Natural variability of TRAIL, IP-10, and CRP in healthy adults - The "HERACLES" study

A novel host-protein score (called MMBV) helps to distinguish bacterial from viral infection by combining the blood concentrations of three biomarkers: tumour necrosis factor related apoptosis inducing ligand (TRAIL), interferon gamma induced protein 10 (IP-10), and C-reactive protein (CRP). These host biomarkers are differentially expressed in response to bacterial versus viral acute infection. We conducted a prospective study, with a time series design, in healthy adult volunteers in the Netherlands. The aim was to determine the variability of TRAIL, IP-10, and CRP and the MMBV score in healthy adults across time. Up to six blood samples were taken from each healthy volunteer over a period of up to four weeks. In 77 healthy participants without recent or current symptoms, MMBV scores (maximal) were bacterial in 1.3 % and viral (or other non-infectious etiology) in 93.5 % of participants. There was little variation in the mean concentrations of TRAIL (74.5 pg/ml), IP-10 (113.6 pg/ml), and CRP (1.90 mg/L) as well as the MMBV score. The variability of biomarker measurement was comparable to the precision of the measurement platform for TRAIL, IP-10, and CRP. Our findings establish the mean values of these biomarkers and MMBV in healthy individuals and indicate little variability between and within individuals over time, supporting the potential utility of this novel diagnostic to detect infection-induced changes.

Host biomarkers and combinatorial scores for the detection of serious and invasive bacterial infection in pediatric patients with fever without source

BACKGROUND

Improved tools are required to detect bacterial infection in children with fever without source (FWS), especially when younger than 3 years old. The aim of the present study was to investigate the diagnostic accuracy of a host signature combining for the first time two viral-induced biomarkers, tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and interferon γ-induced protein-10 (IP-10), with a bacterial-induced one, C-reactive protein (CRP), to reliably predict bacterial infection in children with fever without source (FWS) and to compare its performance to routine individual biomarkers (CRP, procalcitonin (PCT), white blood cell and absolute neutrophil counts, TRAIL, and IP-10) and to the Labscore.

METHODS

This was a prospective diagnostic accuracy study conducted in a single tertiary center in children aged less than 3 years old presenting with FWS. Reference standard etiology (bacterial or viral) was assigned by a panel of three independent experts. Diagnostic accuracy (AUC, sensitivity, specificity) of host individual biomarkers and combinatorial scores was evaluated in comparison to reference standard outcomes (expert panel adjudication and microbiological diagnosis).

RESULTS

241 patients were included. 68 of them (28%) were diagnosed with a bacterial infection and 5 (2%) with invasive bacterial infection (IBI). Labscore, ImmunoXpert, and CRP attained the highest AUC values for the detection of bacterial infection, respectively 0.854 (0.804-0.905), 0.827 (0.764-0.890), and 0.807 (0.744-0.869). Labscore and ImmunoXpert outperformed the other single biomarkers with higher sensitivity and/or specificity and showed comparable performance to one another although slightly reduced sensitivity in children < 90 days of age.

CONCLUSION

Labscore and ImmunoXpert demonstrate high diagnostic accuracy for safely discriminating bacterial infection in children with FWS aged under and over 90 days, supporting their adoption in the assessment of febrile patients.

Host test based on tumor necrosis factor-related apoptosis-inducing ligand, interferon gamma-induced protein-10 and C-reactive protein for differentiating bacterial and viral respiratory tract infections in adults: diagnostic accuracy study

OBJECTIVES

To assess the performance of a test (called BV), integrating the blood levels of three immune proteins into a score, to differentiate bacterial from viral infection among adults with suspected lower respiratory tract infection (LRTI).

METHODS

Prospective diagnostic accuracy study, enrolling febrile adults >18 years with LRTI signs or symptoms for less than 7 days presenting to several hospitals' emergency departments in Israel. The main exclusion criterion was immunodeficiency. Reference standard diagnosis (bacterial/viral/indeterminate) was based on three experts independently reviewing comprehensive patient data including follow-up data. BV generated three results: viral infection or other nonbacterial condition (0 ≤ score < 35), equivocal (35 ≤ score ≤ 65) and bacterial infection including co-infection (65 < score ≤ 100). BV performance was assessed against the reference standard with indeterminate reference standard and equivocal BV cases removed.

RESULTS

Of 490 enrolled patients, 415 met eligibility criteria (median age 56 years, interquartile range 35). The reference standard classified 104 patients as bacterial, 210 as viral and 101 as indeterminate. BV was equivocal in 9.6% (30/314). Excluding indeterminate reference standard diagnoses and equivocal BV results, BV's sensitivity for bacterial infection was 98.1% (101/103; 95% confidence interval 95.4-100), specificity 88.4% (160/181; 83.7-93.1) and negative predictive value 98.8% (160/162; 97.1-100).

DISCUSSION

BV exhibited high diagnostic performance for febrile adults with suspected LRTI among patients with reference standard diagnoses of bacterial or viral LRTI.

An immune-protein score combining TRAIL, IP-10 and CRP for predicting severe COVID-19 disease

COVID-19 patients are oftentimes over- or under-treated due to a deficit in predictive management tools. This study reports derivation of an algorithm that integrates the host levels of TRAIL, IP-10, and CRP into a single numeric score that is an early indicator of severe outcome for COVID-19 patients and can identify patients at-risk to deteriorate. 394 COVID-19 patients were eligible; 29% meeting a severe outcome (intensive care unit admission/non-invasive or invasive ventilation/death). The score's area under the receiver operating characteristic curve (AUC) was 0.86, superior to IL-6 (AUC 0.77; p = 0.033) and CRP (AUC 0.78; p < 0.001). Likelihood of severe outcome increased significantly (p < 0.001) with higher scores. The score differentiated severe patients who further deteriorated from those who improved (p = 0.004) and projected 14-day survival probabilities (p < 0.001). The score accurately predicted COVID-19 patients at-risk for severe outcome, and therefore has potential to facilitate timely care escalation and de-escalation and appropriate resource allocation.

The diagnostic value of nasal microbiota and clinical parameters in a multi-parametric prediction model to differentiate bacterial versus viral infections in lower respiratory tract infections

Background

The ability to accurately distinguish bacterial from viral infection would help clinicians better target antimicrobial therapy during suspected lower respiratory tract infections (LRTI). Although technological developments make it feasible to rapidly generate patient-specific microbiota profiles, evidence is required to show the clinical value of using microbiota data for infection diagnosis. In this study, we investigated whether adding nasal cavity microbiota profiles to readily available clinical information could improve machine learning classifiers to distinguish bacterial from viral infection in patients with LRTI.

Results

Various multi-parametric Random Forests classifiers were evaluated on the clinical and microbiota data of 293 LRTI patients for their prediction accuracies to differentiate bacterial from viral infection. The most predictive variable was C-reactive protein (CRP). We observed a marginal prediction improvement when 7 most prevalent nasal microbiota genera were added to the CRP model. In contrast, adding three clinical variables, absolute neutrophil count, consolidation on X-ray, and age group to the CRP model significantly improved the prediction. The best model correctly predicted 85% of the ‘bacterial’ patients and 82% of the ‘viral’ patients using 13 clinical and 3 nasal cavity microbiota genera (Staphylococcus, Moraxella, and Streptococcus).

Conclusions

We developed high-accuracy multi-parametric machine learning classifiers to differentiate bacterial from viral infections in LRTI patients of various ages. We demonstrated the predictive value of four easy-to-collect clinical variables which facilitate personalized and accurate clinical decision-making. We observed that nasal cavity microbiota correlate with the clinical variables and thus may not add significant value to diagnostic algorithms that aim to differentiate bacterial from viral infections.

1348. A Novel Host-Protein Signature Comprising TRAIL, IP-10 and CRP Differentiates Bacterial from Viral Infection in COPD Patients with Suspected Lower Respiratory Tract Infection

Background

Identifying infectious etiology is often challenging, yet essential for patient management, including antibiotic use. Studies have shown that a host signature comprising TNF-related apoptosis induced ligand (TRAIL), interferon gamma induced protein-10 (IP-10) and C-reactive protein (CRP) accurately differentiates bacterial from viral infection with negative predictive value &gt;98%. Performance data was lacking in chronic obstructive pulmonary disease (COPD) patients with suspected lower respiratory tract infection (LRTI).

Methods

Adults aged &gt;18 years with suspected LRTI were prospectively recruited at 3 medical centers (OBSERVER; grant #684589; NCT003011515). Reference standard infection etiology was adjudicated by 3 independent experts based on clinical, laboratory, microbiological, radiological and follow-up data. Host signature generates a bacterial likelihood score (0-100), providing three results: viral (0-35), equivocal (35-65) and bacterial (65-100). Experts were blinded to the signature result.

