Biomarkers predictive of atrial fibrillation in patients with cryptogenic stroke. Insights from the Nordic Atrial Fibrillation and Stroke (NOR-FIB) study.

BACKGROUND AND PURPOSE: There are currently no biomarkers to select cryptogenic stroke (CS) patients for monitoring with insertable cardiac monitors (ICMs), the most effective tool for diagnosing atrial fibrillation (AF) in CS. The purpose of this study was to assess clinically available biomarkers as predictors of AF. METHODS: Eligible CS and cryptogenic transient ischaemic attack patients underwent 12-month monitoring with ICMs, clinical follow-up and biomarker sampling. Levels of cardiac and thromboembolic biomarkers, taken within 14 days from symptom onset, were compared between patients diagnosed with AF (n = 74) during monitoring and those without AF (n = 185). Receiver operating characteristic curves were created. Biomarkers reaching area under the receiver operating characteristic curve ≥ 0.7 were dichotomized by finding optimal cut-off values and were used in logistic regression establishing their predictive value for increased risk of AF in unadjusted and adjusted models. RESULTS: B-type natriuretic peptide (BNP), N-terminal pro-brain natriuretic peptide (NT-proBNP), creatine kinase, D-dimer and high-sensitivity cardiac troponin I and T were significantly higher in the AF than non-AF group. BNP and NT-proBNP reached the predefined area under the curve level, 0.755 and 0.725 respectively. Optimal cut-off values were 33.5 ng/l for BNP and 87 ng/l for NT-proBNP. Regression analysis showed that NT-proBNP was a predictor of AF in both unadjusted (odds ratio 7.72, 95% confidence interval 3.16-18.87) and age- and sex-adjusted models (odds ratio 4.82, 95% confidence interval 1.79-12.96). CONCLUSION: Several clinically established biomarkers were associated with AF. NT-proBNP performed best as AF predictor and could be used for selecting patients for long-term monitoring with ICMs.

Biomarkers Associated with Atrial Fibrillation in Patients with Ischemic Stroke: A Pilot Study from the NOR-FIB Study.

BACKGROUND AND PURPOSE: Cardioembolic stroke due to paroxysmal atrial fibrillation (AF) may account for 1 out of 4 cryptogenic strokes (CS) and transient ischemic attacks (TIAs). The purpose of this pilot study was to search for biomarkers potentially predicting incident AF in patients with ischemic stroke or TIA. METHODS: Plasma samples were collected from patients aged 18 years and older with ischemic stroke or TIA due to AF (n = 9) and large artery atherosclerosis (LAA) with ipsilateral carotid stenosis (n = 8) and age- and sex-matched controls (n = 10). Analyses were performed with the Olink technology simultaneously measuring 184 biomarkers of cardiovascular disease. For bioinformatics, acquired data were analyzed using gene set enrichment analysis (GSEA). Selected proteins were validated using ELISA. Individual receiver operating characteristic (ROC) curves and odds ratios from logistic regression were calculated. A randomForest (RF) model with out-of-bag estimate was applied for predictive modeling. RESULTS: GSEA indicated enrichment of proteins related to inflammatory response in the AF group. Interleukin (IL)-6, growth differentiation factor (GDF)-15, and pentraxin-related protein PTX3 were the top biomarkers on the ranked list for the AF group compared to the LAA group and the control group. ELISA validated increased expression of all tested proteins (GDF-15, PTX3, and urokinase plasminogen activator surface receptor [U-PAR]), except for IL-6. 19 proteins had the area under the ROC curve (AUC) over 0.85 including all of the proteins with significant evolution in the logistic regression. AUCs were very discriminant in distinguishing patients with and without AF (LAA and control group together). GDF-15 alone reached AUC of 0.95. Based on RF model, all selected participants in the tested group were classified correctly, and the most important protein in the model was GDF-15. CONCLUSIONS: Our results demonstrate an association between inflammation and AF and that multiple proteins alone and in combination may potentially be used as indicators of AF in CS and TIA patients. However, further studies including larger samples sizes are needed to support these findings. In the ongoing NOR-FIB study, we plan further biomarker assessments in patients with CS and TIA undergoing long-term cardiac rhythm monitoring with insertable cardiac monitors.