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Biomarker Candidates for Alzheimer’s Disease Unraveled through In Silico Differential Gene Expression Analysis

Alzheimer’s disease (AD) is neurodegeneration that accounts for 60–70% of dementia cases. Symptoms begin with mild memory difficulties and evolve towards cognitive impairment. The underlying risk factors remain primarily unclear for this heterogeneous disorder. Bioinformatics is a relevant research...

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Autores principales: Silva-Lucero, Maria-del-Carmen, Rivera-Osorio, Jared, Gómez-Virgilio, Laura, Lopez-Toledo, Gustavo, Luna-Muñoz, José, Montiel-Sosa, Francisco, Soto-Rojas, Luis O., Pacheco-Herrero, Mar, Cardenas-Aguayo, Maria-del-Carmen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9139748/
https://www.ncbi.nlm.nih.gov/pubmed/35626321
http://dx.doi.org/10.3390/diagnostics12051165
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author Silva-Lucero, Maria-del-Carmen
Rivera-Osorio, Jared
Gómez-Virgilio, Laura
Lopez-Toledo, Gustavo
Luna-Muñoz, José
Montiel-Sosa, Francisco
Soto-Rojas, Luis O.
Pacheco-Herrero, Mar
Cardenas-Aguayo, Maria-del-Carmen
author_facet Silva-Lucero, Maria-del-Carmen
Rivera-Osorio, Jared
Gómez-Virgilio, Laura
Lopez-Toledo, Gustavo
Luna-Muñoz, José
Montiel-Sosa, Francisco
Soto-Rojas, Luis O.
Pacheco-Herrero, Mar
Cardenas-Aguayo, Maria-del-Carmen
author_sort Silva-Lucero, Maria-del-Carmen
collection PubMed
description Alzheimer’s disease (AD) is neurodegeneration that accounts for 60–70% of dementia cases. Symptoms begin with mild memory difficulties and evolve towards cognitive impairment. The underlying risk factors remain primarily unclear for this heterogeneous disorder. Bioinformatics is a relevant research tool that allows for identifying several pathways related to AD. Open-access databases of RNA microarrays from the peripheral blood and brain of AD patients were analyzed after background correction and data normalization; the Limma package was used for differential expression analysis (DEA) through statistical R programming language. Data were corrected with the Benjamini and Hochberg approach, and genes with p-values equal to or less than 0.05 were considered to be significant. The direction of the change in gene expression was determined by its variation in the log2-fold change between healthy controls and patients. We performed the functional enrichment analysis of GO using goana and topGO-Limma. The functional enrichment analysis of DEGs showed upregulated (UR) pathways: behavior, nervous systems process, postsynapses, enzyme binding; downregulated (DR) were cellular component organization, RNA metabolic process, and signal transduction. Lastly, the intersection of DEGs in the three databases showed eight shared genes between brain and blood, with potential use as AD biomarkers for blood tests.
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spelling pubmed-91397482022-05-28 Biomarker Candidates for Alzheimer’s Disease Unraveled through In Silico Differential Gene Expression Analysis Silva-Lucero, Maria-del-Carmen Rivera-Osorio, Jared Gómez-Virgilio, Laura Lopez-Toledo, Gustavo Luna-Muñoz, José Montiel-Sosa, Francisco Soto-Rojas, Luis O. Pacheco-Herrero, Mar Cardenas-Aguayo, Maria-del-Carmen Diagnostics (Basel) Article Alzheimer’s disease (AD) is neurodegeneration that accounts for 60–70% of dementia cases. Symptoms begin with mild memory difficulties and evolve towards cognitive impairment. The underlying risk factors remain primarily unclear for this heterogeneous disorder. Bioinformatics is a relevant research tool that allows for identifying several pathways related to AD. Open-access databases of RNA microarrays from the peripheral blood and brain of AD patients were analyzed after background correction and data normalization; the Limma package was used for differential expression analysis (DEA) through statistical R programming language. Data were corrected with the Benjamini and Hochberg approach, and genes with p-values equal to or less than 0.05 were considered to be significant. The direction of the change in gene expression was determined by its variation in the log2-fold change between healthy controls and patients. We performed the functional enrichment analysis of GO using goana and topGO-Limma. The functional enrichment analysis of DEGs showed upregulated (UR) pathways: behavior, nervous systems process, postsynapses, enzyme binding; downregulated (DR) were cellular component organization, RNA metabolic process, and signal transduction. Lastly, the intersection of DEGs in the three databases showed eight shared genes between brain and blood, with potential use as AD biomarkers for blood tests. MDPI 2022-05-07 /pmc/articles/PMC9139748/ /pubmed/35626321 http://dx.doi.org/10.3390/diagnostics12051165 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Silva-Lucero, Maria-del-Carmen
Rivera-Osorio, Jared
Gómez-Virgilio, Laura
Lopez-Toledo, Gustavo
Luna-Muñoz, José
Montiel-Sosa, Francisco
Soto-Rojas, Luis O.
Pacheco-Herrero, Mar
Cardenas-Aguayo, Maria-del-Carmen
Biomarker Candidates for Alzheimer’s Disease Unraveled through In Silico Differential Gene Expression Analysis
title Biomarker Candidates for Alzheimer’s Disease Unraveled through In Silico Differential Gene Expression Analysis
title_full Biomarker Candidates for Alzheimer’s Disease Unraveled through In Silico Differential Gene Expression Analysis
title_fullStr Biomarker Candidates for Alzheimer’s Disease Unraveled through In Silico Differential Gene Expression Analysis
title_full_unstemmed Biomarker Candidates for Alzheimer’s Disease Unraveled through In Silico Differential Gene Expression Analysis
title_short Biomarker Candidates for Alzheimer’s Disease Unraveled through In Silico Differential Gene Expression Analysis
title_sort biomarker candidates for alzheimer’s disease unraveled through in silico differential gene expression analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9139748/
https://www.ncbi.nlm.nih.gov/pubmed/35626321
http://dx.doi.org/10.3390/diagnostics12051165
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