Cross-species gene expression analysis identifies a novel set of genes implicated in human insulin sensitivity

Abstract

Objective:Insulin resistance (IR) is one of the earliest predictors of type 2 diabetes. However, diagnosis of IR is limited. High fat fed mouse models provide key insights into IR. We hypothesized that early features of IR are associated with persistent changes in gene expression (GE) and endeavored to (a) develop novel methods for improving signal:noise in analysis of human GE using mouse models; (b) identify a GE motif that accurately diagnoses IR in humans; and (c) identify novel biology associated with IR in humans.Methods:We integrated human muscle GE data with longitudinal mouse GE data and developed an unbiased three-level cross-species analysis platform (single gene, gene set, and networks) to generate a gene expression motif (GEM) indicative of IR. A logistic regression classification model validated GEM in three independent human data sets (n=115).Results:This GEM of 93 genes substantially improved diagnosis of IR compared with routine clinical measures across multiple independent data sets. Individuals misclassified by GEM possessed other metabolic features raising the possibility that they represent a separate metabolic subclass. The GEM was enriched in pathways previously implicated in insulin action and revealed novel associations between β-catenin and Jak1 and IR. Functional analyses using small molecule inhibitors showed an important role for these proteins in insulin action.Conclusions:This study shows that systems approaches for identifying molecular signatures provides a powerful way to stratify individuals into discrete metabolic groups. Moreover, we speculate that the β-catenin pathway may represent a novel biomarker for IR in humans that warrant future investigation.

Tankyrase modulates insulin sensitivity in skeletal muscle cells by regulating the stability of GLUT4 vesicle proteins

“…Notably, ␤-catenin has previously been implicated in insulin resistance. It was part of a human skeletal muscle gene expression signature that was diagnostic for insulin resistance and inhibition of ␤-catenin inhibited insulin-stimulated glucose uptake in L6 myotubes (52) and in 3T3-L1 adipocytes (53). Consistent with a role for ␤-catenin in insulin sensitivity, drug-induced ␤-catenin stabilization enhances insulin-mediated glucose uptake in adipocytes (53).…”

Metabolomic analysis of insulin resistance across different mouse strains and diets

“…Similar to that described above, this was performed using data from individual mice, whereby each mouse's metabolite(s) were utilized to classify that mouse into a certain group, and the accuracy reflects "observed" versus "true" classification. In this analysis, a ratio of 2 represents 100% CA, whereas a ratio of 1 reflects random chance (34). We assessed the CA ratio of the significant 113 metabolites (Cor Met) to classify mice based on insulin resistance (1.37 CA ratio), diet (1.85), and strain (1.72), and the Cor Met signature classified mice significantly better than random chance in all three cases (Fig.…”

β-catenin regulates muscle glucose transport via actin remodelling and M-cadherin binding

“…Canonically, β-catenin is best recognised as the downstream effector of Wnt signalling, in which levels of β-catenin are regulated by a Wnt ligand-inhibited degradation complex, leading to accumulation of the protein and activation of Wnt target genes [ 14 , 15 ]. However, it has been identified in cross-species screens as a candidate gene involved in the development of insulin-resistance [ 16 ] and also implicated in the regulation of GLUT4 trafficking in adipocytes [ 17 ]. Many of the proteins involved in insulin signalling, including Akt, PAK1 and Rac1, are known to modulate β-catenin function in non-muscle cells, as well as insulin-induced actin remodelling [ 4 , [18] , [19] , [20] ].…”