Dataset Information

Circulating microRNAs serve as novel biological markers for intracranial aneurysms.

ABSTRACT:

Background

Biological markers that can be used to predict the risk of intracranial aneurysms (IAs) are not available.

Methods and results

To clarify whether circulating microRNAs could be used as biomarkers for IA, we carried out microarray assays in a screening cohort of 40 IA patients (20 unruptured and 20 ruptured) and 20 healthy volunteers. We identified 20 microRNAs that were unanimously changed in both ruptured and unruptured patients. We confirmed 60% of these changed microRNAs by a separate microarray test with an independent validation cohort (n=143 including 93 IA patients). To identify potential biomarkers, we combined the 2 cohorts and performed quantitative real-time polymerase chain reactions for selected target microRNAs. Logistic regression analysis demonstrated that miR-16 and miR-25 were independent factors for IA occurrence (P<0.001). After controlling for age, sex, smoking, and history of hypertension, the contributions of miR-16 and miR-25 were still highly significant (P<0.001). The adjusted odds ratio values for miR-16 and miR-25 were 1.52 (95% CI 1.31 to 1.77) and 1.53 (1.30 to 1.79). Combining both miR-16 and miR-25 in a single model did not improve the performance of risk association.

Conclusions

Our data suggest that circulating miRNAs may be novel biological markers that are useful in assessing the likelihood of IA occurrence.

SUBMITTER: Li P

PROVIDER: S-EPMC4323791 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Publications

Circulating microRNAs serve as novel biological markers for intracranial aneurysms.

Li Pengxiang P Zhang Qunye Q Wu Xiao X Yang Xinjian X Zhang Yun Y Li Youxiang Y Jiang Fan F

Journal of the American Heart Association 20140923 5

<h4>Background</h4>Biological markers that can be used to predict the risk of intracranial aneurysms (IAs) are not available.<h4>Methods and results</h4>To clarify whether circulating microRNAs could be used as biomarkers for IA, we carried out microarray assays in a screening cohort of 40 IA patients (20 unruptured and 20 ruptured) and 20 healthy volunteers. We identified 20 microRNAs that were unanimously changed in both ruptured and unruptured patients. We confirmed 60% of these changed micro ...[more]

PMID: 25249297

Similar Datasets

Project description:BACKGROUND:Intracranial aneurysms (IAs) are dangerous because of their potential to rupture and cause deadly subarachnoid hemorrhages. Previously, we found significant RNA expression differences in circulating neutrophils between patients with unruptured IAs and aneurysm-free controls. Searching for circulating biomarkers for unruptured IAs, we tested the feasibility of developing classification algorithms that use neutrophil RNA expression levels from blood samples to predict the presence of an IA. METHODS:Neutrophil RNA extracted from blood samples from 40 patients (20 with angiography-confirmed unruptured IA, 20 angiography-confirmed IA-free controls) was subjected to next-generation RNA sequencing to obtain neutrophil transcriptomes. In a randomly-selected training cohort of 30 of the 40 samples (15 with IA, 15 controls), we performed differential expression analysis. Significantly differentially expressed transcripts (false discovery rate?<?0.05, fold change???1.5) were used to construct prediction models for IA using four well-known supervised machine-learning approaches (diagonal linear discriminant analysis, cosine nearest neighbors, nearest shrunken centroids, and support vector machines). These models were tested in a testing cohort of the remaining 10 neutrophil samples from the 40 patients (5 with IA, 5 controls), and model performance was assessed by receiver-operating-characteristic (ROC) curves. Real-time quantitative polymerase chain reaction (PCR) was used to corroborate expression differences of a subset of model transcripts in neutrophil samples from a new, separate validation cohort of 10 patients (5 with IA, 5 controls). RESULTS:The training cohort yielded 26 highly significantly differentially expressed neutrophil transcripts. Models using these transcripts identified IA patients in the testing cohort with accuracy ranging from 0.60 to 0.90. The best performing model was the diagonal linear discriminant analysis classifier (area under the ROC curve?=?0.80 and accuracy?=?0.90). Six of seven differentially expressed genes we tested were confirmed by quantitative PCR using isolated neutrophils from the separate validation cohort. CONCLUSIONS:Our findings demonstrate the potential of machine-learning methods to classify IA cases and create predictive models for unruptured IAs using circulating neutrophil transcriptome data. Future studies are needed to replicate these findings in larger cohorts.

Dataset Information

Circulating microRNAs serve as novel biological markers for intracranial aneurysms.

Background

Methods and results

Conclusions

Publications

Circulating microRNAs serve as novel biological markers for intracranial aneurysms.

Similar Datasets

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