Integration of clinical data with a genome‐scale metabolic model of the human adipocyte. Issue 1 (19th March 2013)

• Record Type: Journal Article
• Authors: Mardinoglu, Adil; Agren, Rasmus; Kampf, Caroline; Asplund, Anna; Nookaew, Intawat; Jacobson, Peter; Walley, Andrew J; Froguel, Philippe; Carlsson, Lena M; Uhlen, Mathias; Nielsen, Jens
• Is Part Of: Molecular systems biology. Volume 9:Issue 1(2013)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2013-03-19
• Subjects: Molecular biology -- Periodicals; Systems biology -- Periodicals; 572.8
• DOI: 10.1038/msb.2013.5
• Languages: English
• ISSNs: 1744-4292

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>We evaluated the presence/absence of proteins encoded by 14 077 genes in adipocytes obtained from different tissue samples using immunohistochemistry. By combining this with previously published adipocyte‐specific proteome data, we identified proteins associated with 7340 genes in human adipocytes. This information was used to reconstruct a comprehensive and functional genome‐scale metabolic model of adipocyte metabolism. The resulting metabolic model, <italic>iAdipocytes1809</italic>, enables mechanistic insights into adipocyte metabolism on a genome‐wide level, and can serve as a scaffold for integration of omics data to understand the genotype–phenotype relationship in obese subjects. By integrating human transcriptome and fluxome data, we found an increase in the metabolic activity around androsterone, ganglioside GM2 and degradation products of heparan sulfate and keratan sulfate, and a decrease in mitochondrial metabolic activities in obese subjects compared with lean subjects. Our study hereby shows a path to identify new therapeutic targets for treating obesity through combination of high throughput patient data and metabolic modeling.</p> </abstract>