Version 1
: Received: 20 July 2021 / Approved: 21 July 2021 / Online: 21 July 2021 (11:57:02 CEST)
How to cite:
Rivero-Segura, N.A.; Gomez-Verjan, J.C.; Ramírez-Aldana, R.M. Towards a MicroRNAs-Based Biomarker Panel for AIS: A Meta-Analysis. Preprints2021, 2021070490. https://doi.org/10.20944/preprints202107.0490.v1
Rivero-Segura, N.A.; Gomez-Verjan, J.C.; Ramírez-Aldana, R.M. Towards a MicroRNAs-Based Biomarker Panel for AIS: A Meta-Analysis. Preprints 2021, 2021070490. https://doi.org/10.20944/preprints202107.0490.v1
Rivero-Segura, N.A.; Gomez-Verjan, J.C.; Ramírez-Aldana, R.M. Towards a MicroRNAs-Based Biomarker Panel for AIS: A Meta-Analysis. Preprints2021, 2021070490. https://doi.org/10.20944/preprints202107.0490.v1
APA Style
Rivero-Segura, N.A., Gomez-Verjan, J.C., & Ramírez-Aldana, R.M. (2021). Towards a MicroRNAs-Based Biomarker Panel for AIS: A Meta-Analysis. Preprints. https://doi.org/10.20944/preprints202107.0490.v1
Chicago/Turabian Style
Rivero-Segura, N.A., Juan Carlos Gomez-Verjan and Ricardo. Mathn Ramírez-Aldana. 2021 "Towards a MicroRNAs-Based Biomarker Panel for AIS: A Meta-Analysis" Preprints. https://doi.org/10.20944/preprints202107.0490.v1
Abstract
Background: Acute ischemic stroke is among the main causes of mortality worldwide; a rapid and opportune diagnosis is crucial to improve a patient's outcome. MicroRNAs are quite useful for a rapid and accurate diagnosis.Methods: We perform both structural networks approach and a meta-analysis (using a random-effect model to evaluate the heterogeneity and risk bias, according to the PRISMA statement) to analyze the feasibility to develop a microRNA-based biomarker panel for an opportune AIS diagnosis. Results: Structural networks identify a set of eight miRNAs (miR-16, miR-124-3p, miR-484, miR-15a, miR-4454, miR-107, miR-125b-5p and miR-320b) as preliminary microRNA-based biomarker panel, from these only three microRNAs are significantly associated with the main risk factors of AIS, (miR-107: hypertension, 95% CI 9.74-53.24 p<0.0001, type 2 Diabetes mellitus, 95% CI 2.18-19.26); p=0.0008; miR-16 hypertension, 95% CI 1.26-3.56 p=0.0046, smoking, 95% CI 1.07-3.54 p=0.0277; and miR-15a hypertension, 95% CI 1.26-3.56 p=0.0046; smoking, 95% CI 1.07-3.54 p=0.0277). However, the meta-analysis reveals that data is highly heterogeneous and biased; and only microRNAs isolated from plasma samples and further processed in microarrays are the most reliable to distinguish AIS patients.Conclusions: Together our results show that although there are some miRNAs that seem to be associated with AIS, we are still far to develop a miRNA-based biomarker for AIS diagnosis and it is necessary to harmonize the protocols, results and include more populations for further studies otherwise we will remain throwing punches in the dark.
Biology and Life Sciences, Biochemistry and Molecular Biology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
