Hui Wang

Our knowledge of global protein-protein interaction (PPI) networks in complex organisms such as humans is hindered by technical limitations of current methods. On the basis of short co-occurring polypeptide regions, we developed a tool called MP-PIPE capable of predicting a global human PPI network within 3 months. With a recall of 23% at a precision of 82.1%, we predicted 172,132 putative PPIs. We demonstrate the usefulness of these predictions through a range of experiments. The speed and accuracy associated with MP-PIPE can make this a potential tool to study individual human PPI networks (from genomic sequences alone) for personalized medicine.

Background: Translational research typically aims to identify and functionally validate individual, disease-specific genes. However, reaching this aim is complicated by the involvement of thousands of genes in common diseases, and that many of those genes are pleiotropic, that is, shared by several diseases. Methods: We integrated genomic meta-analyses with prospective clinical studies to systematically investigate the pathogenic, diagnostic and therapeutic roles of pleiotropic genes. In a novel approach, we first used pathway analysis of all published genome-wide association studies (GWAS) to find a cell type common to many diseases. Results: The analysis showed over-representation of the T helper cell differentiation pathway, which is expressed in T cells. This led us to focus on expression profiling of CD4⁺ T cells from highly diverse inflammatory and malignant diseases. We found that pleiotropic genes were highly interconnected and formed a pleiotropic module, which was enriched for inflammatory, metabolic and proliferative pathways. The general relevance of this module was supported by highly significant enrichment of genetic variants identified by all GWAS and cancer studies, as well as known diagnostic and therapeutic targets. Prospective clinical studies of multiple sclerosis and allergy showed the importance of both pleiotropic and disease specific modules for clinical stratification. Conclusions: In summary, this translational genomics study identified a pleiotropic module, which has key pathogenic, diagnostic and therapeutic roles.

Glucocorticoids (GCs) play a key role in the treatment of seasonal allergic rhinitis (SAR). However, some patients show a low response to GC treatment. We hypothesized that proteins that correlated to discrimination between symptomatic high and low responders (HR and LR) to GC treatment might be regulated by GCs and therefore suitable as biomarkers for GC treatment. We identified 953 nasal fluid proteins in symptomatic HR and LR with a LC MS/MS based-quantitative proteomics analysis and performed multivariate analysis to identify a combination of proteins that best separated symptomatic HR and LR. Pathway analysis showed that those proteins were most enriched in the acute phase response pathway. We prioritized candidate biomarkers for GC treatment based on the multivariate and pathway analysis. Next, we tested if those candidate biomarkers differed before and after GC treatment in nasal fluids from 40 patients with SAR using ELISA. Several proteins including ORM (Pacute phase response pathway decreased significantly in HR but not LR before and after GC treatment. We identified several novel biomarkers for GC treatment response in SAR with combined proteomics, multivariate and pathway analysis. The analytical principles may be generally applicable to identify biomarkers in clinical studies of complex diseases.

Glucocorticoids (GCs) may affect the expression of hundreds of genes in different cells and tissues from patients with intermittent allergic rhinitis (IAR). It is a formidable challenge to understand these complex changes by studying individual genes. In this study, we aimed to identify (i) pathways affected by local GC treatment and (ii) examine if those pathways could be used to find novel markers of local GC treatment in nasal fluids from patients with IAR. Gene expression microarray- and iTRAQ-based proteomic analyses of nasal fluids, nasal fluid cells and nasal mucosa from patients with IAR were performed to find pathways enriched for differentially expressed genes and proteins. Proteins representing those pathways were analyzed with ELISA in an independent material of nasal fluids from 23 patients with IAR before and after treatment with a local GC. Transcriptomal and proteomic high-throughput analyses of nasal fluids, nasal fluid cells and nasal mucosal showed that local GC treatment affected a wide variety of pathways in IAR such as the glucocorticoid receptor pathway and the acute phase response pathway. Extracellular proteins encoded by genes in those pathways were analyzed in an independent material of nasal fluids from patients. Proteins that changed significantly in expression included known biomarkers such as eosinophil cationic protein but also proteins that had not been previously described in IAR, namely CCL2, M-CSF, CXCL6 and apoH. Pathway-based analyses of genomic and proteomic high-throughput data can be used as a complementary approach to identify novel potential markers of GC treatment in IAR.

Summary: Background Previously, expression profiling has been used to analyse allergen‐challenged T‐helper type 2 cells, nasal biopsies and nasal fluid cells from patients with seasonal allergic rhinitis (SAR). Allergen‐challenged peripheral blood mononuclear cells (PBMCs) provide a human in vitro model of how antigen‐presenting cells, CD4⁺ T cells and effector cells such as basophils interact in allergic inflammation.Objective To identify novel genes and pathways in allergen‐challenged PBMCs from patients with SAR using gene expression profiling and functional studies.Methods PBMCs from 11 patients with SAR and 23 healthy controls were analysed with gene expression profiling. mRNA expression of IL17RB in basophils was evaluated using quantitative real‐time PCR. Membrane protein expression and apoptosis of basophils were examined by flow cytometry. Degranulation of basophils was assessed by measuring β‐hexosaminidase release. Cytokine release was measured using ELISA.Results Gene expression microarray analysis of allergen‐challenged PBMCs showed that 209 out of 44 000 genes were differentially expressed in patients compared with controls. IL17RB was the gene whose expression increased most in patients (PPIL17RB. Activation of IL‐17RB by its ligand, IL‐25, inhibited apoptosis of basophils. Moreover, IgE‐mediated degranulation was enhanced by IL‐25.Conclusion Increased expression of IL‐17RB on allergen‐challenged basophil is regulated by IL‐3, inhibits apoptosis and promotes IgE‐mediated degranulation of basophils. Cite this as: H. Wang, R. Mobini, Y. Fang, F. Barrenäs, H. Zhang, Z. Xiang and M. Benson, Clinical & Experimental Allergy, 2010 (40) 1194–1202.