Biomarkers in Sepsis 2018 Critical Care Clinics
Biomarkers in Sepsis 2018 Critical Care Clinics
Biomarkers in Sepsis 2018 Critical Care Clinics
KEYWORDS
Sepsis Biomarkers Procalcitonin Omics technologies Transcriptomics
Diagnosis Prognosis
KEY POINTS
A biomarker is a characteristic by which a pathophysiologic process can be identified.
In the clinical setting, a biomarker needs to quickly assist physicians confronted with an ill
patient in their decision on the best possible treatment.
Biomarkers can be of diagnostic value, prognostic value, and in the future may be of thera-
nostic value.
The omics field of systems biology provides a promising tool for the discovery of novel
biomarkers.
Biomarkers, measured in simply obtainable samples with limited hands-on time or need
for specialized laboratories, may be the key to personalized targeted treatment in the
future clinical management of sepsis.
INTRODUCTION
fast kinetics, high sensitivity and specificity, can be identified by fully automated tech-
nology, has a short turnaround time, and is available as a point-of-care test with low
production costs.1 A biomarker therefore needs to quickly assist physicians con-
fronted with an ill patient in their decision on the best possible treatment. Current clin-
ical biomarkers can be roughly divided into 2 types: diagnostic and prognostic
markers (Fig. 1). Biomarkers that can discriminate sepsis from noninfectious critical
illness or can differentiate between causative organisms in sepsis can be regarded
as diagnostic biomarkers. A diagnostic biomarker can diminish improper use of anti-
biotics and could be used for antibiotic stewardship. Although pathogen detection re-
mains the gold standard in establishing the cause of infection, blood cultures are only
positive in 30% to 40% of the sepsis cases and in one-third of (clinically defined)
sepsis cases all cultures are sterile.4,5 In addition, the presence of a pathogen does
not prove the presence of disease and infections can be caused by multiple patho-
gens, further showing the need for biomarkers that indicate infection. Prognostic bio-
markers can help predict outcomes in patients with sepsis by assigning risk profiles. In
addition, biomarkers can aid in stratifying patients in subgroups based on specific
pathophysiologic features, thereby paving the way to personalized therapy with
biomarker-guided follow-up of response to treatment.6 The approach to using
biomarker tests to select and evaluate specific therapies is known as theranostics
and is seen as a main tool in the future management of many diseases.7 Such
biomarker tests should be applicable on easily obtained samples such as urine or
blood. Rapid testing should identify subgroups of patients that would benefit from
certain targeted therapies. The biomarker test could further be of use by evaluating
the effect of the therapy on its target.
Biomarkers have been implemented in clinical practice in various fields of medicine,
including cardiology (eg, troponin T in myocardial infarction), vascular medicine (eg,
D-dimer in patients suspected of pulmonary embolism), and in particular oncology
Fig. 1. What is a biomarker? Biomarkers are host characteristics, such as molecules or genes,
by which particular physiologic or pathologic processes can be identified. When developing
and validating novel biomarkers their potential clinical use is of utmost importance. Bio-
markers can be used to distinguish sepsis from noninfectious critical illness or to determine
causative pathogens to initiate the best possible treatment, thereby contributing to anti-
biotic stewardship. Furthermore, biomarkers can help stratify patients based on risk profiles,
and predict outcome or identify pathophysiologic pathways that can be the target for
personalized therapy. Biomarker tests that select and monitor specific therapies are known
as theranostics and are seen as a future aid for a targeted personalized approach in patients
with sepsis.
Biomarkers in Sepsis 141
Many protein biomarkers have been evaluated for their ability to discriminate between
sepsis and noninfectious conditions. In critical care, antibiotic therapy is almost invari-
ably initiated on (even modest) suspicion of infection. However, the infection diagnosis
in critically ill patients is likely overestimated. A recent study involving more than 2500
patients treated for sepsis on the intensive care unit (ICU) reported that 13% had a
post-hoc infection likelihood of none, and an additional 30% of only possible, as deter-
mined by well-defined criteria and making use of all clinical, radiological, and microbi-
ological information.16 Remarkably, patients who were initially treated for sepsis but
were post hoc determined to have noninfectious disease had higher mortality,16
thereby underlining the necessity for a diagnostic biomarker to correctly diagnose
sepsis.