Results

Out of 583 adults recruited with suspected LRTI, 422 met infectious criteria, of whom 48 had a recorded history of COPD. 19 cases were adjudicated by the experts as bacterial, 14 as viral and 15 were indeterminate (Figure 1). The mean age was 68.2 years (standard deviation 12.3); 33 (68.8%) presented after two or more days of symptoms and 38 (79.2%) were hospitalized for a median of 6 days. 15 (31.2%) were female. For the patients adjudicated bacterial or viral labels (n=33), the discharge diagnoses were: COPD exacerbation, 12 cases (36.4%); pneumonia, 12 cases (36.4%) (3.0%); acute bronchitis, 2 cases (6.1%); upper RTI ,1 case; unspecified viral infection 1 case (3.0%); or other, 5 cases (15.2%). Host signature correctly classified all 19 bacterial cases and 8 of the viral cases, providing accurate etiology labels for 27/33 COPD patients with reference standard labels (81.8%). The remaining 6 viral cases received equivocal scores (18.2%).

COPD patient enrollment and etiology labels in the Observer study

Conclusion

Host signature accurately differentiates between bacterial and viral infections in patients with COPD history, supporting potential to improve management among these patients frequently admitted for RTIs.

Disclosures

Michal Stein, MeMed (Employee) Meital Paz, MD, MeMed (Employee) Tanya Gottlieb, PhD, MeMed (Employee, Shareholder) Eran Barash, MA, MeMed (Employee) Roy Navon, MSc, MeMed (Employee, Shareholder) Einat Moscoviz, BSc+ MBA, MeMed (Employee) Tahel Ilan Ber, MD, MeMed (Employee, Shareholder) Liran Shani, MD, MeMed (Employee) Olga Boico, PhD, MeMed (Employee) Einav Simon, PhD, MeMed (Employee, Shareholder) Noa Avni, PhD, MeMed (Employee) Kfir Oved, MD, PhD, MeMed (Board Member, Employee, Shareholder) Eran Eden, PhD, MeMed (Board Member, Employee, Shareholder)

32. Host Immune-Protein Signature Combining TRAIL, IP-10 and CRP for Early and Accurate Prediction of Severe COVID-19 Outcome

Background

Accurately identifying COVID-19 patients at-risk to deteriorate remains challenging. Dysregulated immune responses impact disease progression and development of life-threatening complications. Tools integrating host immune-protein expression have proven useful in determining infection etiology and hold potential for prognosticating disease severity.

Methods

Adults with COVID-19 were enrolled at medical centers in Israel, Germany, and the United States (Figure 1). Severe outcome was defined as intensive care unit admission, non-invasive or invasive ventilation, or death. Tumor necrosis factor related apoptosis inducing ligand (TRAIL), interferon gamma inducible protein-10 (IP-10) and C-reactive protein (CRP) were measured using an analyzer providing values within 15 minutes (MeMed Key®). A signature indicating the likelihood of severe outcome was derived generating a score (0-100).

Description of derivation cohort

RT-PCR, reverse transcription polymerase chain reaction.

Results

Between March and November 2020, 518 COVID-19 patients were enrolled, of whom 394 were eligible, 29% meeting a severe outcome. Age ranged between 19-98 (median 61.5), with 59.1% male. Patients meeting severe outcomes exhibited higher levels of CRP and IP-10 and lower levels of TRAIL (Figure 2; p < 0.001). Likelihood of severe outcome increased significantly (p < 0.001) with higher scores. The signature’s area under the receiver operating characteristic curve (AUC) was 0.86 (95% confidence interval: 0.81-0.91). Performance was not confounded by age, sex, or comorbidities and was superior to IL-6 (AUC 0.77; p = 0.033) and CRP (AUC 0.78; p < 0.001). Clinical deterioration proximal to blood draw was associated with higher signature score. Scores of patients meeting a first outcome over 3 days after blood draw were significantly (p < 0.001) higher than scores of non-severe patients (Figure 3). Moreover, the signature differentiated patients who further deteriorated after meeting a severe outcome from those who improved (p = 0.004) and projected 14-day survival probabilities (p < 0.001; Figure 4).

TRAIL, IP-10, CRP and the severity signature score are differentially expressed in severe and non-severe COVID-19 infection

Dots represent patients and boxes denote median and interquartile range (IQR)

The signature score of patients meeting a severe outcome on or after the day of blood draw is significantly (p < 0.001) higher than the signature score of non-severe patients.

Dots represents patients and boxes denote median and IQR

Kaplan-Meier survival estimates for signature score bins

Conclusion

The derived signature combined with a rapid measurement platform has potential to serve as an accurate predictive tool for early detection of COVID-19 patients at risk for severe outcome, facilitating timely care escalation and de-escalation and appropriate resource allocation.

Disclosures

Alon Angel, n/a, MeMed (Employee, Shareholder) Niv Samuel Mastboim, BSc, MeMed (Employee, Shareholder) Oded Shaham, PhD, MeMed (Employee, Shareholder) Tahel Ilan Ber, MD, MeMed (Employee, Shareholder) Roy Navon, MSc, MeMed (Employee, Shareholder) Einav Simon, PhD, MeMed (Employee, Shareholder) Michal Rosenberg, PhD, MeMed (Employee) Yael Israeli, PhD, MeMed (Employee) Mary Hainrichson, PhD, MeMed (Employee, Shareholder) Noa Avni, PhD, MeMed (Employee) Eran Reiner, MD, MeMed (Employee) Kfir Oved, MD, PhD, MeMed (Board Member, Employee, Shareholder) Ilya Kagan, MD, MeMed (Scientific Research Study Investigator) Shaul Lev, M.D, MeMed (Scientific Research Study Investigator) Dror Diker, MD, MeMed (Scientific Research Study Investigator) Amir Jarjou’i, MD, MeMed (Scientific Research Study Investigator) Ramzi Kurd, MD, MeMed (Scientific Research Study Investigator) Guy Danziger, MD, MeMed (Scientific Research Study Investigator) Cihan Papan, MD, MeMed (Scientific Research Study Investigator) Sergey Motov, MD, MeMed (Scientific Research Study Investigator) Maanit Shapira, Ph.D, MeMed (Scientific Research Study Investigator) Tanya Gottlieb, PhD, MeMed (Employee, Shareholder) Eran Eden, PhD, MeMed (Board Member, Employee, Shareholder)

A host signature based on TRAIL, IP-10, and CRP for reducing antibiotic overuse in children by differentiating bacterial from viral infections: a prospective, multicentre cohort study

OBJECTIVES

Identifying infection aetiology is essential for appropriate antibiotic use. Previous studies have shown that a host-protein signature consisting of TNF-related apoptosis-induced ligand (TRAIL), interferon-γ-induced protein-10 (IP-10), and C-reactive protein (CRP) can accurately differentiate bacterial from viral infections.

METHODS

This prospective, multicentre cohort study, entitled AutoPilot-Dx, aimed to validate signature performance and to estimate its potential impact on antibiotic use across a broad paediatric population (>90 days to 18 years) with respiratory tract infections, or fever without source, at emergency departments and wards in Italy and Germany. Infection aetiology was adjudicated by experts based on clinical and laboratory investigations, including multiplex PCR and follow-up data.

RESULTS

In total, 1140 patients were recruited (February 2017-December 2018), of which 1008 met the eligibility criteria (mean age 3.5 years, 41.9% female). Viral and bacterial infections were adjudicated for 628 (85.8%) and 104 (14.2%) children, respectively; 276 patients were assigned an indeterminate reference standard outcome. For the 732 children with reference standard aetiology, the signature discriminated bacterial from viral infections with a sensitivity of 93.7% (95%CI 88.7-98.7), a specificity of 94.2% (92.2-96.1), positive predictive value of 73.0% (65.0-81.0), and negative predictive value of 98.9% (98.0-99.8); in 9.8% the test results were equivocal. The signature performed consistently across different patient subgroups and detected bacterial immune responses in viral PCR-positive patients.

CONCLUSIONS

The findings validate the high diagnostic performance of the TRAIL/IP-10/CRP signature in a broad paediatric cohort, and support its potential to reduce antibiotic overuse in children with viral infections.

