Abstract
Subarachnoid hemorrhage (SAH) is a highly morbid and fatal type of hemorrhagic strokes and it accounts for only 5% of all strokes. SAH is characterized by the sentinel extravasation of the arterial blood into the subarachnoid space and sometimes also involves ventricles and brain parenchyma. An important concern regarding this highly fatal and morbid disease is that it affects younger people of working age compared to the ischemic strokes leading to a significant socioeconomic loss. The major cause of SAH is the rupture of intracranial aneurysms (ICAs), which are weakened bulging lesions usually formed at the arterial bifurcation sites due to chronic shear stress and chronic inflammation. Almost, 3–5% of the population harbors ICAs with a slight prevalence in females compared to males. Transcriptomic studies offer the opportunity to elucidate the pathophysiological mechanisms in the formation, growth and rupture of the ICAs. Consequently, several studies have shown the differential expression of genes in the ruptured and unruptured ICAs and also highlight the implication of the associated pathways. Even peripheral blood and immune cells can be used to differentiate between ruptured and unruptured ICAs. These investigations have biomarker potential as well as they can be used for therapeutic modulation of the pathways showing differential expression of the genes among ruptured and unruptured ICAs.
Original language | English |
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Title of host publication | Transcriptome Profiling : Progress and Prospects |
Editors | Mohammad Ajmal Ali, Joongku Lee |
Number of pages | 9 |
Publisher | Elsevier |
Publication date | 1 Jan 2022 |
Pages | 443-451 |
ISBN (Print) | 978-0-323-97231-4 |
ISBN (Electronic) | 978-0-323-91810-7 |
DOIs | |
Publication status | Published - 1 Jan 2022 |
MoE publication type | A3 Book chapter |
Bibliographical note
Publisher Copyright:© 2023 Elsevier Inc. All rights reserved.
Fields of Science
- Aneurysm
- extracellular matrix
- gene expression
- inflammation
- stroke
- subarachnoid Hemorrhage
- 3112 Neurosciences