Novel brown adipose tissue candidate genes predicted by the human gene connectome
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Department of Ecology and Evolutionary Biology, University of ArizonaIssue Date
2022
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Nature ResearchCitation
Salazar-Tortosa, D. F., Enard, D., Itan, Y., & Ruiz, J. R. (2022). Novel brown adipose tissue candidate genes predicted by the human gene connectome. Scientific Reports, 12(1).Journal
Scientific ReportsRights
Copyright © The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Brown adipose tissue (BAT) is a promising therapeutic target against obesity. Therefore, research on the genetic architecture of BAT could be key for the development of successful therapies against this complex phenotype. Hypothesis-driven candidate gene association studies are useful for studying genetic determinants of complex traits, but they are dependent upon the previous knowledge to select candidate genes. Here, we predicted 107 novel-BAT candidate genes in silico using the uncoupling protein one (UCP1) as the hallmark of BAT activity. We first identified the top 1% of human genes predicted by the human gene connectome to be biologically closest to the UCP1, estimating 167 additional pathway genes (BAT connectome). We validated this prediction by showing that 60 genes already associated with BAT were included in the connectome and they were biologically closer to each other than expected by chance (p < 2.2 × 10−16). The rest of genes (107) are potential candidates for BAT, being also closer to known BAT genes and more expressed in BAT biopsies than expected by chance (p < 2.2 × 10−16; p = 4.39 × 10–02). The resulting new list of predicted human BAT genes should be useful for the discovery of novel BAT genes and metabolic pathways. © 2022, The Author(s).Note
Open access journalISSN
2045-2322PubMed ID
35534514Version
Final published versionae974a485f413a2113503eed53cd6c53
10.1038/s41598-022-11317-2
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Except where otherwise noted, this item's license is described as Copyright © The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License.
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