Semantic interrogation of a multi knowledge domain ontological model of tendinopathy identifies four strong candidate risk genes

Scientific Reports
Colleen J SaundersJunaid Gamieldien

Abstract

Tendinopathy is a multifactorial syndrome characterised by tendon pain and thickening, and impaired performance during activity. Candidate gene association studies have identified genetic factors that contribute to intrinsic risk of developing tendinopathy upon exposure to extrinsic factors. Bioinformatics approaches that data-mine existing knowledge for biological relationships may assist with the identification of candidate genes. The aim of this study was to data-mine functional annotation of human genes and identify candidate genes by ontology-seeded queries capturing the features of tendinopathy. Our BioOntological Relationship Graph database (BORG) integrates multiple sources of genomic and biomedical knowledge into an on-disk semantic network where human genes and their orthologs in mouse and rat are central concepts mapped to ontology terms. The BORG was used to screen all human genes for potential links to tendinopathy. Following further prioritisation, four strong candidate genes (COL11A2, ELN, ITGB3, LOX) were identified. These genes are differentially expressed in tendinopathy, functionally linked to features of tendinopathy and previously implicated in other connective tissue diseases. In conclusion, cross-domain s...Continue Reading

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Citations

Jul 1, 2017·The American Journal of Sports Medicine·Jin-Ok AhnSae Hoon Kim
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Sep 21, 2020·Matrix Biology : Journal of the International Society for Matrix Biology·Mei SunDavid E Birk
Oct 3, 2021·Npj Regenerative Medicine·Paula Sarmiento, Dianne Little

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Datasets Mentioned

BETA
GDS4901

Methods Mentioned

BETA
gene knockout

Software Mentioned

limma
Phenolyzer
R
Neo4J
BORG
affy
Bioconductor
BioOntological Relationship Graph ( BORG )

Related Concepts

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