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The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.

Blood serum miRNA: Non-invasive biomarkers for Alzheimer's disease

Open access
Geekiyanage, Hirosha, Jicha, Gregory A., Nelson, Peter T., Chan, Christina·2012·Experimental Neurology

Abstract

There is an urgent need to identify non-invasive biomarkers for the detection of sporadic Alzheimer’s disease (AD). We previously studied microRNAs (miRNAs) in AD autopsy brain samples and reported a connection between miR-137, -181c, -9, -29a/b and AD, through the regulation of ceramides. In this study, the potential role of these miRNAs as diagnostic markers for AD was investigated. We identified that these miRNAs were down-regulated in the blood serum of probable AD patients. The levels of these miRNAs were also reduced in the serum of AD risk factor models. Although the ability of these miRNAs to conclusively diagnose for AD is currently unknown, our findings suggest a potential use for circulating miRNAs, along with other markers, as non-invasive and relatively inexpensive biomarkers for the early diagnosis of AD, however, with further research and validation.

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Metadata

Authors
Geekiyanage, H., Jicha, G. A., Nelson, P. T., & Chan, C.
Venue
Experimental Neurology
Publisher
Elsevier BV
Published
2012-06
Volume
235
Issue
2
Pages
491-496
ISSN
0014-4886 (ISSN-L)
OpenAlex
W2000356500
Cited by
294
References
11
FWCI
6.58
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Blood serum miRNA: Non-invasive biomarkers for Alzheimer's disease. https://app.cochat.ai/papers/10.1016/j.expneurol.2011.11.026
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Geekiyanage, H., Jicha, G. A., Nelson, P. T., & Chan, C. (2012). Blood serum miRNA: Non-invasive biomarkers for Alzheimer's disease. Experimental Neurology. https://doi.org/10.1016/j.expneurol.2011.11.026

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.