ISSN: 2155-9880
Pascal Stammet, Melanie Kirchmeyer, Lu Zhang, Daniel R. Wagner and Yvan Devaux
Background: Early prediction of outcome after cardiac arrest (CA) may influence treatment strategies. Existing biomarkers are of limited value. Therefore, we sought to determine whether analysis of the transcriptome of circulating blood cells may help to predict outcome after CA.
Methods: Consecutive comatose patients resuscitated after CA and treated with hypothermia were enrolled in this study. Blood samples were drawn 48 hours after CA for gene expression analyses by microarrays and quantitative PCR. Neurological outcome at 6 months was evaluated using the cerebral performance category (CPC). Patients with CPC 1-2 were considered having favorable neurological outcome, whereas patients with CPC 3-5 were considered as having poor outcome.
Results: The initial cohort consisted of 35 patients. Microarrays revealed a biosignature associated with neurological outcome after CA. 582 genes were differentially expressed between patients with favorable neurological outcome (n=21) and patients with poor neurological outcome (n=14). Bioinformatic analyses revealed significant associations between these genes and neuronal damage. Prediction analysis of microarrays identified the chemokine (C-X3-C motif) receptor 1 (CX3CR1) as a candidate prognostic biomarker. CX3CR1 was up-regulated in patients with favorable outcome (2-fold, P<0.001) and predicted neurological outcome with an AUC of 0.92 (95% CI [0.83; 1.00]). In a second cohort of 45 patients, CX3CR1 was increased in patients with favorable outcome (1.6- fold, P=0.003) and predicted outcome with an AUC of 0.76 (95% CI [0.60; 0.92]). Multivariate analyses identified CX3CR1, neuron-specific enolase and acute myocardial infarction at the time of CA as significant predictors of survival. These variables had additive value to predict survival (AUC 0.84).
Conclusion: We identified CX3CR1 as a new candidate prognostic biomarker after CA. Further studies are required to confirm its predictive value.