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Molecular & Cellular Proteomics 7:1863-1875, 2008.
© 2008 by The American Society for Biochemistry and Molecular Biology, Inc.

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Research

Identification of Diagnostic Biomarkers for Infection in Premature Neonates^*

Stephen F. Kingsmore^,, Neil Kennedy^¶, Henry L. Halliday^¶, Jennifer C. Van Velkinburgh, Shengiang Zhong^||, Vanessa Gabriel^**, Judith Grant^**, William D. Beavis^||, Velizar T. Tchernev^,, Lorah Perlee, Serguei Lejnine, Brian Grimwade, Martin Sorette and J. David M. Edgar^¶¶

From the National Center for Genome Resources, Santa Fe, New Mexico, 87505, ^¶ Royal-Jubilee Maternity Service and ^¶¶ Regional Immunology Service, Royal Hospitals Trust, Belfast, Northern Ireland BT12 6BB, United Kingdom, ^|| Agronomy Department, Iowa State University, Ames, Iowa 50011, ^** Department of Neonatal Medicine, Queen's Medical Centre, Nottingham NG7 2UH, United Kingdom, and Molecular Staging, Inc., New Haven, Connecticut 06511

	ABSTRACT

TOP ABSTRACT EXPERIMENTAL PROCEDURES RESULTS DISCUSSION REFERENCES

 
Infection is a leading cause of neonatal morbidity and mortality worldwide. Premature neonates are particularly susceptible to infection because of physiologic immaturity, comorbidity, and extraneous medical interventions. Additionally premature infants are at higher risk of progression to sepsis or severe sepsis, adverse outcomes, and antimicrobial toxicity. Currently initial diagnosis is based upon clinical suspicion accompanied by nonspecific clinical signs and is confirmed upon positive microbiologic culture results several days after institution of empiric therapy. There exists a significant need for rapid, objective, in vitro tests for diagnosis of infection in neonates who are experiencing clinical instability. We used immunoassays multiplexed on microarrays to identify differentially expressed serum proteins in clinically infected and non-infected neonates. Immunoassay arrays were effective for measurement of more than 100 cytokines in small volumes of serum available from neonates. Our analyses revealed significant alterations in levels of eight serum proteins in infected neonates that are associated with inflammation, coagulation, and fibrinolysis. Specifically P- and E-selectins, interleukin 2 soluble receptor , interleukin 18, neutrophil elastase, urokinase plasminogen activator and its cognate receptor, and C-reactive protein were observed at statistically significant increased levels. Multivariate classifiers based on combinations of serum analytes exhibited better diagnostic specificity and sensitivity than single analytes. Multiplexed immunoassays of serum cytokines may have clinical utility as an adjunct for rapid diagnosis of infection and differentiation of etiologic agent in neonates with clinical decompensation.

Recently there has been a considerable interest in the application of host biomarkers for diagnostic tests (9). It appears that biological systems are adaptive and that challenges to host homeostasis cause characteristic topological perturbations of molecular networks. A biomarker is a measurable gene, protein, metabolite, or other indicator of network perturbation that correlates with a specific outcome or clinical state (10). Biomarkers are identified through a four-step process of discovery by appropriate multiplex biochemical analysis followed by replication ideally in independent cohorts, validation of diagnostic sensitivity and specificity, and translation into a clinical diagnostic test (9). Numerous candidate biomarkers have been identified in neonatal sepsis: elevated plasma or serum levels of interleukin 6 (IL-6)¹ (11, 13), tumor necrosis factor (TNF) (11, 13), neutrophil elastase (NE) (14), C-reactive protein (CRP) (12, 15), soluble CD14 (16, 17), granulocyte colony-stimulating factor (G-CSF) (18), soluble intercellular adhesion molecule-1 (ICAM-1) (12), and soluble L-selectin (19) have shown association with infection in neonates. The value of physiological measurements in this context has also been examined recently (20). However, the positive predictive value or negative predictive value (NPV) of individual analytes has not been adequate for routine use in the diagnosis and management of neonatal infection.