Differential Serum and Urine CRP, IP-10, and TRAIL Levels in Pediatric Urinary Tract Infection

Background: It is estimated that clinical evaluation and urinalysis are unable to diagnose >10% of urinary tract infections (UTI) in young children. TNF-related apoptosis induced ligand (TRAIL), interferon gamma induced protein-10 (IP-10), and C-reactive protein (CRP) exhibit differential expression in the blood in response to bacterial vs. viral infection. We assessed if the urinary and serum levels of these host biomarkers discriminate UTI, nephronia, and response to antibiotic treatment. Methods: Hospitalized febrile children aged <18 years with suspected UTI based on abnormal urinalysis were recruited prospectively between 2016 and 2018; also, non-febrile controls were recruited. Following urine culture results and hospitalization course, participants were divided into three groups based on AAP criteria and expert adjudication: UTI, viral infection, and indeterminate. Results: Seventy-three children were enrolled, 61 with suspected UTI and 12 non-febrile controls. Of the 61 with suspected UTI, 40 were adjudicated as UTI, 10 viral infection, and 11 as indeterminate. Urinary CRP and IP-10 levels were significantly higher in the UTI group (p ≤ 0.05). Urinary CRP differentiated UTI from non-bacterial etiology in children under and over 3 months of age, with AUCs 0.98 (95% CI: 0.93-1.00) and 0.82 (0.68-0.95), respectively. Similarly, urinary IP-10 discriminated with AUCs of 0.80 (0.59-1.00) and 0.90 (0.80-1.00), respectively. Serum CRP and IP-10 levels were significantly higher in UTI cases with nephronia (p ≤ 0.03). UTI-induced changes in the levels of urinary and serum biomarkers resolved during recovery. Conclusions: CRP, IP-10, and TRAIL represent biomarkers with potential to aid the clinician in diagnosis and management of UTI.

1213. A TRAIL/IP-10/CRP Signature Distinguishes between Viral and Bacterial Infection in Chronic Obstructive Pulmonary Disease Patients

Background

Challenges in determining the etiology of acute exacerbations of chronic obstructive pulmonary disease (COPD) lead to significant overuse of antibiotics. A new host-response assay that integrates the levels of three proteins (TRAIL, IP-10, and CRP) was shown to exhibit high performance in distinguishing between bacterial and viral disease in two double-blind pediatric validation studies. Here we sought to evaluate its ability to differentiate bacterial from viral infection in adult COPD patients with suspicion of lower respiratory tract infection (LRTI).

Methods

The study population included 492 febrile adult patients prospectively recruited in “Observer”, an EU Horizon 2020 funded study (grant #684589). Patient etiology was determined by majority expert panel based on clinical, laboratory, multiplex PCR, radiological and follow-up data. We compared the expert panel diagnosis with the assay that gives three possible outcomes: viral, bacterial (including viral with bacterial coinfection) or equivocal.

Results

45 out 492 adult patients prospectively recruited with suspicion of LRTI had a medical history of COPD. Of these, 20 cases were assigned as suspected viral infections and 19 as suspected bacterial infections (Figure 1). Antibiotics were prescribed to 19/19 bacterial infections and 16/20 viral infections. The assay correctly classified 19/19 bacterial infections and 12/20 viral infections, with 2 viral cases classified by the assay as bacterial and 6 receiving an equivocal outcome. These data support the assay’s potential to reduce antibiotic overuse from 16/20=80% to 8/20=40% (P=0.01).

FIgure 1: Flow through of COPD patients in prospective performance validation study “Observer”

Conclusion

A new TRAIL/IP-10/CRP signature has potential to significantly reduce antibiotic overuse for patients with suspected LRTI and a history of COPD without missing bacterial infection.

Disclosures

Meital Paz, MD, MeMed Ltd. (Employee) Noa Avni, PhD, MeMed (Employee) Michal Stein, MeMed Ltd. (Employee) Liran Shani, MD, MeMed Ltd. (Employee) Tanya Gottlieb, PhD, MeMed (Employee) Kfir Oved, MD, PhD, MeMed (Employee) Eran Eden, PhD, MeMed (Employee)

426. Use of Real Time IP-10 Measurements to Identify and Monitor the Dysregulated Immune Response in COVID-19 Patients

Background

It is estimated that up to 10% of SARS-CoV-2 patients progress from early and pulmonary stages to the most severe stage of illness, which manifests as an extra-pulmonary systemic hyperinflammatory syndrome. Interferon gamma-induced protein 10 (IP-10) is an inflammatory marker that plays a role in the dysregulated host response of COVID-19 infected patients. Clinical monitoring of IP-10 has been restricted in the absence of a rapid diagnostic test. MeMed Key^TM is a novel platform recently cleared to provide IP-10 measurements in 15 minutes. We hypothesized that providing physicians with real time IP-10 measurements would support detection and continuous monitoring of patients with a dysregulated immune response and potentially allow personalized immunomodulation to improve patient outcome.

IP-10 levels reflect corticosteroid treatment

Methods

From 7^th April 2020 to 10^th May 2020 blood was routinely collected serially from 52 SARS-CoV-2 positive patients hospitalized at a COVID-19 dedicated medical center. A clinical decision support protocol was in place focused on managing viral response, oxygenation and inflammatory state (NCT04389645).

Results

The median age of the 52 patients was 69, 69% were male, 21% were ventilated, 4 died, 2 due to non-COVID-19 related complications. The most common comorbidities were Diabetes 40% and Hypertension 46%. IP-10 >1000 pg/ml correlated with ICU admission (p< 0.05) and increased COVID-19 severity score (p< 0.01). 19 of the 52 patients had IP-10 >1000 pg/ml, of these 12 were treated with corticosteroids. Monitoring IP-10 within the clinical decision support protocol assisted with personalized corticosteroid regimens with the aim of reducing IP-10 < 1000 pg/ml. The 10 patients that survived exhibited IP-10 levels >1000 pg/ml for 2.6 days on average. In contrast, the 2 patients that died of COVID-19 related complications displayed an average of 7.5 days with IP-10 >1000 pg/ml (p< 0.05).

Conclusion

Providing physicians with real time measurements of IP-10 in COVID-19 patients proved a useful tool as part of the clinical decision support protocol. Timely identification, monitoring and personalized treatment of COVID-19 patients exhibiting a dysregulated immune response may aid in improving patient outcome. Further studies are warranted.

Disclosures

Tahel Ilan Ber, MD, MeMed (Employee) Alon Angel, n/a, MeMed (Employee) Lior Kellerman, M.D, MeMed (Employee) Eran Barash, MA, MeMed (Employee) Roy Navon, MSc, MeMed (Employee) Einav Simon, PhD, MeMed (Employee) Noa Avni, PhD, MeMed (Employee) Mary Hainrichson, PhD, MeMed (Employee) Tanya Gottlieb, PhD, MeMed (Employee) Kfir Oved, MD, PhD, MeMed (Employee) Eran Eden, PhD, MeMed (Employee)

2224. Reducing Antibiotic Overuse in Adult Lower Respiratory Tract Infections Using Novel Host–Response-Based Diagnostics

Background

Antibiotic overuse in LRTI is a major healthcare care problem, contributing to antimicrobial resistance. A novel assay that integrates blood levels of three immune-proteins TRAIL\IP-10\CRP was developed to assist in differentiating bacterial from viral disease. The assay exhibited high performance in blinded validation studies focusing on children. We performed a preliminary analysis of the ongoing OBSERVER study, evaluating the assay’s potential to reduce antibiotic misuse in adult patients presenting with suspicion of LRTI.

Methods

OBSERVER (NCT03011515) is an EU Horizon 2020 funded study (grant No. 684589), the first to validate the signature in adult LRTI patients. For every participant recruited at the emergency departments of three hospitals in Israel, we collected medical history, physical examination, routine lab, imaging, and respiratory multiplex PCR data. The assay outcomes are bacterial, viral or equivocal. Reference standard outcome of bacterial, viral, indeterminate or noninfectious, was assigned by expert panel majority adjudication. Indeterminates were excluded from the analysis.

Results

In this preliminary analysis, we included the first 218 patients with locked data (Figure 1). Age ranged from 18 to 96 years (mean 59.5). Clinical syndromes included: 21% pneumonia, 13% acute bronchitis, 6% COPD exacerbation, 32% upper respiratory tract infection and 16% unspecified LRTI or viral infections. The assay demonstrated high diagnostic performance for distinguishing bacterial from viral disease (Figure 2). Assay equivocal rate was 8%. In this cohort, antibiotics were prescribed to 41 of 105 patients with viral reference outcomes indicating an overuse rate of 39%, of these, 34 yielded viral index test outcomes, supporting the potential of the assay to reduce overuse by ~83%.

Conclusion

The TRAIL/IP-10/CRP assay demonstrated high diagnostic performance for differentiating between bacterial and viral disease. Medical literature shows that there is a big gap between guidelines antibiotic prescription recommendations and reported prescribing rates (~25% vs. 40%-50%) for suspected LRTI in adults. The use of this new assay, which has a specificity of 93% and NPV of 99%, can help to close the gap and improve adherence to the guidelines.

Disclosures

All authors: No reported disclosures.

2624. Viral Pneumonia in Children: Facing the Challenge Using the Host Response

Background

Diagnosing viral pneumonia in children is challenging. Chest radiographic imaging and clinical findings cannot reliably distinguish viral from bacterial pneumonia. Furthermore, pathogen-based diagnosis is limited by inaccessible site of infection and high asymptomatic detection rates. The objectives of this analysis were twofold: first, to establish pneumonia etiology by applying a rigorous expert panel process, and second, to evaluate whether a novel host-immune signature that integrates viral induced proteins TRAIL and IP-10 together with bacterial CRP, can accurately differentiate viral from bacterial pneumonia.

