Strategies for Molecular Classification of Asthma Using Bipartite Network Analysis of Cytokine Expression

Abstract

Asthma is a chronic inflammatory disease of the airways that leads to various degrees of recurrent respiratory symptoms affecting patients globally. Specific subgroups of asthma patients have severe disease leading to increased healthcare costs and socioeconomic burden. Despite the overwhelming prevalence of the asthma, there are limitations in predicting response to therapy and identifying patients who are at increased risk of morbidity. This syndrome presents with common clinical signs and symptoms; however, awareness of subgroups of asthma patients with distinct characteristics has surfaced in recent years. Investigators attempt to describe the phenotypes of asthma to ultimately assist with diagnostic and therapeutic applications. Approaches to asthma phenotyping are multifold; however, it can be partitioned into 2 essential groups, clinical phenotyping and molecular phenotyping. Innovative techniques such as bipartite network analysis and visual analytics introduce a new dimension of data analysis to identify underlying mechanistic pathways.

Demystifying the cytokine network: Mathematical models point the way

“…Several recent studies have examined these questions [98–104]. In a study of patients with asthma bipartite network analysis of patients and cytokines allowed the assignment of specific pathogenic mechanisms and cytokines to particular clinical subgroups [102]. Bipartite networks use two sets of nodes and the edges can only connect nodes from different sets.…”

Introduction to Asthma and Phenotyping

“…Although there are several approaches to asthma phenotyping in the literature, clinical phenotyping and molecular phenotyping remain the two most productive approaches (Wenzel 2012 ). The goals of phenotyping are multifold, including forecasting the clinical course, predicting response to therapy, identifying subgroups at risk for adverse events and other complications, and reducing clinical heterogeneity in clinical trials (Pillai et al 2012 ).…”

“…Clinical phenotypes attempt to provide reproducible groupings of patients based observed signs and symptoms, combined with testing carried out as part of usual clinical care, and as such is most commonly an observational approach. Clinical phenotyping focuses on the observed clinical presentation including response to therapy, known inherent characteristics such as weight and sex, and outcomes of diagnostics tests to classify patients into subgroups (Pillai et al 2012 ). In the clinical arena, a patient's "phenotype" describes prominent observed characteristics that arise from gene expression and, importantly, can be infl uenced by environmental elements.…”

“…In contrast, molecular phenotyping looks beyond the visualized presentation and categorizes patients at a molecular level with an emphasis on the genetic makeup, infl ammatory pathways, and signaling mechanisms (Pillai et al 2012 ;Wenzel et al 1999 ). Using these approaches, researchers have made much progress in understanding the mechanistic pathways in asthma that may govern the expression of asthma in heterogeneous groups of patients.…”

“…One can consider a phenotype that is dependent on a specifi c environmental factor (allergen, virus, controller medication) to be an "induced phenotype": that is, a phenotype not expressed unless the environmental factor is present. This "induced phenotype" is important to recognize as it represents the clinical phenotype in the presence of therapy or other modifying factors (Pillai et al 2012 ). The degree to which the clinical-induced phenotypes may inform mechanistic understanding and predict therapeutic responses is not currently known, but is an area of active research at present.…”