- Title
- Gene expression profiles in whole blood and associations with metabolic dysregulation in obesity
- Creator
- Cox, Amanda J.; Zhang, Ping; Evans, Tiffany J.; Scott, Rodney J.; Cripps, Allan W.; West, Nicholas P.
- Relation
- Obesity Research and Clinical Practice Vol. 12, Issue 2, p. 204-213
- Publisher Link
- http://dx.doi.org/10.1016/j.orcp.2017.07.001
- Publisher
- Elsevier
- Resource Type
- journal article
- Date
- 2018
- Description
- Background: Gene expression data provides one tool to gain further insight into the complex biological interactions linking obesity and metabolic disease. This study examined associations between blood gene expression profiles and metabolic disease in obesity. Methods: Whole blood gene expression profiles, performed using the Illumina HT-12v4 Human Expression Beadchip, were compared between (i) individuals with obesity (O) or lean (L) individuals (n = 21 each), (ii) individuals with (M) or without (H) Metabolic Syndrome (n = 11 each) matched on age and gender. Enrichment of differentially expressed genes (DEG) into biological pathways was assessed using Ingenuity Pathway Analysis. Association between sets of genes from biological pathways considered functionally relevant and Metabolic Syndrome were further assessed using an area under the curve (AUC) and cross-validated classification rate (CR). Results: For OvL, only 50 genes were significantly differentially expressed based on the selected differential expression threshold (1.2-fold, p < 0.05). For MvH, 582 genes were significantly differentially expressed (1.2-fold, p < 0.05) and pathway analysis revealed enrichment of DEG into a diverse set of pathways including immune/inflammatory control, insulin signalling and mitochondrial function pathways. Gene sets from the mTOR signalling pathways demonstrated the strongest association with Metabolic Syndrome (p=8.1×10-8; AUC: 0.909, CR: 72.7%). Conclusions: These results support the use of expression profiling in whole blood in the absence of more specific tissue types for investigations of metabolic disease. Using a pathway analysis approach it was possible to identify an enrichment of DEG into biological pathways that could be targeted for in vitro follow-up.
- Subject
- metabolic syndrome; obesity; gene expression; pathway analysis
- Identifier
- http://hdl.handle.net/1959.13/1396968
- Identifier
- uon:34159
- Identifier
- ISSN:1871-403X
- Language
- eng
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