In other clinical conditions where individual analytes lack adequate positive predictive value or NPV, the values of several analytes have been combined, together with an algorithm, to provide a biomarker panel with improved clinical performance (9). Multiplexed measurement of plasma proteins is a logical approach because they constitutively function within networks, pathways, complexes, and families (21–23). Indeed the activity of an individual plasma protein is typically dependent not only upon its abundance but also upon the effects of interacting proteins, modifying proteins, and antagonistic and synergistic proteins. This is especially true of cytokines, which are a group of several hundred small, soluble, plasma proteins relevant to sepsis, that are powerful mediators of target cell activities such as migration, activation, phagocytosis, proliferation, and apoptosis.

Several recent studies have explored the utility of measurement of two or more analytes for diagnosis of neonatal infection (11–13, 17). For example, we have shown that CRP > 6 mg/liter and soluble ICAM-1 > 300 ng/ml in combination in plasma samples collected under endotoxin-free conditions (12, 13) were independent predictors of infection and gave both a high sensitivity for clinical infection (95%) and an NPV of 97% (12). We subsequently demonstrated that routinely collected serum samples reproduced a very high NPV for infection (24). We have further examined the diagnostic utility of the combination of low level CRP and soluble immunological markers.² In a recent review, Ng (25) concluded that a combination of several markers can enhance diagnostic accuracy in neonatal sepsis.

In the present study, we used amplified, multiplexed, immunoassay arrays to measure 142 small serum proteins and assess their utility in differential diagnosis of neonatal infection. In addition, we utilized the most informative of these biomarkers to develop a multiplexed biomarker panel with improved diagnostic performance in neonatal infection.

	EXPERIMENTAL PROCEDURES

TOP ABSTRACT EXPERIMENTAL PROCEDURES RESULTS DISCUSSION REFERENCES

 
Patient Population, Samples, and Laboratory Test Results
Serum samples were obtained from acutely ill, preterm (36 weeks gestation) infants undergoing intensive care in the neonatal units of the University Hospital, Queen's Medical Centre, Nottingham, UK and the Royal-Jubilee Maternity Service, Royal Hospitals Trust, Belfast, Northern Ireland, UK. These infants were either admitted to the neonatal unit with a suspected diagnosis of infection (early onset and late onset infection) or developed clinical signs suggesting that infection may be complicating their management. As part of their acute management, these infants had blood samples taken for routine laboratory analysis, and an extra aliquot of 0.5 ml of blood was collected for the purposes of this study. At presentation, the culture result, white blood cell count, platelet count, gestational age, primary diagnosis, and clinical signs were also recorded.

Blood samples were kept at ambient temperature until serum was separated (within 24 h), and serum was stored at –20 °C until analysis. No extra venepuncture beyond clinical requirements was necessary as a result of this study for either patients or control subjects.

Clinical diagnosis was established in a prospective manner, blind to the results of the study measurements. Infants were classified as "clinically infected" or "non-infected" based on the initial clinical presentation and results of routine investigations ((a) white cell and platelet counts, (b) blood and other cultures, (c) radiological imaging, and (d) response to antibiotics). The infected group was further subclassified as (a) culture-positive infection or (b) culture-negative infection.

Written informed parental consent was obtained for study subjects. Ethical approval was obtained from the Ethics Committee, University Hospital, Queen's Medical Centre, Nottingham, UK.

Sample Processing
Aliquots of the samples were thawed, centrifuged to remove particulate matter, and diluted 1:5 with 18.75 units/ml heparin (Sigma) in AD1 diluent (Immunochemistry Technologies, Bloomington, MN), and 0.25 mg/ml Heteroblock (Omega Biologicals, Bozeman, MT), 0.25 mg/ml immunoglobulin inhibiting reagent (Bioreclamation, Hicksville, NY), and 0.1% Tween 20 (Sigma) were added prior to assay.

