Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2020 May 15;21(10):3517.
doi: 10.3390/ijms21103517.

Transcriptomics in Alzheimer's Disease: Aspects and Challenges

Affiliations
Review

Transcriptomics in Alzheimer's Disease: Aspects and Challenges

Eva Bagyinszky et al. Int J Mol Sci. .

Abstract

Alzheimer's disease (AD) is the most common cause of dementia. Although the heritability of AD is high, the knowledge of the disease-associated genes, their expression, and their disease-related pathways remain limited. Hence, finding the association between gene dysfunctions and pathological mechanisms, such as neuronal transports, APP processing, calcium homeostasis, and impairment in mitochondria, should be crucial. Emerging studies have revealed that changes in gene expression and gene regulation may have a strong impact on neurodegeneration. The mRNA-transcription factor interactions, non-coding RNAs, alternative splicing, or copy number variants could also play a role in disease onset. These facts suggest that understanding the impact of transcriptomes in AD may improve the disease diagnosis and also the therapies. In this review, we highlight recent transcriptome investigations in multifactorial AD, with emphasis on the insights emerging at their interface.

Keywords: Alzheimer’s disease; RNA array; RNA sequencing; alternative splicing; copy number variant; differently expressed genes; neurodegeneration; noncoding RNA; trancriptome.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Overview showing the workflow for transcriptomic studying in Alzheimer’s disease, from transcriptomic data generation to integration of regulatory information to assess gene regulatory networks.
Figure 2
Figure 2
Methodological aspects to consider in most common miRNA biomarkers for Alzheimer’s research.

References

    1. Braak H., Braak E. Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol. 1991;82:239–259. doi: 10.1007/BF00308809. - DOI - PubMed
    1. Bellenguez C., Charbonnier C., Grenier-Boley B., Quenez O., le Guennec K., Nicolas G., Chauhan G., Wallon D., Rousseau S., Richard A.C., et al. Contribution to Alzheimer’s disease risk of rare variants in TREM2, SORL1, and ABCA7 in 1779 cases and 1273 controls. Neurobiol. Aging. 2017;59:220.e1–220.e9. doi: 10.1016/j.neurobiolaging.2017.07.001. - DOI - PubMed
    1. Van Giau V., Bagyinszky E., An S.S.A., Kim S.Y. Role of apolipoprotein E in neurodegenerative diseases. Neuropsychiatr. Dis. Treat. 2015;11:1723–1737. doi: 10.2147/NDT.S84266. - DOI - PMC - PubMed
    1. Vo V.G., An S.S.A. Optimization of specific multiplex DNA primers to detect variable CLU genomic lesions in patients with Alzheimer’s disease. BioChip J. 2015;9:278–284. doi: 10.1007/s13206-015-9306-8. - DOI
    1. Van Giau V., Bagyinszky E., An S.S.A., Kim S. Clinical genetic strategies for early onset neurodegenerative diseases. Mol. Cell. Toxicol. 2018;14:123–142. doi: 10.1007/s13273-018-0015-3. - DOI

MeSH terms

Substances