Identification of airway mucosal type 2 inflammation by using clinical biomarkers in asthmatic patients.

BACKGROUND: The Airways Disease Endotyping for Personalized Therapeutics (ADEPT) study profiled patients with mild, moderate, and severe asthma and nonatopic healthy control subjects. OBJECTIVE: We explored this data set to define type 2 inflammation based on airway mucosal IL-13-driven gene expression and how this related to clinically accessible biomarkers. METHODS: IL-13-driven gene expression was evaluated in several human cell lines. We then defined type 2 status in 25 healthy subjects, 28 patients with mild asthma, 29 patients with moderate asthma, and 26 patients with severe asthma based on airway mucosal expression of (1) CCL26 (the most differentially expressed gene), (2) periostin, or (3) a multigene IL-13 in vitro signature (IVS). Clinically accessible biomarkers included fraction of exhaled nitric oxide (Feno) values, blood eosinophil (bEOS) counts, serum CCL26 expression, and serum CCL17 expression. RESULTS: Expression of airway mucosal CCL26, periostin, and IL-13-IVS all facilitated segregation of subjects into type 2-high and type 2-low asthmatic groups, but in the ADEPT study population CCL26 expression was optimal. All subjects with high airway mucosal CCL26 expression and moderate-to-severe asthma had Feno values (≥35 ppb) and/or high bEOS counts (≥300 cells/mm3) compared with a minority (36%) of subjects with low airway mucosal CCL26 expression. A combination of Feno values, bEOS counts, and serum CCL17 and CCL26 expression had 100% positive predictive value and 87% negative predictive value for airway mucosal CCL26-high status. Clinical variables did not differ between subjects with type 2-high and type 2-low status. Eosinophilic inflammation was associated with but not limited to airway mucosal type 2 gene expression. CONCLUSION: A panel of clinical biomarkers accurately classified type 2 status based on airway mucosal CCL26, periostin, or IL-13-IVS gene expression. Use of Feno values, bEOS counts, and serum marker levels (eg, CCL26 and CCL17) in combination might allow patient selection for novel type 2 therapeutics.

Validated and longitudinally stable asthma phenotypes based on cluster analysis of the ADEPT study.

BACKGROUND: Asthma is a disease of varying severity and differing disease mechanisms. To date, studies aimed at stratifying asthma into clinically useful phenotypes have produced a number of phenotypes that have yet to be assessed for stability and to be validated in independent cohorts. The aim of this study was to define and validate, for the first time ever, clinically driven asthma phenotypes using two independent, severe asthma cohorts: ADEPT and U-BIOPRED. METHODS: Fuzzy partition-around-medoid clustering was performed on pre-specified data from the ADEPT participants (n = 156) and independently on data from a subset of U-BIOPRED asthma participants (n = 82) for whom the same variables were available. Models for cluster classification probabilities were derived and applied to the 12-month longitudinal ADEPT data and to a larger subset of the U-BIOPRED asthma dataset (n = 397). High and low type-2 inflammation phenotypes were defined as high or low Th2 activity, indicated by endobronchial biopsies gene expression changes downstream of IL-4 or IL-13. RESULTS: Four phenotypes were identified in the ADEPT (training) cohort, with distinct clinical and biomarker profiles. Phenotype 1 was "mild, good lung function, early onset", with a low-inflammatory, predominantly Type-2, phenotype. Phenotype 2 had a "moderate, hyper-responsive, eosinophilic" phenotype, with moderate asthma control, mild airflow obstruction and predominant Type-2 inflammation. Phenotype 3 had a "mixed severity, predominantly fixed obstructive, non-eosinophilic and neutrophilic" phenotype, with moderate asthma control and low Type-2 inflammation. Phenotype 4 had a "severe uncontrolled, severe reversible obstruction, mixed granulocytic" phenotype, with moderate Type-2 inflammation. These phenotypes had good longitudinal stability in the ADEPT cohort. They were reproduced and demonstrated high classification probability in two subsets of the U-BIOPRED asthma cohort. CONCLUSIONS: Focusing on the biology of the four clinical independently-validated easy-to-assess ADEPT asthma phenotypes will help understanding the unmet need and will aid in developing tailored therapies. TRIAL REGISTRATION: NCT01274507 (ADEPT), registered October 28, 2010 and NCT01982162 (U-BIOPRED), registered October 30, 2013.

