Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/27491
Appears in Collections:Faculty of Health Sciences and Sport Journal Articles
Peer Review Status: Refereed
Title: A coding and non-coding transcriptomic perspective on the genomics of human metabolic disease
Author(s): Timmons, James A
Atherton, Philip J
Larsson, Ola
Sood, Sanjana
Blokhin, Ilya O
Brogan, Robert J
Volmar, Claude-Henry
Josse, Andrea R
Slentz, Cris
Wahlestedt, Claes
Phillips, Stuart M
Phillips, Bethan E
Gallagher, Iain J
Kraus, William E
Keywords: genomics
Issue Date: 6-Sep-2018
Citation: Timmons JA, Atherton PJ, Larsson O, Sood S, Blokhin IO, Brogan RJ, Volmar C, Josse AR, Slentz C, Wahlestedt C, Phillips SM, Phillips BE, Gallagher IJ & Kraus WE (2018) A coding and non-coding transcriptomic perspective on the genomics of human metabolic disease. Nucleic Acids Research, 46 (15), pp. 7772-7792. https://doi.org/10.1093/nar/gky570.
Abstract: Genome-wide association studies (GWAS), relying on hundreds of thousands of individuals, have revealed > 200 genomic loci linked to metabolic disease (MD). Loss of insulin sensitivity (IS) is a key component of MD and we hypothesized that discovery of a robust IS transcriptome would help reveal the underlying genomic structure of MD. Using 1,012 human skeletal muscle samples, detailed physiology and a tissue-optimized approach for the quantification of coding (> 18,000) and non-coding (> 15,000) RNA (ncRNA), we identified 332 fasting IS-related genes (CORE-IS). Over 200 had a proven role in the biochemistry of insulin and/or metabolism or were located at GWAS MD loci. Over 50% of the CORE-IS genes responded to clinical treatment; 16 quantitatively tracking changes in IS across four independent studies (P = 0.0000053: negatively: AGL, G0S2, KPNA2, PGM2, RND3 and TSPAN9 and positively: ALDH6A1, DHTKD1, ECHDC3, MCCC1, OARD1, PCYT2, PRRX1, SGCG, SLC43A1 and SMIM8). A network of ncRNA positively related to IS and interacted with RNA coding for viral response proteins (P < 1 × 10−48), while reduced amino acid catabolic gene expression occurred without a change in expression of oxidative-phosphorylation genes. We illustrate that combining in-depth physiological phenotyping with robust RNA profiling methods, identifies molecular networks which are highly consistent with the genetics and biochemistry of human metabolic disease.
DOI Link: 10.1093/nar/gky570
Rights: © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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