A Systems Perspective of Complex Diseases: From Reductionism to Integration

Complex systems exist across all levels of biological organization ranging from the simplest (subatomic realm) to most complex (individual organism to whole populations and beyond). This complex nature of both the common diseases and the human beings has kept researchers far from a holistic understanding of underlying biological processes. Over the past decade, there has been a rapid and vast accumulation of large scale high-throughput biological data at physiological, cellular, molecular, and submolecular levels. It includes genetic association studies of complex human diseases and traits, quantification of genome-wide RNA expression patterns, comprehensive profiling of cellular proteins and metabolites, gene regulatory information (DNA methylation, histone modifications, chromatin accessibility, evolutionary constraint, etc.), and characterization of networks of molecular interactions. The clinical utility of such enormous data demands interpretation and understanding at the biological level to reveal mechanistic insights of molecular etiology. An important element of this task is to complement the detailed pieces of biological information with new advanced methods of system integration and reconstruction. This requires conversion of actual biological systems into computational models to make reliable predictions of biological responses following targeted manipulation under untested conditions. The frequency at which signals are presently being discovered mandates a systematic and integrative “omics” approach to bridge the “genotype to phenotype” gap. The chapter highlights the fundamental ways to integrate high-quality biological data that await systemic interpretations.