Methods

This analysis included 1025 febrile children enrolled in two multi-center clinical studies that evaluated the host-immune signature performance: ‘Curiosity’ study (Oved et al., PLoS One 2015) and ‘Pathfinder’ study (Srugo et al., Pediatrics 2017). Pneumonia etiology – viral or bacterial – was determined by a panel of 3 independent experts, after reviewing patients’ clinical, laboratory, microbiological, and radiological data. Only cases with majority panel assignment were included. The host-signature generated one of the three results: viral, equivocal or bacterial, based on predetermined cut-offs.

Results

A total of 709 children were eligible for analysis and had an expert panel etiology determination. Of them, 114 were diagnosed with pneumonia: 51 assigned viral and 63 assigned bacterial (Figure 1). The signature separated viral from bacterial pneumonia with a sensitivity of 94% (95% CI: 85%–99%) and specificity of 95% (85%–99%) with 14% equivocal test results. Out of the 51 children diagnosed with viral pneumonia by the expert panel, 40 (78%) were given antibiotics, and 43 (83%) underwent chest x-ray evaluation. The signature correctly classified 42 of these 51 viral children, indicating its potential to reduce antibiotic overuse rates by 4.4-fold (from 78% to 18%; P < 0.001) and chest x-ray examination by 4.8-fold (from 83% to 18%; P < 0.001).

Conclusion

The TRAIL/IP-10/CRP signature exhibits high accuracy for diagnosing viral pneumonia in children. The signature’s potential to safely decrease unnecessary antibiotics and chest radiographic imaging should be examined in future utility studies.

Disclosures

All authors: No reported disclosures.

Expert panel diagnosis demonstrated high reproducibility as reference standard in infectious diseases

OBJECTIVE

If a gold standard is lacking in a diagnostic test accuracy study, expert diagnosis is frequently used as reference standard. However, interobserver and intraobserver agreements are imperfect. The aim of this study was to quantify the reproducibility of a panel diagnosis for pediatric infectious diseases.

STUDY DESIGN AND SETTING

Pediatricians from six countries adjudicated a diagnosis (i.e., bacterial infection, viral infection, or indeterminate) for febrile children. Diagnosis was reached when the majority of panel members came to the same diagnosis, leaving others inconclusive. We evaluated intraobserver and intrapanel agreement with 6 weeks and 3 years' time intervals. We calculated the proportion of inconclusive diagnosis for a three-, five-, and seven-expert panel.

RESULTS

For both time intervals (i.e., 6 weeks and 3 years), intrapanel agreement was higher (kappa 0.88, 95%CI: 0.81-0.94 and 0.80, 95%CI: NA) compared to intraobserver agreement (kappa 0.77, 95%CI: 0.71-0.83 and 0.65, 95%CI: 0.52-0.78). After expanding the three-expert panel to five or seven experts, the proportion of inconclusive diagnoses (11%) remained the same.

CONCLUSION

A panel consisting of three experts provides more reproducible diagnoses than an individual expert in children with lower respiratory tract infection or fever without source. Increasing the size of a panel beyond three experts has no major advantage for diagnosis reproducibility.

Antibiotic misuse in respiratory tract infections in children and adults-a prospective, multicentre study (TAILORED Treatment)

Respiratory tract infections (RTI) are more commonly caused by viral pathogens in children than in adults. Surprisingly, little is known about antibiotic use in children as compared to adults with RTI. This prospective study aimed to determine antibiotic misuse in children and adults with RTI, using an expert panel reference standard, in order to prioritise the target age population for antibiotic stewardship interventions. We recruited children and adults who presented at the emergency department or were hospitalised with clinical presentation of RTI in The Netherlands and Israel. A panel of three experienced physicians adjudicated a reference standard diagnosis (i.e. bacterial or viral infection) for all the patients using all available clinical and laboratory information, including a 28-day follow-up assessment. The cohort included 284 children and 232 adults with RTI (median age, 1.3 years and 64.5 years, respectively). The proportion of viral infections was larger in children than in adults (209(74%) versus 89(38%), p < 0.001). In case of viral RTI, antibiotics were prescribed (i.e. overuse) less frequently in children than in adults (77/209 (37%) versus 74/89 (83%), p < 0.001). One (1%) child and three (2%) adults with bacterial infection were not treated with antibiotics (i.e. underuse); all were mild cases. This international, prospective study confirms major antibiotic overuse in patients with RTI. Viral infection is more common in children, but antibiotic overuse is more frequent in adults with viral RTI. Together, these findings support the need for effective interventions to decrease antibiotic overuse in RTI patients of all ages.

1962. TRAIL Level and ImmunoXpert™ Score Complement Molecular Viral Detection in the Classification of Febrile Children: An Interim Analysis From the AutoPilotDx-Study

Background

Differentiating between viral and bacterial etiology is essential in order to enable the adequate use of antibiotics. Previous studies showed that TNF-related apoptosis induced ligand (TRAIL) can serve as a useful biomarker for distinguishing between bacterial and viral infections when combined with IP-10 and CRP (ImmunoXpert™). Here we evaluate the potential of a new proteomic fingerprints in children with suspected viral and bacterial infections that had a confirmed viral detection.

Methods

In the prospective multinational multicenter study “AutoPilot-Dx” (NCT03052088) we aim to validate the diagnostic accuracy of the ImmunoXpert™ test. Infection etiology was assigned by majority adjudication of three experts based on comprehensive clinical and laboratory investigation. Viruses were detected using multiplex-PCR applied to nasopharyngeal swabs (Allplex™, Seegene). We performed an interim analysis of the first 134 febrile children recruited that had both PCR viral detection and etiology determination. TRAIL, IP-10, CRP and ImmunoXpert™ values were measured via a Tecan EVO75 ELISA platform.

Results

Bacterial diagnoses were assigned by the experts to 29%, 29% and 25% of patients with adenovirus (ADV), rhinovirus (RV), and respiratory syncytial virus (RSV) detection, respectively. Children with a viral infection including ADV, RSV, and RV had significantly lower ImmunoXpert™ scores as compared with children with a bacterial infection. Notably, TRAIL levels were markedly increased in viral infections as compared with bacterial infection, irrespective of the detected virus.

Conclusion

Classification of viral infections correlated significantly with elevated TRAIL levels and low ImmunoXpert™ scores. The differential expression of TRAIL in response to viral vs. bacterial infections can complement molecular viral detection, appears useful in the diagnostic workup for febrile children and may reduce antibiotic misuse.

Disclosures

L. Etshtein, MeMed Diagnostics: Employee, Salary. N. Mastboim, MeMed Diagnostics: Employee, Salary. A. Cohen, MeMed Diagnostics: Employee, Salary. E. Simon, MeMed: Employee, Salary. O. Boico, MeMed Diagnostics: Employee, Salary. L. Shani, MeMed Diagnostics: Employee, Salary. T. Gottlieb, MeMed Diagnostics: Employee, Salary. R. Navon, MeMed Diagnostics: Employee, Salary. K. Oved, MeMed Diagnostics: Board Member, Employee and Shareholder, Salary. E. Eden, MeMed Diagnostics: Board Member, Employee and Shareholder, Salary.

873. Using the Host Immune Response to Identify Viral-Bacterial Coinfection in Children With Respiratory Syncytial Virus Infection

Background

A major challenge in the effective management of children with RSV infection is the clinical difficulty of distinguishing a simple viral from viral–bacterial coinfections. As a result, despite the low rates of viral–bacterial coinfection, RSV patients are often prescribed antibiotics with recent reports demonstrating more than 60% antibiotic overuse rates (Van Houten et al. 2018). Here, we examined whether a host-immune signature combining the viral-induced proteins TRAIL and IP-10 with the bacterial-induced protein CRP (ImmunoXpert; Oved et al. 2015) can distinguish simple viral from viral–bacterial coinfection in RSV patients.

Methods

We studied 402 febrile children enrolled as part of “Curiosity,” a prospective study designed to develop and validate the host-immune signature. Infection etiology—viral or viral-bacterial coinfection—was determined by a panel of experts following a review of patients’ clinical, laboratory, radiological, microbiological, and follow-up data. RSV strains were detected using a respiratory multiplex PCR applied to nasal swabs (Seeplex-RV15).

