Abstract
Systems biology uses genome-scale data to determine the molecular mechanisms behind normal and disease states. We developed a novel computational method, which allowed for the first time, identification of a disease-associated signature across multiple tissues and organs in systemic sclerosis (SSc), a rare and sometimes fatal autoimmune disease. We find a common immune-fibrotic axis associated with the most severe disease phenotypes, including pulmonary fibrosis and pulmonary arterial hypertension. We evaluated disease-associated gene-gene interactions in the context of tissue-specific functional genomic networks and utilized differential network analysis to gain important insights into the role of pro-fibrotic macrophages in SSc. Using a novel cell type-aware multi-network approach, we find that genes modulated by immunosuppressive treatment occupy privileged positions in the skin-specific network. In total, this study not only presents a set of putative therapeutic targets for SSc, but a framework for multi-tissue functional genomic studies of complex human disease.