Circulating microRNAs to predict neurological outcome after sudden cardiac arrest
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE34643 | GEO | 2013/01/11
SECONDARY ACCESSION(S): PRJNA151255
REPOSITORIES: GEO
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Project description:Studies of miRNA profiling to predict outcome in cardiac arrest patients treated with therapeutic hypothermia (TH) Venous blood was collected in citrated tubes prior discharge. Plasma was harvested by centrifugation and stored at -80°C until assayed. Identical volumes of plasma from the 14 patients of a group (cerebral performance category (CPC): 1-2 or CPC: 3-5) were pooled to reach a final volume of 400µL for each group. The two pools were processed conjointly. Total RNA was extracted using miRVana isolation kit (Applied Biosystems), dephosphorylated and labeled using miRNA Complete Labeling and hybridization kit (Agilent). Hybridization was performed on miRNA Human Microarray Release 12.0 slides (Agilent). 4 arrays per pool were hybridized. Scanning was achieved with the Genepix 4000B Scanner (Molecular Devices, Sunnyvale, USA). Raw data were acquired with the Genepix Pro software (Molecular Devices).
2013-01-11 | E-GEOD-34643 | biostudies-arrayexpress
Project description: Not available
| S-DIXA-D-1113 | biostudies-other
Project description:MicroRNAs (miRNAs) have regulatory functions in organs critical in resuscitation from sudden cardiac arrest due to ventricular fibrillation (VF-SCA); therefore, circulating miRNAs may be markers of VF-SCA outcome.We measured candidate miRNAs (N=45) in plasma using qRT-PCR among participants of a population-based VF-SCA study. Participants were randomly selected cases who died in the field (DF, n=15), died in hospital (DH, n=15), or survived to discharge (DC, n=15), and, age-, sex-, and race-matched controls (n=15). MiRNA levels were compared using ANOVA, t-tests, and fold-changes.Mean age of groups ranged from 66.9 to 69.7. Most participants were male (53-67%) and white (67%). Comparing cases to controls, plasma levels of 17 miRNAs expressed in heart, brain, liver, and other tissues (including miR-29c, -34a, -122, -145, -200a, -210, -499-5p, and -663b) were higher and three non-specific miRNAs lower (miR-221, -330-3p, and -9-5p). Among DH or DC compared with DF cases, levels of two miRNAs (liver-specific miR-122 and non-specific miR-205) were higher and two heart-specific miRNAs (miR-208b and -499-5p) lower. Among DC vs. DF cases, levels of three miRNAs (miR-122, and non-specific miR-200a and -205) were higher and four heart-specific miRNAs (miR-133a, -133b, -208b, and -499-5p) lower. Among DC vs. DH cases, levels of two non-specific miRNAs (miR-135a and -9-3p) were lower.Circulating miRNAs expressed in heart, brain, and other tissues differ between VF-SCA cases and controls and are related to resuscitation outcomes. Measurement of miRNAs may clarify mechanisms underlying resuscitation, improve prognostication, and guide development of therapies. Results require replication.
| S-EPMC4996717 | biostudies-literature
Project description:Prediction of neurological outcomes shortly after cardiac arrest would represent a major breakthrough. We tested the ability of gene expression profiles of blood cells to predict outcome in cardiac arrest patients. 35 consecutive cardiac arrest patients treated with therapeutic hypothermia (33°C for 24h) were included in this prospective monocentre study. Cerebral Performance Category (CPC) was determined at discharge and 6 months later. All patients had blood sampling at the end of hypothermia. Gene expression profiles of blood cells were determined using 25,000~gene microarray in two groups of patients: good outcome (CPC 1-2) and bad outcome (CPC 3-5).