Results

Out of the 402 children with suspected acute infection 29 had a positive RSV detection (Figure 1); of them, 27 had a unanimous expert panel etiology determination: 24 viral and 3 viral–bacterial coinfections. Out of the 24 patients unanimously assigned viral by the expert panel, 13 were given antibiotics, indicating a 54% antibiotic overuse rate. The host-immune signature correctly identified all 3 viral-bacterial coinfection cases, as well as 22 out of the 24 (92%) simple viral patients. This finding supports that the signature has the potential to reduce antibiotic overuse by 6.5-fold (from an overuse of 13/24 = 54% to 2/24 = 8%, P < 0.001).

Conclusion

Our results demonstrate high antibiotic overuse rates for RSV patients, consistent with previous reports. The host-immune signature correctly distinguished simple viral from viral–bacterial coinfection and therefore may have the potential to aid physicians in the correct management of children with RSV infection. Implementation studies are required to evaluate its utility in safely decreasing unnecessary antibiotic use for RSV patients.

Disclosures

N. Mastboim, MeMed Diagnostics: Employee, Salary. K. Oved, MeMed Diagnostics: Board Member, Employee and Shareholder, Salary. T. Gottlieb, MeMed Diagnostics: Employee, Salary. A. Cohen, MeMed Diagnostics: Employee, Salary. R. Navon, MeMed Diagnostics: Employee, Salary. M. Paz, MeMed Diagnostics: Employee, Salary. E. Bamberger, MeMed Diagnostics: Employee, Salary. T. Friedman, MeMed Diagnostics: Employee, Salary. L. Etshtein, MeMed Diagnostics: Employee, Salary. O. Boico, MeMed Diagnostics: Employee, Salary. I. Potasman, MeMed Diagnostics: Holding stock options, Stock options. E. Eden, MeMed Diagnostics: Board Member, Employee and Shareholder, Salary. L. Shani, MeMed Diagnostics: Employee, Salary.

1948. A Host-Response Assay Distinguishes Between Simple Influenza Patients and Influenza Patients With Bacterial Coinfection

Background

Identifying bacterial coinfection in influenza patients can be difficult as the symptoms of simple influenza vs. mixed infections are often similar, leading to antibiotic overuse. A new host-response assay (ImmunoXpert™) that integrates the levels of three proteins (TRAIL, IP-10, and CRP) was shown to exhibit high performance in distinguishing between bacterial and viral disease in two double-blind validation studies. Here we sought to evaluate its ability to differentiate between simple influenza and influenza with bacterial coinfection.

Methods

The study population included 653 febrile pediatric and adult patients prospectively recruited in the “Curiosity” study. Patient etiology (simple viral vs. mixed infection) was determined by unanimous expert adjudication based on comprehensive clinical, laboratory and radiological assessment. Influenza strains (A or B) were detected using multiplex PCR applied to nasal swabs (Seeplex-RV15). We compared the expert panel diagnosis with the assay that gives three possible outcomes: viral, bacterial (including viral with bacterial coinfection) or equivocal. An equivocal outcome does not provide diagnostic information and is observed in ~10% of cases.

Results

Out of 653 patients, 51 had positive influenza detection and unanimous expert diagnosis: 44 simple viral infections and seven influenza with bacterial coinfections (Figure 1). Antibiotics were prescribed to all seven cases of influenza with bacterial coinfection and to 20/44 cases adjudicated as simple viral infections, indicating an overuse rate of 45%. The assay correctly classified 40 of the 44 simple viral cases (out of the remaining four, two were assigned viral with bacterial coinfection, and two received equivocal outcomes) as well as five of the seven viral with bacterial coinfection cases (the remaining two received equivocal outcomes) supporting the assay’s potential to reduce antibiotic overuse 5-fold (from 45% to 4/44 = 9%, P < 0.001).

Conclusion

The host–response assay can differentiate between simple influenza and influenza patients with bacterial coinfection, with potential to reduce antibiotic overuse. Utility studies are warranted to demonstrate that the assay can safely assist physicians in correct management of influenza patients.

Disclosures

M. Paz, MeMed Diagnostics: Employee, Salary. K. Oved, MeMed Diagnostics: Board Member, Employee and Shareholder, Salary. T. Gottlieb, MeMed Diagnostics: Employee, Salary. A. Cohen, MeMed Diagnostics: Employee, Salary. R. Navon, MeMed Diagnostics: Employee, Salary. N. Mastboim, MeMed Diagnostics: Employee, Salary. E. Bamberger, MeMed Diagnostics: Employee, Salary. T. Friedman, MeMed Diagnostics: Employee, Salary. L. Etshtein, MeMed Diagnostics: Employee, Salary. O. Boico, MeMed Diagnostics: Employee, Salary. I. Potasman, MeMed Diagnostics: Holding stock options, Stock options. E. Eden, MeMed Diagnostics: Board Member, Employee and Shareholder, Salary. L. Shani, MeMed Diagnostics: Employee, Salary.

Observational multi-centre, prospective study to characterize novel pathogen-and host-related factors in hospitalized patients with lower respiratory tract infections and/or sepsis - the "TAILORED-Treatment" study

Background

The emergence and spread of antibiotic resistant micro-organisms is a global concern, which is largely attributable to inaccurate prescribing of antibiotics to patients presenting with non-bacterial infections. The use of ‘omics’ technologies for discovery of novel infection related biomarkers combined with novel treatment algorithms offers possibilities for rapidly distinguishing between bacterial and viral infections. This distinction can be particularly important for patients suffering from lower respiratory tract infections (LRTI) and/or sepsis as they represent a significant burden to healthcare systems. Here we present the study details of the TAILORED-Treatment study, an observational, prospective, multi-centre study aiming to generate a multi-parametric model, combining host and pathogen data, for distinguishing between bacterial and viral aetiologies in children and adults with LRTI and/or sepsis.

Methods

A total number of 1200 paediatric and adult patients aged 1 month and older with LRTI and/or sepsis or a non-infectious disease are recruited from Emergency Departments and hospital wards of seven Dutch and Israeli medical centres. A panel of three experienced physicians adjudicate a reference standard diagnosis for all patients (i.e., bacterial or viral infection) using all available clinical and laboratory information, including a 28-day follow-up assessment. Nasal swabs and blood samples are collected for multi-omics investigations including host RNA and protein biomarkers, nasal microbiota profiling, host genomic profiling and bacterial proteomics. Simplified data is entered into a custom-built database in order to develop a multi-parametric model and diagnostic tools for differentiating between bacterial and viral infections. The predictions from the model will be compared with the consensus diagnosis in order to determine its accuracy.

Discussion

The TAILORED-Treatment study will provide new insights into the interplay between the host and micro-organisms. New host- or pathogen-related biomarkers will be used to generate a multi-parametric model for distinguishing between bacterial and viral infections. This model will be helpful to better guide antimicrobial therapy for patients with LRTI and sepsis. This study has the potential to improve patient care, reduce unnecessary antibiotic prescribing and will contribute positively to institutional, national and international healthcare economics.

Trial Registration

NCT02025699. Registration Date: January, 1, 2014.

Electronic supplementary material

The online version of this article (10.1186/s12879-018-3300-9) contains supplementary material, which is available to authorized users.

A host-protein signature is superior to other biomarkers for differentiating between bacterial and viral disease in patients with respiratory infection and fever without source: a prospective observational study

Bacterial and viral infections often present with similar symptoms. Etiologic misdiagnosis can alter the trajectory of patient care, including antibiotic overuse. A host-protein signature comprising tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), interferon gamma-induced protein-10 (IP-10), and C-reactive protein (CRP) was validated recently for differentiating bacterial from viral disease. However, a focused head-to-head comparison of its diagnostic performance against other biomarker candidates for this indication was lacking in patients with respiratory infection and fever without source. We compared the signature to other biomarkers and prediction rules using specimens collected prospectively at two secondary medical centers from children and adults. Inclusion criteria included fever > 37.5 °C, symptom duration ≤ 12 days, and presentation with respiratory infection or fever without source. Comparator method was based on expert panel adjudication. Signature and biomarker cutoffs and prediction rules were predefined. Of 493 potentially eligible patients, 314 were assigned unanimous expert panel diagnosis and also had sufficient specimen volume. The resulting cohort comprised 175 (56%) viral and 139 (44%) bacterial infections. Signature sensitivity 93.5% (95% CI 89.1–97.9%), specificity 94.3% (95% CI 90.7–98.0%), or both were significantly higher (all p values < 0.01) than for CRP, procalcitonin, interleukin-6, human neutrophil lipocalin, white blood cell count, absolute neutrophil count, and prediction rules. Signature identified as viral 50/57 viral patients prescribed antibiotics, suggesting potential to reduce antibiotic overuse by 88%. The host-protein signature demonstrated superior diagnostic performance in differentiating viral from bacterial respiratory infections and fever without source. Future utility studies are warranted to validate potential to reduce antibiotic overuse.

