Evidence map›Paper›PMID 32417785›Full record

ArticleJournal of Alzheimer's disease : JAD2020

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

Barbara Kramarz, Rachael P Huntley, Milagros Rodríguez-López, Paola Roncaglia, Shirin C C Saverimuttu, Helen Parkinson, Rina Bandopadhyay, Maria-Jesus Martin, Sandra Orchard, Nigel M Hooper and 2 more

Abstract read
In one paragraph

Article in Journal of Alzheimer's disease : JAD, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Barbara KramarzFunctional Gene Annotation, Preclinical and Fundamental Science, UCL Institute of Cardiovascular Science, University College London, London, UK.
Rachael P HuntleyFunctional Gene Annotation, Preclinical and Fundamental Science, UCL Institute of Cardiovascular Science, University College London, London, UK.
Milagros Rodríguez-LópezEuropean Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Paola RoncagliaEuropean Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Shirin C C SaverimuttuFunctional Gene Annotation, Preclinical and Fundamental Science, UCL Institute of Cardiovascular Science, University College London, London, UK.
Helen ParkinsonEuropean Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Rina BandopadhyayUCL Institute of Neurology and Reta Lila Weston Institute of Neurological Studies, University College London, London, UK.
Maria-Jesus MartinEuropean Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Sandra OrchardEuropean Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Nigel M HooperDivision of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK.
David BroughDivision of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK.
Ruth C LoveringFunctional Gene Annotation, Preclinical and Fundamental Science, UCL Institute of Cardiovascular Science, University College London, London, UK.

Funding

UniProt - Text Mining and Large Language models to Enhance Functional Annotation in UniProt of Protein Variants Associated with Alzheimer's DiseaseU24HG007822 · NHGRI · GEORGETOWN UNIVERSITY · PI Alex Bateman, Alan James Bridge · 2018 to 2026
$53.0M
Resource ProjectU41HG002273 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMAS, PAUL D. · 2012 to 2021
$34.7M
Department of HealthMedical Research Council MR/L023784/1Medical Research Council MR/L023784/2NHGRI NIH HHS U24 HG007822NHGRI NIH HHS U41 HG002273
6 · The paper itself

Abstract

backgroundGene 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.

objectiveWe 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).

methodsWe 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.

resultsWe 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.

conclusionsThis 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.

Indexed as

Gene ExpressionGene OntologyAlzheimer DiseaseComputational BiologyEncephalitisHumansMicrogliaMolecular Sequence AnnotationAlzheimer’s diseaseCytoscape network analysisGene OntologymicroglianeuroinflammationPANTHER

Identifiers

PMID32417785
PMCPMC7369085

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.