Antibody Microarray Manufacture
Antibody microarray manufacture has been described in detail previously (26). Briefly glass slides were covered with a Teflon mask to provide 16 sample wells and silanized with 3-cyanopropyltriethoxysilane. Each well was printed with quadruplicate spots of each of 64 capture antibodies using a PerkinElmer Life Sciences SpotArray Enterprise piezoelectric arrayer. Six different antibody arrays were prepared, each containing 25–37 unique capture antibodies (Table I).

Data Processing
Data processing procedures were as described previously (26). Briefly data points producing outlier events as a result of missing spots, spots with poor morphology, or printed features demonstrating high pixel outliers were removed. Correlation between sample replicates was performed, and sample replicates with correlation coefficient (R²) values <0.95 were removed. Intensity values were log₂-transformed to minimize dependence of variance on intensity and normalized by analysis of variance to reduce variability observed between replicates (26, 29–32). Sample pass rates following data processing procedures are indicated in Table II.

The estimated effect size is associated with the predictive ability of a particular analyte. For example, an effect size of 0.3 between two groups is equivalent to a probability of correctly identifying the groups of 0.56. The current study used an effect size 0.6 as the cutoff for statistical significance based upon previous studies involving analysis of clinical samples on 142-feature antibody arrays (26, 27).

Pairwise differences in logarithm-transformed MFIs of analyte values in infected neonates with cultures positive for coagulase-negative staphylococci, Escherichia coli, Candida, and group B streptococci were compared by ANOVA, LSMeans (SAS JMP Genomics 3.2) using a false discovery rate correction and a p value <0.05.

Multivariate Analysis—
Because of the rigorous quality controls applied during data processing, the data matrix of samples x analytes contained missing data (Table II). Unfortunately many multivariate analyses are unstable with missing values (33). Model-based methods (34) have long been used to impute values for missing data prior to multivariate analyses, but these methods can introduce bias from incorrectly specified models. To reduce the bias from an incorrectly specified model, we utilized a weighted K-nearest neighbor approach to impute missing values (35). Explicitly we imputed missing values based on corresponding data for the missing analyte from the 20 nearest neighbors irrespective of the clinical diagnosis of the sample. To minimize the impact of imputed data on the discriminant function, we also removed 27 samples and 19 analytes in which more than 25% of the data were imputed. A multivariate discriminant function was developed using the STEPDISC procedure of SAS applied to the average values of log-transformed analyte concentrations for 123 analytes from 80 samples (43 infected and 37 uninfected). The criteria for selection of analytes to enter or remove from the model were based on the significance of the F statistic set to = 0.1. The ability of the resulting set of analytes to predict infection status was evaluated using the DISC procedure of SAS. Because of unequal and perhaps non-normal multivariate distributions within the infected and non-infected groups, the discriminant function was based on the nearest neighbor method in which K was set to 15. The resulting discriminant function was then tested for predictive value by 80 iterations of "leave-one-out" cross-validation.

	RESULTS

TOP ABSTRACT EXPERIMENTAL PROCEDURES RESULTS DISCUSSION REFERENCES

 
Patient Population—
108 serum samples were obtained from 72 infants, comprising 51 samples from 35 clinically infected neonates (early and late onset infection) and 57 samples from 40 non-infected infants. 32 of 51 (63%) clinically infected samples were associated with positive microbiological culture results. Organisms identified in positive cultures were coagulase-negative staphylococci (n = 14), Staphylococcus aureus (n = 2), enterococci (n = 3), group B Streptococcus (n = 3), hemolytic streptococci (n = 1), E. coli (n = 3), Enterococcus faecium (n = 1), and Candida spp. (n = 4). Univariate statistics revealed the clinically infected samples to be associated with a marginally higher white blood cell count (p < 0.05) and significantly greater C-reactive protein (p = 1.9 x e^–25, F-test). Table III shows the demographic characteristics and laboratory values of these groups.

View larger version (31K): [in this window] [in a new window]   FIG. 1. Eight serum analytes with greatest differences in levels between clinically infected and non-infected neonates. Each analyte had significant differences between clinically infected and non-infected neonates (p < 0.05 by ANOVA and effect size >0.6 in log-transformed level). Group mean analyte levels are expressed in pg/ml with S.E. (bars).

