An integrative bioinformatics approach in microRNA data analytics of Alzheimer’s disease

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Published: Dec 28, 2023
Keywords:
Alzheimer’s disease microRNA differential expression analysis data analytics bioinformatics

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Jill Ann Chia
Bioinformatics Programme, Institute of Biological Sciences, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia
Mei Sze Tan
Bioinformatics Programme, Institute of Biological Sciences, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia
Siow-Wee Chang
Bioinformatics Programme, Institute of Biological Sciences, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia / Centre of Research in System Biology, Structural, Bioinformatics and Human Digital Imaging (CRYSTAL), Universiti Malaya, Kuala Lumpur, Malaysia. Corresponding author's e-mail: [email protected]

Abstract

Alzheimer’s disease (AD) is the most common type of dementia clinically recognized by cognitive function impairment. Recently, the blood-based biomarkers relating to AD have been intensively investigated due to the minimum invasiveness and relatively low cost in the collection of blood samples compared to the cerebrospinal fluid in the brain. In line with this, the study of the deregulation of microRNA (miRNA) levels in the blood of AD patients is also rising. In this study, data analysis was performed on the miRNA expression profiling dataset using an integrative bioinformatics approach. K-nearest neighbor imputation and quantile normalization were carried out as the data pre-processing step to remove outliers and reduce bias in the dataset. Differential expression analysis was performed to identify 10 significant dysregulated miRNAs. Subsequently, 16 pathways were determined to be involved by the selected 10 miRNA signatures, and 7 genes were predicted as the common target genes. The roles of these target genes in AD were substantiated through a review of the existing literature. Expansion of the current work on a larger scale of data analysis is needed to further validate and understand the mechanism of miRNAs in AD development.

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How to Cite
Chia, J. A., Tan, M. S. ., & Chang, S.-W. (2023). An integrative bioinformatics approach in microRNA data analytics of Alzheimer’s disease. Science, Engineering and Health Studies, 17, 23030002. Retrieved from https://li01.tci-thaijo.org/index.php/sehs/article/view/257988
Issue
Volume 17, 2023
Section
Biological sciences
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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