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Serum MicroRNA-Based Risk Prediction for Stroke.

Takumi Sonoda1, Juntaro Matsuzaki1, Yusuke Yamamoto1

  • 1From the Division of Molecular and Cellular Medicine, National Cancer Center Research Institute, Tokyo, Japan (T. Sonoda, J.M., Y.Y., T.O.).

Stroke
|May 29, 2019
PubMed
Summary

Researchers identified seven serum microRNAs (miRNAs) that can predict cerebrovascular disorder risk. This discovery offers a potential noninvasive method for early stroke risk assessment.

Keywords:
biomarkerscerebrovascular disorderscirculating microRNAmicroarray analysisserum

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Area of Science:

  • Biochemistry
  • Genetics
  • Neurology

Background:

  • Circulating microRNAs (miRNAs) are recognized as noninvasive biomarkers for various diseases.
  • Early identification of stroke risk is crucial for effective prevention strategies.

Purpose of the Study:

  • To identify specific serum miRNAs capable of predicting the risk of stroke.
  • To develop a predictive model for cerebrovascular disorder using identified miRNAs.

Main Methods:

  • Serum miRNA profiling using microarray analysis on discovery, training, and validation sets.
  • Pearson correlation analysis to identify miRNAs associated with predicted stroke risk in controls.
  • Fisher linear discrimination model with cross-validation to build a predictive model.

Main Results:

  • 10 serum miRNAs correlated with stroke risk in 1523 controls.
  • 7 miRNAs (miR-1228-5p, miR-1268a, miR-1268b, miR-4433b-3p, miR-6090, miR-6752-5p, miR-6803-5p) were significantly associated with cerebrovascular disorder.
  • A 3-miRNA model (miR-1268b, miR-4433b-3p, miR-6803-5p) showed high predictive accuracy in training (AUC 0.95) and validation (AUC 0.89) sets.

Conclusions:

  • Seven serum miRNAs were identified as potential predictors of cerebrovascular disorder risk.
  • A 3-miRNA signature demonstrates significant potential for noninvasive stroke risk assessment.
  • These findings may lead to earlier detection and intervention for individuals at risk of stroke.