A Network Modeling Approach to Analysis of the Th2 Memory Responses Underlying Human Atopic Disease

Abstract

Complex cellular functions within immunoinflammatory cascades are conducted by networks of interacting genes. In this study, we employed a network modeling approach to dissect and interpret global gene expression patterns in allergeninduced Th cell responses that underpin human atopic disease. We demonstrate that a subnet of interconnected genes enriched for Th2 and regulatory T cell-associated signatures plus many novel genes is hardwired into the atopic response and is a hallmark of atopy at the systems level. We show that activation of this subnet is stabilized via hyperconnected "hub" genes, the selective disruption of which can collapse the entire network in a comprehensive fashion. Finally, we investigated gene expression in different Th cell subsets and show that regulatory T cell-and Th2-associated signatures partition at different stages of Th memory cell differentiation. Moreover, we demonstrate the parallel presence of a core element of the Th2-associated gene signature in bystander naive cells, which can be reproduced by rIL-4. These findings indicate that network analysis provides significant additional insight into atopic mechanisms beyond that achievable with conventional microarray analyses, predicting functional interactions between novel genes and previously recognized members of the allergic cascade. This approach provides novel opportunities for design of therapeutic strategies that target entire networks of genes rather than individual effector molecules. The Journal of Immunology, 2009, 182: 6011-6021.T he general concept that complex immunological diseases such as atopy are driven via integrated pathways or molecular cascades has been accepted dogma for more than two decades. The approaches to identification of relevant cascade members and in particular those that are rate limiting in the disease process driven by the cascade have not evolved greatly over this period, and they generally focus on candidate effector or regulator molecules selected stepwise on the basis of their known effector functions and their potential interactions with other perceived pathogenic factors. However, the level of clinical efficacy achieved with therapies designed to target simple linear pathways or causal chains has been disappointing (1, 2).The development of global gene expression profiling technologies has provided opportunities for new approaches to the same problem. The conceptual leap of principal interest in this context comes from the way in which these data are analyzed, in particular the emergence of quantitative algorithms based on network theory (3). This new approach enables a systems-level characterization of the networks of interacting genes that underpin cellular function and behavior, unearthing pathways at the core of disease processes.A fundamental organizing principle of gene networks is their scale-free topology, meaning that network connectivity is dominated by a few centralized genes designated "hubs", which are hyperconnected to a larger number of peripheral genes with few connections...

MicroRNAs act complementarily to regulate disease-related mRNA modules in human diseases

“…Since allergen induces altered expression of immune-related proteins in CD4+ T cells from both patients and healthy controls (Akdis et al 2004;Bosco et al 2009), we hypothesized that miRNAs would change in both patients and controls. Indeed, 199 miRNAs were differentially expressed in patients and 77 miRNAs in controls (fold change ≥1.5, P < 0.05).…”

“…Unlike in most complex diseases, in SAR it is possible to mimic the disease process by obtaining CD4+ T cells outside of the pollen season, when the patients are asymptomatic, and challenge in vitro with pollen or diluent. Thus, it is possible to identify disease-specific changes by comparing expression differences from allergen-and diluent-challenged cells from patients with those observed in controls (Benson et al 2006a;Bosco et al 2009). This comparison will henceforth be referred to as a delta-delta (ΔΔ) expression analysis.…”

A synonymous variation in protease-activated receptor-2 is associated with atopy in Korean children

“…[5][6][7] Little is known about the specific genes associated with susceptibility to atopy, but genes identified to be associated with atopy thus far tend to be involved in allergic responses or the immune system. [8][9][10] Protease-activated receptors (PARs) are G protein-coupled 7-transmembrane domain receptors that can be activated by serine proteases via proteolytic cleavage. 11 Recent evidence suggests that the activation of PARs plays an important role in the inflammatory response and immunological reactions.…”

Decreased Activation Of Inflammatory Networks During Acute Asthma Exacerbations Is Associated With Chronic Airflow Obstruction

“…A holistic approach was employed to analyse the microarray data, based on reverse engineering gene network analysis. [26][27][28] The mechanics of the network analysis algorithm are detailed in Methods; briefly, the algorithm employs a stepwise analytical process to interrogate variations in gene coexpression patterns across all the samples to identify subnets of coexpressed genes or modules. These modules contain the molecular components that execute biological functions and underpin physiological and diseased states.26-28 As illustrated in Figure 1A, network analysis of exacerbation responses in sputum identified twelve modules of coexpressed genes.…”