Decoding Molecular Mechanisms Underlying Outcomes After Ischemic Stroke Thrombectomy by RNA Sequencing of Retrieved Clots

Mol Diagn Ther. 2024 Jul;28(4):469-477. doi: 10.1007/s40291-024-00716-y. Epub 2024 May 20.

Abstract

Background: Transcriptomic profiling has emerged as a powerful tool for exploring the molecular landscape of ischemic stroke clots and providing insights into the pathophysiological mechanisms underlying stroke progression and recovery. In this study, we aimed to investigate the relationship between stroke clot transcriptomes and stroke thrombectomy outcome, as measured by early neurological improvement (ENI) 30 (i.e., a 30% reduction in NIHSS at 24 h post-thrombectomy).

Hypothesis: We hypothesized that there exist distinct clot gene expression patterns between good and poor neurological outcomes.

Methods: Transcriptomic analysis of 32 stroke clots retrieved by mechanical thrombectomy was conducted. Transcriptome data of these clots were analyzed to identify differentially expressed genes (DEGs), defined as those with a log(fold-change) ≥ 1.5 and q < 0.05 between samples with good and poor early neurological outcomes. Gene ontology and bioinformatics analyses were performed on genes with p < 0.01 to identify enriched biological processes and Ingenuity Pathway Analysis canonical pathways. Moreover, AUC analysis assessed the predictive power of DEGs for 90-day function outcome (mRS ≤ 2) and cellular composition of clot was predicted using CIBERSORT. We also assessed whether differential enrichment of immune cell types could indicate patient survival.

Results: A total of 41 DEGs were identified. Bioinformatics showed that enriched biological processes and pathways emphasized the chronic immune response and matrix metalloproteinase inhibition. Moreover, 25 of the DEGs were found to be significant predictors of 90-day mRS. These genes were indicative of monocytes enrichment and neutrophil depletion in patients with poorer outcomes.

Conclusion: Our study revealed a distinct gene expression pattern and dysregulated biological pathways associated with ENI. This expression pattern was also predictive of long-term outcome, suggesting a biological link between those ENIs and 90-day mRS.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Aged
  • Computational Biology / methods
  • Female
  • Gene Expression Profiling*
  • Gene Ontology
  • Gene Regulatory Networks
  • Humans
  • Ischemic Stroke* / genetics
  • Ischemic Stroke* / metabolism
  • Ischemic Stroke* / surgery
  • Male
  • Middle Aged
  • Sequence Analysis, RNA
  • Thrombectomy*
  • Thrombosis / etiology
  • Thrombosis / genetics
  • Transcriptome*
  • Treatment Outcome