By far the most studied biomarker, and the only biomarker that is currently imple-
mented in clinical sepsis guidelines, is PCT. PCT levels increase in response to a
proinflammatory stimulus. Because of the short time between stimulus and induction
of PCT (detectable after 4 hours, peak at 6 hours)17,18 and its long half-life of 25 to
30 hours,19 it is a widely investigated biomarker in sepsis. A recent meta-analysis
showed a pooled sensitivity of 0.77 (95% confidence interval [CI] 0.72–0.81) and a
pooled specificity of 0.79 (95% CI, 0.74–0.84) of PCT to distinguish between sepsis
and a systemic inflammatory response syndrome of noninfectious origin.20 Levels of
PCT between 0.1 and 0.5 ng/mL suggest the presence of bacterial infection for
which antimicrobial therapy is required,21 but no consensus has been reached about
the correct cutoff value for PCT in this decision making.20 Furthermore, PCT levels
associate with severity of illness in patients with severe pneumonia,22 and
decreasing PCT levels associate with improved survival rates.23 Likewise, in a pro-
spective observational study conducted in 858 patients with sepsis, inability to
decrease PCT level by greater than 80% from baseline to day 4 and day 28 was
an independent predictor of mortality.24 Although the use of PCT as a biomarker
for the diagnosis of sepsis is limited because PCT levels also increase in noninfec-
tious diseases, it differentiates better between infectious and noninfectious causes
of critical illness than C-reactive protein (CRP), lipopolysaccharide binding protein
(LBP), and interleukin (IL)-6.25
Different PCT algorithms have been developed to help decision making regarding
the start and duration of antibiotic treatment. In patients with acute respiratory infec-
tions the use of PCT algorithms reduces the initiation of antibiotic treatment (mostly in
primary care settings) and duration of antibiotic treatment (mostly in emergency de-
partments [EDs] and ICU settings) without affecting mortality.26 Similarly, a random-
ized controlled trial found a decrease of 4.5% in use of antibiotics without
differences in mortality, diagnostic procedures, or therapeutic procedures in patients
with severe sepsis or septic shock.27 In a prospective, multicenter, randomized
controlled, open-label intervention trial in 15 hospitals in the Netherlands involving
1575 patients, PCT guidance of antibiotic therapy, consisting of a nonbinding advice
to discontinue antibiotics if PCT concentration decreased by 80% or PCT levels were
less than 0.5 ng/mL, was associated with a reduced consumption of antibiotics and a
diminished mortality at 28 days (20% vs 27% in the standard-of-care group).12 This
finding suggests that PCT concentrations might assist in identifying bacterial infec-
tions, which may result in more adequate diagnosis and treatment.12 Another random-
ized controlled trial in critically ill patients, using a PCT algorithm wherein a 0.1-ng/mL
cutoff determined antibiotic cessation, found no reduction in duration of antibiotic
treatment.28 A recent investigation determined the use of PCT and associated out-
comes in the real-world clinical setting of ICUs in the United States.29 Among more
than 20,000 critically ill patients in 107 hospitals with PCT testing available, 18% of pa-
tients had PCT levels checked; in this population the use of PCT was not associated
with improved antibiotic use or other clinical outcomes.29 Hence, current data on the
use of PCT for antibiotic stewardship in critically ill patients with sepsis are not
consistent.