2013-06-01 | E-GEOD-29540 | biostudies-arrayexpress
Project description:Introduction: The aims of this study were to assess the concordance of different tools and to describe the accuracy of a multimodal approach to predict unfavorable neurological outcome (UO) in cardiac arrest patients. Methods: Retrospective study of adult (>18 years) cardiac arrest patients who underwent multimodal monitoring; UO was defined as cerebral performance category 3-5 at 3 months. Predictors of UO were neurological pupillary index (NPi) ≤ 2 at 24 h; highly malignant patterns on EEG (HMp) within 48 h; bilateral absence of N20 waves on somato-sensory evoked potentials; and neuron-specific enolase (NSE) > 75 μg/L. Time-dependent decisional tree (i.e., NPi on day 1; HMp on day 1-2; absent N20 on day 2-3; highest NSE) and classification and regression tree (CART) analysis were used to assess the prediction of UO. Results: Of 137 patients, 104 (73%) had UO. Abnormal NPi, HMp on day 1 or 2, the bilateral absence of N20 or NSE >75 mcg/L had a specificity of 100% to predict UO. The presence of abnormal NPi was highly concordant with HMp and high NSE, and absence of N20 or high NSE with HMp. However, HMp had weak to moderate concordance with other predictors. The time-dependent decisional tree approach identified 73/103 patients (70%) with UO, showing a sensitivity of 71% and a specificity of 100%. Using the CART approach, HMp on EEG was the only variable significantly associated with UO. Conclusions: This study suggests that patients with UO had often at least two predictors of UO, except for HMp. A multimodal time-dependent approach may be helpful in the prediction of UO after CA. EEG should be included in all multimodal prognostic models.
| S-EPMC8303816 | biostudies-literature
Project description:ObjectiveTo test serum tau as a predictor of neurological outcome after cardiac arrest.MethodsWe measured the neuronal protein tau in serum at 24, 48, and 72 hours after cardiac arrest in 689 patients in the prospective international Target Temperature Management trial. The main outcome was poor neurological outcome, defined as Cerebral Performance Categories 3-5 at 6 months.ResultsIncreased tau was associated with poor outcome at 6 months after cardiac arrest (median = 38.5, interquartile range [IQR] = 5.7-245ng/l in poor vs median = 1.5, IQR = 0.7-2.4ng/l in good outcome, for tau at 72 hours, p < 0.0001). Tau improved prediction of poor outcome compared to using clinical information (p < 0.0001). Tau cutoffs had low false-positive rates (FPRs) for good outcome while retaining high sensitivity for poor outcome. For example, tau at 72 hours had FPR = 2% (95% CI = 1-4%) with sensitivity = 66% (95% CI = 61-70%). Tau had higher accuracy than serum neuron-specific enolase (NSE; the area under the receiver operating characteristic curve was 0.91 for tau vs 0.86 for NSE at 72 hours, p = 0.00024). During follow-up (up to 956 days), tau was significantly associated with overall survival. The accuracy in predicting outcome by serum tau was equally high for patients randomized to 33 °C and 36 °C targeted temperature after cardiac arrest.InterpretationSerum tau is a promising novel biomarker for prediction of neurological outcome in patients with cardiac arrest. It may be significantly better than serum NSE, which is recommended in guidelines and currently used in clinical practice in several countries to predict outcome after cardiac arrest. Ann Neurol 2017;82:665-675.
| S-EPMC5725735 | biostudies-literature
Project description:BACKGROUND:Most deaths of comatose survivors of out-of-hospital sudden cardiac arrest result from withdrawal of life-sustaining treatment (WLST) decisions based on poor neurological prognostication and the family's intention. Thus, accurate prognostication is crucial to avoid premature WLST decisions. However, targeted temperature management (TTM) with sedation or neuromuscular blockade against shivering significantly affects early prognostication. In this study, we investigated whether heart rate variability (HRV) analysis could prognosticate poor neurological outcome in comatose patients undergoing hypothermic TTM. METHODS:Between January 2015 and December 2017, adult patients with out-of-hospital sudden cardiac arrest, successfully resuscitated in the emergency department and admitted to the intensive care unit of the Niigata University in Japan, were prospectively included. All patients had an initial Glasgow Coma Scale motor score of 1 and received hypothermic TTM (at 34?°C). Twenty HRV-related variables (deceleration capacity; 4 time-, 3 geometric-, and 7 frequency-domain; and 5 complexity variables) were computed based on RR intervals between 0:00 and 8:00?am within 24?h after return of spontaneous circulation (ROSC). Based on Glasgow Outcome Scale (GOS) at 2?weeks after ROSC, patients were divided into good outcome (GOS 1-2) and poor outcome (GOS 3-5) groups. RESULTS:Seventy-six patients were recruited and allocated to the good (n?=?22) or poor (n?=?54) outcome groups. Of the 20 HRV-related variables, ln very-low frequency (ln VLF) power, detrended fluctuation analysis (DFA) (?1), and multiscale entropy (MSE) index significantly differed between the groups (p?=?0.001), with a statistically significant odds ratio (OR) by univariate logistic regression analysis (p?=?0.001). Multivariate logistic regression analysis of the 3 variables identified ln VLF power and DFA (?1) as significant predictors for poor outcome (OR?=?0.436, p?=?0.006 and OR?=?0.709, p?=?0.024, respectively). The area under the receiver operating characteristic curve for ln VLF power and DFA (?1) in predicting poor outcome was 0.84 and 0.82, respectively. In addition, the minimum value of ln VLF power or DFA (?1) for the good outcome group predicted poor outcome with sensitivity?=?61% and specificity?=?100%. CONCLUSIONS:The present data indicate that HRV analysis could be useful for prognostication for comatose patients during hypothermic TTM.