Several multivariate classifier panels were obtained using different parameter settings in discriminant analyses. All contained analytes that exhibited significant group differences in univariate analyses, such as uPAR and uPA. Certain classifiers that predicted infection and non-infection correctly in cross-validation studies were rejected because of overfitting concerns due to featuring relatively large numbers of analytes (data not shown). Others were rejected because they featured well annotated analytes that are established biomarkers in other conditions (e.g. CA125). A single classifier was chosen that featured the smallest number of analytes and greatest number of analytes with significant group differences in univariate analyses (n = 5) and that did not contain analytes lacking biological congruence for neonatal sepsis. This classifier consisted of 13 analytes (analyte, partial R² value; CD27, 0.06; CD40, 0.05; ciliary neurotrophic factor receptor , 0.06; FGF6, 0.10; GRO-, 0.07; interferon , 0.05; MCP-3, 0.07; MMP-2, 0.09; P-selectin, 0.09; plasminogen activator inhibitor-II, 0.06; VAP1, 0.08; VEGF-R3, 0.06; uPA, 0.06). This classifier predicted infection in 38 of 43 infected neonates (P(i|i) 0.88) and predicted absence of infection in 31 of 37 uninfected neonates (P(u|u) 0.84). In cross-validation analyses, the classifier predicted infection in 38 of 43 infected neonates (validateP(i|i) 0.88) and predicted absence of infection in 30 of 37 uninfected neonates (validateP(u|u) 0.81).

Differentiation of Etiologic Agent Class by Examination of Host Serum Protein Levels—
Host biomarkers for early differentiation of etiologic agent in neonates with bacteremia were also sought. Log-transformed levels of serum analytes in three neonatal infections with cultures positive for group B streptococci, four with Candida, 16 with coagulase-negative staphylococci, and three with E. coli were compared. Hierarchical clustering and parallel plots of analytes with largest standardized LSMeans effects are shown in Fig. 2. Host responses differed widely between etiologic agents. Coliform infections evoked little change in the serum analytes examined. In contrast, levels of the proinflammatory cytokines IL-6, IL-8 (CXCL8), MCP1 (CCL2), G-CSF, P-selectin, and prolactin were much higher in group B streptococcal bacteremia than other neonatal infections: average IL-8 levels in group B streptococcal infections were 112,130 pg/ml compared with 40 pg/ml in candidemia and 44 pg/ml in Staphylococcus epidermidis bacteremia. Average IL-6 levels were 270,636 pg/ml in group B streptococcal bacteremia, 18 pg/ml in candidemia, and 45 pg/ml in S. epidermidis. MCP1 differentiated candidemia (177 pg/ml) from group B streptococcal bacteremia or S. epidermidis (216,700 and 109,827 pg/ml, respectively). Fungal infections were associated with elevated levels of the costimulatory receptor 4-1BB, IL-18, IL-2sR D dimer, uPAR, and chemokines monokine induced by interferon (MIG; CXCL9) and MIP3 (CCL23) among others. Cultures positive for coagulase-negative staphylococci were associated with elevated insulin-like growth factor II and TRAILR1.

View larger version (74K): [in this window] [in a new window]   FIG. 2. Parallel plot (A) and dendrogram of hierarchical clustering (B) of analytes with largest standardized LSMeans effects in pairwise comparisons of infected neonates with microbiologic cultures positive for coagulase-negative staphylococci (Coag.– Staph.), E. coli, Candida, and group B streptococci (Gp.B Strep.). Eotaxin 3 is highlighted; it is elevated in group B streptococcal infection and depressed in E. coli infection. See Table I for protein abbreviations and full names.

