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MicroRNA-Seq Data Analysis Pipeline to Identify Blood Biomarkers for Alzheimer’s Disease from Public Data

BACKGROUND: Alzheimer’s disease (AD) is the most common cause of dementia with no curative therapy currently available. Establishment of sensitive and non-invasive biomarkers that promote an early diagnosis of AD is crucial for the effective administration of disease-modifying drugs. MicroRNAs (miRN...

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Autores principales: Satoh, Jun-ichi, Kino, Yoshihiro, Niida, Shumpei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Libertas Academica 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4401249/
https://www.ncbi.nlm.nih.gov/pubmed/25922570
http://dx.doi.org/10.4137/BMI.S25132
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author Satoh, Jun-ichi
Kino, Yoshihiro
Niida, Shumpei
author_facet Satoh, Jun-ichi
Kino, Yoshihiro
Niida, Shumpei
author_sort Satoh, Jun-ichi
collection PubMed
description BACKGROUND: Alzheimer’s disease (AD) is the most common cause of dementia with no curative therapy currently available. Establishment of sensitive and non-invasive biomarkers that promote an early diagnosis of AD is crucial for the effective administration of disease-modifying drugs. MicroRNAs (miRNAs) mediate posttranscriptional repression of numerous target genes. Aberrant regulation of miRNA expression is implicated in AD pathogenesis, and circulating miRNAs serve as potential biomarkers for AD. However, data analysis of numerous AD-specific miRNAs derived from small RNA-sequencing (RNA-Seq) is most often laborious. METHODS: To identify circulating miRNA biomarkers for AD, we reanalyzed a publicly available small RNA-Seq dataset, composed of blood samples derived from 48 AD patients and 22 normal control (NC) subjects, by a simple web-based miRNA data analysis pipeline that combines omiRas and DIANA miRPath. RESULTS: By using omiRas, we identified 27 miRNAs expressed differentially between both groups, including upregulation in AD of miR-26b-3p, miR-28–3p, miR-30c-5p, miR-30d-5p, miR-148b-5p, miR-151a-3p, miR-186–5p, miR-425–5p, miR-550a-5p, miR-1468, miR-4781–3p, miR-5001–3p, and miR-6513–3p and downregulation in AD of let-7a-5p, let-7e-5p, let-7f-5p, let-7g-5p, miR-15a-5p, miR-17–3p, miR-29b-3p, miR-98–5p, miR-144–5p, miR-148a-3p, miR-502–3p, miR-660–5p, miR-1294, and miR-3200–3p. DIANA miRPath indicated that miRNA-regulated pathways potentially downregulated in AD are linked with neuronal synaptic functions, while those upregulated in AD are implicated in cell survival and cellular communication. CONCLUSIONS: The simple web-based miRNA data analysis pipeline helps us to effortlessly identify candidates for miRNA biomarkers and pathways of AD from the complex small RNA-Seq data.
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spelling pubmed-44012492015-04-28 MicroRNA-Seq Data Analysis Pipeline to Identify Blood Biomarkers for Alzheimer’s Disease from Public Data Satoh, Jun-ichi Kino, Yoshihiro Niida, Shumpei Biomark Insights Original Research BACKGROUND: Alzheimer’s disease (AD) is the most common cause of dementia with no curative therapy currently available. Establishment of sensitive and non-invasive biomarkers that promote an early diagnosis of AD is crucial for the effective administration of disease-modifying drugs. MicroRNAs (miRNAs) mediate posttranscriptional repression of numerous target genes. Aberrant regulation of miRNA expression is implicated in AD pathogenesis, and circulating miRNAs serve as potential biomarkers for AD. However, data analysis of numerous AD-specific miRNAs derived from small RNA-sequencing (RNA-Seq) is most often laborious. METHODS: To identify circulating miRNA biomarkers for AD, we reanalyzed a publicly available small RNA-Seq dataset, composed of blood samples derived from 48 AD patients and 22 normal control (NC) subjects, by a simple web-based miRNA data analysis pipeline that combines omiRas and DIANA miRPath. RESULTS: By using omiRas, we identified 27 miRNAs expressed differentially between both groups, including upregulation in AD of miR-26b-3p, miR-28–3p, miR-30c-5p, miR-30d-5p, miR-148b-5p, miR-151a-3p, miR-186–5p, miR-425–5p, miR-550a-5p, miR-1468, miR-4781–3p, miR-5001–3p, and miR-6513–3p and downregulation in AD of let-7a-5p, let-7e-5p, let-7f-5p, let-7g-5p, miR-15a-5p, miR-17–3p, miR-29b-3p, miR-98–5p, miR-144–5p, miR-148a-3p, miR-502–3p, miR-660–5p, miR-1294, and miR-3200–3p. DIANA miRPath indicated that miRNA-regulated pathways potentially downregulated in AD are linked with neuronal synaptic functions, while those upregulated in AD are implicated in cell survival and cellular communication. CONCLUSIONS: The simple web-based miRNA data analysis pipeline helps us to effortlessly identify candidates for miRNA biomarkers and pathways of AD from the complex small RNA-Seq data. Libertas Academica 2015-04-15 /pmc/articles/PMC4401249/ /pubmed/25922570 http://dx.doi.org/10.4137/BMI.S25132 Text en © 2015 the author(s), publisher and licensee Libertas Academica Ltd. This is an open access article published under the Creative Commons CC-BY-NC 3.0 license.
spellingShingle Original Research
Satoh, Jun-ichi
Kino, Yoshihiro
Niida, Shumpei
MicroRNA-Seq Data Analysis Pipeline to Identify Blood Biomarkers for Alzheimer’s Disease from Public Data
title MicroRNA-Seq Data Analysis Pipeline to Identify Blood Biomarkers for Alzheimer’s Disease from Public Data
title_full MicroRNA-Seq Data Analysis Pipeline to Identify Blood Biomarkers for Alzheimer’s Disease from Public Data
title_fullStr MicroRNA-Seq Data Analysis Pipeline to Identify Blood Biomarkers for Alzheimer’s Disease from Public Data
title_full_unstemmed MicroRNA-Seq Data Analysis Pipeline to Identify Blood Biomarkers for Alzheimer’s Disease from Public Data
title_short MicroRNA-Seq Data Analysis Pipeline to Identify Blood Biomarkers for Alzheimer’s Disease from Public Data
title_sort microrna-seq data analysis pipeline to identify blood biomarkers for alzheimer’s disease from public data
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4401249/
https://www.ncbi.nlm.nih.gov/pubmed/25922570
http://dx.doi.org/10.4137/BMI.S25132
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