Gene Ontology Curation of Neuroinflammation Biology Improves the Interpretation of Alzheimer’s Disease Gene Expression Data Article Swipe
Barbara Kramarz
,
Rachael P. Huntley
,
M. Rodríguez-López
,
Paola Roncaglia
,
Shirin C C Saverimuttu
,
Helen Parkinson
,
Rina Bandopadhyay
,
María Martin
,
Sandra Orchard
,
Nigel M. Hooper
,
David Brough
,
Ruth C. Lovering
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3233/jad-200207
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3233/jad-200207
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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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3233/jad-200207
- https://content.iospress.com:443/download/journal-of-alzheimers-disease/jad200207?id=journal-of-alzheimers-disease%2Fjad200207
- OA Status
- hybrid
- Cited By
- 20
- References
- 99
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3025676852
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3025676852Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3233/jad-200207Digital Object Identifier
- Title
-
Gene Ontology Curation of Neuroinflammation Biology Improves the Interpretation of Alzheimer’s Disease Gene Expression DataWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-05-13Full publication date if available
- Authors
-
Barbara Kramarz, Rachael P. Huntley, M. Rodríguez-López, Paola Roncaglia, Shirin C C Saverimuttu, Helen Parkinson, Rina Bandopadhyay, María Martin, Sandra Orchard, Nigel M. Hooper, David Brough, Ruth C. LoveringList of authors in order
- Landing page
-
https://doi.org/10.3233/jad-200207Publisher landing page
- PDF URL
-
https://content.iospress.com:443/download/journal-of-alzheimers-disease/jad200207?id=journal-of-alzheimers-disease%2Fjad200207Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://content.iospress.com:443/download/journal-of-alzheimers-disease/jad200207?id=journal-of-alzheimers-disease%2Fjad200207Direct OA link when available
- Concepts
-
Gene ontology, Computational biology, Annotation, Disease, Ontology, Biology, Neuroinflammation, Gene Annotation, Resource (disambiguation), Neuroscience, Bioinformatics, Gene, Gene expression, Data science, Computer science, Genome, Genetics, Medicine, Pathology, Computer network, Epistemology, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
20Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 7, 2024: 5, 2022: 1, 2021: 2, 2020: 5Per-year citation counts (last 5 years)
- References (count)
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99Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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