ArticleAnnals of clinical and translational neurology2016
Blood transcriptome changes after stroke in an African American population.
Article in Annals of clinical and translational neurology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Molecular heterogeneity in human stroke - What can we learn from the peripheral blood transcriptome?Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026Review
- Blood RNA Signatures Enable Accurate Discrimination of Stroke Subtype and Onset Time at Hospital Admission.Research square · 2026Article
- Commentary: a review of technical considerations for planning an RNA-Sequencing experiment.BMC genomics · 2025Review
- Differential Transcript Expression and Alternative RNA Splicing Patterns to Differentiate Focal vs. Generalized-Onset Seizures.Molecular neurobiology · 2025Article
- Retrospective discrimination of PNES and epileptic seizure types using blood RNA signatures.Journal of neurology · 2025Article
- Profiling immune cell-related gene features and immunoregulatory ceRNA in ischemic stroke.Molecular biomedicine · 2024Article
- A case-control comparison of acute-phase peripheral blood gene expression in participants diagnosed with minor ischaemic stroke or stroke mimics.Human genomics · 2023Article
- Early peripheral blood gene expression associated with good and poor 90-day ischemic stroke outcomes.Journal of neuroinflammation · 2023Article
- Effects of repetitive mild traumatic brain injury on weight gain and chronic behavioral outcomes in male rats.PloS one · 2023Article
- Whole Blood Transcriptome Analysis in Children with Sickle Cell Anemia.Frontiers in genetics · 2021Article
- The intracerebral hemorrhage blood transcriptome in humans differs from the ischemic stroke and vascular risk factor control blood transcriptomes.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2019Article
- Distinct plasma proteomic changes in male and female African American stroke patients.International journal of physiology, pathophysiology and pharmacology · 2019Article
- Identification of novel blood biomarker panels to detect ischemic stroke in patients and their responsiveness to therapeutic intervention.Brain research · 2018Article
- Temporal Gene Expression Profiles after Focal Cerebral Ischemia in Mice.Aging and disease · 2018Article
- RNAseq based transcriptomics study of SMCs from carotid atherosclerotic plaque: BMP2 and IDs proteins are crucial regulators of plaque stability.Scientific reports · 2017Article
- Article
- Profiling of exercise-induced transcripts in the peripheral blood cells of Thoroughbred horses.Journal of equine science · 2016Article
- Enhancing and Extending Biological Performance and Resilience.Dose-response : a publication of International Hormesis SocietyReview
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
objectiveMolecular diagnostic medicine holds much promise to change point of care treatment. An area where additional diagnostic tools are needed is in acute stroke care, to assist in diagnosis and prognosis. Previous studies using microarray-based gene expression analysis of peripheral blood following stroke suggests this approach may be effective. Next-generation sequencing (NGS) approaches have expanded genomic analysis and are not limited to previously identified genes on a microarray chip. Here, we report on a pilot NGS study to identify gene expression and exon expression patterns for the prediction of stroke diagnosis and prognosis.
methodsWe recruited 28 stroke patients and 28 age- and sex-matched hypertensive controls. RNA was extracted from 3 mL blood samples, and RNA-Seq libraries were assembled and sequenced.
resultsBioinformatical analysis of the aligned RNA data reveal exonic (30%), intronic (36%), and novel RNA components (not currently annotated: 33%). We focused our study on patients with confirmed middle cerebral artery occlusion ischemic stroke (n = 17). On the basis of our observation of differential splicing of gene transcripts, we used all exonic RNA expression rather than gene expression (combined exons) to build prediction models using support vector machine algorithms. Based on model building, these models have a high predicted accuracy rate >90% (spec. 88% sen. 92%). We further stratified outcome based on the improvement in NIHss scores at discharge; based on model building we observe a predicted 100% accuracy rate.
interpretationNGS-based exon expression analysis approaches have a high potential for patient diagnosis and outcome prediction, with clear utility to aid in clinical patient care.
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Registered trials
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