Wnt10b inhibits obesity in ob/ob and agouti mice.

The Wnt family of secreted signaling molecules has profound effects on diverse developmental processes, including the fate of mesenchymal progenitors. While activation of Wnt signaling blocks adipogenesis, inhibition of endogenous Wnt/beta-catenin signaling by Wnt10b promotes spontaneous preadipocyte differentiation. Transgenic mice with expression of Wnt10b from the FABP4 promoter (FABP4-Wnt10b) have less adipose tissue when maintained on a normal chow diet and are resistant to diet-induced obesity. Here we demonstrate that FABP4-Wnt10b mice largely avert weight gain and metabolic abnormalities associated with genetic obesity. FABP4-Wnt10b mice do not gain significant body weight on the ob/ob background, and at 8 weeks of age, they have an approximately 70% reduction in visceral and subcutaneous adipose tissues compared with ob/ob mice. Similarly, on the lethal yellow agouti (A(y)) background, FABP4-Wnt10b mice have 50-70% less adipose tissue weight and circulating leptin at 5 months of age. Wnt10b-Ay mice are more glucose tolerant and insulin sensitive than A(y) controls, perhaps due to reduced expression and circulation of resistin. Reduced expression of inflammatory cytokines may also contribute to improved glucose homeostasis.

Inhaled Steroids and Active Smoking Drive Chronic Obstructive Pulmonary Disease Symptoms and Biomarkers to a Greater Degree Than Airflow Limitation.

RATIONALE: Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease, and development of novel therapeutics requires an understanding of pathophysiologic phenotypes. OBJECTIVES: The purpose of the Airways Disease Endotyping for Personalized Therapeutics (ADEPT) study was to correlate clinical features and biomarkers with molecular characteristics in a well-profiled COPD cohort. METHODS: A total of 67 COPD subjects (forced expiratory volume in the first second of expiration [FEV1]: 45%-80% predicted) and 63 healthy smoking and nonsmoking controls underwent multiple assessments including patient questionnaires, lung function, and clinical biomarkers including fractional exhaled nitric oxide (FENO), induced sputum, and blood. MEASUREMENTS AND MAIN RESULTS: The impact of inhaled corticosteroids (ICSs), and to a lesser extent current smoking, was more associated with symptom control, exacerbation rates, and clinical biomarkers, than severity by FEV1. The ICS-treated smoking subjects were most symptomatic, with significantly elevated scores on patient-reported outcomes and more annual exacerbations (P < .05). Inhaled corticosteroid users had greater airflow obstruction and air trapping compared with non-ICS users, regardless of smoking status. Smoking, regardless of ICS use, was associated with significantly lower FENO (P < .05). Smoking, in non-ICS users, was associated with an elevated proportion of sputum neutrophils and reduced sputum macrophages. Increased serum C-reactive protein was observed in smokers but not in ICS and nonsmoking ICS users (P < .05). In contrast, only air trapping and neutrophilic inflammation increased with severity, defined by postbronchodilator FEV1. CONCLUSIONS: Compared with COPD severity by FEV1, ICS use and current smoking were better determinants of clinical characteristics and biomarkers. Use of the ADEPT COPD data promises to prove useful in defining biological phenotypes to facilitate personalized therapeutic approaches.

Longitudinally Stable, Clinically Defined Clusters of Patients with Asthma Independently Identified in the ADEPT and U-BIOPRED Asthma Studies.

