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| dc.creator | Dakterzada, Farida | |
| dc.creator | Targa, Adriano | |
| dc.creator | Benítez, Iván | |
| dc.creator | Romero El Khayat, Leila | |
| dc.creator | de Gonzalo Calvo, David | |
| dc.creator | Torres, Gerard | |
| dc.creator | Moncusí Moix, Anna | |
| dc.creator | Huerto Vilas, Raquel | |
| dc.creator | Sánchez de la Torre, Manuel | |
| dc.creator | Barbé Illa, Ferran | |
| dc.creator | Piñol Ripoll, Gerard | |
| dc.date | 2020 | |
| dc.date.accessioned | 2025-11-03T12:15:40Z | |
| dc.date.available | 2025-11-03T12:15:40Z | |
| dc.identifier | https://doi.org/10.1186/s13195-020-00735-x | |
| dc.identifier | 1758-9193 | |
| dc.identifier | http://hdl.handle.net/10459.1/83231 | |
| dc.identifier.uri | http://fima-docencia.ub.edu:8080/xmlui/handle/123456789/24209 | |
| dc.description | Background. MicroRNAs (miRNAs) are noncoding RNAs that are highly relevant as disease biomarkers. Several studies that explored the role of miRNAs in Alzheimer’s disease (AD) demonstrated their usefulness in clinical identification. Nevertheless, miRNAs that may act as endogenous controls (ECs) have not yet been established. The identification of ECs would contribute to the standardization of these biomarkers in AD. The objective of the study was to identify miRNAs that can be used as ECs in AD. Methods. We evaluated 145 patients divided into two different cohorts. One was a discovery cohort of 19 women diagnosed with mild to moderate AD (Mini-Mental State Examination (MMSE) score ≥ 20) and with confirmed pathologic levels of Aβ42 in CSF. The stability assessment cohort consisted of 126 individuals: 24 subjects without AD or any kind of dementia and negative for all core CSF biomarkers of AD, 25 subjects with MCI and negative for CSF biomarkers (MCI −), 22 subjects with MCI and positive for CSF biomarkers (MCI +), and 55 subjects with AD and positive for CSF biomarkers. In the discovery cohort, a profile of 384 miRNAs was determined in the plasma by TaqMan low-density array. The best EC candidates were identified by mean-centering and concordance correlation restricted normalization methods. The stability of the EC candidates was assessed using the GeNorm, BestKeeper, and NormFinder algorithms. Results. Nine miRNAs (hsa-miR-324-5p, hsa-miR-22-5p, hsa-miR-103a-2-5p, hsa-miR-362-5p, hsa-miR-425-3p, hsa-miR-423-5p, hsa-let-7i-3p, hsa-miR-532-5p, and hsa-miR-1301-3p) were identified as EC candidates in the discovery cohort. The validation results indicated that hsa-miR-103a-2-5p was the best EC, followed by hsa-miR-22-5p, hsa-miR-1301-3p, and hsa-miR-425-3p, which had similar stability values in all three algorithms. Conclusions. We identified a profile of four miRNAs as potential plasma ECs to be used for normalization of miRNA expression data in studies of subjects with cognitive impairment. | |
| dc.description | Generalitat of Catalonia, Department of Health (PERIS 2019 SLT008/18/00050), and “Fundació La Marató TV3” (464/C/2014) to GPR. This study was cofinanced by FEDER funds from the European Union (“A way to build Europe”). IRBLleida is a CERCA Programme/Generalitat of Catalonia. FD was supported by the Agency for Management of University and Research Grants (FI_B100153). David de Gonzalo Calvo acknowledges receiving financial support from Instituto de Salud Carlos III (ISCIII); Miguel Servet 2020: CP20/00041, co-funded by the European Social Fund (ESF)/“Investing in your future”. | |
| dc.language | eng | |
| dc.publisher | BCM | |
| dc.relation | Reproducció del document publicat a: https://doi.org/10.1186/s13195-020-00735-x | |
| dc.relation | Alzheimer's Research & Therapy, 2020, vol.12 | |
| dc.rights | cc-by (c) Authors, 2020 | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.rights | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Alzheimer’s disease | |
| dc.subject | Biomarkers | |
| dc.subject | Mild cognitive impairment | |
| dc.subject | miRNAs | |
| dc.subject | Normalization | |
| dc.subject | qPCR | |
| dc.title | Identification and validation of endogenous control miRNAs in plasma samples for normalization of qPCR data for Alzheimer's disease | |
| dc.type | info:eu-repo/semantics/article | |
| dc.type | info:eu-repo/semantics/publishedVersion |
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