Examples of other well-studied protein biomarkers are CRP,30 LBP,31 IL-6,31 sol-
uble triggering receptor expressed on myeloid cells-1 (sTREM-1),32,33 and soluble
urokinase plasminogen activator receptor (suPAR),34 all with a lower sensitivity and
specificity as a biomarker for sepsis compared with PCT. The biggest potential of
PCT so far seems to be to help reduce exposure to antibiotics in patients with acute
respiratory infections and perhaps as a stimulant to physicians to safely reduce the
duration of antibiotic treatment in critically ill patients with presumed bacterial
Biomarkers in Sepsis 143
infection. Nonetheless, PCT cannot be used as a single diagnostic test for sepsis,
because false-negative results could lead to mortality. Considering the weak evi-
dence for the use of PCT in clinical settings, the Surviving Sepsis Campaign guide-
lines stress the point that a clinical decision to initiate, alter, or stop antimicrobial
treatment should never be based solely on changes in any current biomarker,
including PCT.11
Considering the huge potential of biomarkers for personalized medicine in sepsis, the
search for biomarkers has shifted focus from traditional protein and cytokine markers
to systems-based approaches. The omics field of systems biology seeks to charac-
terize and quantify molecules that translate in the structure, function, and dynamics
of an organism. Omics encompasses genomics, epigenetics, transcriptomics, prote-
omics, and metabolomics (Fig. 3). Omics-based methodologies have developed into
more feasible and less costly tools35 and are increasingly used to study host-pathogen
interactions,36 the host response, and biomarkers in sepsis.37 Traditional biomarkers
or sets of biomarkers measure the concentration of circulating proteins, but the rapidly
growing field of systems biology integrates and analyses complex data sets of various
aspects of host signaling and response pathways. In this respect, transcriptomics has
been studied most. The use of RNA molecules as biomarkers has the advantage that
these can be incorporated in polymerase chain reaction–based bedside tests with
limited or no hands-on time, making them attractive for implementation in clinical
practice. Such tests could measure a set of RNA biomarkers concurrently, which is
likely to improve sensitivity and specificity. Several publications on traditional protein
biomarkers have indicated that sets of host proteins are superior to single biomarkers
to diagnose sepsis.13,15
RNA Biomarkers
The genomic response to sepsis shows alterations in the transcriptome of peripheral
white blood cells with significant differences of their RNA transcripts compared with
healthy individuals.7 Several investigations have reported on the ability of host tran-
scriptome analyses to discriminate between infection and noninfectious acute dis-
ease, and even between different causative pathogens38 (Fig. 4). Among these
diagnostic RNA biomarkers the molecular host response classifier SeptiCyte LAB
was recently approved by the US Food and Drug Administration as an aid in differen-
tiating infection-positive (sepsis) from infection-negative systemic inflammation in crit-
ically ill patients on their first day of ICU admission.39 This 4-gene classifier combines
CEACAM4, LAMP1, PLA2G7, and PLAC8 to produce a summary area under the
receiver operating characteristic (ROC) curve (AUC) of 0.89 (95% CI, 0.85–0.93) to
differentiate sepsis from noninfectious systemic inflammatory response syndrome.40
This rapid molecular assay is the first RNA-based clinical diagnostic tool derived
from whole blood approved as a diagnostic test in critically ill patients.40 Another
investigation, performed in a large number of independent cohorts, reported an
11-gene biomarker, named the Sepsis MetaScore, that could reliably distinguish pa-
tients with sepsis from patients with sterile inflammation41 with an AUC of 0.87 (range,
0.70–0.98). Furthermore, a recent study, using genome-wide messenger RNA (mRNA)
expression profiles, identified a set panel of markers composed of 3 upregulated tran-
scripts (Toll-like receptor 5, protectin, and clusterin) and 4 downregulated transcripts
(fibrinogenlike 2, IL-7 receptor, major histocompatibility complex class II, carboxypep-
tidase, and vitellogeniclike) that best described the extent of immune alterations.42 A
gene expression score was created that was greater in patients with definite as well as
with possible/probable infection than in those without infection.42 Our group focused
on the development of context-specific molecular biomarkers; that is, in patients with
a particular clinical presentation, such as suspected community-acquired pneumonia
(CAP).43 We compared whole-genome mRNA profiles in blood leukocytes of patients
treated for suspected CAP on ICU admission, who were designated CAP (cases) and
no-CAP patients (control subjects) by post-hoc assessment. A 78-gene signature was
defined for the diagnosis of CAP, from which a FAIM3:PLAC8 gene expression ratio
was derived that outperformed plasma PCT in discriminating between CAP and no-
CAP patients.43 Moreover, other groups have evaluated the FAIM3:PLAC8 score in
the context of all-cause adult, pediatric, and neonatal sepsis with favorable ROC
AUCs.44,45 This finding indicates that, although the FAIM3:PLAC8 score was derived
as a context-specific biomarker (ie, CAP diagnosis), its applicability may be broad-
ened. These studies have shown that transcriptomics coupled with sophisticated ma-
chine learning and statistical tests may provide an invaluable tool to identify diagnostic
biomarkers of sepsis.
