Identification of Proteins Associated with the Early Restoration of Insulin Sensitivity After Biliopancreatic Diversion.

CONTEXT: Insulin resistance (IR) is a risk factor for type 2 diabetes, diabetic kidney disease, cardiovascular disease and nonalcoholic steatohepatitis. Biliopancreatic diversion (BPD) is the most effective form of bariatric surgery for improving insulin sensitivity. OBJECTIVE: To identify plasma proteins correlating with the early restoration of insulin sensitivity after BPD. DESIGN: Prospective single-center study including 20 insulin-resistant men with morbid obesity scheduled for BPD. Patient characteristics and blood samples were repeatedly collected from baseline up to 4 weeks postsurgery. IR was assessed by homeostatic model assessment for insulin resistance (HOMA-IR), Matsuda Index, and by studying metabolic profiles during meal tolerance tests. Unbiased proteomic analysis was performed to identify plasma proteins altered by BPD. Detailed plasma profiles were made on a selected set of proteins by targeted multiple reaction monitoring mass spectrometry (MRM/MS). Changes in plasma proteome were evaluated in relation to metabolic and inflammatory changes. RESULTS: BPD resulted in improved insulin sensitivity and reduced body weight. Proteomic analysis identified 29 proteins that changed following BPD. Changes in plasma levels of afamin, apolipoprotein A-IV (ApoA4), and apolipoprotein A-II (ApoA2) correlated significantly with changes in IR. CONCLUSION: Circulating levels of afamin, ApoA4, and ApoA2 were associated with and may contribute to the rapid improvement in insulin sensitivity after BPD.

Tissue-specific genes as an underutilized resource in drug discovery.

Tissue-specific genes are believed to be good drug targets due to improved safety. Here we show that this intuitive notion is not reflected in phase 1 and 2 clinical trials, despite the historic success of tissue-specific targets and their 2.3-fold overrepresentation among targets of marketed non-oncology drugs. We compare properties of tissue-specific genes and drug targets. We show that tissue-specificity of the target may also be related to efficacy of the drug. The relationship may be indirect (enrichment in Mendelian disease and PTVesc genes) or direct (elevated betweenness centrality scores for tissue-specifically produced enzymes and secreted proteins). Reduced evolutionary conservation of tissue-specific genes may represent a bottleneck for drug projects, prompting development of novel models with smaller evolutionary gap to humans. We show that the opportunities to identify tissue-specific drug targets are not exhausted and discuss potential use cases for tissue-specific genes in drug research.

Human hepatic gene expression signature of non-alcoholic fatty liver disease progression, a meta-analysis.

Non-alcoholic fatty liver disease (NAFLD) is a wide-spread chronic liver condition that places patients at risk of developing cardiovascular diseases and may progress to cirrhosis or hepatocellular carcinoma if untreated. Challenges in clinical and basic research are caused by poor understanding of NAFLD mechanisms. The purpose of current study is to describe molecular changes occurring in human liver during NAFLD progression by defining a reproducible gene expression signature. We conduct a systematic meta-analysis of published human gene expression studies on liver biopsies and bariatric surgery samples of NAFLD patients. We relate gene expression levels with histology scores using regression models and identify a set of genes showing consistent-sign associations with NAFLD progression that are replicated in at least three independent studies. The analysis reveals genes that have not been previously characterized in the context of NAFLD such as HORMAD2 and LINC01554. In addition, we highlight biomarker opportunities for risk stratification and known drugs that could be used as tool compounds to study NAFLD in model systems. We identify gaps in current knowledge of molecular mechanisms of NAFLD progression and discuss ways to address them. Finally, we provide an extensive data supplement containing meta-analysis results in a computer-readable format.

FKBP5 expression in human adipose tissue increases following dexamethasone exposure and is associated with insulin resistance.

