Genes and pathways contributing to obesity: a systems biology view

Systems biology is an expanding discipline that utilizes high-throughput data from multiple sources to develop models of biologic processes. This chapter reviews basic systems biology concepts and how they inform the traditional search for genes and pathways involved in disease pathogenesis. Systems approaches yield networks representing interactions and relationships among elements, with subnetworks or modules being functional groupings of these. For genetics of common disease-related traits such as obesity, integrative genetics is representative of a top-down systems biology approach, bringing together high-throughput genotyping, global tissue mRNA expression data, and phenotypic data. Coexpression network analysis yields network models that allow identification of groups of coexpressed genes that can be related to particular traits. Combining this with genetics has shown that genetic variation at disease associated loci act though influencing such modules. Constraint-based reconstruction of metabolic networks represents a bottom-up systems biology approach that can be utilized to model the effects of genetic variation. The progressively increasing ability to generate high-throughput data of various types will promote continued application of systems approaches to better understand the processes by which genetic variation influences disease-related traits.