypothesized that compared with patients randomized to active control computerized crossword puzzles and usual care groups, patients in the computerized cognitive training group would have statistically significant improvement in 5 outcomes: 2 co-primary outcomes of memory and serum BDNF levels; and 3 secondary outcomes of working memory, instrumental activities of daily living (IADLs), and health-related quality of life (HRQL).38,40 The computerized cognitive training intervention was an 8-week intervention during which time patients completed 40 hours of training (5 hours per week for 8 weeks). Data were collected at baseline and at 10 weeks and 4 and 8 months after baseline. Patients were randomized to the 3 groups after baseline data collection. In linear mixed models analyses, there were no significant group by time differences in the 5 outcomes at 8 months, but there were statistically significant time differences in all 5 outcomes. Memory (P < .0001), working memory (P = .049), IADLs (P = .023), and HRQL (P = .025) scores significantly improved over time; serum BDNF levels unexpectedly decreased over time (P = .0007) among patients in all 3 groups.38

Sample

The sample was 241 patients from 7 cardiology clinics randomized in MEMOIR-HF. MEMOIR-HF inclusion criteria were: (1) 21 years or older; (2) understands English; (3) access to telephone; (4) able to hear normal conversation; (5) able to read computer monitor; (6) chronic HF, stage C; (7) NYHA class I, II, or III; and (8) prescribed optimized medical care. One additional inclusion criterion for this cohort study was having serum BDNF levels obtained at baseline. Exclusion criteria were: (1) comorbid condition that causes memory loss; (2) terminal illness; and (3) MoCA41 score less than 19.42

Measures

Serum BDNF levels were measured at MEMOIR-HF baseline and follow-up visits at 10 weeks and 4 and 8 months after baseline. Serum BDNF levels were analyzed using a commercially available ELISA assay (R&D Systems, Minneapolis, MN) in batches with duplicates for all patients. The BDNF limit of detection was 20 pg/mL and no samples had measurements below this limit.

International Classification of Diseases (ICD)-10 codes for history of atrial fibrillation were retrieved from the Regenstrief Institute Data Core, the central point of access for health databases at Indiana University (https://www.regenstrief.org/resources/regenstrief-data-core/) (accessed 07/25/2023). Age and gender were obtained by patient self-report at baseline. The LVEF was assessed by the echocardiograms completed prior to and closest to the baseline date. BDNF Val66Met candidate gene analysis was completed at laboratories at Indiana University and University of Maryland. The BDNF variant of interest was the ValMet polymorphism rs6265, which is a substitution of methionine at Codon 66.43 Details of the BDNF Val66Met analysis are presented elsewhere.38,40 Patients were categorized as having the Met polymorphism present (Val/Met or Met/Met) or absent (Val/Val). BNP levels prior to and closest to the baseline were retrieved from the Regenstrief Institute Data Core.

Statistical analysis

Descriptive statistics were computed for demographic and clinical variables of the total sample and the patients with and without a coded history of atrial fibrillation. Comparisons were evaluated using independent t-tests for differences in serum BDNF levels at the 4 timepoints between patients with and without a history of atrial fibrillation.

Linear multiple regression analysis was used to test the hypotheses.44,45 Preliminary analyses were conducted to ensure that the assumptions of normality, linearity, homoschedasticity, and multicollinearity were not violated. In separate equations, history of atrial fibrillation, age, gender, and LVEF were entered simultaneously as independent variables and serum BDNF levels as the dependent variable for each of the 4 timepoints. Two secondary analyses were conducted using linear multiple regression to evaluate BDNF Val66Met gene and BNP levels as independent predictors of serum BDNF levels at the 4 timepoints. BDNF Val66Met was evaluated as a predictor because of its role in producing serum BDNF and it was more prevalent among patients with a history of atrial fibrillation in this sample. BNP was evaluated as a predictor variable because of its relationship with HF severity and serum BDNF levels.26 The statistical software SPSS versions 28 and 29 were used to complete the analyses. The significance level was alpha < .05.