BACKGROUND: ADEPT (Airways Disease Endotyping for Personalized Therapeutics) and U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcome Consortium) are independent asthma biomarker studies that aim to enable personalization of therapies. METHODS: Patients in both studies were identified by similar criteria, and similar clinical parameters and biomarkers were assessed in blood, sputum, and airway samples. Fuzzy partition-around-medoid clustering was performed on the ADEPT dataset (n = 154) and independently on the U-BIOPRED asthma dataset (n = 82), filtered to match ADEPT inclusion criteria. For both studies, the same eight easily measurable clinical variables were used, and ADEPT also included methacholine airway hyperresponsiveness. Models for cluster classification probabilities were derived and applied to the 12-month longitudinal ADEPT data and the full U-BIOPRED adult asthma dataset (n = 397) as independent external validation. MEASUREMENTS AND MAIN RESULTS: Four clusters were identified in the ADEPT-asthma study population with distinct clinical and biomarker profiles. In general, Cluster 1 consists of patients with mild asthma not treated with steroids and well controlled with preserved lung function and a low-inflammatory phenotype; Cluster 2 is partially controlled, with mild airflow obstruction but severe airway hyperresponsiveness and a Th2 phenotype (brittle phenotype); Cluster 3 is partially controlled with mild airflow obstruction but reduced vital capacity, less bronchodilator reversibility, and a non-Th2 phenotype with neutrophilic inflammation (chronic obstructive pulmonary disease-like); and Cluster 4 is poorly controlled, with marked airflow obstruction, marked bronchodilator reversibility, and a mixed inflammatory phenotype. Overall, the ADEPT clusters were stable over 12 months and reproduced by identifying four analogous clusters in the U-BIOPRED asthma dataset, with distributions for most clustering and nonclustering variables similar to ADEPT. CONCLUSIONS: We report four clinical clusters in ADEPT and confirmed these by external validation in U-BIOPRED. The ADEPT clusters have distinct clinical and molecular characteristics, are stable over 12 months, and present opportunities for the development of tailored therapeutics for asthma.

Secreted frizzled-related protein 5 suppresses adipocyte mitochondrial metabolism through WNT inhibition.

Preadipocytes secrete several WNT family proteins that act through autocrine/paracrine mechanisms to inhibit adipogenesis. The activity of WNT ligands is often decreased by secreted frizzled-related proteins (SFRPs). Sfrp5 is strongly induced during adipocyte differentiation and increases in adipocytes during obesity, presumably to counteract WNT signaling. We tested the hypothesis that obesity-induced Sfrp5 expression promotes the development of new adipocytes by inhibiting endogenous suppressors of adipogenesis. As predicted, mice that lack functional SFRP5 were resistant to diet-induced obesity. However, counter to our hypothesis, we found that adipose tissue of SFRP5-deficient mice had similar numbers of adipocytes, but a reduction in large adipocytes. Transplantation of adipose tissue from SFRP5-deficient mice into leptin receptor-deficient mice indicated that the effects of SFRP5 deficiency are tissue-autonomous. Mitochondrial gene expression was increased in adipose tissue and cultured adipocytes from SFRP5-deficient mice. In adipocytes, lack of SFRP5 stimulated oxidative capacity through increased mitochondrial activity, which was mediated in part by PGC1α and mitochondrial transcription factor A. WNT3a also increased oxygen consumption and the expression of mitochondrial genes. Thus, our findings support a model of adipogenesis in which SFRP5 inhibits WNT signaling to suppress oxidative metabolism and stimulate adipocyte growth during obesity.

Loss of toll-like receptor 3 function improves glucose tolerance and reduces liver steatosis in obese mice.

OBJECTIVE: Emerging evidence suggests a link between innate immunity and development of type 2 diabetes mellitus (T2D); however, the molecular mechanisms linking them are not fully understood. Toll-like Receptor 3 (TLR3) is a pathogen pattern recognition receptor that recognizes the double-stranded RNA of microbial or mammalian origin and contributes to immune responses in the context of infections and chronic inflammation. The objective of this study was to determine whether TLR3 activity impacts insulin sensitivity and lipid metabolism. MATERIALS AND METHODS: Wild type (WT) and TLR3 knock-out (TLR3(-/-)) mice were fed a high fat diet (HFD) and submitted to glucose tolerance tests (GTTs) over a period of 33 weeks. In another study, the same group of mice was treated with a neutralizing monoclonal antibody (mAb) against mouse TLR3. RESULTS: TLR3(-/-) mice fed an HFD developed obesity, although they exhibited improved glucose tolerance and lipid profiles compared with WT obese mice. In addition, the increase in liver weight and lipid content normally observed in WT mice on an HFD was significantly ameliorated in TLR3(-/-) mice. These changes were accompanied by up-regulation of genes involved in cholesterol efflux such as PPARδ, LXRα, and LXRα-targeting genes and down-regulation of pro-inflammatory cytokine and chemokine genes in obese TLR3(-/-) mice. Furthermore, global gene expression profiling in liver demonstrated TLR3-specific changes in both lipid biosynthesis and innate immune response pathways. CONCLUSIONS: TLR3 affects glucose and lipid metabolism as well as inflammatory mediators, and findings in this study reveal a new role for TLR3 in metabolic homeostasis. This suggests antagonizing TLR3 may be a beneficial therapeutic approach for the treatment of metabolic diseases.