A novel host-protein assay outperforms routine parameters for distinguishing between bacterial and viral lower respiratory tract infections

Bacterial and viral lower respiratory tract infections (LRTIs) are often clinically indistinguishable, leading to antibiotic overuse. We compared the diagnostic accuracy of a new assay that combines 3 host-biomarkers (TRAIL, IP-10, CRP) with parameters in routine use to distinguish bacterial from viral LRTIs. Study cohort included 184 potentially eligible pediatric and adult patients. Reference standard diagnosis was based on adjudication by an expert panel following comprehensive clinical and laboratory investigation (including respiratory PCRs). Experts were blinded to assay results and assay performers were blinded to reference standard outcomes. Evaluated cohort included 88 bacterial and 36 viral patients (23 did not fulfill inclusion criteria; 37 had indeterminate reference standard outcome). Assay distinguished bacterial from viral LRTI patients with sensitivity of 0.93±0.06 and specificity of 0.91±0.09, outperforming routine parameters, including WBC, CRP and chest x-ray signs. These findings support the assay's potential to help clinicians avoid missing bacterial LRTIs or overusing antibiotics.

A Novel Host-protein Assay Accurately Distinguishes Bacterial From Viral Upper Respiratory Tract Infections

Background

Bacterial and viral infections are often clinically indistinguishable, particularly in upper respiratory tract infections (URTI), which leads to antibiotic misuse. A novel assay (ImmunoXpert™) that integrates measurements of three host-response proteins (TRAIL, IP-10, CRP) was recently developed to assist in differentiation between bacterial and viral etiologies. We evaluated the assay performance in URTI patients and compared it with standard laboratory measures.

Methods

We performed a sub-analysis of 464 patients with clinical suspicion of URTI enrolled in three previously conducted multi-center clinical studies that evaluated the assay performance in patients with acute infections: ‘Curiosity’ study (NCT01917461), ‘Opportunity’ study (NCT01931254), and ‘Pathfinder’ study (NCT01911143). Comparator method was predetermined criteria combined with expert panel adjudication, which was blinded to the test results. Diagnostic performance was evaluated by comparing test and comparator method outcomes.

Results

A unanimous panel adjudication was attained for 61 bacterial (13%) and 241 viral (52%) patients (162 patients (35%) had an indeterminate diagnosis). The assay distinguished between bacterial and viral infected patients with a sensitivity of 92% (95% CI: 82%- 98%) and specificity of 93% (88%-96%) with 11% equivocal test results. Overall the assay outperformed other routine laboratory tests (FIG 1), including: white blood cell count (WBC; cutoff 15,000 cells/µL, sensitivity 48% (35%-60%), P < 10^-−6; specificity 85% (80%-90%), P < 0.05); CRP (cutoff 40 mg/L, sensitivity 82% (72%–92%), P = 0.16, specificity 79% (74%–84%), P < 10^-4); Procalcitonin (PCT; cutoff 0.5 ng/mL, sensitivity 22% (11%–32%), P < 10^–14, specificity 80% (74%–85%), P < 0.001); absolute neutrophil count (ANC; cutoff 10,000 cells/µL, sensitivity 58% (45%–71%), P < 10^-−4, specificity 94% (91%–97%), P = 0.7).

Conclusion

The novel assay demonstrated superior performance compared with routine laboratory tests (WBC, ANC) and biomarkers (CRP, PCT), in distinguishing bacterial from viral etiologies in patients with URTI. It has the potential to help clinicians avoid missing bacterial infections or prescribing unwarranted antibiotics for viral URTIs.

Disclosures

K. Oved, MeMed Diagnostics: Board Member, Employee and Shareholder, Salary E. Eden, MeMed Diagnostics: Board Member, Employee and Shareholder, Salary T. Gottlieb, MeMed Diagnostics: Employee, Salary R. Navon, MeMed Diagnostics: Employee, Salary A. Cohen, MeMed Diagnostics: Employee, Salary O. Boico, MeMed Diagnostics: Employee, Salary M. Paz, MeMed Diagnostics: Employee, Salary L. Etshtein, MeMed Diagnostics: Employee, Salary G. Kronenfeld, MeMed Diagnostics: Employee, Salary T. Friedman, MeMed Diagnostics: Employee, Salary E. Bamberger, MeMed Diagnostics: Employee, Salary I. Chistyakov, MeMed Diagnostics: Consultant, Consulting fee I. Potasman, MeMed Diagnostics: Holding stock options, stock options

Validation of a Novel Assay to Distinguish Bacterial and Viral Infections

BACKGROUND

Reliably distinguishing bacterial from viral infections is often challenging, leading to antibiotic misuse. A novel assay that integrates measurements of blood-borne host-proteins (tumor necrosis factor-related apoptosis-inducing ligand, interferon γ-induced protein-10, and C-reactive protein [CRP]) was developed to assist in differentiation between bacterial and viral disease.

METHODS

We performed double-blind, multicenter assay evaluation using serum remnants collected at 5 pediatric emergency departments and 2 wards from children ≥3 months to ≤18 years without (n = 68) and with (n = 529) suspicion of acute infection. Infectious cohort inclusion criteria were fever ≥38°C and symptom duration ≤7 days. The reference standard diagnosis was based on predetermined criteria plus adjudication by experts blinded to assay results. Assay performers were blinded to the reference standard. Assay cutoffs were predefined.

RESULTS

Of 529 potentially eligible patients with suspected acute infection, 100 did not fulfill infectious inclusion criteria and 68 had insufficient serum. The resulting cohort included 361 patients, with 239 viral, 68 bacterial, and 54 indeterminate reference standard diagnoses. The assay distinguished between bacterial and viral patients with 93.8% sensitivity (95% confidence interval: 87.8%-99.8%) and 89.8% specificity (85.6%-94.0%); 11.7% had an equivocal assay outcome. The assay outperformed CRP (cutoff 40 mg/L; sensitivity 88.2% [80.4%-96.1%], specificity 73.2% [67.6%-78.9%]) and procalcitonin testing (cutoff 0.5 ng/mL; sensitivity 63.1% [51.0%-75.1%], specificity 82.3% [77.1%-87.5%]).

CONCLUSIONS

Double-blinded evaluation confirmed high assay performance in febrile children. Assay was significantly more accurate than CRP, procalcitonin, and routine laboratory parameters. Additional studies are warranted to support its potential to improve antimicrobial treatment decisions.

A multifaceted 'omics' approach for addressing the challenge of antimicrobial resistance

The inappropriate use of antibiotics has severe global health and economic consequences, including the emergence of antibiotic-resistant bacteria. A major driver of antibiotic misuse is the inability to accurately distinguish between bacterial and viral infections based on currently available diagnostic solutions. A multifaceted 'omics' approach that integrates personalized patient data such as genetic predisposition to infections (genomics), natural microbiota composition and immune response to infection (proteomics and transcriptomics) together with comprehensive pathogen profiling has the potential to help physicians improve their antimicrobial prescribing practices. In this respect, the EU has funded a multidisciplinary project (TAILORED-Treatment) that will develop novel omics-based personalized treatment schemes that have the potential to reduce antibiotic consumption, and help limiting the spread of antibiotic resistance.

Noise genetics: inferring protein function by correlating phenotype with protein levels and localization in individual human cells

To understand gene function, genetic analysis uses large perturbations such as gene deletion, knockdown or over-expression. Large perturbations have drawbacks: they move the cell far from its normal working point, and can thus be masked by off-target effects or compensation by other genes. Here, we offer a complementary approach, called noise genetics. We use natural cell-cell variations in protein level and localization, and correlate them to the natural variations of the phenotype of the same cells. Observing these variations is made possible by recent advances in dynamic proteomics that allow measuring proteins over time in individual living cells. Using motility of human cancer cells as a model system, and time-lapse microscopy on 566 fluorescently tagged proteins, we found 74 candidate motility genes whose level or localization strongly correlate with motility in individual cells. We recovered 30 known motility genes, and validated several novel ones by mild knockdown experiments. Noise genetics can complement standard genetics for a variety of phenotypes.

The effect of heat on the mechanical properties of glass ionomer cements

AIM

The objective of this study was to assess the effect of heat application on the mechanical properties of glass ionomer cements.

STUDY DESIGN

experimental design. The effect of heat on glass ionomer cements during their setting was evaluated by measuring compressive strength, flexural strength and microhardness. Moroever, temperature changes from one surface of the glass ionomer cement specimens 2, 4, and 6 mm thick to the other surface were measured. A condensable glass ionomer cement (Fuji IX) and a ceramic-reinforced glass ionomer cement (Amalgomer CR) were used as test materials. Heat was applied with soldering iron for 2 minutes at 80±2oC. All mechanical tests were carried out 24 hours after the setting of glass ionomer cements.

