Phenotypic characteristics of complex diseases such as rheumatoid arthritis are a consequence of interactions of genetic and environmental factors. Biomolecules closely interact with other molecular components and form functional modules, resulting in significant biologic action capability. While traditional biochemical research focuses on a single disease using narrowly constrained data, systems biology aims to interpret large volumes of highly complex and multilevel data obtained from high-through-put technologies to understand how biological systems function as a whole. Such a systems approach to complex diseases, so-called network medicine, can shape our comprehensive understanding of disease mechanisms by identifying modules temporally and spatially perturbed in the context of health and diseases. Given the unmet needs for diagnosis, monitoring, and treatment in rheumatoid arthritis, systems biology is obviously an emerging powerful tool to gain insight into disease mechanisms, study comorbidities, analyze therapeutic drugs and their targets, and discover novel network-based biomarkers.