Antara Dattagupta

Introduction: Stroke is one of the leading causes of adult mortality and disability worldwide.1 During ischemic stroke, neurons are deprived of oxygen and energy and their normal metabolic substrates stop functioning in seconds displaying signs of structural injury after only two minutes.2 MiRNA are post- transcriptional regulators that target the 3’-untranslated regions of target mRNAs.2 MiRNAs show promise as biomarkers for stroke due to their stability in peripheral blood and cell type-specific expression pattern.3 Blood- based biomarkers that can quickly discriminate between a healthy patient and a stroke patient would be clinically significant by opening the future development of a “point-of-care” tool.4  This will be helpful in the future to identify new neurological deficits especially in non-cooperative patients where imaging may be difficult to perform. Methods: MiRNA PC-5P-12969 expression levels were investigated using quantitative real-time polymerase chain reaction assays in an in vitro glucose and oxygen deprivation treated mouse primary hippocampal neuronal cells.5 Results: Expression levels were upregulated by two-fold after 24 hours of re- oxygenation following 4 hours of oxygen and glucose deprivation in mouse hippocampal neuronal cells indicating a time-dependence in expression levels.5 There was also significant upregulation of PC-5P-12969 in the cerebral cortex of stroke mice indicating tissue-specificity since cerebellum tissue was unaffected.5 This study shows the significance of PC-5P-12969 as a potential biomarker for detecting ischemic stroke in patients. PC-5P-12969 has many possible molecular targets for different biological processes.5  For example, PARK2 is a gene and potential molecular target used for processes such as cellular protein catabolic process.5 These targets can be manipulated in the future to help detect a stroke and improve stroke prognosis.5 With the increasing evidence of miRNAs as biomarkers for stroke diagnosis and prognosis, it is important to be able to predict their target genes to observe their effect.6 The probabilistic scoring approach, TargetScore, is proposed as a technique that combines the expression and sequence information of known genes to determine the probability of a gene becoming a miRNA target.6 The prediction results increase in accuracy as the TargetScore value increase.6 Conclusions: Currently, there is a need for a reliable circulating biomarker than can be detected for acute ischemic stroke patients. Rapid identification of stroke type can assist with patient prognosis and care.4 Dysregulation of miRNAs leads to pathological consequences in the brain as miRNAs are the main regulators of homeostasis in neurons.5 Therefore, understanding miRNAs role in stroke pathogenesis will help improve stroke outcome.

1. Falcione S, Kamtchum-Tatuene J, Sykes G, Jickling GC. RNA expression studies in stroke. Current Opinion in Neurology. 2020;33(1):24-29. doi:10.1097/wco.0000000000000786.
2. Khoshnam SE, Winlow W, Farbood Y, Moghaddam HF, Farzaneh M. Emerging Roles of microRNAs in Ischemic Stroke: As Possible Therapeutic Agents. Journal of Stroke. 2017;19(2):166-187. doi:10.5853/jos.2016.01368.
3. Liang T-Y, Lou J-Y. Increased Expression of mir-34a-5p and Clinical Association in Acute Ischemic Stroke Patients and in a Rat Model. Medical Science Monitor. 2016;22:2950-2955. doi:10.12659/msm.900237.
4. Yashar S. Kalani, Eric Alsop, Bessie Meechoovet, Taylor Beecroft, Komal Agrawal, Timothy G. Whitsett, Matthew J. Huentelman, Robert F. Spetzler, Peter Nakaji, Seungchan Kim & Kendall Van Keuren- Jensen (2020) Extracellular microRNAs in blood differentiate between ischaemic and haemorrhagic stroke subtypes, Journal of Extracellular Vesicles, 9:1, 1713540, DOI: 10.1080/20013078.2020.1713540
5. Vijayan M, Alamri FF, Shoyaib AA, Karamyan VT, Reddy PH. Novel miRNA PC-5P-12969 in Ischemic Stroke. Molecular Neurobiology. 2019;56(10):6976-6985. doi:10.1007/s12035-019-1562-x.
6. Wu J, Wang B, Zhou J, Ji F. MicroRNA target gene prediction of ischemic stroke by using variational Bayesian inference for Gauss mixture model. Experimental and Therapeutic Medicine. January 2019:2734- 2740. doi:10.3892/etm.2019.7262.