New approaches to sepsis: molecular diagnostics and biomarkers

Abstract

Sepsis is among the most common causes of death in hospitals. It arises from the host response to infection. Currently, diagnosis relies on nonspecific physiological criteria and culture-based pathogen detection. This results in diagnostic uncertainty, therapeutic delays, the mis- and overuse of antibiotics, and the failure to identify patients who might benefit from immunomodulatory therapies. There is a need for new sepsis biomarkers that can aid in therapeutic decision making and add information about screening, diagnosis, risk stratification, and monitoring of the response to therapy. The host response involves hundreds of mediators and single molecules, many of which have been proposed as biomarkers. It is, however, unlikely that one single biomarker is able to satisfy all the needs and expectations for sepsis research and management. Among biomarkers that are measurable by assays approved for clinical use, procalcitonin (PCT) has shown some usefulness as an infection marker and for antibiotic stewardship. Other possible new approaches consist of molecular strategies to improve pathogen detection and molecular diagnostics and prognostics based on transcriptomic, proteomic, or metabolic profiling. Novel approaches to sepsis promise to transform sepsis from a physiologic syndrome into a group of distinct biochemical disorders and help in the development of better diagnostic tools and effective adjunctive sepsis therapies.

Figures

Fig 1

The inflammatory response. This simplified overview shows the course of the inflammatory response. An insult triggers the release of PAMPs (pathogen-associated molecular patterns) and/or DAMPs (danger-associated molecular patterns), which are sensed by pattern recognition mechanisms such as receptors (pattern recognition receptors (PRRs) on the cell surface or within the cytosol or nucleus of sensor cells as well as by pattern-recognizing complex systems such as the complement system and others. Therefore, sensors can be different types of cells, tissues/organs, or proteins/other molecules, which themselves may function as effectors to modulate the immune response through various different pro- or anti-inflammatory mediators or biomarkers. As a result, the underlying insult can be cleared or not, and organ function may be temporarily or permanently impaired. LPS, lipopolysaccharide (part of the membrane of Gram-negative bacteria); LTA, lipoteichoic acid (part of the cell wall of Gram-positive bacteria); HMGB1, high-mobility-group protein B1; C5a and C3a, complement components 5a and 3a; C5aR, C5a receptor protein; C5b-9, terminal complement complex; aPPT, activated partial thromboplastin time; PT, prothrombin time; AT, antithrombin; ELAM-1, endothelial leukocyte adhesion molecule 1; ICAM-1, intercellular adhesion molecule 1; CRP, C-reactive protein; LBP, LPS-binding protein; PCT, procalcitonin; IL-6, interleukin-6; MIF, macrophage migration inhibitory factor; sTNF, soluble tumor necrosis factor; suPAR, soluble urokinase-type plasminogen activator receptor; sTREM-1, soluble triggering receptor expressed on myeloid cells 1; mHLA-DR, monocytic human leukocyte antigen DR; CD64 and CD48, integral membrane glycoproteins; DIC, disseminated intravascular coagulation.

Fig 2

Various possible courses of the immune response to severe sepsis and septic shock over 28 days. (A to D) Immune responses are displayed, with 1 being maximally proinflammatory and −1 being maximally anti-inflammatory. Dotted lines indicate a course leading to death. (E) Overlay of various possible immune response courses during sepsis and resulting aspects with respect to differences in phenotypes of the inflammatory response at various hypothetical time points.

Fig 3

Positivity rates and concordance of multiplex PCR and blood culture (BC) results from 27 published studies. The left two box plots indicate positive results (in percentages of blood samples); the right two box plots indicate the concordance of negative or positive paired samples (in percentages of all samples) or, with regard to isolates, the concordance of negative results and of identified isolates in paired samples (in percentages of the sum of isolates and negative results). Study data are given in Table 1. Box plots indicate the median, interquartile range, and 10th and 90th percentiles, and dots denote outlying single studies. A total of 7,814 samples/episodes were evaluated for positivity rates, 7,347 samples/episodes were evaluated for the concordance of BC and PCR results, and 6,586 samples/episodes were evaluated for the concordance of isolates (sum of isolates and BC-negative/PCR-negative sample pairs equals 6,847).