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

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 semantic integration of multiple sources of biomedical knowledge, and interrogation of phenotypes and gene functions associated with disease, may significantly increase the probability of identifying strong and unobvious candidate genes in genetic association studies.

Genome-wide analysis identifies differential promoter methylation of Leprel2 , Foxf1 , Mmp25, Igfbp6 , and Peg12 in murine tendinopathy

“…Secondly, Foxf1 induces integrin β3 expression, with high specificity in mouse embryonic fibroblasts . This finding appears to be important since this integrin was identified through the BORG database of genomic and biomedical knowledge as one of four strong candidate risk genes for human tendinopathy (which included COL11A2 , ELN , ITGB3 , and LOX ) . Thirdly, proteomic analysis of pericellular proteins in developing tendons has shown that Mmp25 (like Leprel2 and Foxf1 ) is likely involved in collagen fibril and matrix assembly .…”

“…26 This finding appears to be important since this integrin was identified through the BORG database of genomic and biomedical knowledge as one of four strong candidate risk genes for human tendinopathy (which included COL11A2, ELN, ITGB3, and LOX). 27 Thirdly, proteomic analysis of pericellular proteins in developing tendons has shown that Mmp25 (like Leprel2 and Foxf1) is likely involved in collagen fibril and matrix assembly. 28 Fourthly, a 29 and also by its sensitivity to hypoxia, 30 which has often been implicated in tendinopathic change.…”

Degenerative Suspensory Ligament Desmitis (DSLD) in Peruvian Paso Horses Is Characterized by Altered Expression of TGFβ Signaling Components in Adipose-Derived Stromal Fibroblasts

“…A genetic predisposition to defective matrix organization in human tendinopathy is also supported by a recent bioinformatics analysis [15], which identified four strong candidate risk genes ( COL11A2 , ELN , ITGB3 , LOX ), each of which functions in the controlled turnover of fibrous tissue matrix. In addition, in our own studies, DNA methylome analysis of experimental murine tendinopathy [16] has implicated dysregulation of Leprel2 (Prolyl3-hydroxylase-3), an enzyme which hydroxylates proline in the 3-position and which appears to control collagen fibril diameter specifically in tendon [17].…”

Knowledge Representation and Management, It’s Time to Integrate!

“…The section editors achieved a first selection of 100 papers based on titles and abstracts. After a second review of this set of papers, a selection of 15 candidate best papers was established [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. Five reviewers reviewed these pre-selected papers to select the best four final papers [6][7][8][9].…”

“…Saunders et al [18] proposed a model of BioOntological Relationship Graph database (BORG), which 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. This graph was used and analyzed to screen all human genes for potential links to tendinopathy and finally to propose four candidate genes.…”