Athula Herath

Elevated Sputum Interleukin-5 and Submucosal Eosinophilia in Obese Individuals with Severe Asthma

RATIONALE The relationship between airway inflammation and obesity in severe asthma is poorly understood. OBJECTIVES We sought to determine the relationship between sputum mediator profiles and the distribution of eosinophilic inflammation and obesity in people with severe asthma. METHODS Clinical parameters and eight mediators in sputum were assessed in 131 subjects with severe asthma from a single center categorized into lean, overweight, and obese groups defined by their body mass index. In an independent group of people with severe asthma (n = 45) and healthy control subjects (n = 19) eosinophilic inflammation was enumerated in bronchial submucosa, blood, and sputum and related to their body mass index. MEASUREMENTS AND MAIN RESULTS Sputum IL-5 geometric mean (95% confidence interval) (pg/ml) was elevated in the obese (1.8 [1.2-2.6]) compared with overweight (1.1 [0.8-1.3]; P = 0.025) and lean (0.9 [0.6-1.2]; P = 0.018) subjects with asthma and was correlated with body mass index (r = 0.29; P < 0.001). There was no relationship among body mass index, the sputum cell count, or other sputum mediators. In the bronchoscopy group the submucosal eosinophil number in the subjects with asthma was correlated with body mass index (Spearman rank correlation, rs = 0.38; P = 0.013) and the median (interquartile range) number of submucosal eosinophils was increased in obese (19.4 [11.8-31.2]) (cells per square millimeter) versus lean subjects (8.2 [5.4-14.6]) (P = 0.006). There was no significant association between sputum or peripheral blood eosinophil counts and body mass index. CONCLUSIONS Sputum IL-5 and submucosal eosinophils, but not sputum eosinophils, are elevated in obese people with severe asthma. Whether specific antieosinophilic therapy is beneficial, or improved diet and lifestyle in obese asthma has antiinflammatory effects beyond weight reduction, requires further study.

A micro RNA processing defect in rapidly progressing idiopathic pulmonary fibrosis

Background Idiopathic pulmonary fibrosis exhibits differential progression from the time of diagnosis but the molecular basis for varying progression rates is poorly understood. The aim of the present study was to ascertain whether differential miRNA expression might provide one explanation for rapidly versus slowly progressing forms of IPF. Methodology and Principal Findings miRNA and mRNA were isolated from surgical lung biopsies from IPF patients with a clinically documented rapid or slow course of disease over the first year after diagnosis. A quantitative PCR miRNA array containing 88 of the most abundant miRNA in the human genome was used to profile lung biopsies from 9 patients with rapidly progressing IPF, 6 patients with slowly progressing IPF, and 10 normal lung biopsies. Using this approach, 11 miRNA were significantly increased and 36 were significantly decreased in rapid biopsies compared with normal biopsies. Slowly progressive biopsies exhibited 4 significantly increased miRNA and 36 significantly decreased miRNA compared with normal lung. Among the miRNA present in IPF with validated mRNA targets were those with regulatory effects on epithelial-mesenchymal transition (EMT). Five miRNA (miR-302c, miR-423-5p, miR-210, miR-376c, and miR-185) were significantly increased in rapid compared with slow IPF lung biopsies. Additional analyses of rapid biopsies and fibroblasts grown from the same biopsies revealed that the expression of AGO1 and AGO2 (essential components of the miRNA processing RISC complex) were lower compared with either slow or normal lung biopsies and fibroblasts. Conclusion These findings suggest that the development and/or clinical progression of IPF might be the consequence of aberrant miRNA processing.

Targeting Interleukin-13 with Tralokinumab Attenuates Lung Fibrosis and Epithelial Damage in a Humanized SCID Idiopathic Pulmonary Fibrosis Model

The aberrant fibrotic and repair responses in the lung are major hallmarks of idiopathic pulmonary fibrosis (IPF). Numerous antifibrotic strategies have been used in the clinic with limited success, raising the possibility that an effective therapeutic strategy in this disease must inhibit fibrosis and promote appropriate lung repair mechanisms. IL-13 represents an attractive target in IPF, but its disease association and mechanism of action remains unknown. In the present study, an overexpression of IL-13 and IL-13 pathway markers was associated with IPF, particularly a rapidly progressive form of this disease. Targeting IL-13 in a humanized experimental model of pulmonary fibrosis using tralokinumab (CAT354) was found to therapeutically block aberrant lung remodeling in this model. However, targeting IL-13 was also found to promote lung repair and to restore epithelial integrity. Thus, targeting IL-13 inhibits fibrotic processes and enhances repair processes in the lung.

