Abstract
Sepsis is one of the most complex human diseases that continue to be associated with high mortality rates and substantial medical costs. It is an infection-induced, complex traits systemic syndrome that engages most of the bodys systems and organs. Whereas several etiologic agents can elicit sepsis, disease susceptibility, severity and therapeutic outcomes are modulated by a complex interaction of numerous environmental and constitutive (e.g., genomic) factors. To effectively understand and treat different types of sepsis in susceptible individuals, we need to adopt holistic systems approaches that utilize network-based investigations to integrate disease related complex traits, themselves affected by variations in the host genomic and epigenetic contexts, physiogenomic, metabolomic status as well as by variations in the pathogen. Importantly, a systems approach to sepsis can provide a roadmap to help identify both the host and the pathogen pathways underlying sepsis or variable therapeutic responses to sepsis. This paper introduces the emerging field of “septomics” – i.e., the application of high-throughput omics technologies to sepsis related complex traits - in diagnosing and/or modulating susceptibility and outcomes of sepsis. Additionally, we discuss how unbiased, network-based systems approaches and biotools can help better understand novel gene-by-environment interactions in sepsis, and identify genetic, physiologic and soluble (e.g., proteomics) biomarkers that can precisely predict disease susceptibility, progression or response to therapeutic interventions. Finally, we note that septomics also signals a new application of genome-based medicine in the context of global public health against existing and emerging infectious diseases that are greatly affecting the world populations in both developed and developing countries.
Keywords: Complex trait diseases, gene-environment interactions, physiome, sepsis, septomics, systems biology, systems genetics, translational medicine, personalized patient care