OBJECTIVE: To study effects of dexamethasone on gene expression in human adipose tissue aiming to identify potential novel mechanisms for glucocorticoid-induced insulin resistance. MATERIALS/METHODS: Subcutaneous and omental adipose tissue, obtained from non-diabetic donors (10 M/15 F; age: 28-60 years; BMI: 20.7-30.6 kg/m²), was incubated with or without dexamethasone (0.003-3 µmol/L) for 24 h. Gene expression was assessed by microarray and real time-PCR and protein expression by immunoblotting. RESULTS: FKBP5 (FK506-binding protein 5) and CNR1 (cannabinoid receptor 1) were the most responsive genes to dexamethasone in both subcutaneous and omental adipose tissue (~7-fold). Dexamethasone increased FKBP5 gene and protein expression in a dose-dependent manner in both depots. The gene product, FKBP51 protein, was 10-fold higher in the omental than in the subcutaneous depot, whereas the mRNA levels were similar. Higher FKBP5 gene expression in omental adipose tissue was associated with reduced insulin effects on glucose uptake in both depots. Furthermore, FKBP5 gene expression in subcutaneous adipose tissue was positively correlated with serum insulin, HOMA-IR and subcutaneous adipocyte diameter and negatively with plasma HDL-cholesterol. FKBP5 SNPs were found to be associated with type 2 diabetes and diabetes-related phenotypes in large population-based samples. CONCLUSIONS: Dexamethasone exposure promotes expression of FKBP5 in adipose tissue, a gene that may be implicated in glucocorticoid-induced insulin resistance.

GPR120 (FFAR4) is preferentially expressed in pancreatic delta cells and regulates somatostatin secretion from murine islets of Langerhans.

AIMS/HYPOTHESIS: The NEFA-responsive G-protein coupled receptor 120 (GPR120) has been implicated in the regulation of inflammation, in the control of incretin secretion and as a predisposing factor influencing the development of type 2 diabetes by regulation of islet cell apoptosis. However, there is still considerable controversy about the tissue distribution of GPR120 and, in particular, it remains unclear which islet cell types express this molecule. In the present study, we have addressed this issue by constructing a Gpr120-knockout/ß-galactosidase (LacZ) knock-in (KO/KI) mouse to examine the distribution and functional role of GPR120 in the endocrine pancreas. METHODS: A KO/KI mouse was generated in which exon 1 of the Gpr120 gene (also known as Ffar4) was replaced in frame by LacZ, thereby allowing for regulated expression of ß-galactosidase under the control of the endogenous GPR120 promoter. The distribution of GPR120 was inferred from expression studies detecting ß-galactosidase activity and protein production. Islet hormone secretion was measured from isolated mouse islets treated with selective GPR120 agonists. RESULTS: ß-galactosidase activity was detected as a surrogate for GPR120 expression exclusively in a small population of islet endocrine cells located peripherally within the islet mantle. Immunofluorescence analysis revealed co-localisation with somatostatin suggesting that GPR120 is preferentially produced in islet delta cells. In confirmation of this, glucose-induced somatostatin secretion was inhibited by a range of selective GPR120 agonists. This response was lost in GPR120-knockout mice. CONCLUSIONS/INTERPRETATION: The results imply that GPR120 is selectively present within the delta cells of murine islets and that it regulates somatostatin secretion.

Combining evidence of preferential gene-tissue relationships from multiple sources.

An important challenge in drug discovery and disease prognosis is to predict genes that are preferentially expressed in one or a few tissues, i.e. showing a considerably higher expression in one tissue(s) compared to the others. Although several data sources and methods have been published explicitly for this purpose, they often disagree and it is not evident how to retrieve these genes and how to distinguish true biological findings from those that are due to choice-of-method and/or experimental settings. In this work we have developed a computational approach that combines results from multiple methods and datasets with the aim to eliminate method/study-specific biases and to improve the predictability of preferentially expressed human genes. A rule-based score is used to merge and assign support to the results. Five sets of genes with known tissue specificity were used for parameter pruning and cross-validation. In total we identify 3434 tissue-specific genes. We compare the genes of highest scores with the public databases: PaGenBase (microarray), TiGER (EST) and HPA (protein expression data). The results have 85% overlap to PaGenBase, 71% to TiGER and only 28% to HPA. 99% of our predictions have support from at least one of these databases. Our approach also performs better than any of the databases on identifying drug targets and biomarkers with known tissue-specificity.

Role of Escherichia coli curli operons in directing amyloid fiber formation.

Amyloid is associated with debilitating human ailments including Alzheimer's and prion diseases. Biochemical, biophysical, and imaging analyses revealed that fibers produced by Escherichia coli called curli were amyloid. The CsgA curlin subunit, purified in the absence of the CsgB nucleator, adopted a soluble, unstructured form that upon prolonged incubation assembled into fibers that were indistinguishable from curli. In vivo, curli biogenesis was dependent on the nucleation-precipitation machinery requiring the CsgE and CsgF chaperone-like and nucleator proteins, respectively. Unlike eukaryotic amyloid formation, curli biogenesis is a productive pathway requiring a specific assembly machinery.