A functional genomic model for predicting prognosis in idiopathic pulmonary fibrosis

Background: The course of disease for patients with idiopathic pulmonary fibrosis (IPF) is highly heterogeneous. Prognostic models rely on demographic and clinical characteristics and are not reproducible. Integrating data from genomic analyses may identify novel prognostic models and provide mechanistic insights into IPF. Methods: Total RNA of peripheral blood mononuclear cells was subjected to microarray profiling in a training (45 IPF individuals) and two independent validation cohorts (21 IPF/10 controls, and 75 IPF individuals, respectively). To identify a gene set predictive of IPF prognosis, we incorporated genomic, clinical, and outcome data from the training cohort. Predictor genes were selected if all the following criteria were met: 1) Present in a gene co-expression module from Weighted Gene Co-expression Network Analysis (WGCNA) that correlated with pulmonary function (p 1.5 and false discovery rate (FDR) < 2 %; and 3) Predictive of mortality (p < 0.05) in univariate Cox regression analysis. "Survival risk group prediction" was adopted to construct a functional genomic model that used the IPF prognostic predictor gene set to derive a prognostic index (PI) for each patient into either high or low risk for survival outcomes. Prediction accuracy was assessed with a repeated 10-fold cross-validation algorithm and independently assessed in two validation cohorts through multivariate Cox regression survival analysis. Results: A set of 118 IPF prognostic predictor genes was used to derive the functional genomic model and PI. In the training cohort, high-risk IPF patients predicted by PI had significantly shorter survival compared to those labeled as low-risk patients (log rank p < 0.001). The prediction accuracy was further validated in two independent cohorts (log rank p < 0.001 and 0.002). Functional pathway analysis revealed that the canonical pathways enriched with the IPF prognostic predictor gene set were involved in T-cell biology, including iCOS, T-cell receptor, and CD28 signaling. Conclusions: Using supervised and unsupervised analyses, we identified a set of IPF prognostic predictor genes and derived a functional genomic model that predicted high and low-risk IPF patients with high accuracy. This genomic model may complement current prognostic tools to deliver more personalized care for IPF patients

Bronchial thermoplasty in asthma: current perspectives

Balaji Laxmanan, D Kyle Hogarth Section of Pulmonary and Critical Care Medicine, University of Chicago Medicine, Chicago, IL, USA Abstract: Bronchial thermoplasty (BT) is a novel therapy for patients with severe asthma. Using radio frequency thermal energy, it aims to reduce the airway smooth muscle mass. Several clinical trials have demonstrated improvements in asthma-related quality of life and a reduction in the number of exacerbations following treatment with BT. In addition, recent data has demonstrated the long-term safety of the procedure as well as sustained improvements in rates of asthma exacerbations, reduction in health care utilization, and improved quality of life. Further study is needed to elucidate the underlying mechanisms that result in these improvements. In addition, improved characterization of the asthma subphenotypes likely to exhibit the largest clinical benefit is a critical step in determining the precise role of BT in the management of severe asthma. Keywords: bronchial thermoplasty, severe asthma, airway smooth muscl

Focusing on volatility information instead of portfolio weights as an aid to investor decisions

When faced with the challenge of forming a portfolio containing a risky and a risk-free asset, investors tend to apply the same portfolio weights independently of the volatility of the risky asset. This “percentage heuristic” can lead to different levels of portfolio risk when the same investor is presented with a more or a less risky asset. Using four experiments, we show that asking investors to choose the return distribution for their portfolio while keeping the exact portfolio weights unknown leads to greater similarity in levels of portfolio volatility (across different levels of risk of the risky asset) than asking investors to choose this distribution while additionally facing the portfolio weights. Higher consistency in risk taking is obtained both between and within test subjects

The prevalence of alpha-1 antitrypsin deficiency in Ireland

<p>Abstract</p> <p>Background</p> <p>Alpha-1 antitrypsin deficiency (AATD) results from mutations in the SERPINA1 gene and classically presents with early-onset emphysema and liver disease. The most common mutation presenting with clinical evidence is the Z mutation, while the S mutation is associated with a milder plasma deficiency. AATD is an under-diagnosed condition and the World Health Organisation recommends targeted detection programmes for AATD in patients with chronic obstructive pulmonary disease (COPD), non-responsive asthma, cryptogenic liver disease and first degree relatives of known AATD patients.</p> <p>Methods</p> <p>We present data from the first 3,000 individuals screened following ATS/ERS guidelines as part of the Irish National Targeted Detection Programme (INTDP). We also investigated a DNA collection of 1,100 individuals randomly sampled from the general population. Serum and DNA was collected from both groups and mutations in the SERPINA1 gene detected by phenotyping or genotyping.</p> <p>Results</p> <p>The Irish National Targeted Detection Programme identified 42 ZZ, 44 SZ, 14 SS, 430 MZ, 263 MS, 20 IX and 2 rare mutations. Analysis of 1,100 randomly selected individuals identified 113 MS, 46 MZ, 2 SS and 2 SZ genotypes.</p> <p>Conclusion</p> <p>Our findings demonstrate that AATD in Ireland is more prevalent than previously estimated with Z and S allele frequencies among the highest in the world. Furthermore, our targeted detection programme enriched the population of those carrying the Z but not the S allele, suggesting the Z allele is more important in the pathogenesis of those conditions targeted by the detection programme.</p