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Gene Ontology Curation of Neuroinflammation Biology Improves the Interpretation of Alzheimer’s Disease Gene Expression Data

BACKGROUND: Gene Ontology (GO) is a major bioinformatic resource used for analysis of large biomedical datasets, for example from genome-wide association studies, applied universally across biological fields, including Alzheimer’s disease (AD) research. OBJECTIVE: We aim to demonstrate the applicabi...

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Autores principales: Kramarz, Barbara, Huntley, Rachael P., Rodríguez-López, Milagros, Roncaglia, Paola, Saverimuttu, Shirin C.C., Parkinson, Helen, Bandopadhyay, Rina, Martin, Maria-Jesus, Orchard, Sandra, Hooper, Nigel M., Brough, David, Lovering, Ruth C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IOS Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7369085/
https://www.ncbi.nlm.nih.gov/pubmed/32417785
http://dx.doi.org/10.3233/JAD-200207
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author Kramarz, Barbara
Huntley, Rachael P.
Rodríguez-López, Milagros
Roncaglia, Paola
Saverimuttu, Shirin C.C.
Parkinson, Helen
Bandopadhyay, Rina
Martin, Maria-Jesus
Orchard, Sandra
Hooper, Nigel M.
Brough, David
Lovering, Ruth C.
author_facet Kramarz, Barbara
Huntley, Rachael P.
Rodríguez-López, Milagros
Roncaglia, Paola
Saverimuttu, Shirin C.C.
Parkinson, Helen
Bandopadhyay, Rina
Martin, Maria-Jesus
Orchard, Sandra
Hooper, Nigel M.
Brough, David
Lovering, Ruth C.
author_sort Kramarz, Barbara
collection PubMed
description BACKGROUND: Gene Ontology (GO) is a major bioinformatic resource used for analysis of large biomedical datasets, for example from genome-wide association studies, applied universally across biological fields, including Alzheimer’s disease (AD) research. OBJECTIVE: We aim to demonstrate the applicability of GO for interpretation of AD datasets to improve the understanding of the underlying molecular disease mechanisms, including the involvement of inflammatory pathways and dysregulated microRNAs (miRs). METHODS: We have undertaken a systematic full article GO annotation approach focused on microglial proteins implicated in AD and the miRs regulating their expression. PANTHER was used for enrichment analysis of previously published AD data. Cytoscape was used for visualizing and analyzing miR-target interactions captured from published experimental evidence. RESULTS: We contributed 3,084 new annotations for 494 entities, i.e., on average six new annotations per entity. This included a total of 1,352 annotations for 40 prioritized microglial proteins implicated in AD and 66 miRs regulating their expression, yielding an average of twelve annotations per prioritized entity. The updated GO resource was then used to re-analyze previously published data. The re-analysis showed novel processes associated with AD-related genes, not identified in the original study, such as ‘gliogenesis’, ‘regulation of neuron projection development’, or ‘response to cytokine’, demonstrating enhanced applicability of GO for neuroscience research. CONCLUSIONS: This study highlights ongoing development of the neurobiological aspects of GO and demonstrates the value of biocuration activities in the area, thus helping to delineate the molecular bases of AD to aid the development of diagnostic tools and treatments.
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spelling pubmed-73690852020-07-22 Gene Ontology Curation of Neuroinflammation Biology Improves the Interpretation of Alzheimer’s Disease Gene Expression Data Kramarz, Barbara Huntley, Rachael P. Rodríguez-López, Milagros Roncaglia, Paola Saverimuttu, Shirin C.C. Parkinson, Helen Bandopadhyay, Rina Martin, Maria-Jesus Orchard, Sandra Hooper, Nigel M. Brough, David Lovering, Ruth C. J Alzheimers Dis Research Article BACKGROUND: Gene Ontology (GO) is a major bioinformatic resource used for analysis of large biomedical datasets, for example from genome-wide association studies, applied universally across biological fields, including Alzheimer’s disease (AD) research. OBJECTIVE: We aim to demonstrate the applicability of GO for interpretation of AD datasets to improve the understanding of the underlying molecular disease mechanisms, including the involvement of inflammatory pathways and dysregulated microRNAs (miRs). METHODS: We have undertaken a systematic full article GO annotation approach focused on microglial proteins implicated in AD and the miRs regulating their expression. PANTHER was used for enrichment analysis of previously published AD data. Cytoscape was used for visualizing and analyzing miR-target interactions captured from published experimental evidence. RESULTS: We contributed 3,084 new annotations for 494 entities, i.e., on average six new annotations per entity. This included a total of 1,352 annotations for 40 prioritized microglial proteins implicated in AD and 66 miRs regulating their expression, yielding an average of twelve annotations per prioritized entity. The updated GO resource was then used to re-analyze previously published data. The re-analysis showed novel processes associated with AD-related genes, not identified in the original study, such as ‘gliogenesis’, ‘regulation of neuron projection development’, or ‘response to cytokine’, demonstrating enhanced applicability of GO for neuroscience research. CONCLUSIONS: This study highlights ongoing development of the neurobiological aspects of GO and demonstrates the value of biocuration activities in the area, thus helping to delineate the molecular bases of AD to aid the development of diagnostic tools and treatments. IOS Press 2020-06-15 /pmc/articles/PMC7369085/ /pubmed/32417785 http://dx.doi.org/10.3233/JAD-200207 Text en © 2020 – IOS Press and the authors. All rights reserved https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial (CC BY-NC 4.0) License (https://creativecommons.org/licenses/by-nc/4.0/) , which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Kramarz, Barbara
Huntley, Rachael P.
Rodríguez-López, Milagros
Roncaglia, Paola
Saverimuttu, Shirin C.C.
Parkinson, Helen
Bandopadhyay, Rina
Martin, Maria-Jesus
Orchard, Sandra
Hooper, Nigel M.
Brough, David
Lovering, Ruth C.
Gene Ontology Curation of Neuroinflammation Biology Improves the Interpretation of Alzheimer’s Disease Gene Expression Data
title Gene Ontology Curation of Neuroinflammation Biology Improves the Interpretation of Alzheimer’s Disease Gene Expression Data
title_full Gene Ontology Curation of Neuroinflammation Biology Improves the Interpretation of Alzheimer’s Disease Gene Expression Data
title_fullStr Gene Ontology Curation of Neuroinflammation Biology Improves the Interpretation of Alzheimer’s Disease Gene Expression Data
title_full_unstemmed Gene Ontology Curation of Neuroinflammation Biology Improves the Interpretation of Alzheimer’s Disease Gene Expression Data
title_short Gene Ontology Curation of Neuroinflammation Biology Improves the Interpretation of Alzheimer’s Disease Gene Expression Data
title_sort gene ontology curation of neuroinflammation biology improves the interpretation of alzheimer’s disease gene expression data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7369085/
https://www.ncbi.nlm.nih.gov/pubmed/32417785
http://dx.doi.org/10.3233/JAD-200207
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