Several studies have indicated that host gene expression signatures can assist in
discriminating between causative pathogens in infected patients. In an observational
cohort study in adults presenting to the ED, host gene expression profiling was used to
classify the cause of suspected community-acquired acute respiratory tract infections
(ARIs) into bacterial, viral, or noninfectious origin. The overall accuracy of gene expres-
sion classifiers was 87%, which was significantly better than the use of procalcitonin,
which could assign patients as having bacterial ARI or nonbacterial ARI with 78% ac-
curacy.46 Furthermore, transcriptional profiling of blood leukocytes from hospitalized
patients with lower respiratory tract infections was superior in differentiating bacterial
from viral causes compared with the use of PCT.47 Transcriptome analyses of blood
leukocytes of adult ICU patients with influenza A pneumonia, bacterial pneumonia,
Biomarkers in Sepsis 145
Fig. 4. Host signatures as molecular biomarkers using omics technologies. Using omics-
based methodologies, various host signatures can be determined in an integrated systems
biology approach aiding the development of targeted therapies. This article describes
several molecular biomarkers with diagnostic value (eg, discriminating infectious from
noninfectious critically ill patients or distinguishing between causative pathogens) and
prognostic value (eg, stratifying patients in risk groups correlating with outcome measures
such as mortality). The key is to identify omic biomarkers unique for a certain scenario. An
ideal biomarker can quickly assist physicians confronted with an ill patient in the decision on
the best possible treatment.
146 van Engelen et al
FUTURE PERSPECTIVES
The clinical use of biomarkers in sepsis is still at its infancy, especially compared with
other fields such as vascular medicine and oncology. Thus far, biomarker research in
sepsis has primarily focused on discrimination between infectious and noninfectious
causes of critical illness, and sepsis prognosis. Biomarkers can likely also be used
to stratify patients with sepsis according to biochemical and/or immunologic profiles,
which can provide insight into the main pathophysiologic mechanisms in individual pa-
tients and in pathways that can potentially be targeted. New omics technologies can
be of great help, associating expression at RNA, protein, and metabolite levels with
specific complications and outcomes. The challenge will be to develop biomarker
sets that can be measured in simply obtainable samples such as blood and urine
but that mirror pathophysiologic events at different body sites. Such biomarker sets
could guide the inclusion of patients who might benefit from a targeted therapy and
monitor the effect of the therapeutic on its target using an approach that has been
Biomarkers in Sepsis 149
named theranostics. The authors foresee a future for sepsis management in which
therapies are guided by repeated measurements of biomarker sets reflecting aberra-
tions in host response pathways that can be specifically modified by targeted thera-
peutics, using rapid bedside tests with limited hands-on time and no need for
specialized laboratories. In this personalized medicine approach, individualized ther-
apies would be provided in a pathology-specific way, and not purely based on clinical
presentation.
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