	DISCUSSION

TOP ABSTRACT EXPERIMENTAL PROCEDURES RESULTS DISCUSSION REFERENCES

CRP is a critical, phylogenetically ancient component of the innate immune response. Upon CRP recognition and binding to phosphocholine (a phospholipid expressed on the membranes of many bacteria and damaged host cell walls), the acute phase inflammatory response is initiated (36). Accordingly increased levels of CRP are observed early in response to severe bacterial infection (37). Plasma CRP levels were found to be statistically significantly higher in patients with septic syndrome symptoms, and CRP serum concentration correlated with severity of a patient's clinical state (38). In fatal cases high plasma CRP concentration was recorded during hospitalization, whereas in cases of recovery, rapid CRP decrease was noted (38). In our study, CRP was found to be increased in neonatal patients with infection. Therefore, plasma CRP concentration in patients with bacterial sepsis may be helpful in evaluation of clinical state severity and monitoring of the disease course as well as therapy efficacy. Previously we have shown that plasma CRP > 6 mg/liter has a high sensitivity for clinical infection (95%) and NPV of 97% (12). As a classical acute phase reactant, however, CRP elevation alone has insufficient specificity for diagnosis of neonatal infection.

P- and E-selectins are related cell adhesion molecules expressed and secreted by activated endothelial cells (P- and E-selectins) and platelets (P-selectin). Both P- and E-selectins are components of an adhesion cascade that leads to leukocyte and platelet accumulation at sites of inflammation, infection, and/or injury. Uncontrolled adhesiveness in the microcirculatory system leads to tissue hypoxia (cryptic shock) and eventual organ dysfunction, hallmarks of severe sepsis and septic shock (39). Previous studies of P-selectin have demonstrated elevations in serum and platelets in adult sepsis and septic shock and in platelets in neonatal group B Streptococcus sepsis (40–42). However, only elevated levels of E- (but not P-) selectin have been previously documented in neonatal sepsis (43–45).

In part as a result of E-selectin elevation, another early component of the host response to infection is recruitment of neutrophils. Accordingly it was not surprising to find elevated NE in infected neonates. NE is the major serine proteinase secreted by activated neutrophils (or released by damaged neutrophils), and several previous publications have documented NE as an infection parameter for neonatal diagnosis (14, 46–50).

Further evidence of altered endothelial adhesiveness is increased levels of coagulation/fibrinolysis cascade proteins: uPA, an extracellular serine protease, is involved in the catalytic conversion of plasminogen to the active fibrinolytic enzyme plasmin (51). uPA is activated upon binding to its cognate receptor, uPAR, which is a membrane-linked receptor with extracellular protease activity that transduces intracellular signaling pathways. Although in the healthy state, the balance of coagulation and fibrinolysis is tightly regulated, during sepsis coagulation and fibrinolysis are dysregulated as evidenced, for example, by consumption of plasminogen and protein C, elevation of plasminogen activator inhibitor, and occurrence of disseminated intravascular coagulation. Our study, in agreement with others, found increased circulating levels of uPA in the septic state (51). In addition, increased levels of soluble uPAR in response to a variety of infections have been reported and are an indicator of good prognosis in sepsis (52–56). A significant molar excess was observed in the increase in level of uPAR relative to uPA. This raises the possibility that, in neonatal infection, elevated uPAR may act to sequester uPA (despite elevated levels of uPA) and prevent it from binding the membrane-linked uPAR, thus abrogating normal intracellular signaling. Interestingly NE also activates fibrinolysis during sepsis, and its elevation has been suggested as a homeostatic mechanism to overcome impaired fibrinolysis in sepsis (57).

IL-2sR is a circulating form of one of three components of the high affinity membrane receptor for interleukin 2 present on activated T and B cell thymocyte subsets, pre-B cells and regulatory T cells. Although the biological function of IL-2sR is not completely understood, it is known to indicate T lymphocyte activation during disease. Several previous studies have demonstrated elevated serum levels of IL-2sR in neonatal sepsis (39–44).

IL-18 is a proinflammatory member of the IL-1 cytokine superfamily. Although IL-18 elevation has not been described previously in neonatal sepsis, recent studies have associated it with other disease morbidity. Neonatal necrotizing enterocolitis (58) and respiratory syncytial virus (59) infection have been associated with genetic polymorphisms in IL-18. In a mouse model, elevated IL-18 levels have been reported in neonatal group B streptococcal infections (60). Furthermore elevated levels of IL-18 have been documented in adult sepsis patients and correlate with adverse outcome and Acute Physiology and Chronic Health Evaluation (APACHE) II score (45, 46).