| S-EPMC6798365 | biostudies-literature
Project description:PurposeThe majority of unconscious patients after cardiac arrest (CA) do not fulfill guideline criteria for a likely poor outcome, their prognosis is considered "indeterminate". We compared brain injury markers in blood for prediction of good outcome and for identifying false positive predictions of poor outcome as recommended by guidelines.MethodsRetrospective analysis of prospectively collected serum samples at 24, 48 and 72 h post arrest within the Target Temperature Management after out-of-hospital cardiac arrest (TTM)-trial. Clinically available markers neuron-specific enolase (NSE) and S100B, and novel markers neurofilament light chain (NFL), total tau, ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) and glial fibrillary acidic protein (GFAP) were analysed. Normal levels with a priori cutoffs specified by reference laboratories or defined from literature were used to predict good outcome (no to moderate disability, Cerebral Performance Category scale 1-2) at 6 months.ResultsSeven hundred and seventeen patients were included. Normal NFL, tau and GFAP had the highest sensitivities (97.2-98% of poor outcome patients had abnormal serum levels) and NPV (normal levels predicted good outcome in 87-95% of patients). Normal S100B and NSE predicted good outcome with NPV 76-82.2%. Normal NSE correctly identified 67/190 (35.3%) patients with good outcome among those classified as "indeterminate outcome" by guidelines. Five patients with single pathological prognostic findings despite normal biomarkers had good outcome.ConclusionLow levels of brain injury markers in blood are associated with good neurological outcome after CA. Incorporating biomarkers into neuroprognostication may help prevent premature withdrawal of life-sustaining therapy.
| S-EPMC8421280 | biostudies-literature
Project description:Background: Cardiac arrest (CA) represents the third leading cause of death worldwide. Among survivors, severe neurological sequelae are frequent but difficult to predict. Novel prognostic biomarkers would offer clinicians the possibility to deliver personalized healthcare. The potential of small circulating noncoding RNAs (microRNAs) to predict neurological outcome and survival after CA has been reported. Objective: This study aims to identify circulating circular RNAs (circRNAs) associated with clinical outcome after CA. Methods and Results: Methods and Results: Whole blood samples obtained 48h after return of spontaneous circulation from 23 sex-matched survivors and 23 deceased cardiac arrest (CA) patients were enrolled in this study. Whole transcriptome RNA sequencing identified candidate RNAs associated with neurological outcome and survival. Conclusion: We have identified candidate RNAs associated with clinical outcome after CA whose predictive value remains to be confirmed in large populations.
2022-11-02 | GSE197764 | GEO
Project description:Predicting neurological outcomes after cardiac arrest remains a major issue. This study aimed to identify novel biomarkers capable of predicting neurological prognosis after cardiac arrest. Expression profiles of GSE29540 and GSE92696 were downloaded from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs) between high and low brain performance category (CPC) scoring subgroups. Weighted gene co-expression network analysis (WGCNA) was used to screen key gene modules and crossover genes in these datasets. The protein-protein interaction (PPI) network of crossover genes was constructed from the STRING database. Based on the PPI network, the most important hub genes were identified by the cytoHubba plugin of Cytoscape software. Eight hub genes (RPL27, EEF1B2, PFDN5, RBX1, PSMD14, HINT1, SNRPD2, and RPL26) were finally screened and validated, which were downregulated in the group with poor neurological prognosis. In addition, GSEA identified critical pathways associated with these genes. Finally, a Pearson correlation analysis showed that the mRNA expression of hub genes EEF1B2, PSMD14, RPFDN5, RBX1, and SNRPD2 were significantly and positively correlated with NDS scores in rats. Our work could provide comprehensive insights into understanding pathogenesis and potential new biomarkers for predicting neurological outcomes after cardiac arrest.
| S-EPMC9316619 | biostudies-literature