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Folia Neuropathologica
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abstract:
Original paper

The diagnostic value of serum miR-17-92 cluster in ischemic stroke

Lihua Dong
1
,
Yuanshen Ye
2
,
Guiyuan Huang
1
,
Hongmiao Tao
1

1.
Medical College, Jinhua Polytechnic, Jinhua, China
2.
Department of Neurology, Maoming Petrochemical Hospital, Guangdong Medical University, Maoming, China
Folia Neuropathol 2024; 62:
Online publish date: 2024/04/12
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Introduction:
Ischemic stroke (IS) is a prevalent disease that poses a significant threat to human life and is responsible for a substantial financial burden. Research has established the crucial role of the miR-17-92 cluster in lung cancer, cardiovascular diseases, and traumatic brain injury. Despite this, few research studies had fully detected the potential of the miR-17-92 cluster as a novel circulating marker for diagnosing IS.

Material and methods:
miR-17-92 cluster expression in IS was investigated using GSE117064 dataset via bioinformatics analysis. Moreover, qRT-PCR was conducted to further verify miR-17-92 cluster expression in 58 IS individuals and 50 healthy controls (HCs). These cluster members were examined regarding their potential for detecting and diagnosing IS using the ROC method.

Results:
The expression level of serum miR-20a-5p, miR-19a-3p, miR-18a-5p, and miR-19b-3p was considerably lowered in IS in contrast with HC in both the GSE117064 cohort and clinical cohort. Moreover, these four miRNAs had a fair performance in IS detection. Thereafter, a diagnostic model based on these aforementioned four miRNAs was developed by logistic regression, which had an AUC of 0.974 in the ROC curve. This diagnostic module was verified using the GSE117064 dataset. Further analysis demonstrated an increasing level of the aforementioned miRNAs in day-7 IS patients compared with day-1 IS patients.

Conclusions:
This research verified the downregulation of the miR-17-92 cluster in IS. This diagnostic model enrolling four cluster members may be a promising biomarker for IS detection.

keywords:

miR-17-92 cluster, serum, diagnostic biomarker, ischemic stroke

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