Results

Demographic and clinical variables are presented in Table 1. The sample was 112 men and 129 women with mean age 66.2 years (SD = 12.3) and mean LVEF 48.8% (SD = 14.5%). Of the 241 patients, 103 (42.7%) had a history of atrial fibrillation. The mean serum BDNF levels were 18.3 ng/mL (SD = 7.7) at baseline for the total sample (N = 241), 16.5 ng/mL (SD = 8.6) at 10 weeks (N = 200), 16.6 ng/mL (SD = 8.5) at 4 months (N = 189), and 15.7 ng/mL (SD = 8.) at 8 months (N = 163). Compared with patients without a history of atrial fibrillation, patients with a history of atrial fibrillation had statistically significantly lower levels of serum BDNF at each of the 4 timepoints (Figure 1).

Table 1.

Descriptive statistics for demographic and clinical variables for total sample (n = 241) and patients with (n = 103) and without (n = 138) coded history of atrial fibrillation

Variable Overall History of atrial fibrillation No history of atrial fibrillation
n = 241 n = 103 n = 138
Demographic variables
Age, mean (SD), y 66.2 (12.3) 69.7 (10.6) 63.6 (12.8)
Gender, n (%)
 Men 112 (46.5) 55 (53.4) 57 (41.3)
 Women 129 (53.5) 48 (46.6) 81 (58.7)
Race, n (%)
 Asian 0 0 0
 Native Hawaiian/Pacific Islander 1 (0.4) 1 (1.0) 0
 Black/African American 33 (13.7) 1 (1.0) 32 (23.2)
 White 206 (85.5) 101 (98.1) 105 (76.1)
 More than 1 race 1 (0.4) 0 1 (0.7)
Ethnicity, n (%)
 Hispanic or Latino 3 (1.2) 0 3 (2.2)
 Non-Hispanic or Latino 237 (98.3) 103 (100) 134 (97.1)
 Unknown 1 (0.4) 0 1 (0.7)
Marital status, n (%)
 Married 124 (51.5) 58 (56.3) 66 (47.8)
 Not married 117 (48.5) 45 (43.7) 72 (52.2)
Education, mean (SD), y 13.8 (2.6) 13.9 (2.5) 13.8 (2.7)
BMI, mean (SD), (n = 240) 34.2 (8.8) 33.0 (8.7) 35.1 (8.7)
Clinical variables
LVEF, %, mean (SD), (n = 239) 48.8 (14.5) 49.3 (13.4) 48.3 (15.4)
BNP, mean (SD), pg/mL, (n = 170, 75, 95) 358.5 (490.5) 400.4 (46.0) 325.3 (56.7)
NYHA class, n (%)
I 23 (9.5) 8 (7.9) 15 (10.9)
 II 91 (37.8) 36 (35.6) 55 (39.9)
 III 125 (51.9) 57 (56.4) 68 (49.3)
 Missing 2 (0.8) - -
Medications, n (%)
 ACE inhibitor 84 (34.9) 34 (33) 50 (36.2)
 ARB 60 (24.9) 20 (19.4) 40 (29.0)
 ARNI 17 (7.1) 3 (2.9) 14 (10.1)
 Total RAS inhibitor 158 (65.6) 57 (55.3) 101 (73.2)
 Beta-adrenergic blocker 200 (83.0) 82 (79.6) 118 (85.5)
 Diuretic 187 (77.6) 82 (79.6) 105 (76.1)
 Aldosterone antagonist 67 (27.8) 25 (24.3) 42 (30.4)
 SGLT-2 inhibitor 6 (2.5) 2 (1.9) 4 (2.9)
 Warfarin 49 (20.3) 36 (35.0) 13 (9.4)
 Antiplatelet 53 (22.0) 12 (11.7) 41 (29.7)
 Factor Xa inhibitor 57 (23.7) 50 (48.5) 7 (5.1)
 Thrombin inhibitor 3 (1.2) 3 (2.9) 0
 Antidepressant 77 (32.0) 33 (32) 44 (31.9)
 Anxiolytic/sedative/hypnotic 23 (9.5) 13 (12.6) 10 (7.2)
History comorbid condition, n (%)
 Hypertension 197 (81.7) 85 (82.5) 112 (81.2)
 Coronary artery disease 105 (43.6) 45 (43.7) 60 (43.5)
 Coronary artery bypass graft 49 (20.3) 28 (27.2) 21 (15.2)
 Depression 48 (19.9) 20 (19.4) 28 (20.3)
 Diabetes 107 (44.4) 40 (38.8) 67 (48.6)
 Myocardial infarction 49 (20.3) 23 (22.3) 26 (18.8)
 Sudden cardiac arrest 6 (2.5) 1 (1) 5 (3.6)
 Stroke 23 (9.5) 8 (7.8) 15 (10.9)
 Transient ischemic attack 10 (4.1) 5 (4.9) 5 (3.6)
 Ventricular arrhythmias 38 (15.8) 17 (16.5) 21 (15.2)
MoCA, mean (SD) 25.2 (2.5) 25.2 (2.5) 25.3 (2.6)
BDNF Val66Met n (%) (n = 240) 68 (28.3) 37 (36.3) 31 (22.5)
Open in a new tab

