Early Diagnosis of Sepsis: Is an Integrated Omics Approach the Way Forward?

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REVIEW ARTICLE

Early Diagnosis of Sepsis: Is an Integrated Omics Approach the Way Forward? Raymond J. Langley1 • Hector R. Wong2,3

Ó Springer International Publishing Switzerland 2017

Abstract Sepsis remains one of the leading causes of death in the USA and it is expected to get worse as the population ages. Moreover, the standard of care, which recommends aggressive treatment with appropriate antibiotics, has led to an increase in multiple drug-resistant organisms. There is a dire need for the development of new antibiotics, improved antibiotic stewardship, and therapies that treat the host response. Development of new sepsis therapeutics has been a disappointment as no drugs are currently approved to treat the various complications from sepsis. Much of the failure has been blamed on animal models that do not accurately reflect the course of the disease. However, recent improvements in metabolomic, transcriptomic, genomic, and proteomic platforms have allowed for a broad-spectrum look at molecular changes in the host response using clinical samples. Integration of these multi-omic datasets allows researchers to perform systems biology approaches to identify novel pathophysiology of the disease. In this review, we highlight what is currently known about sepsis and how integrative omics has identified new diagnostic and predictive models of sepsis as well as novel mechanisms. These changes may improve patient care as well as guide future preclinical analysis of sepsis. & Hector R. Wong [email protected] 1

Department of Pharmacology, University of South Alabama, Mobile, AL, USA

2

Division of Critical Care Medicine, Cincinnati Children’s Hospital Medical Center and Cincinnati Children’s Research Foundation, 3333 Burnet Avenue, Cincinnati, OH 45229, USA

3

Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA

Key Points Sepsis leads to high mortality and patient costs, yet there are few biomarkers that can accurately diagnose infections and predict patient outcomes. Integration of large molecular datasets can identify novel mechanisms of disease. The integrative analysis has highlighted the importance of mitochondrial function in predicting patient outcomes and regulating the innate and adaptive immune response.

1 Introduction Sepsis is now defined as a patient presenting with or developing a life-threatening organ dysfunction caused by a dysregulated host response to infection [1]. Globally, 20 million people will be treated in hospitals for sepsis and as many as 5 million of those patients will die each year [2]. Sepsis is a complex, heterogeneous syndrome with high mortality. Outcomes are influenced by the site of infection, causative organisms, acute organ dysfunctions, and co-morbidities [3, 4]. Precision medicine is founded on the concept that therapies can be customized based on the unique phenotypic and molecular features of each patient, and relies on enrichment strategies that can that can disentangle the patient heterogeneity and determine which intervention