RESULTS

No significant differences in compressive strength were found between the control groups and the heated groups. There were no statistically significant differences in the flexural strength value for both groups of Fuji IX. On the contrary, when heat was applied to Amalgomer, its mean flexural strength reached a value that was higher than that of Amalgomer control. Significant differences in microhardness were found between the control groups and the heated groups and between Fuji IX and Amalgomer CR. Temperature rising in both glass ionomer cements was also noted.

STATISTICS

two-way ANOVA was used where appropriate and independent samples t-test was used in case of interaction.

CONCLUSION

It is established that heat application improved the surface mechanical properties of conventional glass ionomer cements.

Dynamic proteomics of human protein level and localization across the cell cycle

Regulation of proteins across the cell cycle is a basic process in cell biology. It has been difficult to study this globally in human cells due to lack of methods to accurately follow protein levels and localizations over time. Estimates based on global mRNA measurements suggest that only a few percent of human genes have cell-cycle dependent mRNA levels. Here, we used dynamic proteomics to study the cell-cycle dependence of proteins. We used 495 clones of a human cell line, each with a different protein tagged fluorescently at its endogenous locus. Protein level and localization was quantified in individual cells over 24h of growth using time-lapse microscopy. Instead of standard chemical or mechanical methods for cell synchronization, we employed in-silico synchronization to place protein levels and localization on a time axis between two cell divisions. This non-perturbative synchronization approach, together with the high accuracy of the measurements, allowed a sensitive assay of cell-cycle dependence. We further developed a computational approach that uses texture features to evaluate changes in protein localizations. We find that 40% of the proteins showed cell cycle dependence, of which 11% showed changes in protein level and 35% in localization. This suggests that a broader range of cell-cycle dependent proteins exists in human cells than was previously appreciated. Most of the cell-cycle dependent proteins exhibit changes in cellular localization. Such changes can be a useful tool in the regulation of the cell-cycle being fast and efficient.

Proteome half-life dynamics in living human cells

Cells remove proteins by two processes: degradation and dilution due to cell growth. The balance between these basic processes is poorly understood. We addressed this by developing an accurate and noninvasive method for measuring protein half-lives, called "bleach-chase," that is applicable to fluorescently tagged proteins. Assaying 100 proteins in living human cancer cells showed half-lives that ranged between 45 minutes and 22.5 hours. A variety of stresses that stop cell division showed the same general effect: Long-lived proteins became longer-lived, whereas short-lived proteins remained largely unaffected. This effect is due to the relative strengths of degradation and dilution and suggests a mechanism for differential killing of rapidly growing cells by growth-arresting drugs. This approach opens a way to understand proteome half-life dynamics in living cells.

Generation of double-labeled reporter cell lines for studying co-dynamics of endogenous proteins in individual human cells

Understanding the dynamic relationship between components of a system or pathway at the individual cell level is a current challenge. To address this, we developed an approach that allows simultaneous tracking of several endogenous proteins of choice within individual living human cells. The approach is based on fluorescent tagging of proteins at their native locus by directed gene targeting. A fluorescent tag-encoding DNA is introduced as a new exon into the intronic region of the gene of interest, resulting in expression of a full-length fluorescently tagged protein. We used this approach to establish human cell lines simultaneously expressing two components of a major antioxidant defense system, thioredoxin 1 (Trx) and thioredoxin reductase 1 (TrxR1), labeled with CFP and YFP, respectively. We find that the distributions of both proteins between nuclear and cytoplasmic compartments were highly variable between cells. However, the two proteins did not vary independently of each other: protein levels of Trx and TrxR1 in both the whole cell and the nucleus were substantially correlated. We further find that in response to a stress-inducing drug (CPT), both Trx and TrxR1 accumulated in the nuclei in a manner that was highly temporally correlated. This accumulation considerably reduced cell-to-cell variability in nuclear content of both proteins, suggesting a uniform response of the thioredoxin system to stress. These results indicate that Trx and TrxR1 act in concert in response to stress in regard to both time course and variability. Thus, our approach provides an efficient tool for studying dynamic relationship between components of systems of interest at a single-cell level.

Central carbon metabolism as a minimal biochemical walk between precursors for biomass and energy

Central carbon metabolism uses a complex series of enzymatic steps to convert sugars into metabolic precursors. These precursors are then used to generate the entire biomass of the cell. Are there simplifying principles that can explain the structure of such metabolic networks? Here we address this question by studying central carbon metabolism in E. coli. We use all known classes of enzymes that work on carbohydrates to generate rules for converting compounds and for generating possible paths between compounds. We find that central carbon metabolism is built as a minimal walk between the 12 precursor metabolites that form the basis for biomass and one precursor essential for the positive net ATP balance in glycolysis: every pair of consecutive precursors in the network is connected by the minimal number of enzymatic steps. Similarly, input sugars are converted into precursors by the shortest possible enzymatic paths. This suggests an optimality principle for the structure of central carbon metabolism. The present approach may be used to study other metabolic networks and to design new minimal pathways.

Development of predictive models for airflow obstruction in alpha-1-antitrypsin deficiency

Alpha-1-antitrypsin deficiency is a genetic condition associated with severe, early-onset chronic obstructive pulmonary disease (COPD). However, there is significant variability in lung function impairment among persons with the protease inhibitor ZZ genotype. Early identification of persons at highest risk of developing lung disease could be beneficial in guiding monitoring and treatment decisions. Using a multicenter, family-based study sample (2002-2005) of 372 persons with the protease inhibitor ZZ genotype, the authors developed prediction models for forced expiratory volume in 1 second (FEV(1)) and the presence of severe COPD using demographic, clinical, and genetic variables. Half of the data sample was used for model development, and the other half was used for model validation. In the training sample, variables found to be predictive of both FEV(1) and severe COPD were age, sex, pack-years of smoking, bronchodilator responsiveness, chronic bronchitis symptoms, and index case status. In the validation sample, the predictive model for FEV(1) explained 50% of the variance in FEV(1), and the model for severe COPD exhibited excellent discrimination (c statistic = 0.88).

Dynamic Proteomics: a database for dynamics and localizations of endogenous fluorescently-tagged proteins in living human cells

Recent advances allow tracking the levels and locations of a thousand proteins in individual living human cells over time using a library of annotated reporter cell clones (LARC). This library was created by Cohen et al. to study the proteome dynamics of a human lung carcinoma cell-line treated with an anti-cancer drug. Here, we report the Dynamic Proteomics database for the proteins studied by Cohen et al. Each cell-line clone in LARC has a protein tagged with yellow fluorescent protein, expressed from its endogenous chromosomal location, under its natural regulation. The Dynamic Proteomics interface facilitates searches for genes of interest, downloads of protein fluorescent movies and alignments of dynamics following drug addition. Each protein in the database is displayed with its annotation, cDNA sequence, fluorescent images and movies obtained by the time-lapse microscopy. The protein dynamics in the database represents a quantitative trace of the protein fluorescence levels in nucleus and cytoplasm produced by image analysis of movies over time. Furthermore, a sequence analysis provides a search and comparison of up to 50 input DNA sequences with all cDNAs in the library. The raw movies may be useful as a benchmark for developing image analysis tools for individual-cell dynamic-proteomics. The database is available at http://www.dynamicproteomics.net/.

GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists

Background

Since the inception of the GO annotation project, a variety of tools have been developed that support exploring and searching the GO database. In particular, a variety of tools that perform GO enrichment analysis are currently available. Most of these tools require as input a target set of genes and a background set and seek enrichment in the target set compared to the background set. A few tools also exist that support analyzing ranked lists. The latter typically rely on simulations or on union-bound correction for assigning statistical significance to the results.

Results

GOrilla is a web-based application that identifies enriched GO terms in ranked lists of genes, without requiring the user to provide explicit target and background sets. This is particularly useful in many typical cases where genomic data may be naturally represented as a ranked list of genes (e.g. by level of expression or of differential expression). GOrilla employs a flexible threshold statistical approach to discover GO terms that are significantly enriched at the top of a ranked gene list. Building on a complete theoretical characterization of the underlying distribution, called mHG, GOrilla computes an exact p-value for the observed enrichment, taking threshold multiple testing into account without the need for simulations. This enables rigorous statistical analysis of thousand of genes and thousands of GO terms in order of seconds. The output of the enrichment analysis is visualized as a hierarchical structure, providing a clear view of the relations between enriched GO terms.

Conclusion

GOrilla is an efficient GO analysis tool with unique features that make a useful addition to the existing repertoire of GO enrichment tools. GOrilla's unique features and advantages over other threshold free enrichment tools include rigorous statistics, fast running time and an effective graphical representation. GOrilla is publicly available at:

Dynamic proteomics of individual cancer cells in response to a drug

Why do seemingly identical cells respond differently to a drug? To address this, we studied the dynamics and variability of the protein response of human cancer cells to a chemotherapy drug, camptothecin. We present a dynamic-proteomics approach that measures the levels and locations of nearly 1000 different endogenously tagged proteins in individual living cells at high temporal resolution. All cells show rapid translocation of proteins specific to the drug mechanism, including the drug target (topoisomerase-1), and slower, wide-ranging temporal waves of protein degradation and accumulation. However, the cells differ in the behavior of a subset of proteins. We identify proteins whose dynamics differ widely between cells, in a way that corresponds to the outcomes-cell death or survival. This opens the way to understanding molecular responses to drugs in individual cells.

