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Blood transcriptome changes after stroke in an African American population
Robert Meller1, Andrea N Pearson1, Jimmaline J Hardy1
1Translational Stroke Program Neuroscience Institute Morehouse School of Medicine Atlanta Georgia.
Annals of Clinical and Translational Neurology
|February 23, 2016
Summary
Next-generation sequencing (NGS) of blood RNA shows high accuracy in predicting stroke diagnosis and patient outcomes. This molecular diagnostic approach offers a promising tool for acute stroke care and clinical decision-making.
Area of Science:
- Genomics
- Molecular Diagnostics
- Bioinformatics
Background:
- Acute stroke diagnosis and prognosis require improved tools.
- Microarray gene expression studies suggest peripheral blood analysis is viable.
- Next-generation sequencing (NGS) offers broader genomic analysis than microarrays.
Purpose of the Study:
- To conduct a pilot study using NGS to identify gene and exon expression patterns for stroke diagnosis and prognosis.
- To explore the utility of exon expression patterns over traditional gene expression for prediction models.
Main Methods:
- Recruited 28 stroke patients and 28 controls.
- Extracted RNA from blood samples for RNA-Seq library preparation and sequencing.
- Focused analysis on 17 patients with middle cerebral artery occlusion ischemic stroke.
Main Results:
- Bioinformatic analysis revealed significant exonic, intronic, and novel RNA components.
- Utilized exonic RNA expression, rather than combined gene expression, for prediction models.
- Support vector machine models achieved >90% accuracy for diagnosis (88% specificity, 92% sensitivity).
- Achieved 100% accuracy in predicting patient outcome based on NIH Stroke Scale improvement.
Conclusions:
- NGS-based exon expression analysis demonstrates high potential for accurate patient diagnosis and outcome prediction.
- This approach has clear utility in aiding clinical patient care for acute stroke.