A statistician's perspective on biomarkers in drug development

Biomarkers play an increasingly important role in many aspects of pharmaceutical discovery and development, including personalized medicine and the assessment of safety data, with heavy reliance being placed on their delivery. Statisticians have a fundamental role to play in ensuring that biomarkers and the data they generate are used appropriately and to address relevant objectives such as the estimation of biological effects or the forecast of outcomes so that claims of predictivity or surrogacy are only made based upon sound scientific arguments. This includes ensuring that studies are designed to answer specific and pertinent questions, that the analyses performed account for all levels and sources of variability and that the conclusions drawn are robust in the presence of multiplicity and confounding factors, especially as many biomarkers are multidimensional or may be an indirect measure of the clinical outcome. In all of these areas, as in any area of drug development, statistical best practice incorporating both scientific rigor and a practical understanding of the situation should be followed. This article is intended as an introduction for statisticians embarking upon biomarker-based work and discusses these issues from a practising statisticians perspective with reference to examples.

A Novel Murine GITR Ligand Fusion Protein Induces Antitumor Activity as a Monotherapy That Is Further Enhanced in Combination with an OX40 Agonist

Purpose: To generate and characterize a murine GITR ligand fusion protein (mGITRL-FP) designed to maximize valency and the potential to agonize the GITR receptor for cancer immunotherapy. Experimental Design: The EC50 value of the mGITRL-FP was compared with an anti-GITR antibody in an in vitro agonistic cell–based reporter assay. We assessed the impact of dose, schedule, and Fc isotype on antitumor activity and T-cell modulation in the CT26 tumor model. The activity of the mGITRL-FP was compared with an agonistic murine OX40L-FP targeting OX40, in CT26 and B16F10-Luc2 tumor models. Combination of the mGITRL-FP with antibodies targeting PD-L1, PD-1, or CTLA-4 was analyzed in mice bearing CT26 tumors. Results: The mGITRL-FP had an almost 50-fold higher EC50 value compared with an anti-murine GITR antibody. Treatment of CT26 tumor-bearing mice with mGITRL-FP–mediated significant antitumor activity that was dependent on isotype, dose, and duration of exposure. The antitumor activity could be correlated with the increased proliferation of peripheral CD8+ and CD4+ T cells and a significant decrease in the frequency of intratumoral Tregs. The combination of mGITRL-FP with mOX40L-FP or checkpoint inhibitor antagonists enhanced antitumor immunity above that of monotherapy treatment. Conclusions: These results suggest that therapeutically targeting GITR represents a unique approach to cancer immunotherapy and suggests that a multimeric fusion protein may provide increased agonistic potential versus an antibody. In addition, these data provide, for the first time, early proof of concept for the potential combination of GITR targeting agents with OX40 agonists and PD-L1 antagonists. Clin Cancer Res; 23(13); 3416–27. ©2017 AACR.

A panel of biomarkers for disease severity in atopic dermatitis

A panel of biomarkers for disease severity in atopic dermatitis J. L. Thijs, S. Nierkens, A. Herath , C. A. F. Bruijnzeel-Koomen, E. F. Knol, B. Giovannone, M. S. de Bruin-Weller and D. Hijnen Department of Dermatology and Allergology, University Medical Center Utrecht, Utrecht, The Netherlands, U-DAIR and Laboratory of Translational Immunology, University Medical Center Utrecht, Utrecht, The Netherlands, MedImmune Biotech, Cambridge, UK and Department of Immunology, University Medical Center Utrecht, Utrecht, The Netherlands

Moving toward endotypes in atopic dermatitis: Identification of patient clusters based on serum biomarker analysis