ACE, angiotensin-converting enzyme; ARB, angiotensin receptor blocking agent; ARNI, angiotensin receptor-neprilysin inhibitor; BDNF, brain-derived neurotrophic factor; BMI, body mass index; BNP, B-type brain natriuretic peptide; LVEF, left ventricular ejection fraction; MoCA, Montreal Cognitive Assessment; NYHA, New York Heart Association; RAS, renin-angiotensin inhibitors; SD, standard deviation; SGLT-2, sodium-glucose co-transporter-2.

Figure 1.

Figure 1.

Open in a new tab

Means, standard deviations, and differences in serum brain-derived neurotrophic factor (BDNF) levels between patients with heart failure with and without atrial fibrillation

Linear multiple regression analyses were conducted to test the hypotheses that history of atrial fibrillation, age, gender, and LVEF predicted serum BDNF levels over 8 months. At baseline, the overall regression model was significant, F (4, 234) = 3.0, R2 = .05, P = .018. History of atrial fibrillation was a statistically significant predictor (β = −.16, t = −2.4, P = .016). Age (β = −.05, t = −0.8, P = .412), gender (β = −.11, t = −1.7, P = .099), and LVEF (β = −.03, t = −0.5, P = .620) were not significant predictors of serum BDNF levels at baseline. At 10 weeks, the overall model was significant, F (4, 194) = 4.8, R2 = .09, P = .001. Age was a significant predictor (β = −.17, t = −2.4, P = .017) and history of atrial fibrillation approached significance (β = −.14, t = −1.9, P = .053). Gender (β = −.12, t = −1.7, P = .092) and LVEF (β = −.12, t = −1.7, P = .098) were not significant predictors of serum BDNF levels at 10 weeks. At 4 months, the overall model was significant, F (4, 183) = 4.9, R2 = .10, P < .001. Age (β = −.15, t = −2.0, P = .046) and history of atrial fibrillation (β = −.21, t = −2.9, P = .005) were significant predictors. Gender (β = −.09, t = −1.2, P = .233) and LVEF (β = −.07, t = −1.0, P = .318) were not significant predictors of serum BDNF levels. At 8 months, the overall model remained significant, F (4, 157) = 4.0, R2 = .09, P = .004. History of atrial fibrillation was a significant predictor (β = −.19, t = −2.5, P = .015), age approached significance (β = −.16, t = −2.0, P = .052), and gender (β = −.06, t = −0.8, P = .442) and LVEF (β = −.10, t = 1.2, P = .225) were not significant predictors of serum BDNF levels. In summary, all 4 regression models were statistically significant, accounting for 5% to 10% of the variance in serum BDNF levels. Statistically significant predictors of serum BDNF levels were history of atrial fibrillation at baseline, age at 10 weeks, history of atrial fibrillation and age at 4 months, and history of atrial fibrillation at 8 months after baseline in this sample.

In secondary multiple regression analyses, BDNF Val66Met was not a significant predictor of serum BDNF levels and results were similar to the analyses without BDNF Val66Met. BNP was not a significant predictor of serum BDNF levels and results were similar to the analyses without BNP.