Interestingly it appears that the eight analytes identified as elevated in the infected neonates function in a network that links several processes, which are well known to be important in the response to systemic infection, e.g. coagulation, cell adhesion, and inflammation (Fig. 3). For example, it has been shown that IL-18 induces E-selectin expression on endothelial cells (61); IL-18 release is stimulated by CRP (62). CRP also induces significant E-selectin expression in human endothelial cells (63). Similarly the endothelial expression of E-selectin was increased by human neutrophil elastase (64). In contrast, uPA (urokinase) administration reduces the serum levels of soluble E-selectin in patients with acute myocardial infarction (65, 66). The presence of uPA increases platelet surface P-selectin expression in a concentration-dependent manner (67). It has also been suggested that intravascular fibrinolysis induced by uPA may induce P-selectin (68). uPA itself, as well as uPAR, are cleaved by neutrophil elastase (69, 70). Adhesion of human monocytes to P-selectin via its surface ligand, P-selectin glycoprotein 1, induced uPAR expression (71). Other studies have reported additional links between the above molecules, e.g. colocalization of neutrophil elastase, uPA, and uPAR (72) or colocalization of uPA and IL-2sR (73). Finally pathogens are known to interact in a specific manner with components of fibrinolytic pathways as well as with CRP (74).

View larger version (34K): [in this window] [in a new window]   FIG. 3. Eight serum proteins (P-selectin, E-selectin, IL-2sR, IL-18, NE, uPA, uPAR, and CRP) that are elevated in infected neonates function in a molecular network that links coagulation/fibrinolysis, cell adhesion, and inflammation, which are critical determinants of the response to systemic infection. Mo/M, monocytes macrophages.

Finally host biomarkers for early differentiation of etiologic agent in neonatal infection were sought. Host responses were compared for the four most common species in positive microbiologic cultures: group B streptococci, Candida, E. coli, and coagulase-negative staphylococci. The rationale for differentiation of etiologic agent based on host serum protein levels is that etiologic agents differ predictably in lifestyle and membrane lipid and protein content, evoking characteristic host responses. We found unique signatures of host response to each etiologic agent (Fig. 2). For example, levels of the proinflammatory cytokines IL-6 and IL-8 were more than 1000-fold higher in group B streptococcal bacteremia than in other neonatal infections. These novel findings will require validation in larger case series but offer the exciting prospect of rapid differentiation of at least some etiologic agents in neonatal sepsis, which would enable early institution of targeted antimicrobial therapy. Differences of the magnitude observed with IL-6 and IL-8, if substantiated, would permit etiologic agent differentiation with rapid, point-of-care, semiqualitative immunoassays.

	ACKNOWLEDGMENTS

 
We thank the employees of Molecular Staging Inc. who developed amplified antibody microarrays.

	FOOTNOTES

 
Received, August 21, 2008

Published, MCP Papers in Press, July 13, 2008, DOI 10.1074/mcp.M800175-MCP200

¹ The abbreviations used are: IL, interleukin; TNF, tumor necrosis factor; NE, neutrophil elastase; CRP, C-reactive protein; G-CSF, granulocyte colony-stimulating factor; ICAM-1, intercellular adhesion molecule-1; NPV, negative predictive value; MFI, mean fluorescence intensity; ANOVA, analysis of variance; uPA, urokinase plasminogen activator; uPAR, urokinase plasminogen-activated receptor; IL-2sR, IL-2 soluble receptor.

² J. D. M. Edgar, manuscript in preparation.

^* This work was supported, in whole or in part, by National Institutes of Health Grant AI066569 and Contract HHSN266200400064C. The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Present address: Crossover CRI AG, Industriestrasse 7, CH-6300 Zug, Switzerland.

To whom correspondence should be addressed: National Center for Genome Resources, 2935 Rodeo Park Dr. E., Santa Fe, NM 87505. Tel.: 505-995-4466; Fax: 505-995-4439; E-mail sfk{at}ncgr.org

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