Background Atopic dermatitis (AD) is a complex, chronic, inflammatory skin disease with a diverse clinical presentation. However, it is unclear whether this diversity exists at a biological level. Objective We sought to test the hypothesis that AD is heterogeneous at the biological level of individual inflammatory mediators. Methods Sera from 193 adult patients with moderate‐to‐severe AD (six area, six sign atopic dermatitis [SASSAD] score: geometric mean, 22.3 [95% CI, 21.3‐23.3] and 39.1 [95% CI, 37.5‐40.9], respectively) and 30 healthy control subjects without AD were analyzed for 147 serum mediators, total IgE levels, and 130 allergen‐specific IgE levels. Population heterogeneity was assessed by using principal component analysis, followed by unsupervised k‐means cluster analysis of the principal components. Results Patients with AD showed pronounced evidence of inflammation compared with healthy control subjects. Principal component analysis of data on sera from patients with AD revealed the presence of 4 potential clusters. Fifty‐seven principal components described approximately 90% of the variance. Unsupervised k‐means cluster analysis of the 57 largest principal components delivered 4 distinct clusters of patients with AD. Cluster 1 had high SASSAD scores and body surface areas with the highest levels of pulmonary and activation‐regulated chemokine, tissue inhibitor of metalloproteinases 1, and soluble CD14. Cluster 2 had low SASSAD scores with the lowest levels of IFN‐&agr;, tissue inhibitor of metalloproteinases 1, and vascular endothelial growth factor. Cluster 3 had high SASSAD scores with the lowest levels of IFN‐&bgr;, IL‐1, and epithelial cytokines. Cluster 4 had low SASSAD scores but the highest levels of the inflammatory markers IL‐1, IL‐4, IL‐13, and thymic stromal lymphopoietin. Conclusion AD is a heterogeneous disease both clinically and biologically. Four distinct clusters of patients with AD have been identified that could represent endotypes with unique biological mechanisms. Elucidation of these endotypes warrants further investigation and will require future intervention trials with specific agents, such as biologics.

Sputum Inflammatory Mediators Are Increased in Aspergillus fumigatus Culture-Positive Asthmatics

Aspergillus fumigatus sensitization and culture in asthma are associated with disease severity and lung function impairment, but their relationship with airway inflammation is poorly understood. We investigated the profile of 24 sputum inflammatory mediators in A. fumigatus culture-positive or-negative moderate-to-severe asthmatics. Fifty-two subjects were recruited from a single center. A. fumigatus was cultured from 19 asthmatics. Asthma control, symptom score, lung function, and sputum cell count were not significantly different between the asthmatics with and without a positive A. fumigatus culture. All of the sputum mediators were numerically increased in subjects with a positive versus negative sputum A. fumigatus culture. Sputum TNF-R2 was significantly elevated (P=0.03) and the mediator that best distinguished A. fumigatus culture-positive from culture-negative subjects (receiver-operator characteristic area under the curve 0.66 [95% CI: 0.51 to 0.82, P=0.045]). A. fumigates-positive culture in moderate-to-severe asthma is associated with increased inflammatory sputum mediators.

Defining Phenotypes in Diabetic Nephropathy: a novel approach using a cross-sectional analysis of a single centre cohort

The global increase in Diabetes Mellitus (DM) has led to an increase in DM-Chronic Kidney Disease (DM-CKD). In this cross-sectional observational study we aimed to define phenotypes for patients with DM-CKD that in future may be used to individualise treatment We report 4 DM-CKD phenotypes in 220 patients recruited from Imperial College NHS Trust clinics from 2004–2012. A robust principal component analysis (PCA) was used to statistically determine clusters with phenotypically different patients. 163 patients with complete data sets were analysed: 77 with CKD and 86 with DM-CKD. Four different clusters were identified. Phenotypes 1 and 2 are entirely composed of patients with DM-CKD and phenotypes 3 and 4 are predominantly CKD (non-DM-CKD). Phenotype 1 depicts a cardiovascular phenotype; phenotype 2: microvascular complications with advanced DM-CKD; phenotype 3: advanced CKD with less anaemia, lower weight and HbA1c; phenotype 4: hypercholesteraemic, younger, less severe CKD. We are the first group to describe different phenotypes in DM-CKD using a PCA approach. Identification of phenotypic groups illustrates the differences and similarities that occur under the umbrella term of DM-CKD providing an opportunity to study phenotypes within these groups thereby facilitating development of precision/personalised targeted medicine.

Chemometrics and Predictive Modelling

The focus of this chapter is Chemometrics and Predictive Modelling. Chemometrics is a multivariate statistical methodology that has a parallel and independent path of development that grew out of the need to statistically analyse chemical measurements with moderate to large numbers of variables, especially in cases when there are more variables than samples (or objects). In recent years, more and more of the Chemometrics methods have been fused into the mainstream of multivariate and high dimensional statistics. In this chapter, we explore the methodological foundations of Chemometrics and supplement it with a motivating example for the reader to appreciate the methodology. We also provide a comprehensive reference list for the readers who may want to read more about Chemometric methods.