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1.  Genomic-Based High Throughput Screening Identifies Small Molecules That Differentially Inhibit the Antiviral and Immunomodulatory Effects of IFN-α 
Molecular Medicine  2008;14(7-8):374-382.
Multiple lines of evidence suggest that inhibition of Type I Interferons, including IFN-α, may provide a therapeutic benefit for autoimmune diseases. Using a chemical genomics approach integrated with cellular and in vivo assays, we screened a small compound library to identify modulators of IFN-α biological effects. A genomic fingerprint was developed from both ex vivo patient genomic information and in vitro gene modulation from IFN-α cell-based stimulation. A high throughput genomic-based screen then was applied to prioritize 268 small molecule inhibitors targeting 41 different intracellular signaling pathways. Active compounds were profiled further for their ability to inhibit the activation and differentiation of human monocytes using disease-related stimuli. Inhibitors targeting NF-κB or Janus Kinase/Signal Transducer and Activator of Transcription (JAK/STAT) signaling emerged as “dissociated inhibitors” because they did not modulate IFN-α anti-viral effects against HSV-1 but potently inhibited other immune-related functions. This work describes a novel strategy to identify small molecule inhibitors for the treatment of autoimmune disorders.
doi:10.2119/2008-00028.Chen
PMCID: PMC2376640  PMID: 18475307
2.  Gene-environment interactions in chronic obstructive pulmonary disease 
Chronic obstructive pulmonary disease (COPD) is one of the leading causes of death throughout the world and is largely associated with cigarette smoking. Despite the appreciation of the central role of smoking in the development of COPD, only a relatively small number of smokers (15%–20%) develop COPD. Recent studies depicting familial aggregation suggest that some subjects may have a genetic predisposition to developing COPD. In this respect, a number of single nucleotide polymorphisms have been reported in association with different COPD features (subphenotypes), although much of this data remains controversial. Classical genetic studies (including twin and family studies) assume an “equal-environment” scenario, but as gene-environment interactions occur in COPD, this assumption needs revision. Thus, new integrated models are needed to examine the major environmental factors associated with COPD which include smoking as well as air pollution, and respiratory infections, and not only genetic predisposition. Revisiting this area, may help answer the question of what has more bearing in the pathogenesis of COPD—the environment or the genomic sequence of the affected subjects. It is anticipated that an improved understanding of this interaction will both enable improved identification of individuals susceptible to developing this disease, as well as improved future treatments for this disease.
PMCID: PMC2629985  PMID: 18990979
chronic obstructive pulmonary disease; environment; genomics; pathogenesis
3.  In Vivo-to-In Silico Iterations to Investigate Aeroallergen-Host Interactions 
PLoS ONE  2008;3(6):e2426.
Background
Allergic asthma is a complex process arising out of the interaction between the immune system and aeroallergens. Yet, the relationship between aeroallergen exposure, allergic sensitization and disease remains unclear. This knowledge is essential to gain further insight into the origin and evolution of allergic diseases. The objective of this research is to develop a computational view of the interaction between aeroallergens and the host by investigating the impact of dose and length of aeroallergen exposure on allergic sensitization and allergic disease outcomes, mainly airway inflammation and to a lesser extent lung dysfunction and airway remodeling.
Methods and Principal Findings
BALB/C mice were exposed intranasally to a range of concentrations of the most pervasive aeroallergen worldwide, house dust mite (HDM), for up to a quarter of their lifespan (20 weeks). Actual biological data delineating the kinetics, nature and extent of responses for local (airway inflammation) and systemic (HDM-specific immunoglobulins) events were obtained. Mathematical equations for each outcome were developed, evaluated, refined through several iterations involving in vivo experimentation, and validated. The models accurately predicted the original biological data and simulated an extensive array of previously unknown responses, eliciting two- and three-dimensional models. Our data demonstrate the non-linearity of the relationship between aeroallergen exposure and either allergic sensitization or airway inflammation, identify thresholds, behaviours and maximal responsiveness for each outcome, and examine inter-variable relationships.
Conclusions
This research provides a novel way to visualize allergic responses in vivo and establishes a basic experimental platform upon which additional variables and perturbations can be incorporated into the system.
doi:10.1371/journal.pone.0002426
PMCID: PMC2409221  PMID: 18545674

Results 1-3 (3)