Discussion

The findings of this study are important and novel because in past studies, lower levels of serum BDNF were associated with death from cardiovascular disease and worse NYHA functional class among patients with HF.25,27 The current study hypotheses were partially supported. History of atrial fibrillation was a significant predictor of serum BDNF levels at baseline and 4 and 8 months. Older age was a significant predictor of serum BDNF at 10 weeks and 4 months. Gender and LVEF were not significant predictors of serum BDNF levels at any timepoint and these variables are not major predictors of survival in HF. The current study findings support a predictive association between atrial fibrillation burden and lower BDNF levels. Patients who had the arrhythmic burden to capture the diagnosis of atrial fibrillation were more likely to have decreased levels of serum BDNF 8 months later. This finding is important because atrial fibrillation may lead to embolization, myocardial injury, and HF exacerbation.4–6,46 In addition, atrial fibrillation burden may modulate levels of serum BDNF.4–6 Alternatively, it is possible that the association is converse to what was tested in this study and that serum BDNF levels are a risk for or mediator of myocardial remodeling. Left ventricular and left atrial dilation predispose patients to atrial fibrillation and increased neurohormonal factors including BNP.25–27 Future studies are needed to validate the magnitude and direction of the newly identified relationship between atrial fibrillation and serum BDNF levels among patients with HF.

In the secondary analyses, BDNF Val66Met and BNP were not significant predictors of serum BDNF levels. However, the Val66Met allele was more prevalent among patients with a history of atrial fibrillation (36.3%) compared with patients without atrial fibrillation (22.5%). It is possible that the sample size limited the ability to detect an association between atrial fibrillation and the Val66Met allele. Future studies with adequately powered samples that stratify patients by BDNF Val66Met allele may provide deeper knowledge about the role of BDNF in HF.

This study has limitations. Serum BDNF levels were not available at the follow-up timepoints for patients whose data collection occurred during the Coronavirus Disease 2019 pandemic when face-to-face contact was prohibited. The history of atrial fibrillation was obtained retrospectively from the electronic health record ICD-10 codes and cardiac rhythm was not monitored by the research team during the study. Lack of documentation would have likely biased results against finding the association between history of atrial fibrillation and serum BDNF levels. Despite the limitations of this study, the data were hypothesis generating and provided a unique opportunity to investigate the relationship between the common, serious comorbid condition of atrial fibrillation and the neurotrophic biomarker serum BDNF in HF. In future studies, a detailed medical history and measurement of atrial fibrillation by cardiac rhythm monitors are needed to fully detect atrial fibrillation burden. Digital wearable technologies may provide a less burdensome method for measurement of atrial fibrillation.47 In future studies, lifestyle factors (e.g., sleep, stress, exercise, nutrition) need to be investigated that may influence BDNF levels among patients with HF.

In conclusion, serum BDNF levels were significantly lower among patients with a coded history of atrial fibrillation across 8 months and history of atrial fibrillation significantly predicted serum BDNF levels at 8 months. To our knowledge, this study is the first in which this association was reported. Clinicians caring for patients with HF need to be vigilant about monitoring for atrial fibrillation because of its frequent occurrence in HF and possible association with lower serum BDNF levels that might presage a worse outcome. Patients with HF and their family caregivers need to be educated about atrial fibrillation as a common comorbid condition in HF.48,49 Specific mechanisms are undetermined for changes in BDNF and its direction of association with heart disease, HF, and atrial fibrillation. Future research on BDNF in heart disease might provide insight into HF and arrhythmic burden and better understanding of HF-related cognitive decline and potential treatments.

Acknowledgements:

We acknowledge Kittie Reid Lake, BA, for assistance with recruitment, intervention delivery, and data collection. We acknowledge William J. Gill, MD, Richard J. Kovacs, MD, and Nathan D. Lambert, MD, Indiana University School of Medicine, Krannert Institute of Cardiology, for assistance with recruitment and data collection. This study was supported by the National Institute of Nursing Research R01 NR016116 and Center for Enhancing Quality of Life in Chronic Illness, Indiana University School of Nursing. Serum BDNF analyte measures were completed by the Translation Core within the Center for Diabetes and Metabolic Diseases at Indiana University School of Medicine (P30DK097512). We acknowledge Evelina Mocci, PhD, for assistance with DNA analysis. DNA analysis measures were completed by the Maryland Genomics at the Institute for Genomic Sciences.

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