Dataset Information

Plasma-derived miRNAs as fluid biomarkers to differentiate Alzheimer’s and Frontotemporal Dementia

ABSTRACT: Alzheimer’s disease (AD) and Frontotemporal Dementia (FTD) are complex neurodegenerative disorders, often sharing overlapping symptoms. Non-coding RNAs play a central role in both conditions, hence the study of miRNAs isolated from plasma-derived extracellular vesicles (EVs) could increase the understanding of the pathological molecular background and support the identification of new diagnostic tools. The main aim of this work was to identify miRNAs deregulated in both disorders but presenting different expression patterns. A selection of the identified deregulated miRNAs was further studied with the purpose of identifying their mRNA targets and understanding their potential pathological involvement. A total of 340 and 291 differentially expressed miRNAs were found in FTD and AD, respectively. Among the commonly deregulated miRNAs with opposite expression trends between the two conditions, miR-638 emerged as a potentially interesting candidate, showing consistent patterns across our experimental analyses. Although these findings are preliminary and require validation in larger cohorts, miR-638 could represent a SEVs-associated biomarker with potential to distinguish AD from FTD. In addition, the expression of two of its predicted targets in peripheral blood mononuclear cells (PBMCs) appeared to align with miR-638 expression in the same cell type, and may reflect distinct underlying brain pathological states, although their differential expression between the two pathologies should be interpreted cautiously.

ORGANISM(S): Homo sapiens

PROVIDER: GSE311885 | GEO | 2026/07/01

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Background: Dementia is one of the most common diseases in elderly people and hundreds of thousand new cases per year of Alzheimer’s disease (AD) are estimated. While the recent decade has seen significant advances in the development of novel biomarkers to identify dementias at their early stage, a great effort has been recently made to identify biomarkers able to improve differential diagnosis. However, only few potential candidates, mainly detectable in cerebrospinal fluid (CSF), have been described so far. Methods: We searched for miRNAs regulating MAPT translation. We employed a capture technology able to find the miRNAs directly bound to the MAPT transcript in cell lines. Afterwards, we evaluated the levels of these miRNAs in plasma samples from FTD (n = 42) and AD patients (n = 33) and relative healthy controls (HCs) (n = 42) by using qRT-PCR. Results: Firstly, we found all miRNAs that interact with the MAPT transcript. Ten miRNAs have been selected to verify their effect on Tau levels increasing or reducing miRNA levels by using cell transfections with plasmids expressing the miRNAs genes or LNA antagomiRs. Following the results obtained, miR-92a-3p, miR-320a and miR-320b were selected to analyse their levels in plasma samples of patients with FTD and AD respect to HCs. The analysis showed that the miR-92a-1-3p was under-expressed in both AD and FTD compared to HCs. Moreover, miR-320a was upregulated in FTD vs. AD patients, particularly in men when we stratified by sex. Respect to HC, the only difference is showed in men with AD who have reduced levels of this miRNA. Instead, miR-320b is up-regulated in both dementias, but only patients with FTD maintain this trend in both genders. Conclusions: Our results seem to identify miR-92a-3p and miR-320a as possible good biomarkers to discriminate AD from HC, while miR-320b to discriminate FTD from HC, particularly in males. Combining three miRNAs improves the accuracy only in females, particularly for differential diagnosis (FTD vs. AD) and to distinguish FTD from HC.

Dataset Information

Plasma-derived miRNAs as fluid biomarkers to differentiate Alzheimer’s and Frontotemporal Dementia

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets