Amitabh Sharma1,2,3,†, Jörg Menche1,2,4,8,†, C. Chris Huang5, Tatiana Ort5, Xiaobo Zhou3, Maksim Kitsak1,2, Nidhi Sahni2, Derek Thibault3, Linh Voung3, Feng Guo3, Susan Dina Ghiassian1,2, Natali Gulbahce6, Frédéric Baribaud5, Joel Tocker5, Radu Dobrin5, Elliot Barnathan5, Hao Liu5, Reynold A. Panettieri Jr7, Kelan G. Tantisira3, Weiliang Qiu3, Benjamin A. Raby3, Edwin K. Silverman3, Marc Vidal2,9, Scott T. Weiss3 and Albert-László Barabási1,2,3,4,8,*
1Center for Complex Networks Research, Department of Physics, Northeastern University, Boston, MA 02115, USA, 2Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA, 3Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA, 4Department of Theoretical Physics, Budapest University of Technology and Economics, H1111, Budapest, Hungary, 5Janssen Research & Development, Inc., 1400 McKean Road, Spring House, PA 19477, USA, 6Department of Cellular and Molecular Pharmacology, University of California 1700, 4th Street, Byers Hall 308D, San Francisco, CA 94158, USA, 7Pulmonary Allergy and Critical Care Division, Department of Medicine, University of Pennsylvania, 125 South 31st Street, TRL Suite 1200, Philadelphia, PA 19104, USA, 8Center for Network Science, Central European University, Nador u. 9, 1051 Budapest, Hungary and 9Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
*To whom correspondence should be addressed at: Center for Complex Networks Research, Department of Physics, Northeastern University, Boston, MA 02115, USA. Email: email@example.com
Recent advances in genetics have spurred rapid progress towards the systematic identification of genes involved in complex diseases. Still, the detailed understanding of the molecular and physiological mechanisms through which these genes affect disease phenotypes remains a major challenge. Here, we identify the asthma disease module, i.e. the local neighborhood of the interactome whose perturbation is associated with asthma, and validate it for functional and pathophysiological relevance, using both computational and experimental approaches. We find that the asthma disease module is enriched with modest GWAS P-values against the background of random variation, and with differentially expressed genes from normal and asthmatic fibroblast cells treated with an asthma-specific drug. The asthma module also contains immune response mechanisms that are shared with other immune-related disease modules. Further, using diverse omics (genomics, gene-expression, drug response) data, we identify the GAB1 signaling pathway as an important novel modulator in asthma. The wiring diagram of the uncovered asthma module suggests a relatively close link between GAB1 and glucocorticoids (GCs), which we experimentally validate, observing an increase in the level of GAB1 after GC treatment in BEAS-2B bronchial epithelial cells. The siRNA knockdown of GAB1 in the BEAS-2B cell line resulted in a decrease in the NFkB level, suggesting a novel regulatory path of the pro-inflammatory factor NFkB by GAB1 in asthma.