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MicroRNAs and mild cognitive impairment: A systematic review
Mild cognitive impairment (MCI) is usually described as an intermediate phase between normal cognition and dementia. Identifying the subjects at a higher risk of progressing from MCI to AD is essential to manage this condition. The diagnosis of MCI is mainly clinical. Several biomarkers have been pr...
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Published in: | Ageing research reviews 2019-03, Vol.50, p.131-141 |
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Main Authors: | , , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Mild cognitive impairment (MCI) is usually described as an intermediate phase between normal cognition and dementia. Identifying the subjects at a higher risk of progressing from MCI to AD is essential to manage this condition. The diagnosis of MCI is mainly clinical. Several biomarkers have been proposed, but mostly for research purposes, as they are based on an invasive procedure to obtain the sample, such as cerebrospinal fluid (CSF). As a consequence, rapid and non-invasive biomarkers are needed to improve diagnosis. The objective of this systematic review is to summarize available evidence on the use of miRNAs as biomarkers in subjects with MCI.
Relevant literature published up to June 2018 was retrieved searching the databases PubMed, ISI Web of Knowledge and the Cochrane Database. Only studies considering microRNAs (miRNAs) and a diagnosis of MCI were included. Data were extracted using a specifically-designed standardized form, and their methodological quality was assessed using QUADAS-2 and QUIPS.
Twenty-one studies of 153 retrieved articles met the predefined inclusion/exclusion criteria. Studies included participants ranging from 6 to 330. More than 40 miRNAs resulted as dysregulated, and miR-206 was the only miRNA that was found as differentially expressed in patients with MCI by more than two studies. However, these results have either not yet been confirmed in other independent cohorts, or data are still inconsistent. Inconsistencies among included studies could be due to several issues including the selection of participants, pre-analytical and analytical procedures, and statistical analyses. |
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ISSN: | 1568-1637 1872-9649 |
DOI: | 10.1016/j.arr.2018.11.005 |