Heritability of lung function in severe alpha-1 antitrypsin deficiency

Severe alpha-1 antitrypsin (AAT) deficiency is a proven genetic risk factor for COPD, but there is marked variation in the development of COPD among AAT deficient subjects. To investigate familial aggregation of lung function in subjects with AAT deficiency, we estimated heritability for forced expiratory volume in 1 s (FEV1) and FEV1/forced vital capacity (FVC) in 378 AAT deficient subjects from 167 families in the AAT Genetic Modifiers Study; all subjects were verified homozygous for the Z AAT deficiency allele. Heritability was evaluated for models that included and excluded an ascertainment correction, as well as for models that excluded, included and were stratified by a cigarette smoking covariate. In models without an ascertainment correction, and in all models without a covariate for smoking, no evidence for familial aggregation of lung function was observed. In models conditioned on the index proband with covariates for smoking, post-bronchodilator FEV1/FVC demonstrated significant heritability (0.26 +/- 0.14, p = 0.03). When we limited the analysis to subjects with a smoking history, post-bronchodilator FEV1 demonstrated significant heritability (0.47 +/- 0.21, p = 0.02). Severity rate phenotypes were also assessed as potential phenotypes for genetic modifier studies. Significant heritability was found with all age-of-onset threshold models that included smoking and ascertainment adjustments. Using the t-distribution, the heritability estimates ranged from 0.43 to 0.64, depending on the age-of-onset of FEV1 decline used for the severity rate calculation. Correction for ascertainment and consideration of gene-by-smoking interactions will be crucial for the identification of genes that may modify susceptibility for COPD in families with AAT deficiency.

Discovering motifs in ranked lists of DNA sequences

Computational methods for discovery of sequence elements that are enriched in a target set compared with a background set are fundamental in molecular biology research. One example is the discovery of transcription factor binding motifs that are inferred from ChIP–chip (chromatin immuno-precipitation on a microarray) measurements. Several major challenges in sequence motif discovery still require consideration: (i) the need for a principled approach to partitioning the data into target and background sets; (ii) the lack of rigorous models and of an exact p-value for measuring motif enrichment; (iii) the need for an appropriate framework for accounting for motif multiplicity; (iv) the tendency, in many of the existing methods, to report presumably significant motifs even when applied to randomly generated data. In this paper we present a statistical framework for discovering enriched sequence elements in ranked lists that resolves these four issues. We demonstrate the implementation of this framework in a software application, termed DRIM (discovery of rank imbalanced motifs), which identifies sequence motifs in lists of ranked DNA sequences. We applied DRIM to ChIP–chip and CpG methylation data and obtained the following results. (i) Identification of 50 novel putative transcription factor (TF) binding sites in yeast ChIP–chip data. The biological function of some of them was further investigated to gain new insights on transcription regulation networks in yeast. For example, our discoveries enable the elucidation of the network of the TF ARO80. Another finding concerns a systematic TF binding enhancement to sequences containing CA repeats. (ii) Discovery of novel motifs in human cancer CpG methylation data. Remarkably, most of these motifs are similar to DNA sequence elements bound by the Polycomb complex that promotes histone methylation. Our findings thus support a model in which histone methylation and CpG methylation are mechanistically linked. Overall, we demonstrate that the statistical framework embodied in the DRIM software tool is highly effective for identifying regulatory sequence elements in a variety of applications ranging from expression and ChIP–chip to CpG methylation data. DRIM is publicly available at http://bioinfo.cs.technion.ac.il/drim.

A computational problem with many applications in molecular biology is to identify short DNA sequence patterns (motifs) that are significantly overrepresented in a target set of genomic sequences relative to a background set of genomic sequences. One example is a target set that contains DNA sequences to which a specific transcription factor protein was experimentally measured as bound while the background set contains sequences to which the same transcription factor was not bound. Overrepresented sequence motifs in the target set may represent a subsequence that is molecularly recognized by the transcription factor. An inherent limitation of the above formulation of the problem lies in the fact that in many cases data cannot be clearly partitioned into distinct target and background sets in a biologically justified manner. We describe a statistical framework for discovering motifs in a list of genomic sequences that are ranked according to a biological parameter or measurement (e.g., transcription factor to sequence binding measurements). Our approach circumvents the need to partition the data into target and background sets using arbitrarily set parameters. The framework is implemented in a software tool called DRIM. The application of DRIM led to the identification of novel putative transcription factor binding sites in yeast and to the discovery of previously unknown motifs in CpG methylation regions in human cancer cell lines.

Polycomb-mediated methylation on Lys27 of histone H3 pre-marks genes for de novo methylation in cancer

Many genes associated with CpG islands undergo de novo methylation in cancer. Studies have suggested that the pattern of this modification may be partially determined by an instructive mechanism that recognizes specifically marked regions of the genome. Using chromatin immunoprecipitation analysis, here we show that genes methylated in cancer cells are specifically packaged with nucleosomes containing histone H3 trimethylated on Lys27. This chromatin mark is established on these unmethylated CpG island genes early in development and then maintained in differentiated cell types by the presence of an EZH2-containing Polycomb complex. In cancer cells, as opposed to normal cells, the presence of this complex brings about the recruitment of DNA methyl transferases, leading to de novo methylation. These results suggest that tumor-specific targeting of de novo methylation is pre-programmed by an established epigenetic system that normally has a role in marking embryonic genes for repression.

An automated method for analysis of flow characteristics of circulating particles from in vivo video microscopy

The behavior of white and red blood cells, platelets, and circulating injected particles is one of the most studied areas of physiology. Most methods used to analyze the circulatory patterns of cells are time consuming. We describe a system named CellTrack, designed for fully automated tracking of circulating cells and micro-particles and retrieval of their behavioral characteristics. The task of automated blood cell tracking in vessels from in vivo video is particularly challenging because of the blood cells' nonrigid shapes, the instability inherent in in vivo videos, the abundance of moving objects and their frequent superposition. To tackle this, the CellTrack system operates on two levels: first, a global processing module extracts vessel borders and center lines based on color and temporal patterns. This enables the computation of the approximate direction of the blood flow in each vessel. Second, a local processing module extracts the locations and velocities of circulating cells. This is performed by artificial neural network classifiers that are designed to detect specific types of blood cells and micro-particles. The motion correspondence problem is then resolved by a novel algorithm that incorporates both the local and the global information. The system has been tested on a series of in vivo color video recordings of rat mesentery. Our results show that the synergy between the global and local information enables CellTrack to overcome many of the difficulties inherent in tracking methods that rely solely on local information. A comparison was made between manual measurements and the automatically extracted measurements of leukocytes and fluorescent microspheres circulatory velocities. This comparison revealed an accuracy of 97%. CellTrack also enabled a much larger volume of sampling in a fraction of time compared to the manual measurements. All these results suggest that our method can in fact constitute a reliable replacement for manual extraction of blood flow characteristics from in vivo videos.

Analysis and recognition of 5' UTR intron splice sites in human pre-mRNA

Prediction of splice sites in non-coding regions of genes is one of the most challenging aspects of gene structure recognition. We perform a rigorous analysis of such splice sites embedded in human 5' untranslated regions (UTRs), and investigate correlations between this class of splice sites and other features found in the adjacent exons and introns. By restricting the training of neural network algorithms to 'pure' UTRs (not extending partially into protein coding regions), we for the first time investigate the predictive power of the splicing signal proper, in contrast to conventional splice site prediction, which typically relies on the change in sequence at the transition from protein coding to non-coding. By doing so, the algorithms were able to pick up subtler splicing signals that were otherwise masked by 'coding' noise, thus enhancing significantly the prediction of 5' UTR splice sites. For example, the non-coding splice site predicting networks pick up compositional and positional bias in the 3' ends of non-coding exons and 5' non-coding intron ends, where cytosine and guanine are over-represented. This compositional bias at the true UTR donor sites is also visible in the synaptic weights of the neural networks trained to identify UTR donor sites. Conventional splice site prediction methods perform poorly in UTRs because the reading frame pattern is absent. The NetUTR method presented here performs 2-3-fold better compared with NetGene2 and GenScan in 5' UTRs. We also tested the 5' UTR trained method on protein coding regions, and discovered, surprisingly, that it works quite well (although it cannot compete with NetGene2). This indicates that the local splicing pattern in UTRs and coding regions is largely the same. The NetUTR method is made publicly available at www.cbs.dtu.dk/services/NetUTR.